Incidence and onset of central venous catheter-related thrombosis in critically ill surgical patients: A prospective observational single-center study.

Study Objective: Catheter-related thrombosis (CRT) is a major complication of central venous catheters (CVCs). However, the incidence, onset, and dependence of CRT on CVC material and/or type in critically ill surgical patients is unknown. Therefore, we here investigated the incidence, onset, and dependence of CRT on a variety of risk factors, including CVC material and type, in critically ill surgical patients.

Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission.

Background: Timely diagnosis is crucial for sepsis treatment. Current machine learning (ML) models suffer from high complexity and limited applicability. We therefore created an ML model using only complete blood count (CBC) diagnostics.

Effective Amino Acid Sequencing of Intact Filgrastim by Multimodal Mass Spectrometry with Topdownr.

Therapeutic proteins, known as biologicals, are an important and growing class of drugs for treatment of a series of human ailments. Amino acid sequence variants of therapeutic proteins can affect their safety and efficacy. Top-down mass spectrometry is well suited for the sequence analysis of intact therapeutic proteins.

A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R.

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics experiments have become increasingly popular because of the wide range of metabolites that can be analyzed and the possibility to measure novel compounds. LC-MS instrumentation and analysis conditions can differ substantially among laboratories and experiments, thus resulting in non-standardized datasets demanding customized annotation workflows. We present an ecosystem of R packages, centered around the , and packages that together provide a modular infrastructure for the annotation of untargeted metabolomics data.

MSnbase, Efficient and Elegant R-Based Processing and Visualization of Raw Mass Spectrometry Data.

We present version 2 of the MSnbase R/Bioconductor package. MSnbase provides infrastructure for the manipulation, processing, and visualization of mass spectrometry data. We focus on the new on-disk infrastructure, that allows the handling of large raw mass spectrometry experiments on commodity hardware and illustrate how the package is used for elegant data processing, method development, and visualization.

Maximizing Sequence Coverage in Top-Down Proteomics By Automated Multimodal Gas-Phase Protein Fragmentation.

Intact protein sequencing by tandem mass spectrometry (MS/MS), known as top-down protein sequencing, relies on efficient gas-phase fragmentation at multiple experimental conditions to achieve extensive amino acid sequence coverage. We developed the "topdownr" R-package for automated construction of multimodal (i.e.

Differential protein expression and peak selection in mass spectrometry data by binary discriminant analysis.

Motivation: Proteomic mass spectrometry analysis is becoming routine in clinical diagnostics, for example to monitor cancer biomarkers using blood samples. However, differential proteomics and identification of peaks relevant for class separation remains challenging.

Results: Here, we introduce a simple yet effective approach for identifying differentially expressed proteins using binary discriminant analysis.

Visualization of proteomics data using R and bioconductor.

Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience.

Species determination of Culicoides biting midges via peptide profiling using matrix-assisted laser desorption ionization mass spectrometry.

Background: Culicoides biting midges are vectors of bluetongue and Schmallenberg viruses that inflict large-scale disease epidemics in ruminant livestock in Europe. Methods based on morphological characteristics and sequencing of genetic markers are most commonly employed to differentiate Culicoides to species level. Proteomic methods, however, are also increasingly being used as an alternative method of identification.

MALDIquant: a versatile R package for the analysis of mass spectrometry data.

Unlabelled: MALDIquant is an R package providing a complete and modular analysis pipeline for quantitative analysis of mass spectrometry data. MALDIquant is specifically designed with application in clinical diagnostics in mind and implements sophisticated routines for importing raw data, preprocessing, non-linear peak alignment and calibration. It also handles technical replicates as well as spectra with unequal resolution.