Biomass fuels are used extensively for cooking globally, posing a severe health threat to more than 2.50 billion people. However, while improved biomass stoves can reduce average pollutant concentrations, their effects on short-term pollution dynamics and inter-room pollutant transport remain poorly understood. This study implemented an advanced biomass intervention in rural households of Xuanwei, Yunnan Province, utilizing real-time monitors to measure PM2.5 concentrations in kitchen, living room, bedroom, and yard. Results showed that stove intervention reduced daily mean PM2.5 levels across all microenvironments. Kitchen PM2.5 concentrations declined by 29.3%, 55.8%, and 30.7% for households adopting direct-fired, recirculating, and gasifier stoves, respectively. High-temporal-resolution analysis further showed substantial attenuation of cooking-related PM2.5 peaks following stove intervention, especially in households using gasifier stoves which reduced cooking peak height and area by 59.3% and 60.2% in kitchen, respectively. Correspondingly, the contribution of cooking activities to kitchen PM2.5 decreased by approximately 30.0%, suggesting that stove replacement attenuated cooking-related pollution. In households using gasifier stoves, the indoor-to-outdoor PM2.5 ratios in living rooms and bedrooms approached unity, suggesting diminished influence from indoor sources. These findings provide preliminary field-based evidence that advanced biomass stoves may mitigate cooking-related PM2.5 pollution and limit its spatial dispersion in biomass-dependent rural households.

Real-time spatial coordination in high-density seaport container yards is a bottleneck in global supply chains. In these environments, GPS signal denial and severe visual occlusion render traditional theoretical scheduling models ineffective. To resolve this operational gap, this paper introduces HY-EnYO, a novel dual-stream ensemble architecture designed to automate the identification of vacant parking bays using monocular CCTV footage without requiring physical sensor infrastructure. Addressing a fundamental limitation of standard single-stream deep learning detectors, which suffer from severe cross-class feature confusion when mapping massive infrastructure alongside dynamic assets within a unified latent space, the proposed framework decouples visual extraction into parallel sub-networks specialized for yard cranes (Mc) and terminal trucks (Mt). While this feature extraction remains probabilistic, final occupancy state reasoning is resolved by a deterministic logic engine. This engine projects perspective-aware parking polygons and evaluates Intersection over Union (IoU) overlap against a spatial threshold (τ=0.08), mathematically counteracting camera perspective distortion and sensor jitter. Compared to standard single-stream baselines, HY-EnYO reduces the computational parameter footprint by over 67% (from 36.49 M to 12.02 M), requires a peak VRAM allocation of only 0.10 GB, and achieves an inference latency of 21.82 ms, ensuring edge-device feasibility. Extensive evaluation on real-world CCTV datasets from the Busan seaport demonstrates peak detection accuracies (maP@0.5) of 0.899 for trucks and 0.999 for cranes. Evaluated across a 316-instance test sequence, the deterministic spatial engine achieves a perfect occupancy precision of 1.000 (preventing false-positive routing deadlocks) and an overall system accuracy of 98.0%, maintaining high operational accuracies of 97.0% and 98.0% under simulated adverse weather and low-illumination conditions, respectively. The framework provides a mathematically rigorous, highly efficient spatial matrix, establishing a data-driven foundation for automated seaport traffic coordination.

Female university ice hockey players in Japan often have limited opportunities to perform additional conditioning because of demanding academic schedules and regular team training. Consequently, brief and practical exercise programs that can be incorporated into daily routines are needed. We report a prospective case series evaluating the feasibility and potential effectiveness of a minimal-dose core training program consisting of a 30-second prone static plank performed three times per week. Three elite female university ice hockey players (one in her late teens and two in their early 20s), all with youth national team experience and competing in Japan's highest-level women's league, participated in this 24-week prospective case series conducted using a BAB single-case experimental design. Participants completed an initial eight-week intervention period, an eight-week withdrawal period, and a second eight-week intervention period while continuing their usual team training. Core function was evaluated using the Sahrmann Core Stability Test (SCST) and Seated Side Tapping Test (SST), athletic performance was assessed using the sit-up test and 40-yard dash, and body composition was measured by bioelectrical impedance analysis. Improvements in SCST, SST, and sit-up performance were consistently observed during the intervention phases, whereas performance plateaued or declined during the withdrawal phase. Sprint performance and body composition changed minimally throughout the study. All participants reported excellent adherence to the program without interference with university life and described increased body awareness and motivation toward training. This case series suggests that an extremely brief, high-frequency core training program may improve core function and muscular endurance through neuromuscular adaptation rather than muscle hypertrophy. Although the findings are limited by the small number of participants, this practical intervention may represent a feasible conditioning strategy for elite student-athletes with limited training time.

Antibody imprinting is well recognized, yet its long-term dynamics and epitope specificity remain poorly understood. Here, we studied individuals sequentially infected with SARS-CoV-1 (SARS-1) and SARS-CoV-2 (SARS-2) over two decades and found durable imprinting of antibody responses following SARS-2 BF.7 breakthrough infection. Approximately 60% of isolated monoclonal antibodies were SARS-1 imprinted and targeted conserved receptor-binding domain regions, whereas 37% overcame imprinting to recognize the SARS-2 receptor-binding motif overlapping the ACE2-binding site. Notably, some SARS-1-only antibodies retained germline-like features and neutralizing activity 20 years after infection. One exceptionally imprinted broadly neutralizing antibody, THZ937, protected hamsters against contact and airborne transmission of Omicron EG.5.1, demonstrating the functional relevance of durable imprinted antibodies. Together, these findings define the remarkable longevity and molecular basis of antibody imprinting and provide insights for pan-sarbecovirus vaccine design.

Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.

CAR T-cells targeting CD19 have revolutionized the treatment of relapsed/refractory B-cell malignancies. However, approximately 50% of patients relapse. Patient-derived data indicates that CD19+ relapse is linked to poor CAR T-cell proliferation and/or persistence. We aimed to improve CD19-CAR T-cell survival by manipulating Notch1, a receptor that is activated following T-cell receptor ligation and is essential for upregulating pro-inflammatory and survival genes in T-cells. However, its role in the context of CAR T-cells remains poorly understood. We found that both lentiviral overexpression of Notch1's intracellular domain (N1ICD) and Notch1 genetic knockout resulted in defective CAR-T cell activation and proliferation. This suggests that CAR T-cells require a precise, balanced level of Notch1 signaling for strong effector function. The PEST domain, located at the most distal C-terminus of the Notch1 intracellular domain, regulates the receptor's half-life through ubiquitylation. To augment the levels of active Notch1 and prolong the receptor's signaling, we genetically deleted this domain in the endogenous N1ICD of CAR T-cells. Notch1 PEST-deleted CAR T-cells showed enhanced proliferation post-activation, leading to increased cytotoxicity against CD19+ tumors in vitro. Transcriptionally, Notch1 PEST deletion resulted in upregulation of interferon response pathways and proliferative genes during CAR activation, consistent with Notch1 activation. In B-ALL xenograft in vivo models, treatment with Notch1 PEST-deleted CAR T-cells resulted in greater tumor reduction and increased CAR-T expansion compared to control CAR T-cells. Our findings demonstrate a critical role of Notch1 in CAR-T effector function and provide a novel strategy to augment endogenous Notch1 activity by leveraging native gene regulation.

A shipping container yard worker from Taiwan contracted laboratory-confirmed pulmonary coccidioidomycosis. He reported no travel history to endemic regions. Occupational exposure to aerosolized dust or soil residues on maritime shipping containers from endemic areas is likely. Our findings highlight international shipping as a potential pathway for introducing geographically restricted pathogens into nonendemic regions.

Geng rice (Oryza sativa subsp. japonica) from northeast China dominates the country's high-value rice market because of its superior eating quality. However, current methods for quality evaluation rely on either labor-intensive, subjective sensory protocols or low-accuracy, calibration-heavy near-infrared spectroscopy (NIRS), thus hindering breeding efforts for high eating quality and market development. Here, we report a vision-based deep learning framework that combines multi-population fine-tuning with industrial vision-language model (VLM) pre-training to predict the eating quality of Geng rice. Trained on datasets from natural and recombinant inbred (RI) populations, our optimal model (Model 4) showed high cross-population stability. It achieved R[2] values of 0.98 for a natural-population validation set (35 cultivars), 0.57 for the independent DA-RI population (201 lines), and 0.61 for a randomly collected set of 30 cultivars from northeast China and 28 cultivars from southern China, consistently outperforming the widely used Satake STA1B analyzer. This approach also enabled us to map a novel, robust quantitative trait locus, qIVOE7, for Geng rice eating quality on chromosome 7. Further analysis suggested that Model 4 relied primarily on the hue dimension of the HSV (hue, saturation, and value) color space for its predictions. This framework provides a highly accurate predictive model and a simple tool for the evaluation of rice eating quality, helping to accelerate the breeding and market development of high-quality rice.

Climate change is reshaping the global distribution of venomous snakes, with important implications for public health. Snakebite envenoming is estimated to cause approximately 63,400 deaths annually, mostly in tropical and developing countries. However, few studies have comprehensively assessed the future global patterns of envenomation risk, particularly across venom types with differing clinical and ecological characteristics. In this study, we modeled the current and future distributions of 193 medically important venomous snake species (neurotoxic and hemotoxic) under 4 climate change scenarios through 2100. We assessed 3 indices to quantify snakebite risks: the Venom Richness Index (VRI) for species-specific venom diversity, the Snakebite Range Expansion Index (SREI) to capture range expansion or contraction, and the Venom Overlap Index (VOI) for geographic co-occurrence of venom types. We found that snakebite risk is projected to increase in temperate and cold regions under high-emissions scenarios, with VRI and SREI increasing in areas such as North America, Europe, and East Asia. In contrast, VRI and SREI are projected to decline across parts of tropical Africa, India, and southern China. VRI transitions are projected to expand in northern Mexico, Brazil, Spain, southwestern China, and southern Australia, increasing the potential for diagnostic uncertainty and treatment complexity. VOI is expected to rise in highly populated but poorly urbanized regions, highlighting the vulnerability of developing countries with limited infrastructure. These spatial and venom-specific shifts underscore the need for regionally tailored antivenom strategies, improved diagnostics, and high-resolution risk forecasting to mitigate the future burden of snakebite under global change.

Fly-ash (FA) is a valuable coal combustion residue with enormous potential to use in agriculture but dose optimisation is a must. The objectives of the present field study (started in 2021; completed 2 crop cycle) was to assess the impact of 12 diverse FA-doses applied annually (10, 20 and 40 t ha[- 1]), biannually (20, 40 and 80 t ha[- 1]) and once (100, 200 and 400 t ha[- 1]) on changes in soil quality, emissions of greenhouse gases (GHGs) and bio-chemical characteristics of maize grains. Conceptual frame work based soil quality index (CFSQI) was developed under both productivity (P) and environmental protection (EP) management goals. Recommended dose of fertiliser (RDF) along with and farm yard manure (FYM) (RDF + FYM) showed the highest CFSQI-P (0.78) and CFSQI-EP (0.71) in 0-15 cm soil depth. The cumulative emissions of nitrous oxide (N2O) and ammonia (NH3) was highest in RDF + FYM (1.49 kg N2O ha[- 1]) and RDF + FYM+FA-alternate year (AY) 80 t ha[- 1] (36.41 mg kg[- 1]), respectively. The Mg and Cu content in maize grain increased significantly with increase in FA dose, while the Cd and Pb contents did not exceed the permissible limits of these metals. The anti-oxidant activity (47.51 µmoltrolox g[- 1]) and total phenol (53.63 mg 100 g[- 1]) contents in grains was recorded highest in annual application of FA at 20 and 40 t ha[- 1] along with RDF + FYM, respectively. The rank analysis suggested based on all (soil properties, GHG emission and grain attributes) traits revealed that application of FA (annually 10 t ha[- 1]) along with RDF + FYM scored highest (0.789) with first rank. Thus, based on the experimental findings, it could be concluded that the application of FA (10 t ha[- 1]) along with integrated fertiliser management emerged as a strategy under maize-wheat system which could improve soil quality, mitigate gaseous emissions and sustain maize grain quality with possible no inimical impacts on animal and human health.