The tumor microenvironment (TME) is a critical factor in antitumor immunity and treatment outcome in cancer therapy. We have developed an analysis tool called the immuno-oncology biological research (IOBR) to investigate the TME and its role in antitumor immunity. Leveraging multi-omics data, IOBR facilitates comprehensive analysis of TME characteristics, immune interactions, and their impact on immunotherapy outcomes.

The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), hazard ratios (HR), and risk ratios (RR), facilitating the identification of non-linear relationships in data. Supporting Cox, Logistic, linear, and quasi-Poisson models, rcssci aids researchers in interpreting complex data relationships before delving into advanced machine learning techniques.

 A first-of-its-kind global-to-local study has found that COVID-19’s impact varied remarkably across 920 locations worldwide, even within the same country. By analyzing data on cases, deaths, and healthy years lost between 2020 and 2021, the researchers revealed that broad national or regional averages may mask substantial local disparities. The study calls for more detailed, location-specific data to guide better public health decisions in future pandemics.

The development of an Integrated Real-Time Precise Point Positioning (InRPPP) system leveraging BeiDou Navigation Satellite System (BDS) B2b, B2a, and B1C services has significantly enhanced satellite-based positioning accuracy. 

A new study introduces an AI-integrated dynamic biomarker system that detects early disease tipping points and classifies thyroid cancer into actionable subtypes, paving the way for precision diagnosis and treatment.

This comprehensive review highlights the compositional and functional heterogeneity of intratumoral microbiota within the tumor microenvironment (TME), and their implications in tumorigenesis and cancer progression. The findings underscore the dual roles of these microbes in modulating immune responses and metabolic processes, offering new directions for cancer diagnostics and therapeutic interventions.

Through large-scale cohort analysis, researchers have established a novel and stable classification of sepsis patients. Multi-machine learning integrated prognostic models prove highly effective in identifying high-risk C3 subtype patients, offering significant clinical utility. ELL2 derived from B cells as a potential new biomarker for prognosis prediction and diagnostic differentiation in sepsis patients.