gcxgclab: An R Package for Two-Dimensional Gas Chromatography Preprocessing and Analysis.

Comprehensive two-dimensional gas chromatography (GC×GC) is an established technique capable of chromatographically separating thousands of analytes in complex matrices. When coupled with highly sensitive detectors such as a high-resolution mass spectrometer, these instruments produce large multidimensional data sets. A prevailing challenge for GC×GC users is efficient data handling and analysis.

A pan-cancer single-cell RNA-seq atlas of intratumoral B cells.

Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large sample cohort. We identify key B cell subset signatures, revealing distinct subpopulations and highlighting the heterogeneity and functional diversity of these cells in the tumor microenvironment.

Risk of incident gout following exposure to recombinant zoster vaccine in US adults aged ≥65 years.

Objective: Assess the risk of incident gout following exposure to recombinant zoster vaccine (RZV).

Methods: This case-only, self-controlled risk interval study included a cohort of US fee-for-service Medicare (Part A, B, and D) beneficiaries aged ≥65 years. The exposure was receipt of at least one dose of the two-dose RZV regimen in 2018 or 2019.

Advanced Method Optimization for Sampling and Analysis Instrumentation.

This work presents a generalized approach for analytical method optimization that branches the gap between techniques historically employed and accurate modern optimization techniques suitable for various applications. The novelty of the described strategy is the utilization of multivariate, multiobjective optimization with Karush-Kuhn-Tucker conditions to bound the optimization space to solutions within the physical limitations of instrumentation. Briefly, the basic steps outlined in this paper are to (1) determine the objective(s) that should be maximized or minimized based on the goals of the analytical application, (2) conduct a screening experiment, (3) perform ANOVA to determine the parameters which have a statistically significant effect on the objective, (4) conduct an experiment (e.