Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# A-21448, RRID:AB_2535865)

Curator: @scibot

SciCrunch record: RRID:AB_2535865

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (IMSR Cat# JAX_006148,RRID:IMSR_JAX:006148)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:006148

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# A-21436, RRID:AB_2535857)

Curator: @scibot

SciCrunch record: RRID:AB_2535857

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# A-11039, RRID:AB_2534096)

Curator: @scibot

SciCrunch record: RRID:AB_2534096

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# A-31573, RRID:AB_2536183)

Curator: @scibot

SciCrunch record: RRID:AB_2536183

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# 13-1900, RRID:AB_2533005)

Curator: @scibot

SciCrunch record: RRID:AB_2533005

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Jackson ImmunoResearch Labs Cat# 703-545-155, RRID:AB_2340375)

Curator: @scibot

SciCrunch record: RRID:AB_2340375

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Thermo Fisher Scientific Cat# A-11016, RRID:AB_2534083)

Curator: @scibot

SciCrunch record: RRID:AB_2534083

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BD Biosciences Cat# 563855, RRID:AB_2869528)

Curator: @scibot

SciCrunch record: RRID:AB_2869528

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_2299396

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 116203, RRID:AB_313704)

Curator: @scibot

SciCrunch record: RRID:AB_313704

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (Abcam Cat# ab13970, RRID:AB_300798)

Curator: @scibot

SciCrunch record: RRID:AB_300798

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 905503 (also 905504), RRID:AB_2734679)

Curator: @scibot

SciCrunch record: RRID:AB_2734679

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 116212, RRID:AB_313713)

Curator: @scibot

SciCrunch record: RRID:AB_313713

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (R and D Systems Cat# AF5715, RRID:AB_2102093)

Curator: @scibot

SciCrunch record: RRID:AB_2102093

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 103112, RRID:AB_312977)

Curator: @scibot

SciCrunch record: RRID:AB_312977

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 103506, RRID:AB_313029)

Curator: @scibot

SciCrunch record: RRID:AB_313029

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 102503, RRID:AB_312910)

Curator: @scibot

SciCrunch record: RRID:AB_312910

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 108139, RRID:AB_2565957)

Curator: @scibot

SciCrunch record: RRID:AB_2565957

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 102410, RRID:AB_312905)

Curator: @scibot

SciCrunch record: RRID:AB_312905

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 103104, RRID:AB_312969)

Curator: @scibot

SciCrunch record: RRID:AB_312969

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (R and D Systems Cat# FAB6524A, RRID:AB_10889851)

Curator: @scibot

SciCrunch record: RRID:AB_10889851

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 123316, RRID:AB_10645329)

Curator: @scibot

SciCrunch record: RRID:AB_10645329

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (R and D Systems Cat# FAB6524P, RRID:AB_10891351)

Curator: @scibot

SciCrunch record: RRID:AB_10891351

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 123309, RRID:AB_940582)

Curator: @scibot

SciCrunch record: RRID:AB_940582

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 104307, RRID:AB_313084)

Curator: @scibot

SciCrunch record: RRID:AB_313084

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 141209 (also 141210), RRID:AB_2564068)

Curator: @scibot

SciCrunch record: RRID:AB_2564068

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 127417, RRID:AB_2629803)

Curator: @scibot

SciCrunch record: RRID:AB_2629803

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 102226, RRID:AB_2128076)

Curator: @scibot

SciCrunch record: RRID:AB_2128076

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 102205, RRID:AB_312882)

Curator: @scibot

SciCrunch record: RRID:AB_312882

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: (BioLegend Cat# 101819, RRID:AB_572010)

Curator: @scibot

SciCrunch record: RRID:AB_572010

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: Illumina NextSeq 500 (RRID:SCR_014983)

Curator: @scibot

SciCrunch record: RRID:SCR_014983

---

What is this?

DOI: 10.1016/j.celrep.2024.115073

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_2742155

---

What is this?

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1016/j.celrep.2024.115007

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_3105777

---

What is this?

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1016/j.cell.2024.11.014

Resource: Python Programming Language (RRID:SCR_008394)

Curator: @scibot

SciCrunch record: RRID:SCR_008394

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: Fiji (RRID:SCR_002285)

Curator: @scibot

SciCrunch record: RRID:SCR_002285

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (IMSR Cat# JAX_022363,RRID:IMSR_JAX:022363)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:022363

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (IMSR Cat# JAX_016963,RRID:IMSR_JAX:016963)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:016963

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (IMSR Cat# JAX_032536,RRID:IMSR_JAX:032536)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:032536

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (IMSR Cat# JAX_025807,RRID:IMSR_JAX:025807)

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:025807

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: RRID:IMSR_JAX:029846

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:029846

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: MATLAB (RRID:SCR_001622)

Curator: @scibot

SciCrunch record: RRID:SCR_001622

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (Aves Labs Cat# GFP-1020, RRID:AB_10000240)

Curator: @scibot

SciCrunch record: RRID:AB_10000240

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (Aves Labs Cat# NFH, RRID:AB_2313552)

Curator: @scibot

SciCrunch record: RRID:AB_2313552

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (Proteintech Cat# 15146-1-AP, RRID:AB_2254244)

Curator: @scibot

SciCrunch record: RRID:AB_2254244

---

What is this?

DOI: 10.1016/j.cell.2024.11.014

Resource: (Takara Bio Cat# 632496, RRID:AB_10013483)

Curator: @scibot

SciCrunch record: RRID:AB_10013483

---

What is this?

DOI: 10.1016/j.cell.2024.11.008

Resource: RRID:IMSR_JAX:000664

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:000664

---

What is this?

DOI: 10.1016/j.cell.2024.11.008

Resource: (IZSLER Cat# BS CL 8, RRID:CVCL_1915)

Curator: @scibot

SciCrunch record: RRID:CVCL_1915

---

What is this?

DOI: 10.1016/j.cell.2024.11.008

Resource: (IZSLER Cat# BS CL 86, RRID:CVCL_0059)

Curator: @scibot

SciCrunch record: RRID:CVCL_0059

---

What is this?

DOI: 10.1016/j.cell.2024.11.008

Resource: (CCLV Cat# CCLV-RIE 0583, RRID:CVCL_RW96)

Curator: @scibot

SciCrunch record: RRID:CVCL_RW96

---

What is this?

DOI: 10.1016/j.cell.2024.11.008

Resource: None

Curator: @areedewitt04

SciCrunch record: RRID:CVCL_0542

---

What is this?

DOI: 10.1016/j.brainresbull.2024.111169

Resource: Parkinson's Progression Markers Initiative (RRID:SCR_006431)

Curator: @scibot

SciCrunch record: RRID:SCR_006431

---

What is this?

DOI: 10.1016/j.bbadis.2024.167633

Resource: (IZSLER Cat# BS TCL 165, RRID:CVCL_0201)

Curator: @scibot

SciCrunch record: RRID:CVCL_0201

---

What is this?

DOI: 10.1016/j.bbadis.2024.167633

Resource: (RRID:CVCL_0063)

Curator: @scibot

SciCrunch record: RRID:CVCL_0063

---

What is this?

DOI: 10.1016/j.bbadis.2024.167633

Resource: (CLS Cat# 300342/p657_SK-OV-3, RRID:CVCL_0532)

Curator: @scibot

SciCrunch record: RRID:CVCL_0532

---

What is this?

DOI: 10.1016/j.bbadis.2024.167633

Resource: (ATCC Cat# HTB-161, RRID:CVCL_0465)

Curator: @scibot

SciCrunch record: RRID:CVCL_0465

---

What is this?

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1002/cam4.70495

Resource: R Project for Statistical Computing (RRID:SCR_001905)

Curator: @scibot

SciCrunch record: RRID:SCR_001905

---

What is this?

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1158/1535-7163.mct-24-0140

Resource: None

Curator: @mzhang007

SciCrunch record: RRID:IMSR_GPT:N000013

---

What is this?

DOI: 10.1158/1535-7163.mct-24-0140

Resource: None

Curator: @sjvitug

SciCrunch record: RRID:IMSR_GPT:N000013

---

What is this?

DOI: 10.1158/0008-5472.can-24-2450

Resource: None

Curator: @mzhang007

SciCrunch record: RRID:IMSR_JAX:002019

---

What is this?

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

Traceback (most recent call last): File "/home/ubuntu/dashboard/py/create_release_tables.py", line 54, in format_anno_for_release parsedanno = HypothesisAnnotation(anno) File "/home/ubuntu/dashboard/py/hypothesis.py", line 231, in init self.links = row['document']['link'] TypeError: string indices must be integers

DOI: 10.1016/j.xpro.2024.103484

Resource: None

Curator: @inessasarian

SciCrunch record: RRID:IMSR_JAX:000664

---

What is this?

DOI: 10.1016/j.crmeth.2024.100930

Resource: None

Curator: @inessasarian

SciCrunch record: RRID:AB_2722750

---

What is this?

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Вот тут не понимаю, на всякий случай лучше проверить, тот ли скрин.

Чужой.

На скрине вижу Post Comment. Это подразумевалось и надо заменить или где-то что-то другое есть?

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой.

Чужой скрин.

Не тот.

Тоже не тот скрин.

Тоже.

Чужой скрин.

Скрин из HtB.

Чужой скрин?

В конце строки.

И тут.

Нет линейки.

جملة "Zebra Stripes" تعني "خطوط الحمار الوحشي".

في سياق تصميم الويب أو جداول HTML، يشير المصطلح إلى استخدام ألوان متناوبة للصفوف (عادةً لون فاتح ولون غامق) لجعل البيانات أكثر وضوحًا وسهولة في القراءة، كما تبدو مثل نمط خطوط الحمار الوحشي

Welcome back and in this lesson I want to talk in a little bit of detail about gateway load balances.

Now these are a relatively new addition to the load balancer family and are designed for very specific sets of use cases which I'll cover in this lesson.

Now we have a lot of architectural theory to cover so let's jump in and get started straight away.

Now before we talk about gateway load balances, I want to step through the type of situation where you might choose to use one.

Consider this architecture, the Categorum Application Server in a public subnet communicating with the public internet.

Now what's missing here is some kind of inspection based security appliance, something which can check data for any exploits to protect our application server.

Now if this is an important application, which it is because it involves cats, we can improve the architecture, we can add a security appliance and this would be a transparent security device.

It would sit in the flow of traffic inbound and outbound transparently reviewing traffic as it enters the application from the public internet so protecting the application against any known exploits and then filtering any traffic on the way back out.

For example, detecting and preventing any information leakage.

Now this works well assuming that we don't really have to think about scaling.

The issue comes when we grow or shrink our application.

Remember AWS pushes the concept of elasticity where applications can grow and shrink based on increasing and decreasing load on a system.

When you need to deal with a growing and shrinking number of application instances and where this growth is extreme you need an appropriate number of security appliances and this can be complex and prone to failures.

Now this solution is tightly coupled where the application and security instances are tied together.

The failure of one can impact the other.

It doesn't scale well even in a single application environment and it's even more complex if you're trying to build multi-tenant applications.

It's this type of situation where you need to use some kind of security appliance at scale and have flexibility around network architecture when you might choose to use a gateway load balancer and over the remainder of this lesson I want to step through what they do, how they function and how to use them.

A gateway load balancer is a product which AWS have developed to help you run and scale third-party security appliances things such as firewalls, intrusion detection systems or intrusion prevention systems, even data analysis tools.

You might use these for example to perform inbound and outbound transparent traffic inspection or protection.

Now AWS have a lot of awesome networking products but there are many large businesses who use third-party security and networking products.

You might do this because you have existing skills on those products and want to use them inside AWS or you might have a formal requirement to use those products or a specific feature or set of features which only one specific vendor can deliver.

So in those cases you'll need to use a third-party appliance and to do that at scale in a manageable way you'll need to use a gateway load balancer.

At a high level a gateway load balancer has two major components.

First, gateway load balancer endpoints which run from a VPC where the traffic you want to monitor, filter or control originates from or is destined to.

So in the example I'll be using the VPC where the Category Application Instance is hosted.

Now gateway load balancer endpoints are much like interface endpoints within VPCs which you've experienced so far but with some key improvements which I'll talk about in a second.

The other component is the gateway load balancer or GWLB itself and this load balancers packets across multiple back-end instances and these are just normal EC2 instances running security software.

In order for this type of architecture to work the gateway load balancer needs to forward packets without any alteration.

The security appliance needs to review packets as they're sent or as they're received.

After all that's the whole point.

These packets have source and destination IP addresses which might be okay on the original network but which might not work on the network where the security appliances are hosted from.

And so gateway load balancers use a protocol called Geneva and this is a tunnelling protocol.

A tunnel is created between the gateway load balancer and the back-end instances so the security appliances.

Packets are encapsulated and sent through this tunnel to the appliances.

Now let's review this visually which should help you understand how all of the components fit together.

Let's say that we have a laptop and this is accessing the Categorum application.

Now I'm keeping this simple for now and not including any VPC boundaries.

I'll show you this in a moment.

So traffic leaves this source laptop and moves into a VPC through an internet gateway and arrives at a gateway load balancer endpoint.

So gateway load balancer endpoints this is like a normal VPC interface endpoint with one major difference.

It can be added to a route table as the next hop and this allows it to be part of traffic flows controlled by that route table.

So traffic via a route table is directed at this endpoint and then the traffic flows through to a gateway load balancer.

So gateway load balancers allow three and four devices similar in many ways to a network load balancer.

But it integrates with gateway load balancer endpoints and it encapsulates all traffic that it handles between it and the targets using the Geneva protocol.

And this means that packets are unaltered.

They have the same source IP destination IP source port destination port and contents as when they were created and sent.

This allows the security appliances to scan the packets review them for any security issues block them as required perform analysis or adjust them as needed.

And when finished the packets are returned over the same tunnel encapsulated back to the load balancer where the Geneva encapsulation is removed and then the packets move back to the gateway load balancer endpoint and through to the intended destination.

Now the benefits of this architecture are that gateway load balancers will load balance across security appliances so you can horizontally scale.

The gateway load balancer manages flow stickiness so one flow of data will always use one appliance and this is useful because it allows that appliance to monitor the state of flows through a system.

It provides abstraction.

It means that you can use multiple security appliances to provide resilience.

If one of them fails then packets are just moved over to another available security appliance.

So in this way it's much like other load balancers within AWS.

Now just before we finish up with this lesson I wanted to provide a little bit more of a detailed typical architecture where you might use a gateway load balancer.

So this is the category application.

It's running in a pair of private subnets at the bottom behind an application load balancer which is running in a pair of public subnets.

Off to the right we have a separate VPC running a set of security appliances inside an auto scaling group so this can grow and shrink based on load to the application.

Now what I want to do now is to step through traffic flow through this architecture and show you how the gateway load balancer architecture works to ensure we can scale this security platform.

So we start at the top with a client which is accessing the web application.

Now this flow is going to be arriving at the application load balancer which uses public addressing and so logically it first hits the internet gateway.

The internet gateway is configured with an ingress route table also known as a gateway route table which influences what happens as traffic arrives at the VPC.

In this case our packets are destined for the public IP that the application load balancer on the right is using.

The internet gateway first translates the destination public IP address onto the corresponding private IP of that application load balancer and this will be running inside the 10.16.96.0/20 subnet.

So this is the subnet where the application load balancer is running from.

So the third route is used because it's the most specific route for the 10.16.96.0/20 range and traffic is sent towards the gateway load balancer endpoint in the right availability zone.

Remember gateway load balancer endpoints are like interface endpoints but they can be the targets within routes.

So the gateway load balancer endpoint receives these packets and then moves these packets through to the gateway load balancer itself which is running in the security VPC.

At this point the packets still have the original IP addressing and normally this would be a problem since the security VPC might be using a different or maybe even conflicting IP range.

So while the source and destination addressing remains the same the packets are encapsulated using the Geneva protocol and sent through unaltered to the security appliance chosen by the gateway load balancer.

The exact nature of the analysis which takes place depends on the security appliance and that's one of the benefits of using a gateway load balancer.

It just allows third party appliances to be used in a scalable way.

It doesn't inflict a particular feature set on us as network engineers or architects.

So once the analysis has happened the packets are returned encapsulated to the gateway load balancer.

The encapsulation is stripped and returned via the endpoint to the Category VPC.

Since the original IP addressing is maintained the route table on the top public subnet is used which has a local route for the VPC side arrange.

This as the most specific route available is used and packets flow through to the application load balancer and from there through to the chosen application instance.

And of course this logic is decided upon by the application load balancer.

Now the return path uses the same logic data leaves the application instance in response to the initial communication from the laptop and so it will return via the application load balancer.

The load balancer is in a subnet which has a local route but the default route goes towards the gateway load balancer endpoint in the same availability zone.

Now since traffic is going back to the client device who originally accessed the Category application it will have a public IP version 4 destination IP address and so the default route will be used.

This means the packets will flow back to the gateway load balancer endpoint and then from there through to the gateway load balancer where they'll be encapsulated passed through to the appliances then back to the load balancer de-encapsulated and passed back to the gateway load balancer endpoint.

Once they're back at the gateway load balancer endpoint the subnet which the gateway load balancer endpoints are in has the internet gateway as the default route and so this will be used and traffic moves through the internet gateway where its source IP will be changed to the corresponding public one of the application load balancer and then the data will be sent on through to the original client device.

And that's it transparent inline network security done in a scalable resilient and abstracted way.

Now I'm going to be talking more about some of the more nuanced features in other lessons but for now that's the basics covered of gateway load balancers.

In terms of other architecture they share many elements with network and application load balancers including the target group architecture but they have a very specific purpose network security at scale.

Now with that being said that's everything which I wanted to cover in this video so go ahead and complete the lesson and then when you're ready I look forward to you joining me in the next.

eLife Assessment

This study investigated mitochondrial dysfunction and the impairment of the ciliary Sonic Hedgehog signaling in Lowe syndrome (LS), a timely topic given the limited research in this area. The data from patient iPSC-derived neurons and a mouse model were collected using solid methods, but the evidence supporting key claims is incomplete, and some technical aspects fall short of expectations. Despite these limitations, the study provides a useful foundation for exploring the relationship between mitochondrial defects and primary cilia in neural development.

Reviewer #1 (Public review):

Summary:

This study by Lo et al. seeks to explain the cellular defects underlying the brain phenotypes of Lowe syndrome (LS). There have been limited studies on this topic and hence this is a timely study.

Strengths:

Studies such as these can contribute to an understanding of the cellular and developmental mechanisms of brain disorders.

Weaknesses:

This study by Lo et al. seeks to explain the cellular defects underlying the brain phenotypes of Lowe syndrome (LS). There have been limited studies on this topic and hence this is a timely study.

The study uses two models: (1) an LS IOB knockout mouse and (2) neurons derived from iPSC lines from LS patients. These two models are used to present three separate findings: (1) altered mitochondria function, (2) altered numbers of neurons and glia in both models, and (3) some evidence of altered Sonic Hedgehog signaling projected as a defect in cilia.

Conceptually, there are some problems of serious concern which must be carefully considered:<br /> (1) The IOB mouse was very extensively phenotyped when it was generated by Festa et.al HMM, 2019. It does not have any obvious phenotypes of brain deficits although the studies in this paper were very detailed indeed.<br /> (2) Reduced brain size is reported as a phenotype of the IOB mouse in this study. Yet over the many clinical studies of LS published over the years, altered brain size has not been noted, either in clinical examination or in the many MRI reports of LS patients.

While reading through these results it is striking that the link between the three reported phenotypes is at least tenuous, and in fact may not exist at all. The link between mitochondria and neurogenesis is based on a single paper that has been cited incorrectly and out of context. There is no evidence presented for a link between the Shh signaling defect reported and the mitochondrial phenotype.

General comments

(1) The preparation of the manuscript requires improvement. There are many errors in the presentation of data.<br /> (2) The use of references needs to be re-considered. Sometimes a reference is used when in fact the results included in that paper are the opposite of what the authors intend.<br /> (3) The authors conclude the paper by claiming that mitochondrial dysfunction and impairments of the ciliary SHH contribute to abnormal neuronal differentiation in LS, but the mechanism by which this sequence of events might happen hasn't been shown.

Final comments:

(1) Phenotype of increased astrocytes:<br /> The phenotype of increased astrocytes in both the IOB mouse brain or iPSC-derived cultures iN cells requires clarification as one of the markers used as an astrocyte marker, BRN2, is commonly used as a neuronal marker. As LS is a neurodevelopmental disorder, and the phenotype in question is related to differentiation, it is crucial to shed light on the developmental timeline in which this phenotype is seen in the mouse brain.

(2) Ciliary homeostasis:<br /> Mitochondrial dysfunction in astrocytes has been shown to induce a ciliogenic program. However, almost the opposite is shown in this paper, with regards to ciliation. Morphology of the cilia was not assessed either, which is an important feature of ciliary homeostasis. The improper ciliary homeostasis here appears to be the improper Shh signalling, which has not been shown to be related to mitochondrial dysfunction. This leaves one wondering how exactly the different phenotypes shown in this paper are connected.

(3) This paper lacks a clear mechanistic approach. While the data validates the 3 broad phenotypes mentioned, there is a lack of connection between these phenotypes or an answer to why these phenotypes appear. While the discussion attempts to shed light on this by referencing previous studies, some of the referenced studies show contradicting results. Hence, it would be beneficial to clarify these gaps with further experiments and address the larger question of the connection between the mitochondria, Shh signalling, and astrocyte formation.

(4) Most importantly, there is no mention of how the loss of OCRL, a 5-phosphatase enzyme, results in the appearance of the mentioned phenotypes. Since there are multiple studies in the field of Lowe Syndrome that shed light on the various functions of OCRL, both catalytic and non-catalytic, it is important to address the role of OCRL in resulting in these phenotypes.

(5) There are numerous errors in the qPCR experiments performed with regard to the genes that were assayed. The genes mentioned in the text section do not match those indicated in the graphs or legends. This takes away the confidence of the reader in this data.

Reviewer #2 (Public review):

Summary:

This manuscript investigates how neural cell development is affected in Lowe syndrome. Using neural cultures differentiated from human iPSCs carrying either an LS mutation or a genetically engineered mutation in OCRL, the authors show a depletion of mitochondrial DNA and a decrease in mitochondrial activities that correlate with an increased formation of astrocytes at the expense of neurons. Similar effects on mitochondria and on astrocyte development were observed in an LS mouse model. Moreover, these mutant brain cells are less likely to be ciliated and show a reduction in Sonic Hedgehog signalling.

Strengths/Weaknesses:

The study derives strength from the analyses of two different models of Lowe syndrome, both reaching similar conclusions. However, the observed changes in mitochondrial defects, neuronal/astrocytic development, and primary cilia are only correlated, with no attempt to investigate a causal relationship. Moreover, the mouse model is only analysed at the adult stage providing no insights into the development of the defects. Different brain regions are analysed with immunostainings and qRT-PCR making it challenging to draw clear correlations between these findings. The quality of the corresponding figures is often poor and the selection of markers is frequently inappropriate. Taken together, these limitations complicate the interpretations of the data and significantly limit the conclusions that can be drawn from the study.

eLife Assessment

This valuable study proposes a theoretical model of clathrin coat formation based on membrane elasticity that seeks to determine whether this process occurs by increasing the area of a protein-coated patch with constant curvature, or by increasing the curvature of a protein-coated patch that forms in an initially flat conformation (so called constant curvature or constant area models). Identifying energetically favorable pathways and comparing the obtained shapes with experiments provides solid support to the constant-area pathway. This work will be of interest for biologists and biophysicists interested in membrane remodelling and endocytosis. It provides an innovative approach to tackle the question of constant curvature vs. constant area coat protein formation, although some of the model's assumption are only partially supported by experimental evidence.

Reviewer #1 (Public review):

Summary:

The authors develop a set of biophysical models to investigate whether a constant area hypothesis or a constant curvature hypothesis explains the mechanics of membrane vesiculation during clathrin-mediated endocytosis.

Strengths:

The models that the authors choose are fairly well-described in the field and the manuscript is well-written.

Weaknesses:

One thing that is unclear is what is new with this work. If the main finding is that the differences are in the early stages of endocytosis, then one wonders if that should be tested experimentally. Also, the role of clathrin assembly and adhesion are treated as mechanical equilibrium but perhaps the process should not be described as equilibria but rather a time-dependent process. Ultimately, there are so many models that address this question that without direct experimental comparison, it's hard to place value on the model prediction.<br /> While an attempt is made to do so with prior published EM images, there is excessive uncertainty in both the data itself as is usually the case but also in the methods that are used to symmetrize the data. This reviewer wonders about any goodness of fit when such uncertainty is taken into account.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors employ theoretical analysis of an elastic membrane model to explore membrane vesiculation pathways in clathrin-mediated endocytosis. A complete understanding of clathrin-mediated endocytosis requires detailed insight into the process of membrane remodeling, as the underlying mechanisms of membrane shape transformation remain controversial, particularly regarding membrane curvature generation. The authors compare constant area and constant membrane curvature as key scenarios by which clathrins induce membrane wrapping around the cargo to accomplish endocytosis. First, they characterize the geometrical aspects of the two scenarios and highlight their differences by imposing coating area and membrane spontaneous curvature. They then examine the energetics of the process to understand the driving mechanisms behind membrane shape transformations in each model. In the latter part, they introduce two energy terms: clathrin assembly or binding energy, and curvature generation energy, with two distinct approaches for the latter. Finally, they identify the energetically favorable pathway in the combined scenario and compare their results with experiments, showing that the constant-area pathway better fits the experimental data.

Strengths:

The manuscript is well-written, well-organized, and presents the details of the theoretical analysis with sufficient clarity.<br /> The calculations are valid, and the elastic membrane model is an appropriate choice for addressing the differences between the constant curvature and constant area models.<br /> The authors' approach of distinguishing two distinct free energy terms-clathrin assembly and curvature generation-and then combining them to identify the favorable pathway is both innovative and effective in addressing the problem.<br /> Notably, their identification of the energetically favorable pathways, and how these pathways either lead to full endocytosis or fail to proceed due to insufficient energetic drives, is particularly insightful.

Weaknesses:

Membrane remodeling in cellular processes is typically studied in either a constant area or constant tension ensemble. While total membrane area is preserved in the constant area ensemble, membrane area varies in the constant tension ensemble. In this manuscript, the authors use the constant tension ensemble with a fixed membrane tension, σe. However, they also use a constant area scenario, where 'area' refers to the surface area of the clathrin-coated membrane segment. This distinction between the constant membrane area ensemble and the constant area of the coated membrane segment may cause confusion.

As mentioned earlier, the theoretical analysis is performed in the constant membrane tension ensemble at a fixed membrane tension. The total free energy E_tot of the system consists of membrane bending energy E_b and tensile energy E_t, which depends on membrane tension, σe. Although the authors mention the importance of both E_b and E_t, they do not present their individual contributions to the total energy changes. Comparing these contributions would enable readers to cross-check the results with existing literature, which primarily focuses on the role of membrane bending rigidity and membrane tension.

The authors introduce two different models, (1,1) and (1,2), for generating membrane curvature. Model 1 assumes a constant curvature growth, corresponding to linear curvature growth, while Model 2 relates curvature growth to its current value, resembling exponential curvature growth. Although both models make physical sense in general, I am concerned that Model 2 may lead to artificial membrane bending at high curvatures. Normally, for intermediate bending, ψ > 90, the bending process is energetically downhill and thus proceeds rapidly. the bending process is energetically downhill and thus proceeds rapidly. However, Model 2's assumption would accelerate curvature growth even further. This is reflected in the endocytic pathways represented by the green curves in the two rightmost panels of Fig. 4a, where the energy steeply increases at large ψ. I believe a more realistic version of Model 2 would require a saturation mechanism to limit curvature growth at high curvatures.

long list of cool humans interested in hypermaps

eLife Assessment

This study provides valuable quantitative data and analysis that reveals variations in 'Dorsal' nuclear dynamics along the dorso-ventral axis in the early Drosophila embryo. The evidence that supports that these variations are due to Dorsal/Cactus interactions in dorsal nuclei is convincing, albeit incomplete to understand the biological implications of these findings for developmental patterning.

Reviewer #1 (Public review):

Summary:

Al Asafen and colleagues apply a set of scanning fluorescence correlation spectroscopic approaches (Raster Image Correlation Spectroscopy (RICS), cross-correlation RICS, and pair-correlation function spectroscopy) to address the nuclear-cytoplasmic kinetics of the Dorsal (Dl) transcription factor in early Drosophila embryos. The Toll/Dl system has long been appreciated to establish dorsal-ventral polarity of the embryo through Toll-dependent control of Dl nuclear localization, and provides an example of a morphogen gradient produced with high enough precision to yield robust biophysical measurements of general transcription factor activity and function. By measuring GFP-tagged Dl protein, either in wild-type embryos or in mutant embryos with low/medium/high levels of Toll signaling, the authors report diffusivity of Dl in nuclear and cytoplasmic compartments of the embryo, as well as the fraction of mobile and immobile Dl, which can be correlated with DNA binding through cross-correlation RICS. A model is presented where Cactus/IkB is implicated in preventing Dl from binding to DNA.

Strengths:

The experiments on wild-type GFP-tagged Dorsal are performed well, are mostly reported well, and are interpreted fairly.

Weaknesses:

The discrepancy between experiment and theory as pertains to Michaelis-Menten kinetics is not fully motivated in the text, and could benefit from a more clear presentation. The experiments performed to distinguish between the contribution of Toll-dependent phosphorylation and Cactus interaction models for limiting Dorsal DNA binding are possibly confounded by the presence of wild-type, GFP-tagged Dorsal protein.

Reviewer #2 (Public review):

Summary:

In this manuscript, Al Asafen, Clark et al., use fluorescence correlation spectroscopy (FCS) to quantitatively analyze the mobility of Dl along the DV axis of the early Drosophila embryo. Dl is essential for dorsal-ventral (DV) patterning and its gradient initiates the activation of several genes and thereby orchestrates the formation of the Drosophila body plan. While the mechanisms underlying the formation of the Dl gradient have been extensively studied by this group and others, there are some observations for which there is not yet a mechanistic explanation. For example, the peak of the Dl gradient grows continuously during nuclear cycles 10-14. This is likely due to Cact-dependent Dl diffusion and Dl binding to DNA. However, the biophysical parameters governing Dl nuclear dynamics that would support these claims have not been previously measured. In this work, the authors provide evidence that GFP-tagged Dl may be separated into a mobile pool and an immobile pool. Interestingly, the fraction of immobile Dl is position-dependent along the DV axis, revealing more binding to DNA in the ventral than in the dorsal nuclei. This is either due to higher binding affinity in ventral locations (due to Toll-dependent Dl phosphorylation) or to higher Dl-Cact binding in dorsal nuclei that would prevent Dl from binding to DNA. Using dl-mutant alleles, the authors support the latter hypothesis.

Strengths:

The manuscript is well written and their conclusions are convincingly supported by their methodology and analysis. As a quantitative study, the biophysical analysis seems rigorous, in general.

Although this is not the first study that employs FSC to investigate the dynamics of a morphogen, it further exemplifies how these quantitative tools can be used to uncover mechanistic aspects of morphogen dynamics during development. In particular, the manuscript reports novel biophysical parameters of Dl dynamics that will be helpful in future hypotheses-driven modeling studies.

Weaknesses:

In my opinion, the main weakness of the manuscript is that the main biological implication of the study, namely that the asymmetry in the fraction of immobile Dl is a result of nuclear Dl-Cact binding which prevents Dl from binding DNA (Figure 5), occurs in a region of the embryo where there is very little Dl anyways (Figure 1A, 5A). While it is interesting that the fraction of immobile Dl increases (just a little, but significantly) in dorsal nuclei in mutants expressing a form of Dl with reduced Cact binding it is unclear what is the biological impact of this effect in a location where Dl is nearly absent. As can be seen in Figure 3F, the fraction of immobile is unaffected in Dl-mutant forms with reduced DNA binding, because it is already very low. It is unlikely that Dl binding to Cact in dorsal nuclei would affect shuttling as well since the fraction is very low anyway.

While the authors have a very clear understanding of the biology of the Dl gradient, I feel that the manuscript is more written as a 'tools' paper (i.e., to exemplify how FSC methods and analysis can be used for biological discovery). This is ok, but I think that the authors should discuss further what are the biological implications of these findings other than the contribution to uncovering the biophysical parameters. For example, I think that the implications of the rejected hypothesis (i.e., that Toll-dependent Dl phosphorylation does not seem to have an impact on Dl binding affinities to DNA) are important and should be further discussed (even if no additional experiments are performed). What is then the role of Dl phosphorylation? Perhaps it could have an impact on patterning robustness in lateral regions. The authors should report in Figure 5 also what happens to the fraction of Dl bound to DNA in lateral regions in the reduced Cact binding and reduced Toll phosphorylation mutants.

The way that position along the DV axis is reported using the nuclear-cytoplasmic-ratio (NCR) in Figures 1-3 is not incorrect, but I wonder if it is the best way of doing it. The reason is that it spreads out a relatively small region of the embryo (the ventral-most locations) and shrinks a relatively large region of the embryo (lateral and dorsal regions), see Figure 1A. Perhaps reporting the NCR in log_2 units would be more appropriate.

Warum das? Warum nicht noch coLab oder capture oder so?

Wenn du oben noch den Absatz zum Release machst, dann kann ja einer der beiden Absätze hier auch andersfarbig sein. Sonst verläuft sich das immer so.

Termine stehen ab der 2. Kalenderwoche 2025 zur Verfügung. Weitere Termine folgen monatlich. ...

Hier finde ich die Auflistung verwirrend. Kommt nicht von uns, ich weiß. Aber hier haben wir ganze Sätze und auch Stichpunkte. Vorschlag: den ersten Satz auch umwandeln:

• Eine Woche Zugang zur Microsoft-Azure-Umgebung für die praktische Durchführung (6 Stunden Netto-Bearbeitungszeit)
• 90 Tage Zugang zur OS-Academy
• Anmeldung via Academy oder Mail, siehe unten

Zur Anmeldung verwirrt. Hier ist kein Formular, wie man denken würde oder vielleicht die Weiterleitung zur OSA. Daher lieber "Anfrage zum Training schicken".

Dann ist noch der Empfänger falsch. Da steht auch mailto drin. Das sollte raus. Und den Betreff dann bitte Training 11.10 machen.

Das kam von Micha, richtig? Finde ich an sich ok. aber gerne noch etwas mehr Einleiten. Vorschlag:

"Release 11.10. – Die Neuerungen und unser Angebot"

Dann würde ich einfach die EInleitung der Release-Seite noch mal schreiben und dann überleiten mit: "Passend dazu haben wir alle Neuerungen für Sie in einem neuen Training zusammegestellt.

Können auch zwei Blöcke sein. Aber dann fallen wir nicht gleich mit dem Training in die Tür, sondern würdigen noch mal das Release.

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https://www.modernlib.com/FAQpages/generalFAQ/faqToleNum.html

The shift to "we" here feels a little more collective, a reminder that you're not alone in facing challenges. It brings everyone together in the same struggle, with the same hope to get through it

The lyrical repetition emphasizes the overarching message of perseverance throughout the song. The original "I will get by' line switches the use of pronouns to "we" which is symbolic of the song's use of collectivism to make itself more accessible to its audience.

4th extended (modified) chorus)

This conclusive lyric sets up the ending chorus of the song and nicely wraps up the track in a satisfactory, full-circle fashion. The lyrics comment on a cohesive structure of the song that establishes a clear lyrical flow and chronology that is satisfactory for music listeners.

This is another key line that flips the script. Instead of seeing grey (mperfection, age, struggle) as something bad, It's presented as something that "suits" you, It's like saying, "Yeah, things might be messed up, but they also make you who you are" It's a pretty solid piece of wisdom wrapped in a Grateful Dead vibe

This lyric presents positive imagery of carrying on and persevering. Its emblematic of "choosing to be happy" and contributes to the songs overall positive messaging.

This lyric builds on the song's simplification of stress. Problems can seem big and overwhelming when one is "in the weeds" however the general use of reassuring language here adds to the songs "safe haven" environment that the comforting lyrics create.

This is a playful twist on the idiom "the shoe fits," but it's a little twisted in that it's the "shoe" on the hand. It feels like a moment of acceptance-like the speaker is saying, "Well, if this is how things are. I'll just roll with it."

Chorus 3

The speaker admits that things are tough, maybe tougher than you think, but still pulls back to the mantra 'it's alright'. It's almost like saying, "Yeah, life's tough, but you just have to deal with it and keep going."

These lines paint a pretty grim picture of personal struggles. The rent being late and the dog starving is a very specific relatable image of things falling apart. But the fact that it's not the end of the world shows that even in tough situations, it's still "alright:

The lyric 'and try to keep a little love' again stresses positivity and is a repetition of a previous lyric 'and try to keep a little grace' This is another example of how lyrical repetition in used regularly throughout the song. It resembles similar lyrical trends in popular mainstream music that are musically satisfactory to the listener. "Love" a trope commonly sung about in popular music a also integrated into the lyrics of the song

The use of "we" stresses the innate collectivism the song harbors throughout its structure. The union of artist and audience further makes the song palatable and accessible for a broader universal audience beyond the band's regular returning listeners

Trying to keep a little grace is emblematic of keeping one's 'cool" and persevering through hard times. This message is emblematic of the song's uplifting purpose of stressing perseverance. This contributes to the song's positive messaging

The ABC's are a stand-in term for struggles that "we all must face". The song employs collectivism, uniting its listeners under their different struggles.

This alludes to the old military alphabet before it was changed in 1952 to what it is today.