An Osaka Metropolitan University-led research team developed a transparent framework that connects task-level technological change to macroeconomic outcomes, revealing that automation is best understood as an equilibrium, economy-wide phenomenon rather than a collection of technology-specific indicators. 

A study published in Management Science finds that the industry’s standard approach of matching video game players against opponents with similar skill levels is not necessarily the most effective way to keep people engaged. Instead, researchers show that more sophisticated matchmaking systems—ones that account for how players respond to recent wins, losses and competitive experiences over time—can significantly increase player retention.

This consensus establishes a physician‑pharmacist co‑management model to standardize omalizumab use for allergic asthma. Using GRADE evidence grading and the Delphi method (agreement >80% on 12 recommendations), it provides frameworks for joint and pharmacist‑led clinics, clinical pathways (dosing, 60‑min observation, quarterly follow‑up), hierarchical referral, and pharmacist training. The model aims to improve adherence, asthma control, and cost‑effectiveness.

Stroke incidence and mortality are rising, and post‑stroke neuronal loss with long‑term disability remains a major challenge. Natural herbal remedies offer a cost‑effective option for recovery. Withania somnifera (Ashwagandha) has documented neuroprotective properties. This review summarizes its role in enhancing neuronal plasticity and post‑stroke recovery. Preclinical studies show that W. somnifera reduces infarct volume, mitigates neuroinflammation, oxidative stress, and apoptosis, while promoting neurotransmitter levels, motor function, and memory. It modulates key proteins (HO‑1, PARP‑1, Sema3A), activates PI3K/Akt pathway, and restores BDNF and SIRT1. However, clinical trials are needed to confirm efficacy in humans.

Cancer is an evolutionary process involving the accumulation of diverse somatic mutations and clonal evolution over time. Phylogenetic inference from samples obtained from an individual patient offers a powerful approach to unraveling the intricate evolutionary history of cancer and provides insights that can inform cancer treatment. Somatic copy number alterations (CNAs) are important in cancer evolution and are often used as markers, alone or with other somatic mutations, for phylogenetic inferences, particularly in low-coverage DNA sequencing data. Many phylogenetic inference methods using CNAs detected from bulk or single-cell DNA sequencing data have been developed over the years. However, there have been no systematic reviews on these methods. To summarize the state-of-the-art of the field and inform future development, this review presents a comprehensive survey on the major challenges in inference, different types of methods, and applications of these methods. The challenges are discussed from the aspects of input data, models of evolution, and inference algorithms. The different methods are grouped according to the markers used for inference and the types of the reconstructed trees. The applications include using phylogenetic inference to understand intra-tumor heterogeneity, metastasis, treatment resistance, and early cancer development. This review also sheds light on future directions of cancer phylogenetic inference using CNAs, including the improvement of scalability, the utilization of new types of data, and the development of more realistic models of evolution.