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Inside Back Cover: Structure‐Informed Design of Distinct Parallel G‐Quadruplex Stabilizers for <i>KRAS</i> ‐Driven Cancer Therapy (Angew. Chem. Int. Ed. 32/2026)

A protein–small molecule conjugate as a bispecific inhibitor of proteases implicated in cancer metastasis

Peripheral DNA methylation of candidate Alzheimer’s disease risk genes and its associations with cognition, brain volume and amyloid-β burden

The FMO score stratifies hepatocellular carcinoma risk in individuals with obesity: a nationwide cohort study

Abstract The fibrotic/at-risk MASH in obesity (FMO) score, comprising four routine biochemical parameters, noninvasively identifies individuals with obesity at risk for metabolic dysfunction-associated steatohepatitis (MASH). Although it predicts composite liver-related outcomes, whether it stratifies hepatocellular carcinoma (HCC) risk remains unknown. Using the Japan Medical Data Center claims database (2007–2024), we evaluated 1,336,229 individuals with obesity, stratified into rule-out (FMO ≤ 0.05), indeterminate-risk (0.05 &lt; FMO &lt; 0.22), and rule-in (FMO ≥ 0.22) zones. During a median follow-up of 3.7 years, 693 HCC events occurred, with incidence rates of 0.091, 0.168, and 0.260 per 1,000 person-years across zones. Compared with rule-out, the rule-in zone was significantly associated with HCC in univariate (hazard ratio, 2.850; 95% CI, 2.328–3.489) and multivariate analyses (adjusted hazard ratio [aHR], 1.783; 95% CI, 1.409–2.257). The indeterminate-risk zone also showed elevated risk (aHR, 1.446; 95% CI, 1.206–1.732; all p  &lt; 0.001). Associations were consistent across all predefined subgroups. Among over 1.3 million individuals with obesity, the FMO score showed substantial utility for HCC risk stratification. Derived from routine metabolic parameters, it might help identify individuals at elevated HCC risk warranting enhanced surveillance. Word count: 187 words.

Global, multilingual, physician-invited, patient-completed digital registry enabling pre-consultation engagement and supporting more efficient care pathways in venous disease

Honokiol induces an autophagy and apoptosis imbalance by modulating the p62 and Nrf2 signaling loop in canine osteosarcoma

Deep learning and edge computing framework for proactive pothole detection with Internet of Things

SYCP3 enhances prostate cancer metastasis and modulates the DNA damage response pathway

Abstract Prostate cancer (PCa) is a prevalent male cancer with high survival rates, except in advanced or metastatic stages, for which effective treatments are lacking. Metastatic PCa involves complex mechanisms including loss of tumor suppressor genes and DNA repair molecules, which impacts therapy responses. Analyses of tumor samples demonstrated that SYCP3 expression is frequently upregulated in PCa tumors from patients in advanced stages. Due to the implication of SYCP3 on DNA repair processes, we have analyzed the role of SYCP3 on the cellular response to radiotherapy (RT) and found that its depletion induced RT resistance, suggesting a role for SYCP3 in DNA damage response and genomic instability. Additionally, based on a previous CRISPR/Cas9 genome-wide screening identifying SYCP3 as a potential regulator of metastatic invasion in DU145 PCa cells, we performed biological validation analyses, which showed that SYCP3 depletion significantly reduced the invasive and migratory abilities of DU145 cells and increased their adhesion capacity. All these data support a role for SYCP3 in PCa metastasis and provides opportunities for personalized medicine.

Sandaracopimaric acid against the MAO-B/LRRK2 axis in Parkinson’s disease

Abstract Parkinson’s disease lacks disease-modifying therapies; MAO-B inhibition remains a symptomatic standard, whereas LRRK2 kinase is a genetically validated Parkinson’s disease target. Here, the resin-acid diterpene sandaracopimaric acid (SCP) was evaluated as a CNS-oriented, hypothesis-generating scaffold rather than as a validated inhibitor. SwissADME predicted high gastrointestinal absorption, blood-brain barrier permeation and non-substrate behavior toward P-gp, with low aqueous solubility as the main developability limitation; ProTox-III suggested low acute oral toxicity (LD 50 approximately 20,000 mg·kg⁻¹; class 6). Redocking-validated docking to MAO-B (2V5Z; RMSD = 1.068 Å), LRRK2 (8FO7; RMSD = 1.693 Å), along with a complementary MAO-A selectivity counter-screen (2Z5X; RMSD = 0.270 Å) supported an MAO-B-favouring profile for SCP (-7.9 kcal·mol⁻¹) compared with LRRK2 (-6.9 kcal·mol⁻¹) and MAO-A (-6.2 kcal·mol⁻¹). In 100-ns GROMACS simulations, SCP remained more compactly retained in MAO-B than in LRRK2. MM/GBSA and PCA further supported a more favorable, single-basin MAO-B recognition pattern, whereas LRRK2 displayed a more solvent-exposed and flexible regime. Overall, SCP stands out computationally as an MAO-B-preferring natural scaffold ripe for experimental follow-up, where MAO-A/B enzymatic selectivity testing and LRRK2 kinase assays will serve to validate its true therapeutic viability.

Multivariate analysis of morpho-chemical characteristics in loquat (Eriobotrya japonica (Thunb.) Lindl.) genotypes

Effects of blood flow restriction–augmented baduanjin training on quadriceps strength and postural stability in sedentary young men: a randomized controlled trial

Abstract This randomized controlled trial examined whether augmenting traditional Baduanjin (BDJ) exercise with blood flow restriction (BFR) enhances quadriceps muscle function and postural stability in sedentary young men. A total of 38 participants were randomly assigned to either BDJ or BFR-BDJ training for 8 weeks. Quadriceps peak torque, total work, and single-leg stance stability under eyes-open and eyes-closed conditions were assessed using isokinetic dynamometry and force-platform measures. Compared with BDJ alone, BFR-BDJ produced significantly greater improvements in quadriceps strength and reductions in sway velocity during eyes-open stance. No between-group differences were observed under eyes-closed conditions, suggesting visual dependence in balance enhancement. No adverse events occurred. These findings indicate that integrating BFR with BDJ provides a low-intensity yet effective training strategy to improve lower-limb neuromuscular performance and functional stability in individuals unable or unwilling to engage in high-load exercise.

Data-driven fault diagnosis of wind turbine generator bearings via heterogeneous vibration and acoustic sensing

Lightweight LLM summarization with LSTM for early ICU deterioration prediction

Methodologic Standards for Follow-Up Extension in Cardiovascular Trials: A Scientific Statement From the American Heart Association

Extension follow-up trials are essential for understanding the long-term safety and efficacy of cardiovascular interventions. Whereas primary randomized trials primarily capture short-term outcomes, extended observation may reveal delayed benefits or harms that are highly relevant to clinical decision-making. However, methodologic standards for extension trials remain poorly defined, leading to inconsistent design, analysis, and reporting. This scientific statement outlines best practices for cardiovascular trial extensions, addressing outcome selection, duration and completeness of follow-up, and analytic strategies suited to evolving treatment effects. Practical considerations, including strategies for participant retention, reconsent, data continuity, and resource allocation, are also discussed.

Anomaly diagnosis of crude oil online near-infrared spectroscopy analysis system with ensemble ICSSOA-SVM

Synchronous spectrofluorimetric determination of tryptophan and kynurenine in human plasma using hydroxypropyl-β-cyclodextrin complexation for investigating their role in major depressive disorder

Genome-wide identification, evolutionary analysis, and expression profiling of protein phosphatase 2C genes in sweet potato (Ipomoea batatas L.)

Seasonal prokaryotic community and geochemical dynamics of an extreme environment: the Naftlije Mud Volcano, Iran

Abstract Mud volcanoes (MVs) are unique terrestrial ecosystems that serve as analogs for hydrocarbon-rich extraterrestrial environments, yet their seasonal microbial dynamics remain poorly understood. This study investigates the seasonal shifts in the prokaryotic community of the Naftlije Mud Volcano (NMV) in northeastern Iran, utilizing 16 S rDNA amplicon sequencing (849 OTUs from 2.9 million reads) alongside comprehensive geochemical analysis over three sampling seasons from 2022 to 2023. We focused on Salsa Lake, a shallow sedimentary environment associated with the NMV, revealing salinity levels between 6% and 8.2%, sulfate concentrations ranging from 170 to 940 ppm, and total petroleum hydrocarbons (TPH) fluctuating between 430 and 989 ppm. Our findings demonstrate substantial community composition changes in response to environmental factors: sulfur-oxidizing Thiomicrospira dominated during the dry season (70% of reads), Arcobacter was prevalent in the wet season (55%), and anoxygenic phototrophic Halorhodospira constituted 76% of reads during the pink summer bloom. Marinobacter remained a consistent presence year-round (2–10%). Notably, unclassified OTUs accounted for 10–20% of sequences, indicating a reservoir of novel diversity. Richness (Chao1) declined from approximately 580 to 180 OTUs as TPH increased and sulfate decreased, while Shannon diversity peaked at 3.2 under diluted spring conditions. These results illustrate that even modest seasonal changes in environmental factors are reflected in the lake’s green-to-pink transitions, actively restructuring the microbial community responsible for sulfur and hydrocarbon cycling, and generating color-linked biosignatures with potential astrobiological implications.

Genomic insights into capital-driven transmission and distance-limited outbreaks of CRAB in Zhejiang ICU networks

Abstract Carbapenem-resistant Acinetobacter baumannii (CRAB) is recognized as one of the most common pathogens responsible for nosocomial infections and mortality among patients in intensive care units (ICUs). Currently, the genomic epidemiological characteristics, transmission patterns, and influencing factors of CRAB dissemination within ICUs remain insufficiently investigated. We conducted a multicenter genomic epidemiological analysis of 138 CRAB isolates collected from ICUs of tertiary hospitals across 8 prefecture-level cities in Zhejiang province between 2018 and 2023. Antimicrobial susceptibility testing and whole-genome sequencing were performed on these isolates. By integrating genomic data from the capital city in public database, we identified population structures and reconstructed transmission events to assess dynamic changes over time. Between 2018 and 2023, CRAB isolates from tertiary hospitals in 9 prefecture-level cities in Zhejiang Province predominantly consisted of the Epidemic Super Lineage (ESL) Clade A and B. The profile of antimicrobial resistance genes was strongly associated with phylogenetic lineage. Short-term outbreaks identified using a 5-SNP threshold demonstrated a significant correlation with geographical distances within 178.7 km. Temporal phylogenetic analysis revealed that the prolonged and sustained transmission of CRAB strains across ICUs in Zhejiang originating in the 2010s, showed a temporal association with the expansion of high-speed rail infrastructure in the provincial capital starting in 2010. CRAB in ICUs from 9 hospitals in Zhejiang Province predominantly consisted of the ESL Clade A and B. Geographical distance and transportation are critical factors influencing the transmission of CRAB outbreaks among ICUs in different cities. The provincial capital appears to exert a persistent influence on non-capital cities, which should be interpreted in light of the larger sample size from Hangzhou.

Ensemble deep learning for optimizing user immersion and engagement in virtual reality

Abstract Virtual Reality (VR) is transforming various domains by providing immersive experiences, but a significant barrier still exists in the inability to recognize user immersion and involvement precisely. To address this study introduces the Adaptive Virtual Reality Design using Immersion Levels and User Engagement (AVRDIL-UEGE) algorithm, which leverages an ensemble of deep learning models to optimize VR immersion and user engagement. By employing a multi-stage approach, the model first standardizes input data using Linear Scaling Normalization (LSN) to enhance accuracy. Subsequently, it integrates Stacked Long Short-Term Memory (SLSTM), Stacked Sparse Autoencoder (SSAE), and Elman Neural Network (ENN) in an ensemble framework to capture complex temporal and spatial patterns. Hyperparameter tuning is performed using the Multi-strategy Improved Red Deer Optimization (MIRDO) algorithm, ensuring robust model performance. Experimental results on the benchmark VR dataset demonstrate the superior predictive accuracy of AVRDIL-UEGE, with a classification accuracy of 98.40% and an MCC of 0.95 compared to traditional machine learning approaches. The proposed model offers significant improvements in user immersion detection, paving the way for more responsive and personalized VR experiences. This work contributes to advancing VR analytics by providing a data-driven, scalable solution for immersive design optimization in real-time applications.