Correction: The effect of uncertainty in patient classification on diagnostic performance estimations.

[This corrects the article DOI: 10.1371/journal.pone.

The effect of uncertainty in patient classification on diagnostic performance estimations.

Background: The performance of a new diagnostic test is typically evaluated against a comparator which is assumed to correspond closely to some true state of interest. Judgments about the new test's performance are based on the differences between the outputs of the test and comparator. It is commonly assumed that a small amount of uncertainty in the comparator's classifications will negligibly affect the measured performance of a diagnostic test.

Validation of a Host Response Assay, SeptiCyte LAB, for Discriminating Sepsis from Systemic Inflammatory Response Syndrome in the ICU.

Rationale: A molecular test to distinguish between sepsis and systemic inflammation of noninfectious etiology could potentially have clinical utility.

Objectives: This study evaluated the diagnostic performance of a molecular host response assay (SeptiCyte LAB) designed to distinguish between sepsis and noninfectious systemic inflammation in critically ill adults.

Methods: The study employed a prospective, observational, noninterventional design and recruited a heterogeneous cohort of adult critical care patients from seven sites in the United States (n = 249).

Progression to and spontaneous regression of high-grade anal squamous intraepithelial lesions in HIV-infected and uninfected men.

Objective: To quantify incidence of, and risk factors for, progression to and spontaneous regression of high-grade anal squamous intraepithelial lesions (ASILs).

Design: Retrospective review of patients at St Vincent's Hospital Anal Cancer Screening Clinic during a period when high-grade ASILs were not routinely treated (2004-2011).

Methods: All patients who had an anal Papanicolaou smear or high-resolution anoscopy were included, except for patients with previous anal cancer.

Harvest: an open-source tool for the validation and improvement of peptide identification metrics and fragmentation exploration.

Background: Protein identification using mass spectrometry is an important tool in many areas of the life sciences, and in proteomics research in particular. Increasing the number of proteins correctly identified is dependent on the ability to include new knowledge about the mass spectrometry fragmentation process, into computational algorithms designed to separate true matches of peptides to unidentified mass spectra from spurious matches. This discrimination is achieved by computing a function of the various features of the potential match between the observed and theoretical spectra to give a numerical approximation of their similarity.