Browse Articles

Genomic and phenotypic insights into Pseudocolwellia antarctica sp. nov., a novel psychrotolerant bacterium with symbiotic potential from Antarctic zooplankton

Correction to “Dense Platinum-Based Intermetallic Nanoparticles Confined into Hollow Mesoporous Carbon for Durable High-Power Heavy-Duty Fuel Cells”

Evaluation of disinfection efficiency of new high oxygen membrane air disinfecting machine in hospital ward environment

Effect of Heterohalide Composition on the Dopant–Exciton Exchange Interactions in Mn ²⁺ -Doped Cesium Lead Halide Perovskite Nanocrystals

New energy demonstration urban construction enhances ecological environmental resilience: evidence from China

Thermal Regulation of CO ₂ Activation Pathways via Interfacial Water Restructuring Enables Ampere-Level, Near-Unity CO Electrosynthesis

Development and validation of a prediction model of length of ICU stay for benchmarking: a retrospective cohort study

Abstract Efficient use of intensive care unit (ICU) resources requires accurate prediction of length of stay (LOS), yet existing LOS models show inconsistent performance across settings and may not generalize to Japanese ICUs. We conducted a retrospective cohort study using the Japanese Intensive Care Patient Database, including adults admitted to 87 ICUs between April 2022 and March 2023. The primary outcome was ICU LOS in days. Generalized additive models with several distributional assumptions were fitted using the Acute Physiology and Chronic Health Evaluation III score, primary disease category, emergency surgery status, and admission source as predictors. Model performance was evaluated using deviance explained with internal validation. The best-performing model was applied to derive ICU-level standardized length-of-stay ratios (SLOSR) and observed minus expected length of stay (OMELOS), summarized using funnel plots with and without overdispersion correction. Among 65,395 patients, median ICU LOS was 3 days (interquartile range: 2–5). A gamma model with a log link achieved the highest cross-validated deviance explained (0.415). Overdispersion correction reduced the proportion of ICUs exceeding the 95% control limits from 69% to 9.2%. These findings indicate that a gamma-based generalized additive model enables case-mix–adjusted ICU LOS benchmarking and that overdispersion correction substantially affects outlier identification.

De Novo Design of Miniature and Efficient Metallo-Ketoreductases

Cardiorespiratory fitness modulates the effect of acute exercise on vigilance performance in trained soldiers

Diastereoselective and Chemically Reversible C–C Bond Formation Mediated by an (N-heterocyclic)boryloxy Aluminyl Compound

Genetic analyses of autoimmune mutants uncover the MPK3/6-CHR5-SNC1 module in Arabidopsis

Lignin-Functionalized Supramolecular Binder Enables Aggressive Cathode Chemistries in Advanced Li-Ion Batteries

Retraction Note: Computational simulation and modelling of uranium extraction using tributylphosphate through membrane extractor

Fluorogenic Red to Near-Infrared Tetrazine–Cyanine Probes for Bioorthogonal Organelle Membrane Imaging and Spatiotemporal Disruption

ARUDet: active retrieval and uncertainty-aware detection for sports video object detection

Acidosis Regulates Microtubule Dynamics via the β1 Integrin/RhoA/CRMP-2 Axis

Breast cancer in Bosnia and Herzegovina: real-world patterns of diagnosis, treatment, and survival outcomes

Abstract Timely diagnosis is critical for improving breast cancer outcomes, especially in resource-limited health systems. This study provides the first real-world evidence from Bosnia and Herzegovina on diagnostic and treatment intervals, adherence, and survival in women with breast cancer. We conducted a retrospective analysis of breast cancer cases diagnosed between 2019 and 2023 at the Clinical Centre University of Sarajevo, the largest cancer center in the country, managing approximately 60% of cases in the Federation of Bosnia and Herzegovina. Most patients (78.1%; 95% CI: 73.8–82.3) were diagnosed through self-referral due to symptoms, with 62.4% of cancers detected at stages 1 and 2. The mean patient and system diagnostic intervals were 38.1 days (95% CI: 23.4–52.8) and 38.6 days (95% CI: 29.9–47.3), respectively, with a total diagnostic interval of 70 days (95% CI: 58.9–82.5). Almost all diagnostic procedures had a waiting time of less than ten days. Among all women undergoing surgery, radical mastectomy was performed in 61% (95% CI: 55–66), while among women with stage 1–2 disease, 55% (95% CI: 48–62) underwent radical mastectomy. Treatment duration averaged 3.7 months for chemotherapy (95% CI: 3.4–4.1) and 0.48 months for radiotherapy (95% CI: 0.26–0.69), with higher compliance for radiotherapy (99.5%; 95% CI: 98–100) than chemotherapy (78%; 95% CI: 72–84). Three-year progression-free survival was 85.7%, and overall three-year survival was 86%. Early breast cancer detection and favorable survival can be achieved even in resource-constrained settings.

Giant Lattice Expansion through Structural Frustration Release in a Dense Oxide

Explainable deep unsupervised learning for flood monitoring and anomaly detection using multivariate DWLR sensors

Phase Separation Driven by Dynamic Interactions in the N-Terminal Intrinsically Disordered Region of the DEAD-Box RNA Helicase DDX3X