36 Matching Annotations
  1. Jan 2023
    1. Whether interventions at stage 1 or 2 might alter the progression to clinical type 1 diabetes has been unclear. We therefore tested whether teplizumab treatment would prevent or delay the onset of clinical type 1 diabetes in high-risk persons.
    2. One promising type of therapy appears to be Fc receptor–nonbinding anti-CD3 monoclonal antibodies, such as teplizumab; multiple studies involving patients with type 1 diabetes have shown that teplizumab treatment reduces the loss of beta-cell function, even as long as 7 years after diagnosis.7–11 The drug modifies CD8+ T lymphocytes, which are thought to be the important effector cells that kill beta cells.12,13
    3. In genetically susceptible persons, type 1 diabetes progresses through asymptomatic stages before the development of overt hyperglycemia. These stages are characterized by the appearance of autoantibodies (stage 1) and then dysglycemia (stage 2).
    4. Teplizumab delayed progression to clinical type 1 diabetes in high-risk participants.
    5. randomized, placebo-controlled, double-blind trial of teplizumab (an Fc receptor–nonbinding anti-CD3 monoclonal antibody)
    6. interventions that might affect clinical progression before diagnosis are needed.
  2. Sep 2022
    1. GNU Emacs, which is a sort of hybrid between Windows Notepad, a monolithic-kernel operating system, and the International Space Station. It’s a bit tricky to explain, but in a nutshell, Emacs is a platform written in 1976 (yes, almost half a century ago) for writing software to make you more productive, masquerading as a text editor.
    1. It is worth noting that in the DIPP Finnish birth cohort (n = 128), IAA affinity was not found to correlate with disease progression (91).

      This is a mistake in citation, It should have been the citation number 137. The mistake is understandable as both articles are published in 2009 and has the same first author.

  3. Mar 2021
    1. 14 of which were sampled at multiple timepoints
    2. RNA sequencing on samples from 46 individuals with PCR-positive, symptomatic SARS-CoV-2 infection
    3. 77 peripheral blood samples across 46 subjects with COVID-19 and compared them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls.
    4. seasonal coronavirus (n=59)
    5. divided based on disease severity and time from symptom onset
    6. elucidate novel aspects of the host response to SARS-CoV-2
    7. influenza (n=17)
    8. bacterial pneumonia (n=20)
    9. healthy controls (n=19)
    1. elucidate key pathways in the host transcriptome of patients infected with SARS-CoV-2, we used RNA sequencing (RNA Seq) to analyze nasopharyngeal (NP) swab and whole blood (WB) samples from 333 COVID-19 patients and controls, including patients with other viral and bacterial infections.
    2. host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood
  4. Jul 2015
    1. educational uses of annotation technology

      The most important thing in educational use is categorizing your annotation and notes. I left Diigo due to removal of "lists" from their platform and I'm following your project for the past 7 months and yet this platform lack that fundamental feature as well.

  5. Feb 2015
    1. the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression
    1. Note that the non-parametric model is not none-parametric.
    2. Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being assessed.

      Why called non-parametrci

    1. Note: creating multiple accounts or teams solely to circumvent limits on the "purchased" in silico data is grounds for disqualification.

      Multi account rules

    2. The goal of the DREAM Olfaction Prediction Challenge is to find models that can predict how a molecule smells from its physical and chemical features.
    1. The use of the term n − 1 is called Bessel's correction, and it is also used in sample covariance and the sample standard deviation (the square root of variance)

      Why in \(\sigma^2\) is not equal to \(s^2\)

    2. Sample variance can also be applied to the estimation of the variance of a continuous distribution from a sample of that distribution.
    1. Suppose the value of for wages is 10% and the values of for kilograms of meat is 25%. This means that the wages of workers are consistent. Their wages are close to the overall average of their wages. But the families consume meat in quite different quantities. Some families use very small quantities of meat and some others use large quantities of meat. We say that there is greater variation in their consumption of meat. The observations about the quantity of meat are more dispersed or more variant.

      Interpretation of Relative Deviation Coefficient

    1. The FDA has also established an acceptable daily intake (ADI) for each artificial sweetener. This is the maximum amount considered safe to consume each day over the course of your lifetime. ADIs are intended to be about 100 times less than the smallest amount that might cause health concerns.

      How is Acceptable Daily Intake calculated by FDA

    2. Artificial sweeteners are regulated by the Food and Drug Administration (FDA) as food additives.
    1. its victims are extremely vulnerable to infectious diseases and some of them, such as David Vetter, have become famous for living in a sterile environment.

      Basic info

    2. SCID is the most severe form of primary immunodeficiencies,[4] and there are now at least nine different known genes in which mutations lead to a form of SCID.[5]
  6. Jan 2015
    1. Probit analysis will produce results similar logistic regression.

      Probit regression vs. Logistic regression

    2. R requires forward slashes (/) not back slashes (\) when specifying a file location even if the file is on your hard drive.
    3. Logistic regression, also called a logit model, is used to model dichotomous outcome variables. In the logit model the log odds of the outcome is modeled as a linear combination of the predictor variables.