Browse Articles

Occupational sleepiness in suburban metro drivers: association with fatigue, occupational balance and work functioning

Abstract The study examined levels of daytime sleepiness, occupational fatigue, perceived work functioning and occupational balance among suburban metro train drivers, and identified independent predictors of daytime sleepiness. A cross-sectional study was conducted with 191 public transport train drivers who completed validated self-report measures assessing sleep-related functional outcomes (FOSQ), daytime sleepiness (ESS), occupational fatigue (SOFI), work role functioning (WRFQ) and occupational balance (OBQ-E). Descriptive analyses and Pearson correlations were performed, and a multiple linear regression model adjusted for work shift identified independent predictors of daytime sleepiness. Clinically relevant levels of daytime sleepiness (ESS median 11, IQR 7–15) and occupational fatigue were observed. Sleepiness showed a moderate positive correlation with occupational fatigue ( r  = .544, p < .001) and negative correlations with occupational balance ( r = − .419, p < .001) and work role functioning ( r = − .434, p < .001). The regression model adjusted for work shift was significant (F(6,173) = 17.00, p < .001) and explained 37.1% of the variance. Occupational fatigue (β = 0.298, p = .002), occupational balance (β = −0.210, p = .007) and work role functioning (β = −0.169, p = .045) were significant predictors of daytime sleepiness, whereas work-shift categories were not significant after adjustment. Interventions targeting fatigue management and occupational balance may help reduce sleepiness and enhance operational safety.

Goblet cells mechanically breach the epithelial barrier in gut homeostasis

Abstract The intestinal epithelium forms a tight barrier against the harsh luminal environment. Absorptive enterocytes have a polygonal, columnar morphology, while mucus-producing goblet cells exhibit a rounded apical shape and a voluminous cell body, raising the question of how epithelial integrity is preserved in tissues with such morphological heterogeneity. Here, we show that, under homeostatic conditions in vivo, goblet cells mechanically induce tight-junction fractures between neighboring enterocytes. This effect is exacerbated by goblet cell hypertrophy and is associated with increased gut permeability. Using in vivo and organoid models, combined with pharmacological, genetic and mechanical perturbations and theoretical modeling, we demonstrate that these fractures arise from a force imbalance at cell interfaces: goblet cells exert pressure on adjacent enterocytes, whose junctional rupture depends on tissue rheology controlled by myosin II. Our findings uncover a mechanical role for goblet cells in epithelial cohesion and barrier regulation, revealing how cellular heterogeneity shapes tissue integrity.

Integrated proteomics–driven discovery of synovial fluid biomarkers reflecting structural damage and pain in knee osteoarthritis

Synergy between reactive manganese species and enzymes drives litter decomposition hotspots

Abstract Oxidative decomposition of plant litter is a central control on carbon storage and productivity in terrestrial ecosystems. Although this process is commonly assumed to be greatest under oxic conditions, recent findings highlight redox-sensitive metals and enzymes as potent, but poorly understood, mediators. Using controlled soil reactors, we show that stimulating microbial production of reactive manganese(III) at oxic–anoxic interfaces simultaneously increased the expression of diverse litter-decomposing enzymes; together, these metal and enzyme catalysts acted synergistically to accelerate litter decomposition. This 29% increase in decomposition was best predicted by multi-fold increases in the expression of putative Mn(III)-forming and litter-degrading enzymes at the interface, rather than by patterns in strictly oxic or anoxic zones. These results provide evidence to the growing body of research challenging the assumption that oxidative decomposition is maximized under fully oxic conditions. Instead, they reveal a tight interplay among oxygen supply, reactive metal regeneration, and enzyme activity that renders oxic–anoxic interfaces hotspots of litter decomposition in soils.

Attentional focus modulates neuromechanical organization and motor complexity during walking

Abstract Attentional focus instructions have long been recognized for their impact on motor performance and learning, yet their influence on the neuromechanical aspects of gait—spanning multiple analytical levels—remains underexplored. In this study, the authors investigated how attentional focus (internal, external, or no focus) and sex affect lower-limb coordination during walking, drawing on a blend of biomechanical and neuromuscular methods. The complexity of kinematic and electromyographic (EMG) signals was quantified using sample entropy, the inter-joint coordination was evaluated through the Uncontrolled Manifold (UCM) framework by calculating the synergy index (ΔV = log₁₀(V_UCM / V_ORT)) in the sagittal, frontal, and transverse planes, and muscle synergies were extracted via non-negative matrix factorization, emphasizing the number needed to account for 90% of the total variance (VAF). The findings highlighted a persistent main effect of attentional focus across all levels. External focus led to greater kinematic and EMG sample entropy, suggesting heightened movement complexity. Likewise, the UCM synergy index (ΔV) was markedly higher with external focus in every plane, indicating more variability that stabilized the task. In muscle synergy analysis, attentional focus reshaped neuromuscular modularity, requiring fewer synergies to achieve 90% VAF under external focus. Sex differences were modest, appearing only in sagittal-plane ΔV, with no interactions between attentional focus and sex. These results illustrate how attentional focus reshapes gait organization from signal complexity to inter-joint coordination and neuromuscular patterns. Together, they bolster the notion that external focus encourages more adaptive, task-oriented control during walking. This underscores the benefits of multilevel analyses in unpacking the mechanisms behind attentional influences on locomotion.

Phase locking and multistability in the topological Kuramoto model on cell complexes

Abstract Higher-order interactions fundamentally shape collective dynamics in oscillator networks. The topological Kuramoto model captures these effects by extending synchronization models to include interactions between cells of arbitrary dimension within simplicial and cell complexes. We introduce the topological nonlinear Kirchhoff conditions to characterize all phase-locked states of the topological Kuramoto model. These states are organized by winding numbers associated with generalized independent cycles, which quantify how phases wind around these cycles. Using rings, Platonic solids, and regular simplices as illustrative examples, we uncover a universal rule: boundaries must have at least five elements for multistability to arise. We further find that independent winding numbers associated with lower- and higher-dimensional boundaries generate cascades of multistability across dimensions. These results show how the topology and boundary structure of cell complexes influence phase locking and multistability, and provide a general framework for collective dynamics on cell complexes.

Deep learning based feature extraction for liver tumour classification using computed tomography images

Observed thresholds in sea-level rise driving global tidal wetland loss

Design and transfection of CRISPR/Cas9 constructs for the myostatin gene in Labeo rohita muscle cells

Finding the perfect promoter for Cas9 in homing gene drives using single cell transcriptome data

Abstract Gene drive can modify or suppress vector populations by spreading drive alleles. In CRISPR homing drives, regulating Cas9 expression has been effective for improving drive performance, but selecting suitable promoters is often a major challenge. Here, we evaluate 35 Cas9 constructs with distinct promoters in Drosophila melanogaster and identify associations between drive performance and single-cell RNA expression patterns of the promoter-associated genes. Our results indicate that higher drive conversion is associated with elevated expression of the promoter-associated gene in reproductive cells, but embryo resistance allele formation correlates with excessive female germline expression. For males, early germline expression produces superior performance. Thus, optimal drive performance requires restricting Cas9 expression to a tight quantitative and spatiotemporal window. Additionally, we find that an in situ construct significantly reduces potentially harmful somatic expression. Based on these results, we propose criteria for selecting promoters, providing a rationale and guidance for optimization of homing gene drives.

Evaluation of soil degradation caused by wildfire through integration of remote sensing soil quality indices and micromorphological analyses

Semiconductor room-temperature maser

Abstract We report the first demonstration of a semiconductor maser based on silicon vacancies (V Si ) in 4H-silicon carbide (SiC). Using an active feedback loop, we enhance the resonator’s quality factor, enabling continuous-wave maser operation even above room temperature. We analyzed the SiC maser as a high-performance preamplifier, with measured gain exceeding 10 dB at 110 K and simulations suggesting potential amplification beyond 30 dB. Leveraging the small zero-field splitting of V Si , the device can also function as an optically pumped microwave photon absorber, reducing the resonator’s mode temperature by 40 K relative to the environment. Additionally, the maser’s ultranarrow linewidth supports highly sensitive magnetometry, achieving a nine-order-of-magnitude improvement in contrast-to-linewidth ratio over electrical and optical detection of magnetic resonance. This results in an estimated magnetic field sensitivity of 20 pT/√Hz at room-temperature based on the relative intensity noise of the excitation laser. These results underscore the potential of SiC to reshape room-temperature maser technologies, and lay the groundwork for future development of compact, electrically driven maser diodes.

Performance enhancement of hybrid shake table via passive load balancing and nonlinear system identification using coupled ODE modelling

Abstract This study aims to identify a suitable passive load-balancing mechanism for a hybrid shake table, which decouples spatial and planar motion for enhanced control. By minimizing reliance on extensive experimental data, the research seeks to improve system stiffness, compensate for heavy payloads, and enhance the overall performance of shake tables. A regression-based nonlinear least-squares (NLS) technique enhanced by the trust-region-reflective (TRR) algorithm is proposed for system identification. A fusion-based approach is adopted, in which experimental data is used to develop a reduced-fidelity state-space model (SSM) of the shake table, while simulation data is used to evaluate passive load-balancing mechanisms. The study solves higher-order coupled ordinary differential equations (ODEs) to estimate stiffness and damping parameters for various configurations. Among the four vertical motion actuator (VMA) assembly configurations, the configuration equipped with a passive hydraulic damper exhibited superior performance. It attained the highest fit percentages (98.01% and 87.66%), the highest coefficient of determination R 2 values (0.9996 and 0.9847), the lowest normalized root mean square error (NRMSE) values (0.0022 and 0.0083), minimal amplitude errors (0.0338 and 0.1350), and the most negligible phase errors (0 and 0.08) for displacement and velocity responses, respectively. Among the passive mechanisms analyzed, a hydraulic damper proved to be the most effective load-balancing mechanism, demonstrating high stiffness, superior damping, and optimal force compensation. This enhancement is attributed to its nonlinear spring and damping characteristics, which enhance stability under heavy loads. This research presents a standardized approach for solving coupled ODEs in dynamic systems. The findings provide a novel framework for improving shake table performance, with potential applications in earthquake simulation, robotics, and industrial motion platforms.

Electrically driven inverse metamagnetic transition in Sm1-xSrxMnO₃

Dynamics and modulation of weakly nonlinear fast magnetosonic waves in pulsar magnetosphere

Central role for fast nociceptors in mechanical nocifensive behavior and sensitization

Abstract Nociceptors, primary afferent nerve fibers that signal noxious stimuli, are broadly divided into slowly conducting unmyelinated C fibers and fast-conducting myelinated A fibers. Whereas C-nociceptors have been extensively studied, considerably less is known about the function of A-nociceptors. Here we demonstrate, combining genetic targeting of these fibers in mice with observations in human participants, a key involvement of A-nociceptors in mechanical nociceptive withdrawal reflexes and affective pain. In mice, optogenetic stimulation induced rapid and precise withdrawal reflexes as well as place aversion and facial expression changes consistent with pain affect, while inhibition strongly impaired mechanical nociceptive withdrawal reflexes. Prolonged A-nociceptor activation induced mechanical pain hypersensitivity and central sensitization. In a rare individual lacking thickly myelinated Aβ fibers, and in healthy participants during preferential Aβ-fiber nerve block, mechanical withdrawal reflexes were absent and mechanical pain perception reduced. Together, these findings identify fast-conducting mechano-nociceptors as essential drivers of nocifensive behaviors in mice and humans.

Short term associations of weather and air quality with ophthalmic outpatient attendance in eastern China

Abstract The magnitude and timing of short-term associations of weather and air quality with ophthalmic attendance remain poorly quantified. We analysed completed attendances from a tertiary ophthalmology department in Jiangsu, China (2015–2025; 3,788 days) using a time-stratified case-crossover design with conditional Poisson regression. Exposures included catchment-weighted meteorology, nitrogen dioxide (NO₂), and fine particulate matter (PM₂.₅); extreme heat, cold, and heavy rainfall were accumulated over 0–3 and 0–7 days. Over 0–3 days, each additional extreme-heat or heavy-rainfall day was associated with lower completed attendance (rate ratios 0.961 [95% CI 0.954–0.967] and 0.937 [95% CI 0.923–0.952], respectively; both p  < 0.0001), whereas extreme cold showed no clear association. From a baseline of 293 visits/day, two heat days and two heavy-rainfall days corresponded to approximately 23 and 36 fewer visits/day, respectively. Lag analyses suggested delayed positive rainfall associations compatible with partial compensation, but no comparable heat pattern within 21 days. The retrospective trigger simulation had 39% precision and 59% recall; approximately 61% of triggered days were false alarms. Locally derived heat thresholds and rainfall amount-related estimates may support preparedness planning. Because completed attendance—not underlying ophthalmic need—was measured, real-time use requires prospective validation of safety, equity, and unmet-need outcomes.

Highly stable quasi-solid-state initially anode-free lithium metal batteries enabled by dynamic integrated interface engineering

YOLOv8-based real-time obstacle detection in farmland environments for heavy-load agricultural UAVs

Abstract Heavy-load agricultural UAVs operating at low altitude over farmland often encounter three major difficulties: unreliable recognition of distant small obstacles, unstable localization of elongated targets, and strong interference from cluttered backgrounds. To cope with these challenges, this work introduces a lightweight real-time obstacle detection framework by redesigning YOLOv8n for farmland scenes. In the backbone, SPD-Conv, retained high-resolution $$\:{P}_{2}$$ features, and the DGA-C2f module are jointly used to preserve fine-grained cues for small and slender obstacles. In the feature aggregation stage, a lightweight scale-difference fusion network is constructed, where the LSDF module is embedded into a bidirectional interaction scheme to strengthen cross-level feature collaboration. In the prediction stage, a direction-aware decoupled head is adopted so that orientation modeling can assist localization and improve the regression quality of elongated targets. Experiments on a self-built farmland obstacle dataset show that the resulting model reaches 89.3% Precision, 88.0% Recall, 91.8% mAP@0.5, and 85.0% mAP@0.5:0.95. Compared with YOLOv8n, the proposed model improves Precision, Recall, mAP@0.5, and mAP@0.5:0.95 by 1.5, 1.8, 2.4, and 2.3% points, respectively. It also maintains real-time inference performance with appropriate parameters, 8.9 GFLOPs, and 123 FPS, demonstrating a clear balance among detection accuracy, lightweight complexity, and deployment efficiency for farmland obstacle perception.

Substituent-rebound skeletal editing for precise boron-to-carbon single-atom swapping

Abstract Developing methods that enable single-atom exchange within an aromatic scaffold, while preserving its peripheral substitution, represents an important but highly ambitious goal in synthesis. In principle, such approaches would allow the impact of a single-atom change within a molecular framework to be distinguished from the effects of also altering the peripheral substituents. Yet despite this conceptual power, single-step methodologies for single-atom exchange in aromatic systems remain rare. Herein, we present a boron-to-carbon swapping reaction via a substituent-rebound process, converting 1,2-benzazaborines into the corresponding quinolines. The employment of glyoxylic acid as the carbon-atom source allows the original substituent on the boron atom to be recaptured and incorporated into the quinoline product, representing a rare example of true single-atom skeletal editing. The transformation exhibits high levels of functional group tolerance and is applicable to the late-stage modifications of natural product and pharmaceutical derivatives. Furthermore, comprehensive mechanistic investigations elucidate the intricacies of this process, establishing a foundation for future single-atom editing manifolds that can facilitate the interrogation of structure–function relationships with atom-level precision.