First immune-transcriptomic map of lung cancer plus tuberculosis.

CD4/CD8 ratio and NK cells up; antigen presentation pathways enriched.

Six-gene signature validated; four-gene model AUC 0.94 for LC-PTB.

MTB remodels tumor microenvironment via metabolic-immune crosstalk.

This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine for cancer drug delivery. It demonstrates how ML algorithms—including support vector machines, neural networks, and deep learning models—are revolutionizing nanoparticle design, drug release prediction, and personalized therapy planning. The article outlines the complete ML workflow from data acquisition to model interpretation, compares key algorithms, and presents real-world case studies spanning multidrug carrier optimization and cancer diagnostics. While highlighting substantial preclinical advances, the authors identify critical barriers to clinical translation such as data heterogeneity, model opacity, and regulatory challenges. The review concludes with a forward-looking roadmap emphasizing data standardization, explainable AI, and clinical validation to bridge the gap between computational innovation and patient-ready nanomedicine.

Researchers propose a new route to electrically control magnetism using molecular ferroelectric altermagnets. By tuning molecular dipole alignments, the team demonstrates that spin polarization can be switched on, off, or reversed without altering magnetic order. Verified through theoretical model and first-principles studies in hybrid perovskites and metal-organic frameworks, this work introduces a flexible, low-power platform for electrically driven spintronics, bridging molecular ferroelectrics and next-generation magnetic memory technologies.

Red light plays a crucial role in shaping flower development, yet its underlying influence on flowering timing in roses has remained unclear.