New GC roots can be added with guix build --root, for example (see Invoking guix build). The guix gc --list-roots command lists them.

The garbage collector has a set of known roots: any file under /gnu/store reachable from a root is considered live and cannot be deleted; any other file is considered dead and may be deleted.

In longitudinal studies, the marker is measured several times within a fixed follow-up. If a marker measurement has ability to signify a pending change in the clinical status of a patient, then a time-dependent ROC curve on a time-varying marker can be used to guide key medical decisions.

the disease status of an individual is observed and updated at each time point in time-dependent ROC curve analysis. With additional information of time of disease onset for each individual, a ROC curve can be constructed at several time points and the marker’s predictive ability can be compared. Thus, time-dependent ROC curve is an efficient tool in measuring the performance of a candidate marker given the true disease status of individuals at certain time points.

the receiver operating characteristic (ROC) curve is a tool that simply describes the range of trade-offs achieved by a diagnostic test.

The performance of a marker is evaluated by the area under the ROC curve (AUC) in which a higher AUC value indicates a better marker performance. The AUC is also equal to the probability of a diseased individual having a higher marker value than a healthy individual [8].

The goal of this article is to propose a new direct method that provides straightforward inference for AUC(t) and IAUC. Our method directly models AUC(t) as a function of time t using a flexible and yet parsimonious parametric model, namely, the fractional polynomials model proposed by Royston and Altman (1994).

For the purpose of estimating the time‐dependent AUC and IAUC, the “indirect” methods have some drawbacks. For example, most ROC‐estimation procedures rely on strong parametric assumptions such as proportional hazards, which may lead to potential bias due to the misspecification of the time‐to‐event model. In addition, because these methods are “indirect,” they are not particularly efficient and require unnecessary intensive computation.

everal time‐dependent measures have been proposed in the literature, including time‐dependent sensitivity, specificity, ROC and AUC (Heagerty, Lumley, and Pepe, 2005; Heagerty and Zheng, 2005).

Heagerty and Zheng (2005) showed that IAUC is equivalent to the global concordance summary with a proper weight function.

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.

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

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).

Teplizumab delayed progression to clinical type 1 diabetes in high-risk participants.

randomized, placebo-controlled, double-blind trial of teplizumab (an Fc receptor–nonbinding anti-CD3 monoclonal antibody)

interventions that might affect clinical progression before diagnosis are needed.

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.

It is worth noting that in the DIPP Finnish birth cohort (n = 128), IAA affinity was not found to correlate with disease progression (91).

14 of which were sampled at multiple timepoints

RNA sequencing on samples from 46 individuals with PCR-positive, symptomatic SARS-CoV-2 infection

77 peripheral blood samples across 46 subjects with COVID-19 and compared them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls.

seasonal coronavirus (n=59)

divided based on disease severity and time from symptom onset

elucidate novel aspects of the host response to SARS-CoV-2

influenza (n=17)

bacterial pneumonia (n=20)

healthy controls (n=19)

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.

host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood

educational uses of annotation technology

the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression

Note that the non-parametric model is not none-parametric.

Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being assessed.

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

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.

The survival rate for people with your particular cancer might be based on thousands of people.

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)

Sample variance can also be applied to the estimation of the variance of a continuous distribution from a sample of that distribution.

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.

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.

Artificial sweeteners are regulated by the Food and Drug Administration (FDA) as food additives.

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.

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]

Probit analysis will produce results similar logistic regression.

R requires forward slashes (/) not back slashes (\) when specifying a file location even if the file is on your hard drive.

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.