Reviewer #1 (Public review):

This is a re-review following an author revision. I will go point-by-point in response to my original critiques and the authors' responses. I appreciate the authors taking the time to thoughtfully respond to the reviewer critiques.

Query 1. Based on the authors' description of their contribution to the algorithm design, it sounds like a hyperparameter search wrapped around existing software tools. I think that the use of their own language to describe these modules is confusing to potential users as well as unintentionally hides the contributions of the original LigBuilder developers. The authors should just explain the protocol plainly using language that refers specifically to the established software tools. Whether they use LigBuilder or something else, at the end of the day the description is a protocol for a specific use of an existing software rather than the creation of a new toolkit.

Query 2. I see. Correct me if I am mistaken, but it seems as though the authors are proposing using the Authenticator to identify the best distributions of compounds based on an in silico oracle (in this case, Vina score), and train to discriminate them. This is similar to training QSAR models to predict docking scores, such as in the manuscript I shared during the first round of review. In principle, one could perform this in successive rounds to create molecules that are increasingly composed of features that yield higher docking scores. This is an established idea that the authors demonstrate in a narrow context, but it also raises concern that one is just enriching for compounds with e.g., an abundance of hydrogen bond donors and acceptors. Regarding points (4) and (5), it is unclear to me how the authors perform train/test splits on unlabeled data with supervised machine learning approaches in this setting. This seems akin to a Y-scramble sanity check. Finally, regarding the discussion on the use of experimental data or FEP calculations for the determination of HABs and LABs, I appreciate the authors' point; however, the concern here is that in the absence of any true oracle the models will just learn to identify and/or generate compounds that exploit limitations of docking scores. Again, please correct me if I am mistaken. It is unclear to me how this advances previous literature in CADD outside of the specific context of incorporating some ideas into a GPCR-Gprotein framework.

Query 3. The authors mention that the hyperparameters for the ML models are just the package defaults in the absence of specification by the user. I would be helpful to know specifically what the the hyperparameters were for the benchmarks in this study; however, I think a deeper concern is still that these models are almost certainly far overparameterized given the limited training data used for the models. It is unclear why the authors did not just build a random forest classifier to discriminate their HABs and LABs using ligand- or protein-ligand interaction fingerprints or related ideas.

Query 4. It is good, and expected, that increasing the fraction of the training set size in a random split validation all the way to 100% would allow the model to perfectly discriminate HABs and LABs. This does not demonstrate that the model has significant enrichment in prospective screening, particularly compared to simpler methods. The concern remains that these models are overparameterized and insufficiently validated. The authors did not perform any scaffold splits or other out-of-distribution analysis.

Query 5. The authors contend that Gcoupler uniquely enables training models when data is scarce and ultra-large screening libraries are unavailable. Today, it is rather straightforward to dock a minimum of thousands of compounds. Using tools such as QuickVina2-GPU (https://pubs.acs.org/doi/10.1021/acs.jcim.2c01504), it is possible to quite readily dock millions in a day with a single GPU and obtain the AutoDock Vina score. GPU-acclerated Vina has been combined with cavity detection tools likely multiple times, including here (https://arxiv.org/abs/2506.20043). There are multiple cavity detection tools, including the ones the authors use in their protocol.

Query 6. The authors contend that the simulations are converged, but they elected not to demonstrate stability in the predicting MM/GBSA binding energies with block averaging across the trajectory. This could have been done through the existing trajectories without additional simulation.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public review):

Summary

Query: In this manuscript, the authors introduce Gcoupler, a Python-based computational pipeline designed to identify endogenous intracellular metabolites that function as allosteric modulators at the G protein-coupled receptor (GPCR) - Gα protein interface. Gcoupler is comprised of four modules:

I. Synthesizer - identifies protein cavities and generates synthetic ligands using LigBuilder3

II. Authenticator - classifies ligands into high-affinity binders (HABs) and low-affinity binders (LABs) based on AutoDock Vina binding energies

III. Generator - trains graph neural network (GNN) models (GCM, GCN, AFP, GAT) to predict binding affinity using synthetic ligands

IV. BioRanker - prioritizes ligands based on statistical and bioactivity data

The authors apply Gcoupler to study the Ste2p-Gpa1p interface in yeast, identifying sterols such as zymosterol (ZST) and lanosterol (LST) as modulators of GPCR signaling. Our review will focus on the computational aspects of the work. Overall, we found the Gcoupler approach interesting and potentially valuable, but we have several concerns with the methods and validation that need to be addressed prior to publication/dissemination.

We express our gratitude to Reviewer #1 for their concise summary and commendation of our work. We sincerely apologize for the lack of sufficient detail in summarizing the underlying methods employed in Gcoupler, as well as its subsequent experimental validations using yeast, human cell lines, and primary rat cardiomyocyte-based assays.

We wish to state that substantial improvements have been made in the revised manuscript, every section has been elaborated upon to enhance clarity. Please refer to the point-by-point response below and the revised manuscript.

Query: (1) The exact algorithmic advancement of the Synthesizer beyond being some type of application wrapper around LigBuilder is unclear. Is the grow-link approach mentioned in the methods already a component of LigBuilder, or is it custom? If it is custom, what does it do? Is the API for custom optimization routines new with the Synthesizer, or is this a component of LigBuilder? Is the genetic algorithm novel or already an existing software implementation? Is the cavity detection tool a component of LigBuilder or novel in some way? Is the fragment library utilized in the Synthesizer the default fragment library in LigBuilder, or has it been customized? Are there rules that dictate how molecule growth can occur? The scientific contribution of the Synthesizer is unclear. If there has not been any new methodological development, then it may be more appropriate to just refer to this part of the algorithm as an application layer for LigBuilder.

We appreciate Reviewer #1's constructive suggestion. We wish to emphasize that

(1) The LigBuilder software comprises various modules designed for distinct functions. The Synthesizer in Gcoupler strategically utilizes two of these modules: "CAVITY" for binding site detection and "BUILD" for de novo ligand design.

(2) While both modules are integral to LigBuilder, the Synthesizer plays a crucial role in enabling their targeted, automated, and context-aware application for GPCR drug discovery.

(3) The CAVITY module is a structure-based protein binding site detection program, which the Synthesizer employs for identifying ligand binding sites on the protein surface.

(4) The Synthesizer also leverages the BUILD module for constructing molecules tailored to the target protein, implementing a fragment-based design strategy using its integrated fragment library.

(5) The GROW and LINK methods represent two independent approaches encompassed within the aforementioned BUILD module.

Author response image 1.

Schematic representation of the key strategy used in the Synthesizer module of Gcoupler.

Our manuscript details the "grow-link" hybrid approach, which was implemented using a genetic algorithm through the following stages:

(1) Initial population generation based on a seed structure via the GROW method.

(2) Selection of "parent" molecules from the current population for inclusion in the mating pool using the LINK method.

(3) Transfer of "elite" molecules from the current population to the new population.

(4) Population expansion through structural manipulations (mutation, deletion, and crossover) applied to molecules within the mating pool.

Please note, the outcome of this process is not fixed, as it is highly dependent on the target cavity topology and the constraint parameters employed for population evaluation. Synthesizer customizes generational cycles and optimization parameters based on cavity-specific constraints, with the objective of either generating a specified number of compounds or comprehensively exploring chemical diversity against a given cavity topology.

While these components are integral to LigBuilder, Synthesizer's innovation lies

(1) in its programmatic integration and dynamic adjustment of these modules.

(2) Synthesizer distinguishes itself not by reinventing these algorithms, but by their automated coordination, fine-tuning, and integration within a cavity-specific framework.

(3) It dynamically modifies generation parameters according to cavity topology and druggability constraints, a capability not inherently supported by LigBuilder.

(4) This renders Synthesizer particularly valuable in practical scenarios where manual optimization is either inefficient or impractical.

In summary, Synthesizer offers researchers a streamlined interface, abstracting the technical complexities of LigBuilder and thereby enabling more accessible and reproducible ligand generation pipelines, especially for individuals with limited experience in structural or cheminformatics tools.

Query: (2) The use of AutoDock Vina binding energy scores to classify ligands into HABs and LABs is problematic. AutoDock Vina's energy function is primarily tuned for pose prediction and displays highly system-dependent affinity ranking capabilities. Moreover, the HAB/LAB thresholds of -7 kcal/mol or -8 kcal/mol lack justification. Were these arbitrarily selected cutoffs, or was benchmarking performed to identify appropriate cutoffs? It seems like these thresholds should be determined by calibrating the docking scores with experimental binding data (e.g., known binders with measured affinities) or through re-scoring molecules with a rigorous alchemical free energy approach.

We again express our gratitude to Reviewer #1 for these inquiries. We sincerely apologize for the lack of sufficient detail in the original version of the manuscript. In the revised manuscript, we have ensured the inclusion of a detailed rationale for every threshold utilized to prioritize high-affinity binders. Please refer to the comprehensive explanation below, as well as the revised manuscript, for further details.

We would like to clarify that:

(1) The Authenticator module is not solely reliant on absolute binding energy values for classification. Instead, it calculates binding energies for all generated compounds and applies a statistical decision-making layer to define HAB and LAB classes.

(2) Rather than using fixed thresholds, the module employs distribution-based methods, such as the Empirical Cumulative Distribution Function (ECDF), to assess the overall energy landscape of the compound set. We then applied multiple statistical tests to evaluate the HAB and LAB distributions and determine an optimal, data-specific cutoff that balances class sizes and minimizes overlap.

(3) This adaptive approach avoids rigid thresholds and instead ensures context-sensitive classification, with safeguards in place to maintain adequate representation of both classes for downstream model training, and in this way, the framework prioritizes robust statistical reasoning over arbitrary energy cutoffs and aims to reduce the risks associated with direct reliance on Vina scores alone.

(4) To assess the necessity and effectiveness of the Authenticator module, we conducted a benchmarking analysis where we deliberately omitted the HAB and LAB class labels, treating the compound pool as a heterogeneous, unlabeled dataset. We then performed random train-test splits using the Synthesizer-generated compounds and trained independent models.

(5) The results from this approach demonstrated notably poorer model performance, indicating that arbitrary or unstructured data partitioning does not effectively capture the underlying affinity patterns. These experiments highlight the importance of using the statistical framework within the Authenticator module to establish meaningful, data-driven thresholds for distinguishing High- and Low-Affinity Binders. The cutoff values are thus not arbitrary but emerge from a systematic benchmarking and validation process tailored to each dataset.

Please note: While calibrating docking scores with experimental binding affinities or using rigorous methods like alchemical free energy calculations can improve precision, these approaches are often computationally intensive and reliant on the availability of high-quality experimental data, a major limitation in many real-world screening scenarios.

In summary, the primary goal of Gcoupler is to enable fast, scalable, and broadly accessible screening, particularly for cases where experimental data is sparse or unavailable. Incorporating such resource-heavy methods would not only significantly increase computational overhead but also undermine the framework’s intended usability and efficiency for large-scale applications. Instead, our workflow relies on statistically robust, data-driven classification methods that balance speed, generalizability, and practical feasibility.

Query: (3) Neither the Results nor Methods sections provide information on how the GNNs were trained in this study. Details such as node features, edge attributes, standardization, pooling, activation functions, layers, dropout, etc., should all be described in detail. The training protocol should also be described, including loss functions, independent monitoring and early stopping criteria, learning rate adjustments, etc.

We again thank Reviewer #1 for this suggestion. We would like to mention that in the revised manuscript, we have added all the requested details. Please refer to the points below for more information.

(1) The Generator module of Gcoupler is designed as a flexible and automated framework that leverages multiple Graph Neural Network architectures, including Graph Convolutional Model (GCM), Graph Convolutional Network (GCN), Attentive FP, and Graph Attention Network (GAT), to build classification models based on the synthetic ligand datasets produced earlier in the pipeline.

(2) By default, Generator tests all four models using standard hyperparameters provided by the DeepChem framework (https://deepchem.io/), offering a baseline performance comparison across architectures. This includes pre-defined choices for node features, edge attributes, message-passing layers, pooling strategies, activation functions, and dropout values, ensuring reproducibility and consistency. All models are trained with binary cross-entropy loss and support default settings for early stopping, learning rate, and batch standardization where applicable.

(3) In addition, Generator supports model refinement through hyperparameter tuning and k-fold cross-validation (default: 3 folds). Users can either customize the hyperparameter grid or rely on Generator’s recommended parameter ranges to optimize model performance. This allows for robust model selection and stability assessment of tuned parameters.

(4) Finally, the trained models can be used to predict binding probabilities for user-supplied compounds, making it a comprehensive and user-adaptive tool for ligand screening.

Based on the reviewer #1 suggestion, we have now added a detailed description about the Generator module of Gcoupler, and also provided relevant citations regarding the DeepChem workflow.

Query: (4) GNN model training seems to occur on at most 500 molecules per training run? This is unclear from the manuscript. That is a very small number of training samples if true. Please clarify. How was upsampling performed? What were the HAB/LAB class distributions? In addition, it seems as though only synthetically generated molecules are used for training, and the task is to discriminate synthetic molecules based on their docking scores. Synthetic ligands generated by LigBuilder may occupy distinct chemical space, making classification trivial, particularly in the setting of a random split k-folds validation approach. In the absence of a leave-class-out validation, it is unclear if the model learns generalizable features or exploits clear chemical differences. Historically, it was inappropriate to evaluate ligand-based QSAR models on synthetic decoys such as the DUD-E sets - synthetic ligands can be much more easily distinguished by heavily parameterized ligand-based machine learning models than by physically constrained single-point docking score functions.

We thank reviewer #1 for these detailed technical queries. We would like to clarify that:

(1) The recommended minimum for the training set is 500 molecules, but users can add as many synthesized compounds as needed to thoroughly explore the chemical space related to the target cavity.

(2) Our systematic evaluation demonstrated that expanding the training set size consistently enhanced model performance, especially when compared to AutoDock docking scores. This observation underscores the framework's scalability and its ability to improve predictive accuracy with more training compounds.

(3) The Authenticator module initially categorizes all synthesized molecules into HAB and LAB classes. These labeled molecules are then utilized for training the Generator module. To tackle class imbalance, the class with fewer data points undergoes upsampling. This process aims to achieve an approximate 1:1 ratio between the two classes, thereby ensuring balanced learning during GNN model training.

(4) The Authenticator module's affinity scores are the primary determinant of the HAB/LAB class distribution, with a higher cutoff for HABs ensuring statistically significant class separation. This distribution is also indirectly shaped by the target cavity's topology and druggability, as the Synthesizer tends to produce more potent candidates for cavities with favorable binding characteristics.

(5) While it's true that synthetic ligands may occupy distinct chemical space, our benchmarking exploration for different sites on the same receptor still showed inter-cavity specificity along with intra-cavity diversity of the synthesized molecules.

(6) The utility of random k-fold validation shouldn't be dismissed outright; it provides a reasonable estimate of performance under practical settings where class boundaries are often unknown. Nonetheless, we agree that complementary validation strategies like leave-class-out could further strengthen the robustness assessment.

(7) We agree that using synthetic decoys like those from the DUD-E dataset can introduce bias in ligand-based QSAR model evaluations if not handled carefully. In our workflow, the inclusion of DUD-E compounds is entirely optional and only considered as a fallback, specifically in scenarios where the number of low-affinity binders (LABs) synthesized by the Synthesizer module is insufficient to proceed with model training.

(8) The primary approach relies on classifying generated compounds based on their derived affinity scores via the Authenticator module. However, in rare cases where this results in a heavily imbalanced dataset, DUD-E compounds are introduced not as part of the core benchmarking, but solely to maintain minimal class balance for initial model training. Even then, care is taken to interpret results with this limitation in mind. Ultimately, our framework is designed to prioritize data-driven generation of both HABs and LABs, minimizing reliance on synthetic decoys wherever possible.

Author response image 2.

Scatter plots depicting the segregation of High/Low-Affinity Metabolites (HAM/LAM) (indicated in green and red) identified using Gcoupler workflow with 100% training data. Notably, models trained on lesser training data size (25%, 50%, and 75% of HAB/LAB) severely failed to segregate HAM and LAM (along Y-axis). X-axis represents the binding affinity calculated using IC4-specific docking using AutoDock.

Based on the reviewer #1’s suggestion, we have now added all these technical details in the revised version of the manuscript.

Query: (5) Training QSAR models on docking scores to accelerate virtual screening is not in itself novel (see here for a nice recent example: https://www.nature.com/articles/s43588-025-00777-x), but can be highly useful to focus structure-based analysis on the most promising areas of ligand chemical space; however, we are perplexed by the motivation here. If only a few hundred or a few thousand molecules are being sampled, why not just use AutoDock Vina? The models are trained to try to discriminate molecules by AutoDock Vina score rather than experimental affinity, so it seems like we would ideally just run Vina? Perhaps we are misunderstanding the scale of the screening that was done here. Please clarify the manuscript methods to help justify the approach.

We acknowledge the effectiveness of training QSAR models on docking scores for prioritizing chemical space, as demonstrated by the referenced study (https://www.nature.com/articles/s43588-025-00777-x) on machine-learning-guided docking screen frameworks.

We would like to mention that:

(1) While such protocols often rely on extensive pre-docked datasets across numerous protein targets or utilize a highly skewed input distribution, training on as little as 1-10% of ligand-protein complexes and testing on the remainder in iterative cycles.

(2) While powerful for ultra-large libraries, this approach can introduce bias towards the limited training set and incur significant overhead in data curation, pre-computation, and infrastructure.

(3) In contrast, Gcoupler prioritizes flexibility and accessibility, especially when experimental data is scarce and large pre-docked libraries are unavailable. Instead of depending on fixed docking scores from external pipelines, Gcoupler integrates target-specific cavity detection, de novo compound generation, and model training into a self-contained, end-to-end framework. Its QSAR models are trained directly on contextually relevant compounds synthesized for a given binding site, employing a statistical classification strategy that avoids arbitrary thresholds or precomputed biases.

(4) Furthermore, Gcoupler is open-source, lightweight, and user-friendly, making it easily deployable without the need for extensive infrastructure or prior docking expertise. While not a complete replacement for full-scale docking in all use cases, Gcoupler aims to provide a streamlined and interpretable screening framework that supports both focused chemical design and broader chemical space exploration, without the computational burden associated with deep learning docking workflows.

(5) Practically, even with computational resources, manually running AutoDock Vina on millions of compounds presents challenges such as format conversion, binding site annotation, grid parameter tuning, and execution logistics, all typically requiring advanced structural bioinformatics expertise.

(6) Gcoupler's Authenticator module, however, streamlines this process. Users only need to input a list of SMILES and a receptor PDB structure, and the module automatically handles compound preparation, cavity mapping, parameter optimization, and high-throughput scoring. This automation reduces time and effort while democratizing access to structure-based screening workflows for users without specialized expertise.

Ultimately, Gcoupler's motivation is to make large-scale, structure-informed virtual screening both efficient and accessible. The model serves as a surrogate to filter and prioritize compounds before deeper docking or experimental validation, thereby accelerating targeted drug discovery.

Query: (6) The brevity of the MD simulations raises some concerns that the results may be over-interpreted. RMSD plots do not reliably compare the affinity behavior in this context because of the short timescales coupled with the dramatic topological differences between the ligands being compared; CoQ6 is long and highly flexible compared to ZST and LST. Convergence metrics, such as block averaging and time-dependent MM/GBSA energies, should be included over much longer timescales. For CoQ6, the authors may need to run multiple simulations of several microseconds, identify the longest-lived metastable states of CoQ6, and perform MM/GBSA energies for each state weighted by each state's probability.

We appreciate Reviewer #1's suggestion regarding simulation length, as it is indeed crucial for interpreting molecular dynamics (MD) outcomes. We would like to mention that:

(1) Our simulation strategy varied based on the analysis objective, ranging from short (~5 ns) runs for preliminary or receptor-only evaluations to intermediate (~100 ns) and extended (~550 ns) runs for receptor-ligand complex validation and stability assessment.

(2) Specifically, we conducted three independent 100 ns MD simulations for each receptor-metabolite complex in distinct cavities of interest. This allowed us to assess the reproducibility and persistence of binding interactions. To further support these observations, a longer 550 ns simulation was performed for the IC4 cavity, which reinforced the 100 ns findings by demonstrating sustained interaction stability over extended timescales.

(3) While we acknowledge that even longer simulations (e.g., in the microsecond range) could provide deeper insights into metastable state transitions, especially for highly flexible molecules like CoQ6, our current design balances computational feasibility with the goal of screening multiple cavities and ligands.

(4) In our current workflow, MM/GBSA binding free energies were calculated by extracting 1000 representative snapshots from the final 10 ns of each MD trajectory. These configurations were used to compute time-averaged binding energies, incorporating contributions from van der Waals, electrostatic, polar, and non-polar solvation terms. This approach offers a more reliable estimate of ligand binding affinity compared to single-point molecular docking, as it accounts for conformational flexibility and dynamic interactions within the binding cavity.

(5) Although we did not explicitly perform state-specific MM/GBSA calculations weighted by metastable state probabilities, our use of ensemble-averaged energy estimates from a thermally equilibrated segment of the trajectory captures many of the same benefits. We acknowledge, however, that a more rigorous decomposition based on metastable state analysis could offer finer resolution of binding behavior, particularly for highly flexible ligands like CoQ6, and we consider this a valuable direction for future refinement of the framework.

Reviewer #2 (Public review):

Summary:

Query: Mohanty et al. present a new deep learning method to identify intracellular allosteric modulators of GPCRs. This is an interesting field for e.g. the design of novel small molecule inhibitors of GPCR signalling. A key limitation, as mentioned by the authors, is the limited availability of data. The method presented, Gcoupler, aims to overcome these limitations, as shown by experimental validation of sterols in the inhibition of Ste2p, which has been shown to be relevant molecules in human and rat cardiac hypertrophy models. They have made their code available for download and installation, which can easily be followed to set up software on a local machine.

Strengths:

Clear GitHub repository

Extensive data on yeast systems

We sincerely thank Reviewer #2 for their thorough review, summary, and appreciation of our work. We highly value their comments and suggestions.

Weaknesses:

Query: No assay to directly determine the affinity of the compounds to the protein of interest.

We thank Reviewer #2 for raising these insightful questions. During the experimental design phase, we carefully accounted for validating the impact of metabolites in the rescue response by pheromone.

We would like to mention that we performed an array of methods to validate our hypothesis and observed similar rescue effects. These assays include:

a. Cell viability assay (FDA/PI Flourometry-based)

b. Cell growth assay

c. FUN1^TM-based microscopy assessment

d. Shmoo formation assays

e. Mating assays

f. Site-directed mutagenesis-based loss of function

g. ransgenic reporter-based assay

h. MAPK signaling assessment using Western blot.

i. And via computational techniques.

Concerning the in vitro interaction studies of Ste2p and metabolites, we made significant efforts to purify Ste2p by incorporating a His tag at the N-terminal. Despite dedicated attempts over the past year, we were unsuccessful in purifying the protein, primarily due to our limited expertise in protein purification for this specific system. As a result, we opted for genetic-based interventions (e.g., point mutants), which provide a more physiological and comprehensive approach to demonstrating the interaction between Ste2p and the metabolites.

Author response image 3.

(a) Affinity purification of Ste2p from Saccharomyces cerevisiae. Western blot analysis using anti-His antibody showing the distribution of Ste2p in various fractions during the affinity purification process. The fractions include pellet, supernatant, wash buffer, and sequential elution fractions (1–4). Wild-type and ste2Δ strains served as positive and negative controls, respectively. (b) Optimization of Ste2p extraction protocol. Ponceau staining (left) and Western blot analysis using anti-His antibody (right) showing Ste2p extraction efficiency. The conditions tested include lysis buffers containing different concentrations of CHAPS detergent (0.5%, 1%) and glycerol (10%, 20%).

Furthermore, in addition to the clarification above, we have added the following statement in the discussion section to tone down our claims: “A critical limitation of our study is the absence of direct binding assays to validate the interaction between the metabolites and Ste2p. While our results from genetic interventions, molecular dynamics simulations, and docking studies strongly suggest that the metabolites interact with the Ste2p-Gpa1 interface, these findings remain indirect. Direct binding confirmation through techniques such as surface plasmon resonance, isothermal titration calorimetry, or co-crystallization would provide definitive evidence of this interaction. Addressing this limitation in future work would significantly strengthen our conclusions and provide deeper insights into the precise molecular mechanisms underlying the observed phenotypic effects.”

We request Reviewer #2 to kindly refer to the assays conducted on the point mutants created in this study, as these experiments offer robust evidence supporting our claims.

Query: In conclusion, the authors present an interesting new method to identify allosteric inhibitors of GPCRs, which can easily be employed by research labs. Whilst their efforts to characterize the compounds in yeast cells, in order to confirm their findings, it would be beneficial if the authors show their compounds are active in a simple binding assay.

We express our gratitude and sincere appreciation for the time and effort dedicated by Reviewer #2 in reviewing our manuscript. We are confident that our clarifications address the reviewer's concerns.

Reviewer #3 (Public review):

Summary:

Query: In this paper, the authors introduce the Gcoupler software, an open-source deep learning-based platform for structure-guided discovery of ligands targeting GPCR interfaces. Overall, this manuscript represents a field-advancing contribution at the intersection of AI-based ligand discovery and GPCR signaling regulation.

Strengths:

The paper presents a comprehensive and well-structured workflow combining cavity identification, de novo ligand generation, statistical validation, and graph neural network-based classification. Notably, the authors use Gcoupler to identify endogenous intracellular sterols as allosteric modulators of the GPCR-Gα interface in yeast, with experimental validations extending to mammalian systems. The ability to systematically explore intracellular metabolite modulation of GPCR signaling represents a novel and impactful contribution. This study significantly advances the field of GPCR biology and computational ligand discovery.

We thank and appreciate Reviewer #3 for vesting time and efforts in reviewing our manuscript and for appreciating our efforts.

Recommendations for the authors:

Reviewing Editor Comments:

We encourage the authors to address the points raised during revision to elevate the assessment from "incomplete" to "solid" or ideally "convincing." In particular, we ask the authors to improve the justification for their methodological choices and to provide greater detail and clarity regarding each computational layer of the pipeline.

We are grateful for the editors' suggestions. We have incorporated significant revisions into the manuscript, providing comprehensive technical details to prevent any misunderstandings. Furthermore, we meticulously explained every aspect of the computational workflow.

Reviewer #2 (Recommendations for the authors):

Query: Would it be possible to make the package itself pip installable?

Yes, it already exists under the testpip repository and we have now migrated it to the main pip. Please access the link from here: https://pypi.org/project/gcoupler/

Query: I am confused by the binding free energies reported in Supplementary Figure 8. Is the total DG reported that of the protein-ligand complex? If that is the case, the affinities of the ligands would be extremely high. They are also very far off from the reported -7 kcal/mol active/inactive cut-off.

We thank Reviewer #2 for this query. We would like to mention that we have provided a detailed explanation in the point-by-point response to Reviewer #2's original comment. Briefly, to clarify, the -7 kcal/mol active/inactive cutoff mentioned in the manuscript refers specifically to the docking-based binding free energies (ΔG) calculated using AutoDock or AutoDock Vina, which are used for compound classification or validation against the Gcoupler framework.

In contrast, the binding free energies reported in Supplementary Figure 8 are obtained through the MM-GBSA method, which provides a more detailed and physics-based estimate of binding affinity by incorporating solvation and enthalpic contributions. It is well-documented in the literature that MM-GBSA tends to systematically underestimate absolute binding free energies when compared to experimental values (10.2174/1568026616666161117112604; Table 1).

Author response image 4.

Scatter plot comparing the predicted binding affinity calculated by Docking and MM/GBSA methods, against experimental ΔG (10.1007/s10822-023-00499-0)

Our use of MM-GBSA is not to match experimental ΔG directly, but rather to assess relative binding preferences among ligands. Despite its limitations in predicting absolute affinities, MM-GBSA is known to perform better than docking for ranking compounds by their binding potential. In this context, an MM-GBSA energy value still reliably indicates stronger predicted binding, even if the numerical values appear extremely higher than typical experimental or docking-derived cutoffs.

Thus, the two energy values, docking-based and MM-GBSA, serve different purposes in our workflow. Docking scores are used for classification and thresholding, while MM-GBSA energies provide post hoc validation and a higher-resolution comparison of binding strength across compounds.

To corroborate their findings, can the authors include direct binding affinity assays for yeast and human Ste2p? This will help in establishing whether the observed phenotypic effects are indeed driven by binding of the metabolites.

We thank Reviewer #2 for raising these insightful questions. During the experimental design phase, we carefully accounted for validating the impact of metabolites in the rescue response by pheromone.

We would like to mention that we performed an array of methods to validate our hypothesis and observed similar rescue effects. These assays include:

a. Cell viability assay (FDA/PI Flourometry- based)

b. Cell growth assay

c. FUN1^TM-based microscopy assessment

d. Shmoo formation assays

e. Mating assays

f. Site-directed mutagenesis-based loss of function

g. Transgenic reporter-based assay

h. MAPK signaling assessment using Western blot.

i. And via computational techniques.

Concerning the in vitro interaction studies of Ste2p and metabolites, we made significant efforts to purify Ste2p by incorporating a His tag at the N-terminal. Despite dedicated attempts over the past year, we were unsuccessful in purifying the protein, primarily due to our limited expertise in protein purification for this specific system. As a result, we opted for genetic-based interventions (e.g., point mutants), which provide a more physiological and comprehensive approach to demonstrating the interaction between Ste2p and the metabolites.

Furthermore, in addition to the clarification above, we have added the following statement in the discussion section to tone down our claims: “A critical limitation of our study is the absence of direct binding assays to validate the interaction between the metabolites and Ste2p. While our results from genetic interventions, molecular dynamics simulations, and docking studies strongly suggest that the metabolites interact with the Ste2p-Gpa1 interface, these findings remain indirect. Direct binding confirmation through techniques such as surface plasmon resonance, isothermal titration calorimetry, or co-crystallization would provide definitive evidence of this interaction. Addressing this limitation in future work would significantly strengthen our conclusions and provide deeper insights into the precise molecular mechanisms underlying the observed phenotypic effects.”

We request Reviewer #2 to kindly refer to the assays conducted on the point mutants created in this study, as these experiments offer robust evidence supporting our claims.

Did the authors perform expression assays to make sure the mutant proteins were similarly expressed to wt?

We thank reviewer #2 for this comment. We would like to mention that:

(1) In our mutants (S75A, T155D, L289K)-based assays, all mutants were generated using integration at the same chromosomal TRP1 locus under the GAL1 promoter and share the same C-terminal CYC1 terminator sequence used for the reconstituted wild-type (rtWT) construct, thus reducing the likelihood of strain-specific expression differences.

(2) Furthermore, all strains were grown under identical conditions using the same media, temperature, and shaking parameters. Each construct underwent the same GAL1 induction protocol in YPGR medium for identical durations, ensuring uniform transcriptional activation across all strains and minimizing culture-dependent variability in protein expression.

(3) Importantly, both the rtWT and two of the mutants (T155D, L289K) retained α-factor-induced cell death (PI and FUN1-based fluorometry and microscopy; Figure 4c-d) and MAPK activation (western blot; Figure 4e), demonstrating that the mutant proteins are expressed at levels sufficient to support signalling.

Reviewer #3 (Recommendations for the authors):

My comments that would enhance the impact of this method are:

(1) While the authors have compared the accuracy and efficiency of Gcoupler to AutoDock Vina, one of the main points of Gcoupler is the neural network module. It would be beneficial to have it evaluated against other available deep learning ligand generative modules, such as the following: 10.1186/s13321-024-00829-w, 10.1039/D1SC04444C.

Thank you for the observation. To clarify, our benchmarking of Gcoupler’s accuracy and efficiency was performed against AutoDock, not AutoDock Vina. This choice was intentional, as AutoDock is one of the most widely used classical techniques in computer-aided drug design (CADD) for obtaining high-resolution predictions of ligand binding energy, binding poses, and detailed atomic-level interactions with receptor residues. In contrast, AutoDock Vina is primarily optimized for large-scale virtual screening, offering faster results but typically with lower resolution and limited configurational detail.

Since Gcoupler is designed to balance accuracy with computational efficiency in structure-based screening, AutoDock served as a more appropriate reference point for evaluating its predictions.

We agree that benchmarking against other deep learning-based ligand generative tools is important for contextualizing Gcoupler’s capabilities. However, it's worth noting that only a few existing methods focus specifically on cavity- or pocket-driven de novo drug design using generative AI, and among them, most are either partially closed-source or limited in functionality.

While PocketCrafter (10.1186/s13321-024-00829-w) offers a structure-based generative framework, it differs from Gcoupler in several key respects. PocketCrafter requires proprietary preprocessing tools, such as the MOE QuickPrep module, to prepare protein pocket structures, limiting its accessibility and reproducibility. In addition, PocketCrafter’s pipeline stops at the generation of cavity-linked compounds and does not support any further learning from the generated data.

Similarly, DeepLigBuilder (10.1039/D1SC04444C) provides de novo ligand generation using deep learning, but the source code is not publicly available, preventing direct benchmarking or customization. Like PocketCrafter, it also lacks integrated learning modules, which limits its utility for screening large, user-defined libraries or compounds of interest.

Additionally, tools like AutoDesigner from Schrödinger, while powerful, are not publicly accessible and hence fall outside the scope of open benchmarking.

Author response table 1.

Comparison of de novo drug design tools. SBDD refers to Structure-Based Drug Design, and LBDD refers to Ligand-Based Drug Design.

In contrast, Gcoupler is a fully open-source, end-to-end platform that integrates both Ligand-Based and Structure-Based Drug Design. It spans from cavity detection and molecule generation to automated model training using GNNs, allowing users to evaluate and prioritize candidate ligands across large chemical spaces without the need for commercial software or advanced coding expertise.

(2) In Figure 2, the authors mention that IC4 and IC5 potential binding sites are on the direct G protein coupling interface ("This led to the identification of 17 potential surface cavities on Ste2p, with two intracellular regions, IC4 and IC5, accounting for over 95% of the Ste2p-Gpa1p interface (Figure 2a-b, Supplementary Figure 4j-n)..."). Later, however, in Figure 4, when discussing which residues affect the binding of the metabolites the most, the authors didn't perform MD simulations of mutant STE2 and just Gpa1p (without metabolites present). It would be beneficial to compare the binding of G protein with and without metabolites present, as these interface mutations might be affecting the binding of G protein by itself.

Thank you for this insightful suggestion. While we did not perform in silico MD simulations of the mutant Ste2-Gpa1 complex in the absence of metabolites, we conducted experimental validation to functionally assess the impact of interface mutations. Specifically, we generated site-directed mutants (S75A, L289K, T155D) and expressed them in a ste2Δ background to isolate their effects.

As shown in the Supplementary Figure, these mutants failed to rescue cells from α-factor-induced programmed cell death (PCD) upon metabolite pre-treatment. This was confirmed through fluorometry-based viability assays, FUN1^TM staining, and p-Fus3 signaling analysis, which collectively monitor MAPK pathway activation (Figure 4c–e).

Importantly, the induction of PCD in response to α-factor in these mutants demonstrates that G protein coupling is still functionally intact, indicating that the mutations do not interfere with Gpa1 binding itself. However, the absence of rescue by metabolites strongly suggests that the mutated residues play a direct role in metabolite binding at the Ste2p–Gpa1p interface, thus modulating downstream signaling.

While further MD simulations could provide structural insight into the isolated mutant receptor–G protein interaction, our experimental data supports the functional relevance of metabolite binding at the identified interface.

(3) While the experiments, performed by the authors, do support the hypothesis that metabolites regulate GPCR signaling, there are no experiments evaluating direct biophysical measurements (e.g., dissociation constants are measured only in silicon).

We thank Reviewer #3 for raising these insightful comments. We would like to mention that we performed an array of methods to validate our hypothesis and observed similar rescue effects. These assays include:

a. Cell viability assay (FDA/PI Flourometry- based)

b. Cell growth assay

c. FUN1^TM-based microscopy assessment

d. Shmoo formation assays

e. Mating assays

f. Site-directed mutagenesis-based loss of function

g. Transgenic reporter-based assay

h. MAPK signaling assessment using Western blot.

i. And via computational techniques.

Concerning the direct biophysical measurements of Ste2p and metabolites, we made significant efforts to purify Ste2p by incorporating a His tag at the N-terminal, with the goal of performing Microscale Thermophoresis (MST) and Isothermal Titration Calorimetry (ITC) measurements. Despite dedicated attempts over the past year, we were unsuccessful in purifying the protein, primarily due to our limited expertise in protein purification for this specific system. As a result, we opted for genetic-based interventions (e.g., point mutants), which provide a more physiological and comprehensive approach to demonstrating the interaction between Ste2p and the metabolites.

Furthermore, in addition to the clarification above, we have added the following statement in the discussion section to tone down our claims: “A critical limitation of our study is the absence of direct binding assays to validate the interaction between the metabolites and Ste2p. While our results from genetic interventions, molecular dynamics simulations, and docking studies strongly suggest that the metabolites interact with the Ste2p-Gpa1 interface, these findings remain indirect. Direct binding confirmation through techniques such as surface plasmon resonance, isothermal titration calorimetry, or co-crystallization would provide definitive evidence of this interaction. Addressing this limitation in future work would significantly strengthen our conclusions and provide deeper insights into the precise molecular mechanisms underlying the observed phenotypic effects.”

(4) The authors do not discuss the effects of the metabolites at their physiological concentrations. Overall, this manuscript represents a field-advancing contribution at the intersection of AI-based ligand discovery and GPCR signaling regulation.

We thank reviewer #3 for this comment and for recognising the value of our work. Although direct quantification of intracellular free metabolite levels is challenging, several lines of evidence support the physiological relevance of our test concentrations.

- Genetic validation supports endogenous relevance: Our genetic screen of 53 metabolic knockout mutants showed that deletions in biosynthetic pathways for these metabolites consistently disrupted the α-factor-induced cell death, with the vast majority of strains (94.4%) resisting the α-factor-induced cell death, and notably, a subset even displayed accelerated growth in the presence of α‑factor. This suggests that endogenous levels of these metabolites normally provide some degree of protection, supporting their physiological role in GPCR regulation.

- Metabolomics confirms in vivo accumulation: Our untargeted metabolomics analysis revealed that α-factor-treated survivors consistently showed enrichment of CoQ6 and zymosterol compared to sensitive cells. This demonstrates that these metabolites naturally accumulate to protective levels during stress responses, validating their biological relevance.

This definition assumes large language datasets and transformer architecture knowledge. Is there are a way to define GPT without assuming these other two terms as they aren't defined in Key Terms?

Should this be Large Language Model vs. just Language Model? Accompanying video refers to it purely as LLM

Could benefit from an example from a volume stand point or complexity stand point what "extremely large" means. Could be subjective

vascular neurocognitive disorder

Version 4 of this preprint has been peer-reviewed and recommended by Peer Community in Ecology.<br /> See the peer reviews and the recommendation.

decentralizations lead to inconsistent approaches, reinforces SAE as default standard

lack of national policy allows for fragmented approach, can lead to inequities in multilingual education, reinforces monolingual norms

fucking insane

Le smartphone devient un objet “toxicomaniaque” : il ne sert plus à communiquer, mais à pallier à une angoisse d’absence. Janssen fait ici le lien entre dépendance numérique et fragilité du moi — la connexion devient une drogue relationnelle.

Janssen applique la théorie de Winnicott au monde numérique : le smartphone, au lieu d’aider à supporter l’absence comme le ferait un objet transitionnel, ne permet pas de la vivre. Il garde la personne dans une impression de présence continue.

En citant Bauman (L’amour liquide, 2004), Janssen montre que la technologie alimente des liens à la fois trop proches et trop éloignés : une illusion de connexion permanente qui masque une distance émotionnelle grandissante.

1. A place in the article where you have a question - try to make the question relevant to things we've been talking about in class, or relevant to your own life and interests.

One of the most significant interests I have is colonial studies. To paraphrase a famous quote from Malcom X, I find it incredibly interesting to examine the wound left by the knife of colonialism, and how it still effects the global south, in spite of the fact that many people refuse to admit that there is a wound. Through this interest I have learned a decent amount of history about many countries, like Botswana, Egypt, Chile; but what's funny to me (as someone who is Arab) is that I have a huge gap in knowledge when it comes to the history (in particular post-ottoman history) of the Arab world, especially the Levant. So the entire time I was reading this article I was searching in my brain to say if there were any particular conflicts in the area, unfortunately there is a nearly infinite amount of those, that she could be referencing but I couldn't put a finger on it.

All this to say, I am very interested to know which conflicts she has personally experienced in the region.

1. A sentence, expression, or paragraph that you felt told a very important and deep truth - what makes this truth important or special to you?

I think this particular quote really hits at something I consider to be very true and does so in a very literarily rich way. Everyone in our class is bilingual but I'm not sure how many people in our class have dual identities like I do. English and Arabic are not just languages to me they represent two very different parts of my identitity and my life, and so her description of the sometimes visceral nature of translation. I experience it every day, I would say about 50% of the Arabic I understand I don't undertsand through the Arabic language itself, it has to be filtered through and translated into English in my head for me to properly understand it. As for when I am speaking, I would say 80% of the Arabic I speak does not come from words or feelings that naturally come to me from the Arabic language, they come to me in English and I have to translate it. In the process, I feel like the words lose their ability to express my emotions, this stripping of their true meaning is what this quote really captures very well.

1. A sentence, expression, or paragraph that you found beautiful - why is it personally beautiful to you?

I found this particular quote beautiful b/c for whatever reason styrofoam is one of those things thats very tactile-ally memorable to me. Its one of those things whose feeling i can instantly imagine once its called to my attention, and the way the auhor uses it here is really beautiful in my opinion. Its such a great way to convey this unique feeling she is describing, where something is both light but still is a burden and awkard to move with.

I see a clear difference between simply eavesdropping on a conversation on a public space and purposefully using technology to tap a telephone call. I think that a textualism approach to the constitution in this case is challenging due to the advancements in technology that have happened since the writing of the constitution.

Hello texualism!

is there a difference between being overheard and being recorded?

What does the constitution think about people being non consensually filmed in a public field and that being used in court?

This makes so much sense! Of course if you find out through the investigation that the suspect is doing bad stuff, you are going to concede that the prior suspicion had due cause.

This argument makes no sense. Of course they didn't burst into the telephone booth, that doesn't give them to the right to listen to any calls.

The difference between a general "right to privacy" and what the court argues is outlined in the 4th amendment is very interesting to me. What privacy does the 4th amendment protect and from who does it protect citizens? The government can't invade our privacy, but can other citizens? What does this mean about private investigators?

Fourth Amendment: protects people from unreasonable searches and seizures. This means that the government cannot search through your belongings without a warrant. This entire case states that the Fourth Amendment protects the people of America (through search and seizure, even in Katz's case).

I am curious about storyboards for two reasons. One, this is a technique I will have to use when building the prototype of my immersive college and career coaching platform. Two, it is interesting that this has to be done once there are already some other brainstormed ideas available. It seems like more of an add-on to some of the other ideas.

This very useful to me because as an introvert, I do not always come up with ideas very quickly. However, once I have something to work from, the ideas do not stop flowing. I have never done this before but I would love to try this method.

If the idea of this is to eliminate fear in sharing, wont the lack of anonymity contribute to the introverts' fear of expressing their ideas? also if this ends in a group discussion, doesn't that mean that the discussion will likely be dominated by a select few? I'm just not sure that this is a reliable method to make sure everyone is included.

This technique has been used in Dr. Ha's classes and is very useful. It has helped me create ideas and flows that are linked to the main idea. This structure has been the most effective for me in ideation creation.

For me this many ideas seems like way too much to process and discuss. To see which ideas would be the most useful would be a long and exhausting process.

The nerves that connet to the CNS and spread throughout the rest of the body

There needs to be an abundance of neurons fired to cause this

This is a bit curious to me because I am wondering if this can become somewhat confusing for the team members. I'd like to see this one in action to see how the switching tactics could help.

I find this strategy useful because many times it is easy to just come up with really wacky ideas. It brings a child-like creativity to the brainstorming process.

I really like this because it highlights the benefit of working with a team and sharing ideas. I think that in academia (and general work environments), learning from others can be overlooked by producing original ideas, so I like the focus on growing from various ideas and diversifying team outcomes and work.

This technique is a little confusing and seems like its solving completely different issues that will still include another brainstorming session to figure out the new problem statement.

I thought this comment is very useful as if you begin to question every aspect of your business, you can always search for improvement and more effective ways to do things to progress your business forward.

what does that mean?

A reflection that touches on feminsim to create a sense of unity with female audience members which will then make them more likely to agree with her as a speaker.

This is a very interesting algorithm choice by Elon Musk, as I find it strange that he made it so interacting with accounts you dislike will cause you too see more of them. The basic concept of it makes any normal person assume that this would deter people from his app "X", but it actually makes sense when you think about how much drama, controversies, and hate is prevalent within that app. I think he is using this strategy to basically "rage bait" people to engaging more with the app by causing them to try to win internet battles, etc.

This source is criticizing how Elon musk is trying to control X by trashing specific accounts that he hates, but the X algorithm is just recommending more things that he hates. Thus, creating a hate filled trash fest of a recommendation that he helped create.

This article talks about systematic bias, which is basically a tendency to operate in ways which result in certain social groups being favored and others being devalued. This is something I had studied in history class, as we had learned about historic examples such as when the U.S. criminal sentencing guidelines created a harsher sentence on cheaper cocaine more common with black communities and people of color, compared to more expensive cocaine which was used in white populations, in order to criminalize POC greater. This is also something which I have seen being used on social media, as recently I have seen a lot of media of illegal immigrants committing crimes on the news and social media platforms, compared to crimes committed by white people.

Echo chambers are often the cause for the creation and execution of extremist ideologies and actions. That said, the ethnicity of moderating such groups could be problematic, as for some ethical frame works, this could violate a common pillar, that of freedom of speech. However, in some other frame works, the need to stop any potential dangers caused by these echo chambers might out weight the need to maintain freedom of speech. However, this then brings into question the extent of control and moderation a governing body should have on any group.

It struck me how relevant this paper is to the chapter’s point that recommendation algorithms don’t just serve content but shape what we see and how we interpret it. The study shows how digital media can drive affective polarization via “partisan sorting” — which nicely connects to the chapter’s warning that algorithms can deepen divisions by reinforcing “you vs them” dynamics.

You tube is a big part in the spreading the idea of the flat Earth to people online. Of course You tube is full of information but also misinformation, but the Youtube algorithm makes it all too easy to funnel users down a conspiracy theory rabbit hole. After interviewing people at fat earth conventions, they found that many of them got the idea from Youtube videos. They propose that the only way to fight misinformation on Youtube is to make accurate, informative videos themselves, which I would argue is happening a lot on You tube today.

I find this loop hole funny. By interacting with accounts you don't like you will see more of them. I also find it interesting that there is no solutions being made to resolve this. Although I think the solution would be for the algorithim to scan what you post which would be weird.

I think this is interesting because this tweet is saying that Twitter thrives off of any kind of engagement, even negative engagement. I think it's interesting how Elon Musk does not make measures to foster a more positive environment on Twitter, instead telling people that they should not stop trashing certain accounts if they don't want their recommendations to be accounts that they would trash.

This article basically talks about the definition and the impact of systemic bias. This bias usually comes from the education and occupation field. It impacts a lot people even when people did not do anything.

This article shocked me. It talks about Target and says that they keep a profile on customers to keep track of what they buy and notice trends in what they buy. They do this tracking so that they can do targeted advertising and send coupons to people for things they think the person may be interested in buying in the future. Specifically this article talks about how Target can figure out when someone is pregnant and they send coupons of baby stuff to the persons house. They did this with a high school girl and her dad got upset about it because he thought it was insensitive to send baby stuff to a high schooler. It turned out the girl was pregnant and her father did not know yet. It is crazy to think that Target was able to figure out that she was pregnant before her dad and that was the reason he found out. I think it is really weird though that they keep track of people's purchases in this way, there is no privacy anymore.

Facebook does not let users opt out of connecting their phone numbers to their accounts. This raises privacy concerns because of how it removes a layer of anonymity. Users have no control over whether they can be searched up or not.

Kelsey D. Altherton's tweet from 2019 stuck with me. I love his sarcasm and point of view with structural problems. I'm tying my own experience with these types of dumb views on structural problems vs personal issues. I grew up in a low income family where my family worked in agriculture, with very very little pay. Where raises were non existent in this workforce despite living in this world of rising prices with anything imaginable. So it was very difficult for groceries, mortgage, taxes, insurance, bills, etc. So I agree with Kelsey, it's definitely not a personal issue nor can it be fixed through the individual.

I always believe that apps or algorithms that are related to a person's own health, including both mental and physical health, should be doubly considered before it is published since they could directly influence a person. If a person doesn't like a social media app, they can just delete it, and it will not affect their personal life much. In this case, this app was continuously recalling the user's sufferings, which largely affected the user's life and mental health.

Systemic bias is a tendency of a particular outcome that favors or disfavors specific social groups. It is interchangeable with the term institutional bias and structural bias. Most of the times, systemic bias is used towards minorities, and it can lead to institutional racism. Due to systemic bias that occurs in organizations, it causes human resource mistreatment and decrease the productivity and viability of organizations.

This part explains that systemic bias means a system unfairly favors some groups over others. It shows how this can lead to problems like institutional racism. I learned that bias can be built into normal rules and routines without people even noticing.

This article outlines how retail companies, in this example, Target, collect customers' data and make assumptions about their personal lives based on what they are buying. This information has shocked and scared customers based on the accuracy of the data and the non-consensual nature of the way these companies are collecting this data.

Many people think that algorithms are just "automatically running numbers", without emotions or biases. However, in this news story, Facebook was investigated by the US Department of Justice for its advertising recommendation system being suspected of discrimination, and later reached a settlement. The real irony is that no one was sitting there manually excluding certain groups; it was just the platform's "optimization logic" that automated, scaled, and executed this bias at a low cost. In other words, discrimination doesn't require a bad person; it only needs an "efficiency-first, click-through rate-king" advertising system. On the surface, it seems to be helping businesses find "the most likely people to see the ads", but in reality, it has set up invisible thresholds in the real world, preventing certain groups from ever seeing the same opportunities. As a result, "technological neutrality" has become a nice-sounding but empty slogan.

Elon musk in this tweet is saying that algorithms are based off of your interactions so if you interact with things that make you upset then the algorithm will show you more of that. I think that he is right, which is the first time anyone has said that ever, people do enjoy getting riled up by things on social media. The thing that he fails to understand is that some people have a right to be angry and express that and because they cant stop themselves does not make them weaker.

This article highlights how the internet is forever even if we don't want it to be. It is interesting to me because although I have always been careful what I post on social media it had never really occurred to me that something could unintentionally go viral and remind me of a bad time in my life forever.

Some strategies I think social media platforms could do to improve recommendations could be an optional section where you could include some of your interests. A different strategy could be consensually analyzing the user and their data to better prescribe things they could be interested in.

Majority of the times, people stay on one video for longer because they are interested at the content of the video. However, what if people continue playing that video just because they are doing something else and not paying attention to the video. I'm curious about wether the platform would count that as the interested content? Does the company only evaluate the amount of time that user spends on one video, or is there other perspective in the evaluation.

Recommendation algorithms have always been sort of a mystery to me. I'm always seeing people on TikTok posting videos such as "How to beat the algorithm", and "how to go viral", so this really shows that it can often be a strategic thing to have the algorithm recommend your content. However one thing I do find it a lot of these algorithm primarily rely on engagement, and how often users are searching for that content, in order to further recommend it to others.

In my own experience, I’ve seen both “good” and “bad” recommendations: one time a platform surfaced a deeply niche topic I had read once and I found it fascinating; another time it repeatedly suggested things totally irrelevant and frankly annoying.

I often use social medias such as intergram to recommend me ad of different clothing brands that I might be interested in, instead of seeking it out myself. I found that by doing my own research for clothing, it has been difficult to find brands that I actually like. However, with the amount of ads along with the algorithm understanding my interests, they often do show me brands and items that I quite like, and would purchase.

I like how reddit reccomends posts for mee based on the topics and communities I follow as well was what posts within those communities are trending.

These algorithms help users to get a better using experience. Without the algorithms, the users might find out the app or the platform is boring. Some of the algorithms can be so complicate, and it gathers most information and data on your platform to perform a better using experience.

My experience with this explanation of what algorithms can do is exactly this. I know with snapchat specifically, I have watched their recommendation algorithm grow significantly over the years. Their saved gallery section now has "x year(s) ago today" which is awesome- I like the recommendation algorithm snapchat has going. Now with instagram, they have something similar but that idea did come off snapchats algorithm,

This section helped me understand how recommendation algorithms decide what content I see online. I was surprised by how many personal factors, like my location and interactions, can influence what gets shown to me. It also makes me think about how much data these platforms collect and how that affects my privacy.

I find it really surprising that social media companies can use the search history from the people around me to recommend me content. By constantly finding content that is relevant to what I was talking about in real life, social media websites can keep me engaged. It's honestly a little dystopian; it makes it seem like every single social media company knows everything about your life and is manipulating you into engaging with their platform.

This recommendation algorithm may seem like something helpful but I think it is part of and facilitates the evil side of social media in my opinion. The evil side of social media that I how found is the addictive side and the way that social media companies go about creating their apps is to make them addictive. The more time users spend on their app the more they can sell ads for and so they want to keep people's attention as long as possible. This recommendation algorithm aids in this by recommending posts to users that it thinks will keep them on the app and get their attention the most.

I love to cook, and I also have celiac disease, which means I can't eat gluten. I've had a good experience with social media sites providing recommendations, such as my Instagram explore page, which often shows me gluten-free dinner or dessert recipes that I actually try and use.

This is so interesting to me. The idea that recommendation algorithms use our data to show us what they think we want to see/buy. In my experience with recommendation algorithms they are fairly accurate and that is a little scary.

why is this?

This tweet my Elon is interesting, because while this could just be me, it feels like Elon is in favor of this "you get more accounts that you hate" mechanic on the site. Makes sense since hate and malice is what gets people to stay on sites longer, but still, its funny how the person with the most power in this situation is actively blaming the user for outcomes completely in his control.

We always emphasize how these social media algorithms let people become addicted to scrolling information streams and wasting all our time. However, we should reflect on who's taking the responsibility to manage our own time. The answer is very clear, ourselves. And what we post on social media should also take responsibility for any consequences, even though the algorithm provided the information. Therefore, I believe it is significant to improve the algorithm and regulate our own behaviors online to create a more friendly and moral virtual society on the platform.

The most heart-wrenching aspect of this statement lies in the fact that it reveals the problem does not stem from a single "bad judge", but rather the entire system itself is inherently biased. In other words, sometimes, without anyone intentionally discriminating, the rules themselves will automatically enforce discrimination, and even make people believe that this is a "normal" or "neutral" procedure.

Dans l'article mettre les liens vers RCF et RadioB https://www.rcf.fr/culture/dans-le-coain https://www.radio-b.fr/la-chronique-du-herisson-286

Dans le chapeau de l'article (en rouge) rajouter mercredi 19 novembre

co-présidente

Companies are almost incentivized to put people in echo chambers because of how that increases time spent in the app. People like to have their beliefs validated. I feel like this could be limiting because of how one's beliefs would never be challenged.

Potential for harm or benefit different for every actor

Realation to bond

SaveFprReference

Relating to semiotics — the study of signs, symbols, and sign processes (how meaning is created, communicated, and interpreted).

symbols and written languages?

through symbolic means or written?

Peculiar to an individual or group; characterized by unique, personal, or quirky traits that deviate from the norm or standard — often in behavior, thinking, language, or style.

Relating to, based on, or expressed through analogy — a comparison between two things that are similar in some respects but otherwise different, used to explain, clarify, or reason about a concept by drawing parallels.

SSS meaning

Involving two or more academic disciplines or fields of study that integrate concepts, methods, theories, or tools to address a common problem, question, or phenomenon — going beyond the boundaries of a single discipline.

Done according to a systematic or orderly plan; characterized by careful organization, step-by-step progression, and attention to detail.

important to have a variety?

different symbol systems

another development to similarities

compare and contrast the two different chapters

finding out what the sss model is intended to do

everything in this block of text is important because it compares and contrasts and gives us insight to the similarities between two scholars

ex from the reading

Social relational ?

the volumes had a bunch of diversity and a ton of different opinions represented

another name Lev Vygotsky, a soviet psychologist

more books and volumes by jean Piaget society.

conference with 2 to 4 leading scholars

first book mentioned

Never done or known before; without previous example or precedent.

what is she referring to when talking about the information age

Her first point in making that we are not sheltered from tons of information and change through various sources

what is a RRQ reader?

the book is not mainstream and rather a different type of research?

giving them a warning as to say there is so much information available that it might interfere with their opinion or research?

The Jean Piaget Society: Society for the Study of Knowledge and Development is an international, interdisciplinary organization dedicated to exploring the developmental construction of human knowledge. Established in 1970, it draws inspiration from the work of Swiss developmental psychologist Jean Piaget (1896–1980), who pioneered theories on cognitive development, genetic epistemology, and the active role of children in constructing knowledge. piaget.org for membership, conference details, and resources.

Question: How do you know your device has malware? Such as a phone or tablet.

Question: I have done this before in the past to free up space on computer, but I still see popups related to searches even if I clear my cache and cookies. Are the cookies always going to generate personal ads based on what I searched even if cleared?

Comment: I never really considered cookies to be the reason why I see relevant topics on other websites. For example, when I google something and then two minutes later see it on my tiktok I always joke "our phones can hear us" but no, it's actually us looking it up and the cookies generating it across platforms.

spaces...and time

Often tools are hidden and teachers do not know that it is provided so they end up getting by as they have always done.

does the tool provide ways for teachers to collaborate?

This is something that is often overlooks. I've been in organizations that have tools that ultimately do the same thing

Eixo X com dados replicados

Números posicionados de maneira errada em cima das barras

contraste do label em cima do cinza.

Are many cultural issues just derivative of economic issues?

But, what changed?

I live in the north

I wonder what do Pytheas’s travels in 330 BCE reveal about early exploration?

It’s crazy to see that the Vikings didn’t just raid but they reshaped Europe and helped bring an end tot he powerful dynasty.

Something I found interesting about this is how Hawala shows how early global trade relied on trust long before banks even existed.

It’s interesting how by 750, the Umayyad Caliphate had created one of the largest empires in history.

1. A post should be shown to a user if they have designated in a list selection that those kinds of posts are something they want to see. If a video falls outside those parameters hide it from them.

2. Show a post to a user if it is similar to posts that they have interacted with in the past. In either subject, tag, creator, etc.

QG diagnostics of real (current) weather

here, and again below, it is "ethical disciple" not "discipline" that translates tshul khrims/ śīla. So please make the glossary entry tag the whole term "ethical discipline"

eLife Assessment

This study provides valuable insights into the evolutionary conservation of sex determination mechanisms in ants by identifying a candidate sex-determining region in a parthenogenetic species. It uses solid, well-executed genomic analyses based on differences in heterozygosity between females and diploid males. While the candidate locus awaits functional validation in this species, the study provides convincing support for the ancient origin of a non-coding locus implicated in sex determination.

Reviewer #1 (Public review):

The authors have implemented several clarifications in the text and improved the connection between their findings and previous work. As stated in my initial review, I had no major criticisms of the previous version of the manuscript, and I continue to consider this a solid and well-written study. However, the revised manuscript still largely reiterates existing findings and does not offer novel conceptual or experimental advances. It supports previous conclusions suggesting a likely conserved sex determination locus in aculeate hymenopterans, but does so without functional validation (i.e., via experimental manipulation) of the candidate locus in O. biroi. I also wish to clarify that I did not intend to imply that functional assessments in the Pan et al. study were conducted in more than one focal species; my previous review explicitly states that the locus's functional role was validated in the Argentine ant.

Reviewer #3 (Public review):

The authors have made considerable efforts to conduct functional analyses to the fullest extent possible in this study; however, it is understandable that meaningful results have not yet been obtained. In the revised version, they have appropriately framed their claims within the limits of the current data and have adjusted their statements as needed in response to the reviewers' comments.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1 (Public review):

This study investigates the sex determination mechanism in the clonal ant Ooceraea biroi, focusing on a candidate complementary sex determination (CSD) locus-one of the key mechanisms supporting haplodiploid sex determination in hymenopteran insects. Using whole genome sequencing, the authors analyze diploid females and the rarely occurring diploid males of O. biroi, identifying a 46 kb candidate region that is consistently heterozygous in females and predominantly homozygous in diploid males. This region shows elevated genetic diversity, as expected under balancing selection. The study also reports the presence of an lncRNA near this heterozygous region, which, though only distantly related in sequence, resembles the ANTSR lncRNA involved in female development in the Argentine ant, Linepithema humile (Pan et al. 2024). Together, these findings suggest a potentially conserved sex determination mechanism across ant species. However, while the analyses are well conducted and the paper is clearly written, the insights are largely incremental. The central conclusion - that the sex determination locus is conserved in ants - was already proposed and experimentally supported by Pan et al. (2024), who included O. biroi among the studied species and validated the locus's functional role in the Argentine ant. The present study thus largely reiterates existing findings without providing novel conceptual or experimental advances.

Although it is true that Pan et al., 2024 demonstrated (in Figure 4 of their paper) that the synteny of the region flanking ANTSR is conserved across aculeate Hymenoptera (including O. biroi), Reviewer 1’s claim that that paper provides experimental support for the hypothesis that the sex determination locus is conserved in ants is inaccurate. Pan et al., 2024 only performed experimental work in a single ant species (Linepithema humile) and merely compared reference genomes of multiple species to show synteny of the region, rather than functionally mapping or characterizing these regions.

Other comments:

The mapping is based on a very small sample size: 19 females and 16 diploid males, and these all derive from a single clonal line. This implies a rather high probability for false-positive inference. In combination with the fact that only 11 out of the 16 genotyped males are actually homozygous at the candidate locus, I think a more careful interpretation regarding the role of the mapped region in sex determination would be appropriate. The main argument supporting the role of the candidate region in sex determination is based on the putative homology with the lncRNA involved in sex determination in the Argentine ant, but this argument was made in a previous study (as mentioned above).

Our main argument supporting the role of the candidate region in sex determination is not based on putative homology with the lncRNA in L. humile. Instead, our main argument comes from our genetic mapping (in Fig. 2), and the elevated nucleotide diversity within the identified region (Fig. 4). Additionally, we highlight that multiple genes within our mapped region are homologous to those in mapped sex determining regions in both L. humile and Vollenhovia emeryi, possibly including the lncRNA.

In response to the Reviewer’s assertion that the mapping is based on a small sample size from a single clonal line, we want to highlight that we used all diploid males available to us. Although the primary shortcoming of a small sample size is to increase the probability of a false negative, small sample sizes can also produce false positives. We used two approaches to explore the statistical robustness of our conclusions. First, we generated a null distribution by randomly shuffling sex labels within colonies and calculating the probability of observing our CSD index values by chance (shown in Fig. 2). Second, we directly tested the association between homozygosity and sex using Fisher’s Exact Test (shown in Supplementary Fig. S2). In both cases, the association of the candidate locus with sex was statistically significant after multiple-testing correction using the Benjamini-Hochberg False Discovery Rate. These approaches are clearly described in the “CSD Index Mapping” section of the Methods.

We also note that, because complementary sex determination loci are expected to evolve under balancing selection, our finding that the mapped region exhibits a peak of nucleotide diversity lends orthogonal support to the notion that the mapped locus is indeed a complementary sex determination locus.

The fourth paragraph of the results and the sixth paragraph of the discussion are devoted to explaining the possible reasons why only 11/16 genotyped males are homozygous in the mapped region. The revised manuscript will include an additional sentence (in what will be lines 384-388) in this paragraph that includes the possible explanation that this locus is, in fact, a false positive, while also emphasizing that we find this possibility to be unlikely given our multiple lines of evidence.

In response to Reviewer 1’s suggestion that we carefully interpret the role of the mapped region in sex determination, we highlight our careful wording choices, nearly always referring to the mapped locus as a “candidate sex determination locus” in the title and throughout the manuscript. For consistency, the revised manuscript version will change the second results subheading from “The O. biroi CSD locus is homologous to another ant sex determination locus but not to honeybee csd” to “O. biroi’s candidate CSD locus is homologous to another ant sex determination locus but not to honeybee csd,” and will add the word “candidate” in what will be line 320 at the beginning of the Discussion, and will change “putative” to “candidate” in what will be line 426 at the end of the Discussion.

In the abstract, it is stated that CSD loci have been mapped in honeybees and two ant species, but we know little about their evolutionary history. But CSD candidate loci were also mapped in a wasp with multi-locus CSD (study cited in the introduction). This wasp is also parthenogenetic via central fusion automixis and produces diploid males. This is a very similar situation to the present study and should be referenced and discussed accordingly, particularly since the authors make the interesting suggestion that their ant also has multi-locus CSD and neither the wasp nor the ant has tra homologs in the CSD candidate regions. Also, is there any homology to the CSD candidate regions in the wasp species and the studied ant?

In response to Reviewer 1’s suggestion that we reference the (Matthey-Doret et al. 2019) study in the context of diploid males being produced via losses of heterozygosity during asexual reproduction, the revised manuscript will include (in what will be lines 123-126) the highlighted portion of the following sentence: “Therefore, if O. biroi uses CSD, diploid males might result from losses of heterozygosity at sex determination loci (Fig. 1C), similar to what is thought to occur in other asexual Hymenoptera that produce diploid males (Rabeling and Kronauer 2012; Matthey-Doret et al. 2019).”

We note, however, that in their 2019 study, Matthey-Doret et al. did not directly test the hypothesis that diploid males result from losses of heterozygosity at CSD loci during asexual reproduction, because the diploid males they used for their mapping study came from inbred crosses in a sexual population of that species.

We address this further below, but we want to emphasize that we do not intend to argue that O. biroi has multiple CSD loci. Instead, we suggest that additional, undetected CSD loci is one possible explanation for the absence of diploid males from any clonal line other than clonal line A. In response to Reviewer 1’s suggestion that we reference the (Matthey-Doret et al. 2019) study in the context of multilocus CSD, the revised manuscript version will include the following additional sentence in the fifth paragraph of the discussion (in what will be lines 372-374): “Multi-locus CSD has been suggested to limit the extent of diploid male production in asexual species under some circumstances (Vorburger 2013; Matthey-Doret et al. 2019).”

Regarding Reviewer 2’s question about homology between the putative CSD loci from the (Matthey-Doret et al. 2019) study and O. biroi, we note that there is no homology. The revised manuscript version will have an additional Supplementary Table (which will be the new Supplementary Table S3) that will report the results of this homology search. The revised manuscript will also include the following additional sentence in the Results, in what will be lines 172-174: “We found no homology between the genes within the O. biroi CSD index peak and any of the genes within the putative L. fabarum CSD loci (Supplementary Table S3).”

The authors used different clonal lines of O. biroi to investigate whether heterozygosity at the mapped CSD locus is required for female development in all clonal lines of O. biroi (L187-196). However, given the described parthenogenesis mechanism in this species conserves heterozygosity, additional females that are heterozygous are not very informative here. Indeed, one would need diploid males in these other clonal lines as well (but such males have not yet been found) to make any inference regarding this locus in other lines.

We agree that a full mapping study including diploid males from all clonal lines would be preferable, but as stated earlier in that same paragraph, we have only found diploid males from clonal line A. We stand behind our modest claim that “Females from all six clonal lines were heterozygous at the CSD index peak, consistent with its putative role as a CSD locus in all O. biroi.” In the revised manuscript version, this sentence (in what will be lines 199-201) will be changed slightly in response to a reviewer comment below: “All females from all six clonal lines (including 26 diploid females from clonal line B) were heterozygous at the CSD index peak, consistent with its putative role as a CSD locus in all O. biroi.”

Reviewer #2 (Public review):

The manuscript by Lacy et al. is well written, with a clear and compelling introduction that effectively conveys the significance of the study. The methods are appropriate and well-executed, and the results, both in the main text and supplementary materials, are presented in a clear and detailed manner. The authors interpret their findings with appropriate caution.

This work makes a valuable contribution to our understanding of the evolution of complementary sex determination (CSD) in ants. In particular, it provides important evidence for the ancient origin of a non-coding locus implicated in sex determination, and shows that, remarkably, this sex locus is conserved even in an ant species with a non-canonical reproductive system that typically does not produce males. I found this to be an excellent and well-rounded study, carefully analyzed and well contextualized.

That said, I do have a few minor comments, primarily concerning the discussion of the potential 'ghost' CSD locus. While the authors acknowledge (line 367) that they currently have no data to distinguish among the alternative hypotheses, I found the evidence for an additional CSD locus presented in the results (lines 261-302) somewhat limited and at times a bit difficult to follow. I wonder whether further clarification or supporting evidence could already be extracted from the existing data. Specifically:

We agree with Reviewer 2 that the evidence for a second CSD locus is limited. In fact, we do not intend to advocate for there being a second locus, but we suggest that a second CSD locus is one possible explanation for the absence of diploid males outside of clonal line A. In our initial version, we intentionally conveyed this ambiguity by titling this section “O. biroi may have one or multiple sex determination loci.” However, we now see that this leads to undue emphasis on the possibility of a second locus. In the revised manuscript, we will split this into two separate sections: “Diploid male production differs across O. biroi clonal lines” and “O. biroi lacks a tra-containing CSD locus.”

(1) Line 268: I doubt the relevance of comparing the proportion of diploid males among all males between lines A and B to infer the presence of additional CSD loci. Since the mechanisms producing these two types of males differ, it might be more appropriate to compare the proportion of diploid males among all diploid offspring. This ratio has been used in previous studies on CSD in Hymenoptera to estimate the number of sex loci (see, for example, Cook 1993, de Boer et al. 2008, 2012, Ma et al. 2013, and Chen et al., 2021). The exact method might not be applicable to clonal raider ants, but I think comparing the percentage of diploid males among the total number of (diploid) offspring produced between the two lineages might be a better argument for a difference in CSD loci number.

We want to re-emphasize here that we do not wish to advocate for there being two CSD loci in O. biroi. Rather, we want to explain that this is one possible explanation for the apparent absence of diploid males outside of clonal line A. We hope that the modifications to the manuscript described in the previous response help to clarify this.

Reviewer 2 is correct that comparing the number of diploid males to diploid females does not apply to clonal raider ants. This is because males are vanishingly rare among the vast numbers of females produced. We do not count how many females are produced in laboratory stock colonies, and males are sampled opportunistically. Therefore, we cannot report exact numbers. However, we will add the highlighted portion of the following sentence (in what will be lines 268-270) to the revised manuscript: “Despite the fact that we maintain more colonies of clonal line B than of clonal line A in the lab, all the diploid males we detected came from clonal line A.”

(2) If line B indeed carries an additional CSD locus, one would expect that some females could be homozygous at the ANTSR locus but still viable, being heterozygous only at the other locus. Do the authors detect any females in line B that are homozygous at the ANTSR locus? If so, this would support the existence of an additional, functionally independent CSD locus.

We thank the reviewer for this suggestion, and again we emphasize that we do not want to argue in favor of multiple CSD loci. We just want to introduce it as one possible explanation for the absence of diploid males outside of clonal line A.

The 26 sequenced diploid females from clonal line B are all heterozygous at the mapped locus, and the revised manuscript will clarify this in what will be lines 199-201. Previously, only six of those diploid females were included in Supplementary Table S2, and that will be modified accordingly.

(3) Line 281: The description of the two tra-containing CSD loci as "conserved" between Vollenhovia and the honey bee may be misleading. It suggests shared ancestry, whereas the honey bee csd gene is known to have arisen via a relatively recent gene duplication from fem/tra (10.1038/nature07052). It would be more accurate to refer to this similarity as a case of convergent evolution rather than conservation.

In the sentence that Reviewer 2 refers to, we are representing the assertion made in the (Miyakawa and Mikheyev 2015) paper in which, regarding their mapping of a candidate CSD locus that contains two linked tra homologs, they write in the abstract: “these data support the prediction that the same CSD mechanism has indeed been conserved for over 100 million years.” In that same paper, Miyakawa and Mikheyev write in the discussion section: “As ants and bees diverged more than 100 million years ago, sex determination in honey bees and V. emeryi is probably homologous and has been conserved for at least this long.”

As noted by Reviewer 2, this appears to conflict with a previously advanced hypothesis: that because fem and csd were found in Apis mellifera, Apis cerana, and Apis dorsata, but only fem was found in Mellipona compressipes, Bombus terrestris, and Nasonia vitripennis, that the csd gene evolved after the honeybee (Apis) lineage diverged from other bees (Hasselmann et al. 2008). However, it remains possible that the csd gene evolved after ants and bees diverged from N. vitripennis, but before the divergence of ants and bees, and then was subsequently lost in B. terrestris and M. compressipes. This view was previously put forward based on bioinformatic identification of putative orthologs of csd and fem in bumblebees and in ants [(Schmieder et al. 2012), see also (Privman et al. 2013)]. However, subsequent work disagreed and argued that the duplications of tra found in ants and in bumblebees represented convergent evolution rather than homology (Koch et al. 2014). Distinguishing between these possibilities will be aided by additional sex determination locus mapping studies and functional dissection of the underlying molecular mechanisms in diverse Aculeata.

Distinguishing between these competing hypotheses is beyond the scope of our paper, but the revised manuscript will include additional text to incorporate some of this nuance. We will include these modified lines below (in what will be lines 287-295), with the additions highlighted:

“A second QTL region identified in V. emeryi (V.emeryiCsdQTL1) contains two closely linked tra homologs, similar to the closely linked honeybee tra homologs, csd and fem (Miyakawa and Mikheyev 2015). This, along with the discovery of duplicated tra homologs that undergo concerted evolution in bumblebees and ants (Schmieder et al. 2012; Privman et al. 2013) has led to the hypothesis that the function of tra homologs as CSD loci is conserved with the csd-containing region of honeybees (Schmieder et al. 2012; Miyakawa and Mikheyev 2015). However, other work has suggested that tra duplications occurred independently in honeybees, bumblebees, and ants (Hasselmann et al. 2008; Koch et al. 2014), and it remains to be demonstrated that either of these tra homologs acts as a primary CSD signal in V. emeryi.”

(4) Finally, since the authors successfully identified multiple alleles of the first CSD locus using previously sequenced haploid males, I wonder whether they also observed comparable allelic diversity at the candidate second CSD locus. This would provide useful supporting evidence for its functional relevance.

As is already addressed in the final paragraph of the results and in Supplementary Fig. S4, there is no peak of nucleotide diversity in any of the regions homologous to V.emeryiQTL1, which is the tra-containing candidate sex determination locus (Miyakawa and Mikheyev 2015). In the revised manuscript, the relevant lines will be 307-310. We want to restate that we do not propose that there is a second candidate CSD locus in O. biroi, but we simply raise the possibility that multi-locus CSD *might* explain the absence of diploid males from clonal lines other than clonal line A (as one of several alternative possibilities).

Overall, these are relatively minor points in the context of a strong manuscript, but I believe addressing them would improve the clarity and robustness of the authors' conclusions.

Reviewer #3 (Public review):

Summary:

The sex determination mechanism governed by the complementary sex determination (CSD) locus is one of the mechanisms that support the haplodiploid sex determination system evolved in hymenopteran insects. While many ant species are believed to possess a CSD locus, it has only been specifically identified in two species. The authors analyzed diploid females and the rarely occurring diploid males of the clonal ant Ooceraea biroi and identified a 46 kb CSD candidate region that is consistently heterozygous in females and predominantly homozygous in males. This region was found to be homologous to the CSD locus reported in distantly related ants. In the Argentine ant, Linepithema humile, the CSD locus overlaps with an lncRNA (ANTSR) that is essential for female development and is associated with the heterozygous region (Pan et al. 2024). Similarly, an lncRNA is encoded near the heterozygous region within the CSD candidate region of O. biroi. Although this lncRNA shares low sequence similarity with ANTSR, its potential functional involvement in sex determination is suggested. Based on these findings, the authors propose that the heterozygous region and the adjacent lncRNA in O. biroi may trigger female development via a mechanism similar to that of L. humile. They further suggest that the molecular mechanisms of sex determination involving the CSD locus in ants have been highly conserved for approximately 112 million years. This study is one of the few to identify a CSD candidate region in ants and is particularly noteworthy as the first to do so in a parthenogenetic species.

Strengths:

(1) The CSD candidate region was found to be homologous to the CSD locus reported in distantly related ant species, enhancing the significance of the findings.

(2) Identifying the CSD candidate region in a parthenogenetic species like O. biroi is a notable achievement and adds novelty to the research.

Weaknesses

(1) Functional validation of the lncRNA's role is lacking, and further investigation through knockout or knockdown experiments is necessary to confirm its involvement in sex determination.

See response below.

(2) The claim that the lncRNA is essential for female development appears to reiterate findings already proposed by Pan et al. (2024), which may reduce the novelty of the study.

We do not claim that the lncRNA is essential for female development in O. biroi, but simply mention the possibility that, as in L. humile, it is somehow involved in sex determination. We do not have any functional evidence for this, so this is purely based on its genomic position immediately adjacent to our mapped candidate region. We agree with the reviewer that the study by Pan et al. (2024) decreases the novelty of our findings. Another way of looking at this is that our study supports and bolsters previous findings by partially replicating the results in a different species.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

L307-308 should state homozygous for either allele in THE MAJORITY of diploid males.

This will be fixed in the revised manuscript, in what will be line 321.

Reviewer #3 (Recommendations for the authors):

The association between heterozygosity in the CSD candidate region and female development in O. biroi, along with the high sequence homology of this region to CSD loci identified in two distantly related ant species, is not sufficient to fully address the evolution of the CSD locus and the mechanisms of sex determination.

Given that functional genetic tools, such as genome editing, have already been established in O. biroi, I strongly recommend that the authors investigate the role of the lncRNA through knockout or knockdown experiments and assess its impact on the sex-specific splicing pattern of the downstream tra gene.

Although knockout experiments of the lncRNA would be illuminating, the primary signal of complementary sex determination is heterozygosity. As is clearly stated in our manuscript and that of (Pan et al. 2024), it does not appear to be heterozygosity within the lncRNA that induces female development, but rather heterozygosity in non-transcribed regions linked to the lncRNA. Therefore, future mechanistic studies of sex determination in O. biroi, L. humile, and other ants should explore how homozygosity or heterozygosity of this region impacts the sex determination cascade, rather than focusing (exclusively) on the lncRNA.

With this in mind, we developed three sets of guide RNAs that cut only one allele within the mapped CSD locus, with the goal of producing deletions within the highly variable region within the mapped locus. This would lead to functional hemizygosity or homozygosity within this region, depending on how the cuts were repaired. We also developed several sets of PCR primers to assess the heterozygosity of the resultant animals. After injecting 1,162 eggs over several weeks and genotyping the hundreds of resultant animals with PCR, we confirmed that we could induce hemizygosity or homozygosity within this region, at least in ~1/20 of the injected embryos. Although it is possible to assess the sex-specificity of the splice isoform of tra as a proxy for sex determination phenotypes (as done by (Pan et al. 2024)), the ideal experiment would assess male phenotypic development at the pupal stage. Therefore, over several more weeks, we injected hundreds more eggs with these reagents and reared the injected embryos to the pupal stage. However, substantial mortality was observed, with only 12 injected eggs developing to the pupal stage. All of these were female, and none of them had been successfully mutated.

In conclusion, we agree with the reviewer that functional experiments would be useful, and we made extensive attempts to conduct such experiments. However, these experiments turned out to be extremely challenging with the currently available protocols. Ultimately, we therefore decided to abandon these attempts.  

We opted not to include these experiments in the paper itself because we cannot meaningfully interpret their results. However, we are pleased that, in this response letter, we can include a brief description for readers interested in attempting similar experiments.

Since O. biroi reproduces parthenogenetically and most offspring develop into females, observing a shift from female- to male-specific splicing of tra upon early embryonic knockout of the lncRNA would provide much stronger evidence that this lncRNA is essential for female development. Without such functional validation, the authors' claim (lines 36-38) seems to reiterate findings already proposed by Pan et al. (2024) and, as such, lacks sufficient novelty.

We have responded to the issue of “lack of novelty” above. But again, the actual CSD locus in both O. biroi and L. humile appears to be distinct from (but genetically linked to) the lncRNA, and we have no experimental evidence that the putative lncRNA in O. biroi is involved in sex determination at all. Because of this, and given the experimental challenges described above, we do not currently intend to pursue functional studies of the lncRNA.

References

Hasselmann M, Gempe T, Schiøtt M, Nunes-Silva CG, Otte M, Beye M. 2008. Evidence for the evolutionary nascence of a novel sex determination pathway in honeybees. Nature 454:519–522.

Koch V, Nissen I, Schmitt BD, Beye M. 2014. Independent Evolutionary Origin of fem Paralogous Genes and Complementary Sex Determination in Hymenopteran Insects. PLOS ONE 9:e91883.

Matthey-Doret C, van der Kooi CJ, Jeffries DL, Bast J, Dennis AB, Vorburger C, Schwander T. 2019. Mapping of multiple complementary sex determination loci in a parasitoid wasp. Genome Biology and Evolution 11:2954–2962.

Miyakawa MO, Mikheyev AS. 2015. QTL mapping of sex determination loci supports an ancient pathway in ants and honey bees. PLOS Genetics 11:e1005656.

Pan Q, Darras H, Keller L. 2024. LncRNA gene ANTSR coordinates complementary sex determination in the Argentine ant. Science Advances 10:eadp1532.

Privman E, Wurm Y, Keller L. 2013. Duplication and concerted evolution in a master sex determiner under balancing selection. Proceedings of the Royal Society B: Biological Sciences 280:20122968.

Rabeling C, Kronauer DJC. 2012. Thelytokous parthenogenesis in eusocial Hymenoptera. Annual Review of Entomology 58:273–292.

Schmieder S, Colinet D, Poirié M. 2012. Tracing back the nascence of a new sex-determination pathway to the ancestor of bees and ants. Nature Communications 3:1–7.

Vorburger C. 2013. Thelytoky and Sex Determination in the Hymenoptera: Mutual Constraints. Sexual Development 8:50–58.

aportacion 3

Primero se define qué quieres investigar objetivo, y de ahí sale el título.

Si el título no coincide con lo que realmente se hizo, confunde al lector y resta credibilidad.

Aportacion 2 en la parte de que te exijan títulos supe cortos está bien hasta que te das cuenta de que terminas diciendo cualquier cosa. Es como cuando resumes una película y solo dices trata de algun problema.. pues sí pero no se entiende nada Mejor que sobre una palabra a que falte claridad.

aportacion 1 Criticar un título por ser demasiado largo es como quejarse de un mapa por ser demasiado detallado. El verdadero problema no es la cantidad de palabras, sino si cada una de ellas es necesaria para no perder el rumbo. Prefiero un título de 25 palabras que me lleve exactamente al destino, que uno de 10 que me deje a mitad del camino.

this is going over a girl with poor time managements.

talking about the poor time management skills.

Oportunidades profesionales en BSI

effeminate men

seems to contradict the above

concept of nobility as stemming from heroic acts

locate this

great causal walk-through

the lightest is associated with essence and spirit

how rain happens

cf oxygen isotopes! lol

so this describes the fit between constitutions and waters

martinez

sanchez

eLife Assessment

The manuscript presents important findings that advance our understanding of how microglia adapt their surveillance strategies during chronic neurodegeneration. The evidence presented is convincing, with appropriate and validated methodology broadly supporting the claims given by the authors.

Reviewer #1 (Public review):

Summary:

In this manuscript, Subhramanian et al. carefully examined how microglia adapt their surveillance strategies during chronic neurodegeneration, specifically in prion-infected mice. The authors used ex vivo time-lapse imaging and in vitro strategies, finding that reactive microglia exhibit a highly mobile, "kiss-and-ride" behavior, which contrasts with the more static surveillance typically observed in homeostatic microglia. The manuscript provides fundamental mechanistic insights into the dynamics of microglia-neuron interactions, implicates P2Y6 signaling in regulating mobility, and suggests that intrinsic reprogramming of microglia might underlie this behavior. The conclusions are therefore compelling.

Strengths:

(1) The novelty of the study is high, in particular, the demonstration that microglia lose territorial confinement and dynamically migrate from neuron to neuron under chronic neurodegeneration.

(2) The possible implications of a stimulus-independent high mobility in reactive microglia are particularly striking. Although this is not fully explored (see comments below).

(3) The use of time-lapse imaging in organotypic slices rather than overexpression models provided a more physiological approach.

(4) Microglia-neuron interactions in neurodegeneration have broad implications for understanding the progression of other diseases that are associated with chronic inflammation, such as Alzheimer's and Parkinson's.

Weaknesses:

(1) The Cx3cr1/EGFP line labels all myeloid cells, which makes it difficult to conclude that all observed behaviors are attributable to microglia rather than infiltrating macrophages. The authors refer to this and include it as a limitation. Nonetheless, complementary confirmation by additional microglia markers would strengthen their claims.

(2) Although the authors elegantly describe dynamic surveillance and envelopment hypothesis, it is unclear what the role of this phenotype is for disease progression, i.e., functional consequences. For example, are the neurons that undergo sustained envelopment more likely to degenerate?

(3) Moreover, although the increase in mobility is a relevant finding, it would be interesting for the authors to further comment on what the molecular trigger(s) is/are that might promote this increase. These adaptations, which are at least long-lasting, confer apparent mobility in the absence of external stimuli.

(4) The authors performed, as far as I could understand, the experiments in cortical brain regions. There is no clear rationale for this in the manuscript, nor is it clear whether the mobility is specific to a particular brain region. This is particularly important, as microglia reactivity varies greatly depending on the brain region.

(5) It would be relevant information to have an analysis of the percentage of cells in normal, sub-clinical, early clinical, and advanced stages that became mobile. Without this information, the speed/distance alone can have different interpretations.

Reviewer #2 (Public review):

This is a nice paper focused on the response of microglia to different clinical stages of prion infection in acute brain slices. The key here is the use of time-lapse imaging, which captures the dynamics of microglial surveillance, including morphology, migration, and intracellular neuron-microglial contacts. The authors use a myeloid GFP-labeled transgenic mouse to track microglia in SSLOW-infected brain slices, quantifying differences in motility and microglial-neuron interactions via live fluorescence imaging. Interesting findings include the elaborate patterns of motility among microglia, the distinct types and duration of intracellular contacts, the potential role of calcium signaling in facilitating hypermobility, and the fact that this motion-promoting status is intrinsic to microglia, persisting even after the cells have been isolated from infected brains. Although largely a descriptive paper, there are mechanistic insights, including the role of calcium in supporting movement of microglia, where bursts of signaling are identified even within the time-lapse format, and inhibition studies that implicate the purinergic receptor and calcium transient regulator P2Y6 in migratory capacity.

Strengths:

(1) The focus on microglia activation and activity in the context of prion disease is interesting.

(2) Two different prions produce largely the same response.

(3) Use of time-lapse provides insight into the dynamics of microglia, distinguishing between types of contact - mobility vs motility - and providing insight into the duration/transience and reversibility of extensive somatic contacts that include brief and focused connections in addition to soma envelopment.

(4) Imaging window selection (3 hours) guided by prior publications documenting preserved morphology, activity, and gene expression regulation up to 4 hours.

(5) The distinction between high mobility and low mobility microglia is interesting, especially given that hyper mobility seems to be an innate property of the cells.

(6) The live-imaging approach is validated by fixed tissue confocal imaging.

(7) The variance in duration of neuron/microglia contacts is interesting, although there is no insight into what might dictate which status of interaction predominates.

(8) The reversibility of the enveloping action, that is not apparently a commitment to engulfment, is interesting, as is the fact that only neurons are selected for this activity.

(9) The calcium studies use the fluorescent dye calbryte-590 to pick up neuronal and microglial bursts - prolonged bursts are detected in enveloped neurons and in the hyper-mobile microglia - the microglial lead is followed up using MRS-2578 P2Y6 inhibitor that blunts the mobility of the microglia.

Weaknesses:

(1) The number of individual cells tracked has been provided, but not the number of individual mice. The sex of the mice is not provided.

(2) The statistical approach is not clear; was each cell treated as a single observation?

(3) The potential for heterogeneity among animals has not been addressed.

(4) Validation of prion accumulation at each clinical stage of the disease is not provided.

(5) How were the numerous captures of cells handled to derive morphological quantitative values? Based on the videos, there is a lot of movement and shape-shifting.

(6) While it is recognized that there are limits to what can be measured simultaneously with live imaging, the authors appear to have fixed tissues from each time point too - it would be very interesting to know if the extent or prion accumulation influences the microglial surveillance - i.e., do the enveloped ones have greater pathology>

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Tolong kirim

to define this for my second defining annotation: an eruption of the body in this context refers to disease, such as a rash, abrasion, or infection. -cherryb history 211

I felt another annotation of this was important because I think while this Author describes deplorable conditions and struggles such as inadequate food, and rough seas, i cant help but think of the deplorable conditions discussed in the previous chapters abord the salve ships. Those people were subjected to things far worse than this, with little to no food at all, cramped conditions, rampant sickness, and they did not have the ability to fully stand in some instances let alone lay down. It is wild to think about the privilege of this man in comparison, despite his self proclaimed inconveniences and experiences. -cherryb history 211

This highlights the relationship with religion the author has, with him also citing psalm 107 earlier in the text. He claims that it is God that has allowed the boat to stay together and arrive in one peace, noting that if they did not do so, it was the devil's or the "evil ones" doing. So, not so much luck, or the work of the captain and crew. but divine intervention. -cherryb history 211

This part of the article describes the mental toll being at sea and working the boat had on the members of the crew during this time. Was it a form of post traumatic stress, or was it side effects from spoiled food.. I desire more context on what insanity looked like or really was, as we understand within a modern lens, that the understanding of insanity and mental illness were very different historically. I think a perspective we are missing is the crew members of the boat, and if the crew member who was deemed insane had the faculties to write, his perspective might be vital in understanding the voyage form a crew memebers perspective. Cherryb history 211

This shows that the rough seas, storms, and sickness were not only the things faced, but the rations were horrible. He describes the salted fish and meats as "rancid smelling". I also think, contextually, it is interesting to see that beer was considered an essential part of rations. There is a mention of fresh water, but its fascinating to me that the amount of beer given in rations exceeds the allocation of water twofold. What were the beliefs surrounding alcohol at this time, was it believed to have supplemental health effects? - cherryb history 211

This is interesting because it provides us with the historical context that some passengers abord this ship did not have the same destination as others, some chose to get oof the boat early at Upton instead of getting off at Philadelphia, like the author. He states that getting off at Upland would arguably be more unpleasant, citing many inconveniences. What kind of inconveniences is he referring to, I wonder? - cherry b history 211

one of two annotations defining a word. In this context, tempest is a storm, and a particularly violent one. -cherryb history 211

This describes the important who, what, and when of historical context, with the who being Francis Daniel Pastorious, and the ocean voyage he underwent being the what. Finally, the voyage took place in the year 1684. This is important because it gives us an understanding of what sea voyages were like in the 1600's and as the subtitle highlights.. shows the "discomfort and dangers of oceanic travel in the 17th century -cherryb history 211

I thought this was interesting. It highlights the unpleasant conditions of taking embarking on a sea voyage at this time. I'm thinking about one of the very important questions related to annotating documents which is what other perspectives are missing? I would want to hear the perspective of the Crefelder family, who lost a daughter on the voyage. What would it be like to experience loss at sea in this way, and do they see her death as being lessened by the birth of two other children? -cherryb

eLife Assessment

This study introduces a valuable new metric-phenological lag-to help partition the drivers of observed versus expected shifts in spring phenology under climate warming. The conceptual framework is clearly presented and supported by an extensive dataset, and the revisions have improved the manuscript, though some concerns-particularly regarding uncertainty quantification, spatial analysis, and modeling assumptions-remain only partially addressed. The strength of evidence is generally solid, but further analysis would help to validate the study's conclusions.

Reviewer #3 (Public review):

Summary:

The authors developed a new phenological lag metric and applied this analytical framework to a global dataset to synthesize shifts in spring phenology and assess how abiotic constraints influence spring phenology.

Strengths:

The dataset developed in this study is extensive, and the phenological lag metric is valuable.

Weaknesses:

The stability of the method used to calculate forcing requirements needs improvement, for example by including different base temperature thresholds. In addition, the visualization of the results should be improved.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public review): 

Jiang et al. present a measure of phenological lag by quantifying the effects of abiotic constraints on the differences between observed and expected phenological changes, using a combination of previously published phenology change data for 980 species, and associated climate data for study sites. They found that, across all samples, observed phenological responses to climate warming were smaller than expected responses for both leafing and flowering spring events. They also show that data from experimental studies included in their analysis exhibited increased phenological lag compared to observational studies, possibly as a result of reduced sensitivity to climatic changes. Furthermore, the authors present evidence that spatial trends in phenological responses to warming may differ than what would be expected from phenological sensitivity, due to the seasonal timing of when warming occurs. Thus, climate change may not result in geographic convergences of phenological responses. This study presents an interesting way to separate the individual effects of climate change and other abiotic changes on the phenological responses across sites and species. 

Strengths: 

A straightforward mathematical definition of phenological lag allows for this method to potentially be applied in different geographic contexts. Where data exists, other researchers can partition the effects of various abiotic forcings on phenological responses that differ from those expected from warming sensitivity alone. 

Identifying phenological lag, and associated contributing factors, provides a method by which more nuanced predictions of phenological responses to climate change can be made. Thus, this study could improve ecological forecasting models. 

Weaknesses: 

The analysis here could be more robust. A more thorough examination of phenological lag would provide stronger evidence that the framework presented has utility. The differences in phenologica lag by study approach, species origin, region, and growth form are interesting, and could be expanded. For example, the authors have the data to explore the relationships between phenological lag and the quantitative variables included in the final model (altitude, latitude, mean annual temperature) and other spatial or temporal variables. This would also provide stronger evidence for the author's claims about potential mechanisms that contribute to phenological lag. 

We did examine the relationships of phenological lag with geographic or climatic variables in our analyses. Other than the weak correlations with latitude and altitude cited in the discussion section (lines 292-293), phenological lag was not related to mean annual temperature or long-term precipitation for both leafing and flowering.  

The authors include very little data visualizations, and instead report results and model statistics in tables. This is difficult to interpret and may obscure underlying patterns in the data. Including visual representations of variable distributions and between-variable relationships, in addition to model statistics, provides stronger evidence than model statistics alone. 

Table 2 shows the influences of geographic or climatic variables, particularly those related to drivers of spring phenology, i.e., budburst temperature, forcing change, and phenological lag, on phenological changes. As quantitative contributions of these drivers have been extracted, the influences of remaining variables are either minor or insignificant. Thus, examination of variable distributions, which has been done in previous syntheses, is probably not necessary.         

Some of independent variables were apparently correlated (r <0.6), e.g., MAT with altitude and latitude, budburst temperature with forcing change and spring warming, and forcing change with spring warming.

Reviewer #3 (Public review): 

Summary: 

The authors developed a new phenological lag metric and applied this analytical framework to a global dataset to synthesize shifts in spring phenology and assess how abiotic constraints influence spring phenology. 

Strengths: 

The dataset developed in this study is extensive, and the phenological lag metric is valuable. 

Weaknesses: 

The stability of the method used in this study needs improvement, particularly in the calculation of forcing requirements. In addition, the visualization of the results (such as Table 1) should be enhanced. 

Not clear how to improve the calculation of forcing accumulation.    

Recommendations for the authors: 

Editor (Recommendations for the authors): 

To improve the robustness of the metric and the conclusions drawn, we recommend that the authors: 

Test the sensitivity of their results to different base temperature thresholds and to nonlinear forcing response models, even for a subset of species. The proposed framework relies on an accurate understanding of species-specific thermal responses, which remain poorly resolved.

Different above-zero base temperatures have been used previously, although justifications are mostly following previous work. As we indicated in our first responses, the use of above-zero base temperatures underestimates forcing from low temperatures, which has more impacts on species with early spring phenology or in areas of cold climate due to greater proportions of forcing accumulations from low temperatures. The use of high base temperatures can lead to an interpretation that early season species require little or no forcing to break buds, which is biologically incorrect. Thus, the use of above-zero base temperatures would be more appropriate for particular locations or species than for meta-analysis across different spring phenology and climatic conditions. 

The research on multiple warming is limited in terms of levels of warming used (mostly one and occasionally two) for assessing non-linear forcing responses. This can be the focus of future work.  

Our framework is based on drivers of spring phenology and not dependent on “accurate understanding of species-specific thermal responses”. However, a good understanding of species- and site-specific responses to phenological constraints (e.g., insufficient winter chilling, photoperiod, and environmental stresses) does help determine the nature of phenological lag. All these are explained in our paper.     

Analyze relationships between phenological lag and additional geographic or climatic gradients already available in the dataset (e.g., latitude, mean annual temperature, interannual variability). 

We did examine the relationships of phenological lag with geographic or climatic variables in our analyses. Other than the weak correlations with latitude and altitude cited in the discussion section (lines 292-293), phenological lag was not related to mean annual temperature or long-term precipitation for both leafing and flowering.  

Our objective is to understand changes in spring phenology and differences in plant phenological responses across different functional groups or climatic regions, although our approach can be used to study interannual variability of spring phenology. Our metadata are compiled for comparing warmer vs control treatments (often multiyear averages), not for assessing interannual variability.      

Improve data visualization to better convey how phenological lag varies across environmental and biological contexts. 

See responses above.

Consider incorporating explicit uncertainty estimates around phenological lag calculations.  These steps would improve the interpretability and generalizability of the framework, helping it move from a useful heuristic to a more robust and empirically grounded analytical tool. 

The calculation of phenological lag is based on drivers of spring phenology with uncertainty depending primarily on uncertainty in phenological observations. Previous uncertainty assessments can be used here (see a few selected studies below).   

Alles, G.R., Comba, J.L., Vincent, J.M., Nagai, S. and Schnorr, L.M., 2020. Measuring phenology uncertainty with large scale image processing. Ecological Informatics, 59, p.101109.

Liu G, Chuine I, Denéchère R, Jean F, Dufrêne E, Vincent G, Berveiller D, Delpierre N. Higher sample sizes and observer intercalibration are needed for reliable scoring of leaf phenology in trees. Journal of Ecology. 2021 Jun;109(6):2461-74.

Tang, J., Körner, C., Muraoka, H., Piao, S., Shen, M., Thackeray, S.J. and Yang, X., 2016.Emerging opportunities and challenges in phenology: a review. Ecosphere, 7(8), p.e01436. 

Nagai, S., Inoue, T., Ohtsuka, T., Yoshitake, S., Nasahara, K.N. and Saitoh, T.M., 2015. Uncertainties involved in leaf fall phenology detected by digital camera. Ecological Informatics, 30, pp.124-132.

Fought against youth drinking/partying unlike Franklin who enjoyed those things.

Edwards studied spiders. similar to Franklin's kite experiment, shows both had scientific curiosity. But Edwards chose religion over science

reflects they're deitist beliefs

Franklin's own words showing he enjoyed pleasures like: socializing, drinking, music. Rejected in strict religious life

Secular = focused on life NOW rather than afterlife/heaven. Franklin cared about improving life on earth, not about the after life: opposite of religious focus.

experiment showing Franklin's scientific curiosity and search for reasoning through siicence

method of socrates: asking questions to find truth instead of accepting what you're told.

Proved natural laws could be discovered through science, not religion.

Enlightenment belief that humans can use logic to understand how world works. Don't need the Bible to get answers.

Working in print shop gave Franklin education through reading.

Print shops = where books/newspapers made. Access to new ideas.

Running away = act of questioning authority and rejecting hierarchy. Connects to Enlightenment

Here is a summary of the article and a step-by-step process for disagreeing constructively based on its findings.

Summary: How to Disagree Constructively

Disagreements can be highly beneficial, leading to better decisions and preventing errors. However, they often escalate into damaging conflicts. The common advice—to be empathetic and adopt open body language—often fails because there is an "intention-behavior gap." Your counterpart cannot read your mind; they only know what your words and actions communicate.

The problem is that our words often fail to convey our good intentions. For example, intending to be curious, we might ask, "How can you believe that?" which sounds judgmental.

Research by Julia Minson, Hanne Collins, and Michael Yeomans shows that the key to constructive disagreement is translating positive mental states (like curiosity and respect) into observable, verbal behaviors.

A 5-Step Procedure for Constructive Disagreement

This process focuses on using specific language to make your positive intentions clear to your counterpart, lowering the temperature and fostering a productive conversation.

Step 1: Explicitly Signal Your Desire to Learn

Instead of just feeling curious, you must state your curiosity. This signals that you want to understand, not attack.

• Why it works: It frames the disagreement as a mutual learning exercise rather than a battle.
• Example Language:
  • "It seems we are seeing this differently. I am curious how you think about XYZ."
  • "I'd like to understand more about your perspective on this."

Step 2: Acknowledge Their Perspective

People in a conflict need to know they have been heard. The most effective way to do this is to restate the core of their argument to prove you were listening.

• Why it works: It validates the other person and ensures you are arguing against their actual point, not a misunderstanding of it.
• Example Language:
  • "So, if I'm understanding you correctly, your main concern is..."
  • "What I'm hearing you say is that..."
  • (If you don't understand): "Could you clarify what you mean by...?"

Step 3: Find and State Common Ground

No matter how significant the disagreement, you can usually find shared beliefs, goals, or values if you "zoom out."

• Why it works: This reminds both parties that you are on the same general team, reinforcing the collaborative (not competitive) nature of the conversation.
• Example Language:
  • "I agree with some of what you’re saying, especially..."
  • "I think we both want what's best for the project."
  • "We both agree that the current situation isn't working."

Step 4: Hedge Your Claims

Research shows that in factual disagreements, the average person is wrong at least 50% of the time. Acknowledge this possibility by showing humility instead of asserting absolute certainty.

• Why it works: It leaves open the possibility that you could be wrong, which makes you appear more open-minded and less threatening.
• Example Language:
  • "From my viewpoint..."
  • "The way I've been thinking about it is..."
  • "Sometimes it is the case that..."
  • "I might be missing something, but..."

Step 5: Share Your Story (When Appropriate)

Strong beliefs are often rooted in personal experiences. Sharing the story behind your belief can be more effective for building trust than relying solely on facts and data.

• Why it works: It humanizes your position, explains the emotion behind your logic, and builds an interpersonal bridge.
• Example Language:
  • "The reason I feel strongly about this is because I had an experience where..."
  • "My perspective on this was shaped when I..."

Note for Leaders

To foster this culture, leaders should model these five verbal behaviors and actively train employees in these specific conversational skills—not just tell them to "be curious" or "be respectful."

This storm was deadly.

enter comment

use this material in my third body paragraph about storms and jamaica

Typing shouldn't be taught until around 6th grade I feel like being taught typing while still learning to write can be confusing and stunt both writing and typing.

having Chromebooks has negatively effected the amount of people reading paper copy books as well as how well people understand a text.

If technology is known to be decreasing performance why is it still so widely used in school.

I have always had an easier time reading on paper and understanding then reading it over and over on a computer. The computer makes it hard to focus.

This article really helps me understand the idea behind banning phones in Texas.

considering so many schools are almost entirely technology including ours based now, that raises a lot of concern.

He and his wife renounced their titles as the Duke and Duchess of York. They both gave up their royal privileges as they were further isolated from the throne.

Before the leak of the picture, there was an attempt to cover up

add to essay

super thin argument, but it's not wrong.

eLife Assessment

This study provides novel and convincing evidence that both dopamine D1 and D2 expressing neurons in the nucleus accumbens shell are crucial for the expression of cue-guided action selection, a core component of decision-making. The research is systematic and rigorous in using optogenetic inhibition of either D1- or D2-expressing medium spiny neurons in the NAc shell to reveal attenuation of sensory-specific Pavlovian-Instrumental transfer, while largely sparing value-based decision on an instrumental task. The important findings in this report build on prior research and resolve some conflicts in the literature regarding decision-making.

Reviewer #1 (Public review):

In the current article, Octavia Soegyono and colleagues study "The influence of nucleus accumbens shell D1 and D2 neurons on outcome-specific Pavlovian instrumental transfer", building on extensive findings from the same lab. While there is a consensus about the specific involvement of the Shell part of the Nucleus Accumbens (NAc) in specific stimulus-based actions in choice settings (and not in General Pavlovian instrumental transfer - gPIT, as opposed to the Core part of the NAc), mechanisms at the cellular and circuitry levels remain to be explored. In the present work, using sophisticated methods (rat Cre-transgenic lines from both sexes, optogenetics and the well-established behavioral paradigm outcome-specific PIT - sPIT), Octavia Soegyono and colleagues decipher the differential contribution of dopamine receptors D1 and D2 expressing-spiny projection neurons (SPNs).

After validating the viral strategy and the specificity of the targeting (immunochemistry and electrophysiology), the authors demonstrate that while both NAc Shell D1- and D2-SPNs participate in mediating sPIT, NAc Shell D1-SPNs projections to the Ventral Pallidum (VP, previously demonstrated as crucial for sPIT), but not D2-SPNs, mediates sPIT. They also show that these effects were specific to stimulus-based actions, as value-based choices were left intact in all manipulations.

This is a well-designed study and the results are well supported by the experimental evidence. The paper is extremely pleasant to read and add to the current literature.

Reviewer #2 (Public review):

Summary:

This manuscript by Soegyono et a. describes a series of experiments designed to probe the involvement of dopamine D1 and D2 neurons within the nucleus accumbens shell in outcome-specific Pavlovian-instrumental transfer (osPIT), a well-controlled assay of cue-guided action selection based on congruent outcome associations. They used an optogenetic approach to phasically silence NAc shell D1 (D1-Cre mice) or D2 (A2a-Cre mice) neurons during a subset of osPIT trials. Both manipulations disrupted cue-guided action selection but had no effects on negative control measures/tasks (concomitant approach behavior, separate valued guided choice task), nor were any osPIT impairments found in reporter only control groups. Separate experiments revealed that selective inhibition of NAc shell D1 but not D2 inputs to ventral pallidum were required for osPIT expression, thereby advancing understanding of the basal ganglia circuitry underpinning this important aspect of decision making.

Strengths:

The combinatorial viral and optogenetic approaches used here were convincingly validated through anatomical tract-tracing and ex vivo electrophysiology. The behavioral assays are sophisticated and well-controlled to parse cue and value guided action selection. The inclusion of reporter only control groups is rigorous and rules out nonspecific effects of the light manipulation. The findings are novel and address a critical question in the literature. Prior work using less decisive methods had implicated NAc shell D1 neurons in osPIT but suggested that D2 neurons may not be involved. The optogenetic manipulations used in the current study provides a more direct test of their involvement and convincingly demonstrate that both populations play an important role. Prior work had also implicated NAc shell connections to ventral pallidum in osPIT, but the current study reveals the selective involvement of D1 but not D2 neurons in this circuit. The authors do a good job of discussing their findings, including their nuanced interpretation that NAc shell D2 neurons may contribute to osPIT through their local regulation of NAc shell microcircuitry.

Weaknesses:

The current study exclusively used an optogenetic approach to probe the function of D1 and D2 NAc shell neurons. Providing a complementary assessment with chemogenetics or other appropriate methods would strengthen conclusions, particularly the novel demonstration for D2 NAc shell involvement. Likewise, the null result of optically inhibiting D2 inputs to ventral pallidum leaves open the possibility that a more complete or sustained disruption of this pathway may have impaired osPIT.

Conclusions:

The research described here was successful in providing critical new insights into the contributions of NAc D1 and D2 neurons in cue-guided action selection. The authors' data interpretation and conclusions are well reasoned and appropriate. They also provide a thoughtful discussion of study limitations and implications for future research. This research is therefore likely to have a significant impact on the field.

Comments on the previous version:

I have reviewed the rebuttal and revised manuscript and have no remaining concerns.

Author response:

The following is the authors’ response to the previous reviews

Reviewer#1 (Public Review):

In the current article, Octavia Soegyono and colleagues study "The influence of nucleus accumbens shell D1 and D2 neurons on outcome-specific Pavlovian instrumental transfer", building on extensive findings from the same lab. While there is a consensus about the specific involvement of the Shell part of the Nucleus Accumbens (NAc) in specific stimulus-based actions in choice settings (and not in General Pavlovian instrumental transfer - gPIT, as opposed to the Core part of the NAc), mechanisms at the cellular and circuitry levels remain to be explored. In the present work, using sophisticated methods (rat Cre-transgenic lines from both sexes, optogenetics and the well-established behavioral paradigm outcome-specific PIT - sPIT), Octavia Soegyono and colleagues decipher the diOerential contribution of dopamine receptors D1 and D2 expressing-spiny projection neurons (SPNs).

After validating the viral strategy and the specificity of the targeting (immunochemistry and electrophysiology), the authors demonstrate that while both NAc Shell D1- and D2SPNs participate in mediating sPIT, NAc Shell D1-SPNs projections to the Ventral Pallidum (VP, previously demonstrated as crucial for sPIT), but not D2-SPNs, mediates sPIT. They also show that these eOects were specific to stimulus-based actions, as valuebased choices were left intact in all manipulations.

This is a well-designed study and the results are well supported by the experimental evidence. The paper is extremely pleasant to read and add to the current literature.

We thank the Reviewer for their positive assessment.

Comments on revisions:  

We thank the authors for their detailed responses and for addressing our comments and concerns.

To further improve consistency and transparency, we kindly request that the authors provide, for Supplemental Figures S1-S4, panels E (raw data for lever presses during the PIT test), the individual data points together with the corresponding statistical analyses in the figure legends.

Panel E of Figures S1-S4 now includes the individual data points. The outcome-specific data have already been analysed, and we report these analyses in the main manuscript. These analyses are more informative than those requested by the Reviewer since they report the net eFects of the stimuli on choice between actions while controlling for potential individual baseline instrumental performance. All data remain fully transparent and are publicly available on an online repository in accordance with eLife policies (see relevant section in Materials and Methods).  

In addition, regarding Supplemental Figure S3, panel E, we note the absence of a PIT eOect in the eYFP group under the ON condition, which appears to diOer from the net response reported in the main Figure 5, panel B. Could the authors clarify this apparent discrepancy?

We apologize for the error, which has now been corrected. 

We also note a discrepancy between the authors' statement in their response ("40 rats excluded based on post-mortem analyses") and the number of excluded animals reported in the Materials and Methods section, which adds up to 47. We kindly ask the authors to clarify this point for consistency.

We thank the Reviewer for identifying the error reported in our initial response. The total number of animals excluded was 47, as reported in the manuscript. 

Finally, as a minor point, we suggest indicating the total number of animals used in the study in the Materials and Methods section.

The total number of animals has been included in the Materials and Methods section.

Reviewer #2 (Public Review):

Summary:

This manuscript by Soegyono et a. describes a series of experiments designed to probe the involvement of dopamine D1 and D2 neurons within the nucleus accumbens shell in outcome-specific Pavlovian-instrumental transfer (osPIT), a well-controlled assay of cueguided action selection based on congruent outcome associations. They used an optogenetic approach to phasically silence NAc shell D1 (D1-Cre mice) or D2 (A2a-Cre mice) neurons during a subset of osPIT trials. Both manipulations disrupted cue-guided action selection but had no eOects on negative control measures/tasks (concomitant approach behavior, separate valued guided choice task), nor were any osPIT impairments found in reporter only control groups. Separate experiments revealed that selective inhibition of NAc shell D1 but not D2 inputs to ventral pallidum were required for osPIT expression, thereby advancing understanding of the basal ganglia circuitry underpinning this important aspect of decision making.

Strengths:

The combinatorial viral and optogenetic approaches used here were convincingly validated through anatomical tract-tracing and ex vivo electrophysiology. The behavioral assays are sophisticated and well-controlled to parse cue and value guided action selection. The inclusion of reporter only control groups is rigorous and rules out nonspecific eOects of the light manipulation. The findings are novel and address a critical question in the literature. Prior work using less decisive methods had implicated NAc shell D1 neurons in osPIT but suggested that D2 neurons may not be involved. The optogenetic manipulations used in the current study provides a more direct test of their involvement and convincingly demonstrate that both populations play an important role. Prior work had also implicated NAc shell connections to ventral pallidum in osPIT, but the current study reveals the selective involvement of D1 but not D2 neurons in this circuit. The authors do a good job of discussing their findings, including their nuanced interpretation that NAc shell D2 neurons may contribute to osPIT through their local regulation of NAc shell microcircuitry.

We thank the Reviewer for their positive assessment.

Weaknesses:

The current study exclusively used an optogenetic approach to probe the function of D1 and D2 NAc shell neurons. Providing a complementary assessment with chemogenetics or other appropriate methods would strengthen conclusions, particularly the novel demonstration for D2 NAc shell involvement. Likewise, the null result of optically inhibiting D2 inputs to ventral pallidum leaves open the possibility that a more complete or sustained disruption of this pathway may have impaired osPIT.

We acknowledge the reviewer's valuable suggestion that demonstrating NAc-S D1- and D2-SPNs engagement in outcome-specific PIT through another technique would strengthen our optogenetic findings. Several approaches could provide this validation. Chemogenetic manipulation, as the reviewer suggested, represents one compelling option. Alternatively, immunohistochemical assessment of phosphorylated histone H3 at serine 10 (P-H3) oFers another promising avenue, given its established utility in reporting striatal SPNs plasticity in the dorsal striatum (Matamales et al., 2020). We hope to complete such an assessment in future work since it would address the limitations of previous work that relied solely on ERK1/2 phosphorylation measures in NAc-S SPNs (Laurent et al., 2014). The manuscript was modified to report these future avenues of research (page 12). 

Regarding the null result from optical silencing of D2 terminals in the ventral pallidum, we agree with the reviewer's assessment. While we acknowledge this limitation in the current manuscript (page 13), we aim to address this gap in future studies to provide a more complete mechanistic understanding of the circuit.

Conclusions:

The research described here was successful in providing critical new insights into the contributions of NAc D1 and D2 neurons in cue-guided action selection. The authors' data interpretation and conclusions are well reasoned and appropriate. They also provide a thoughtful discussion of study limitations and implications for future research. This research is therefore likely to have a significant impact on the field.

We thank the Reviewer for their positive assessment.

Comments on revisions:

I have reviewed the rebuttal and revised manuscript and have no remaining concerns.

We are pleased to have addressed the Reviewer’s query.

References

Laurent, V., Bertran-Gonzalez, J., Chieng, B. C., & Balleine, B. W. (2014). δ-Opioid and Dopaminergic Processes in Accumbens Shell Modulate the Cholinergic Control of Predictive Learning and Choice. J Neurosci, 34(4), 1358-1369. https://doi.org/10.1523/JNEUROSCI.4592-13.2014

Matamales, M., McGovern, A. E., Mi, J. D., Mazzone, S. B., Balleine, B. W., & BertranGonzalez, J. (2020). Local D2- to D1-neuron transmodulation updates goal-directed learning in the striatum. Science, 367(6477), 549-555. https://doi.org/10.1126/science.aaz5751