Search Results (10,630)

Drought tolerance in rice is a complex quantitative trait that is difficult to predict from high-dimensional genomic data. We developed an interpretable deep-learning framework using phenotypic and genome-wide SNP genotype data from 426 rice accessions. Seven drought-response agronomic traits were integrated through principal component analysis and membership functions to derive a continuous drought-tolerance index. Four genomic representations were evaluated, and a convolutional neural network (CNN) was coupled with multi-head self-attention and Bernoulli input masking. With maximal information coefficient (MIC) screening, the proposed model achieved the highest mean Pearson correlation coefficient (PCC) of 0.6114, representing relative improvements of 5.39% and 6.01% over DeepGS and DNNGP, respectively. Attention-derived positional importance scores prioritized genomic signals centered on SNPs located within Os03g0221300, Os03g0372500, and Os12g0586300. Exploratory PC-adjusted additive allelic-dosage analyses in the same panel provided additional association evidence for all three prioritized loci. In this rice panel, the framework combined genomic prediction with model-derived candidate-locus prioritization and exploratory population-structure-adjusted marker–phenotype association analysis. Full article

Introduction: Diabetic painful neuropathy (DPN) is one of the most common and debilitating complications of diabetes, substantially impairing the quality of life of patients. In the absence of disease-modifying therapies, treatment remains focused on symptomatic pain control with non-opioid pharmacologic agents; however, comparative evidence guiding optimal medication selection remains limited. Using a systematic review, pairwise meta-analysis, and network meta-analysis, this study compares the effectiveness of current non-opioid-based treatments, including amitriptyline, duloxetine, gabapentin, and pregabalin, for pain reduction in patients with DPN. Methods: PubMed and Google Scholar were systematically searched for randomized and clinical trials published between 2010 and 2025 evaluating these medications as monotherapy for DPN. A total of n = 11 studies met the inclusion criteria. Pain outcomes measured using the Numeric Rating Scale (NRS), Visual Analog Scale (VAS), or Brief Pain Inventory (BPI) were standardized to a common metric. Random-effects pairwise meta-analyses were performed to estimate within-drug treatment effects, followed by a frequentist network meta-analysis to compare therapies through direct and indirect evidence. Mean change in pain severity was the primary outcome. We performed heterogeneity, network consistency, and sensitivity analyses under varying correlation assumptions. Results: A total of 1397 participants across 11 studies were included. Pairwise meta-analysis demonstrated substantial pain reduction with duloxetine (mean change [MC] 27.8; 95% CI 18.5–37.1), gabapentin (MC 34.8; 95% CI 9.3–60.3), and pregabalin (MC 19.7; 95% CI 8.9–30.5). Although amitriptyline trials individually reported improvement, the pooled estimate did not reach statistical significance. Network meta-analysis indicated that gabapentin, duloxetine, and amitriptyline were associated with better estimated analgesic benefit than pregabalin; the differences among gabapentin, duloxetine, and amitriptyline were modest and not statistically significant. Sensitivity analyses supported the robustness of the findings, and no significant network inconsistency was detected. Conclusions: Commonly used non-opioid pharmacologic therapies for DPN provide broadly comparable analgesic benefit, with gabapentin showing comparatively preferable reduction in pain severity within the network analysis. Given the modest differences between agents and substantial variability in individual response, treatment decisions should be individualized according to patient comorbidities, tolerability, and therapeutic goals. Larger, methodologically standardized comparative trials are needed to strengthen the evidence base and support more precise, evidence-based management of DPN. Full article

Intradialytic hypotension (IDH) is a common complication of hemodialysis and is associated with treatment interruption, reduced patient tolerance, cardiovascular events, and hospitalization. Existing machine learning studies often use only limited dynamic dialysis information and provide insufficient feature interpretation. This study proposes an IDH risk prediction method based on multi-domain dynamic features and an improved Sparrow Search Algorithm (ISSA). After temporal alignment, outlier handling, and missing-value imputation, a candidate feature set was constructed from 12 baseline variables and 48 time-domain, frequency-domain, and time–frequency-domain features extracted from six continuous dialysis parameters. ISSA was then used to select a 13-dimensional feature subset comprising eight baseline and five dynamic features. Several machine learning models were evaluated before and after feature selection. Using a public hemodialysis monitoring dataset from a tertiary medical center, XGBoost achieved the best overall performance. Adding the five selected dynamic features increased ROC-AUC from 0.8355 to 0.8410 (ΔAUC = 0.0055, 95% CI: 0.0010–0.0100, p = 0.020), indicating a statistically significant incremental contribution. TreeSHAP analysis identified the spectral centroid of dialysis duration, conductivity, dialysate temperature, dialysis duration, and pre-dialysis body weight as important predictors. The proposed framework supports compact and interpretable early IDH risk prediction. Full article

Cold stress induces adaptive remodeling of adipose tissue, yet the coordinated molecular network, particularly the interplay between upstream signaling pathways and downstream cellular responses, remains incompletely understood. This study investigated whether cold stress regulates adipose tissue beiging, apoptosis, and systemic metabolic remodeling through autophagy and inflammation mediated by the β3-adrenergic receptor (ADRB3)-extracellular signal-regulated kinase (ERK) signaling axis. The results demonstrated that cold stress significantly increased energy expenditure and markedly improved glucose tolerance and insulin sensitivity in Min pigs. In subcutaneous adipose tissue, cold stress induced pronounced beiging, as evidenced by reduced adipocyte size, the presence of multilocular lipid droplets, and upregulation of beige adipocyte marker genes, accompanied by increased preadipocyte apoptosis. Transcriptomic analysis revealed significant enrichment of pathways related to autophagy and lipolysis, with inflammation (notably the TNF signaling pathway) also identified as a potential contributing process. Mechanistically, cold stress activated the ADRB3-ERK signaling axis, leading to enhanced autophagic activity, and inflammation-related genes were also upregulated, suggesting that inflammation may serve as a candidate process cooperating with autophagy. In conclusion, this study reveals a novel molecular mechanism whereby cold stress activates the ADRB3-ERK signaling axis to stimulate autophagy, with inflammation potentially cooperating as a candidate process, thereby driving adipose tissue beiging, apoptosis, and systemic metabolic remodeling. Full article

This paper studies a nonnegative square-root diffusion subject to finite-activity multiplicative jumps whose multipliers follow a Gamma distribution. The analysis develops the mathematical foundation that is needed before moment calculations can be used: existence and pathwise uniqueness of a nonnegative càdlàg solution, absorption at zero, and finiteness of every positive integer moment on finite time intervals. A localization argument then justifies Dynkin’s formula for the unbounded monomials. The resulting moment system is lower triangular. We give both an integral recursion and a matrix-exponential representation, derive stable closed forms for the first three moments using continuous divided differences, and cover all coincident-growth-rate cases without singular expressions. A long-run theorem identifies the dominant exponential rate and the polynomial correction caused by repeated dominant rates. Numerical integration of the moment ordinary differential equations independently confirms the analytic formulas, with maximum relative discrepancies below 10⁻⁸ under the coarsest reported tolerance. A multi-parameter analysis further quantifies variance, skewness, and excess kurtosis. The contribution is not the individual use of square-root diffusion, Gamma multipliers, or generator methods; it is a rigorous and computationally stable characterization of their specific multiplicative-jump combination. Full article

Rising costs, supply uncertainty, and geopolitical dependence associated with rare-earth permanent magnets have created an urgent need to reduce permanent magnet (PM) usage in electric machine designs while maintaining high electromagnetic performance. This paper presents a comprehensive comparative investigation of PM reduction strategies for three widely adopted traction machine topologies: Surface Permanent Magnet (SPM), Interior Permanent Magnet (IPM), and Permanent Magnet-Assisted Synchronous Reluctance (PMASynRM) machines. We developed a unified evaluation framework by integrating each machine’s electromagnetic characteristics, electrical operating constraints, and practical inverter limitations across a wide operating speed range. Finite element analysis (FEA) is employed to systematically investigate the effects of progressive PM volume reduction by independently varying magnet width and length while keeping stator geometry, winding configuration, material properties, and operating conditions. We reduced PM dimensions from 100% to 30% of the baseline design to evaluate their impact on torque-speed characteristics, efficiency, and flux-weakening capability. The results reveal that the impact of PM reduction depends strongly on both machine topology and the magnet reduction strategy. Across all machine topologies, reducing magnet width consistently preserves higher torque capability, efficiency, and high-speed operating performance compared with reducing magnet length. Among the machines investigated, the SPM topology exhibits the greatest sensitivity to PM reduction, particularly in the constant-torque region, owing to its complete reliance on permanent magnet excitation. In contrast, the IPM and PMASynRM machines show much greater tolerance to reduced PM volume because the additional contribution of reluctance torque from rotor saliency improves torque retention, extends the constant-power speed range, and reduces efficiency degradation. These findings provide valuable design insights into the trade-offs between permanent magnet utilization and machine performance, offering practical guidelines for minimizing rare-earth material consumption while maintaining competitive traction performance in next-generation electric vehicles and other sustainable electrification applications. Full article

Distributed sensing systems must ultimately reach a single shared decision, whether an alarm, a classification, or a control action. Achieving this is challenging because the two underlying technologies rely on conflicting assumptions. Quorum-based consensus protocols provide a consistent, totally ordered decision log, but they depend on relatively stable network connectivity and lose availability during network partitions. In contrast, disruption-tolerant communication relies on store-and-forward mechanisms that continue operating despite intermittent connectivity, yet these mechanisms are not designed to support the synchronous message exchanges required by consensus protocols. This work investigates how these two approaches interact by deploying the Raft consensus protocol over a resilient, multi-transport, store-and-forward communication layer. The system is evaluated in NS-3 under varying degrees of network partitioning, adversarial source participation, and node failures, while also validating the transport abstraction through packet-level analysis. The study yields four main findings. First, the integrated system maintains safety: committed logs remain consistent in every experiment, including scenarios where isolated leaders rejoin the network and discard uncommitted log entries. Once connectivity is restored, the system converges to a common state within a bounded recovery time. Second, intermittent connectivity can trigger excessive Raft term growth, a phenomenon effectively controlled by enabling PreVote together with CheckQuorum. This configuration reduces post-recovery convergence time by approximately an order of magnitude while also revealing a trade-off between the CheckQuorum timeout and the transport carry deadline. Third, decision accuracy follows the predictions of the Condorcet jury theorem: as partitions reduce the effective number of participating nodes, the system becomes more susceptible to adversarial influence, lowering the threshold at which incorrect decisions can dominate. Finally, we quantify the resilience of different data-fusion strategies against confidence-inflation attacks. Our evaluation focuses on crash-fault tolerance in the presence of malicious data sources, and we explicitly discuss the limitations of this model. Full article

Dissolved oxygen (DO) is a key environmental factor affecting the survival and development of farmed fish. However, the hypoxia responses of white trevally (Pseudocaranx dentex) remain poorly understood. In this study, we determined the DO tolerance thresholds and integrated physiological, histological, and molecular responses of white trevally to hypoxic stress. Smaller fish exhibited higher values for critical oxygen tension (3.50 ± 0.18 mg/L) and loss of equilibrium (LOE, 0.92 ± 0.14 mg/L), whereas larger fish showed lower values. Hypoxia significantly elevated serum cortisol, glucose, alanine aminotransferase, and aspartate aminotransferase levels, which peaked at LOE. Under hypoxia, histological analysis revealed lamellar clubbing, hypertrophy, and hyperplasia in gills, and vacuolization and nuclear migration in liver sections. In the liver, superoxide dismutase and catalase activities and malondialdehyde content increased, while glutathione peroxidase activity decreased. Upregulation was observed for stress-related genes (HSP70, HSP90, mineralocorticoid receptor, and glucocorticoid receptor) and pro-apoptotic genes (p53, BAX, and Caspase-3), while Bcl-2 was downregulated. Principal component analysis indicated that hypoxia triggered stress responses, tissue damage and apoptotic signaling; smaller fish were the most vulnerable, emphasizing the need for size-specific management in aquaculture. Collectively, these findings provide baseline data that may support the healthy development of traditional white trevally aquaculture. Full article

Light-emitting diode (LED) photobiomodulation has emerged as a non-invasive approach for skin quality improvement and reduction in visible aging signs. This study evaluated the efficacy and tolerability of a combined skincare regimen consisting of a home-use silicone LED facial mask emitting red light used together with a cosmetic serum for skin rejuvenation. An open, single-centre clinical study without a control group was conducted in 20 healthy female volunteers aged 40–55 years presenting visible facial wrinkles and skin imperfections. Participants used the LED mask twice daily for 10 min over 56 days, each session being followed by application of a standardized cosmetic serum, so that the LED device and the serum were evaluated as a single combined regimen. Skin evaluations were performed at baseline (D0), after 28 days (D28), and after 56 days (D56) using three-dimensional skin topography (AEVA-HE), high-frequency ultrasound imaging (Ultrascan^® UC22), biomechanical measurements (Cutometer^® dual MPA 580), and pigmentation analysis (Mexameter^® MX18). In the exploratory analysis, a statistically significant improvement in the Cutometer firmness parameter (F4) was observed at D56 compared with baseline (p = 0.03). Changes in elasticity, pigmentation, wrinkle-related topographic measurements and dermal thickness did not reach statistical significance and are reported only as non-significant numerical trends. The treatment was well tolerated, with no significant skin reactions observed. These preliminary findings suggest that a combined regimen incorporating home-use LED photobiomodulation and a cosmetic serum may be associated with an improvement in skin firmness. Because the study was uncontrolled and the LED device was used together with a serum, the observed changes cannot be attributed to photobiomodulation alone and should be interpreted as preliminary. Full article

Hypercholesterolemia is a major risk factor for cardiovascular and hepatic diseases. Recently, probiotics have garnered significant attention as a promising, non-pharmacological approach to regulate lipid metabolism. In this study, we screened potential cholesterol-lowering lactic acid bacteria from Jiangshui, a traditional Chinese fermented vegetable beverage. Initially, 52 acid-producing isolates were obtained using CaCO₃-supplemented MRS agar. Subsequent screening for bile salt hydrolase (BSH) activity yielded five promising strains. These isolates were further evaluated for gastrointestinal tolerance, cell surface hydrophobicity, and in vitro cholesterol removal capacity. Strain JS-51, identified as Limosilactobacillus reuteri via 16S rRNA sequencing, exhibited superior probiotic properties. It demonstrated high cell surface hydrophobicity (72.36 ± 1.24%), robust survival under harsh conditions (pH 3.0 and 0.5% bile salts), and the highest in vitro cholesterol removal rate (55.15 ± 1.87% at 48 h). The in vivo hypocholesterolemic efficacy of L. reuteri JS-51 was then evaluated in a high-fat diet-induced Sprague Dawley rat model. Following a four-week daily oral administration at doses of 10⁶, 10⁷, and 10⁸ CFU/mL, JS-51 elicited a dose-dependent reduction in serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol (p < 0.001), alongside an increase in high-density lipoprotein cholesterol. Histopathological analysis revealed observable morphological amelioration of hepatic steatosis, a reduction in the liver index by up to 5.56%, and the restoration of normal hepatocyte architecture. These phenotypic findings indicate that L. reuteri JS-51 possesses robust in vitro probiotic potential and effective in vivo lipid-lowering capabilities, highlighting its potential as a functional starter culture or dietary supplement for managing hypercholesterolemia. Full article

This study aimed to examine the relationships among autistic traits, psychological pain, anger rumination, and tolerance for psychological pain in medical students. This single-center, cross-sectional study included 544 medical students at Kırıkkale University Faculty of Medicine, Türkiye (mean age: 22.40 ± 1.91 years; 55.3% women). Participants completed the Autism Spectrum Quotient (AQ), Orbach and Mikulincer Mental Pain Scale-8 (OMMP-8), Tolerance for Mental Pain Scale-10 (TMPS-10), and Anger Rumination Scale (ARS). Higher autistic traits were associated with greater psychological pain and anger rumination and lower tolerance for psychological pain. Students with AQ scores ≥26 had significantly higher psychological pain and anger rumination and lower tolerance for psychological pain than those with AQ scores <26. In multivariable analysis, autistic traits, anger rumination, and tolerance for psychological pain were independently associated with psychological pain. Cross-sectional indirect-effect analyses showed significant indirect effects through anger rumination (b = 0.112, 95% CI [0.066, 0.162]) and tolerance for psychological pain (b = 0.185, 95% CI [0.127, 0.243]), while the corresponding direct effects remained significant. These findings highlight the relationships among autistic traits, anger rumination, tolerance for psychological pain, and psychological pain in medical students. Full article

Seed vigour is a key trait determining field seedling establishment and storage longevity in rice. In this study, we aimed to systematically evaluate the vigour variation patterns of rice germplasm from different sub-populations and geographic origins under artificial ageing and explore the feasibility of multi-spectral imaging for non-destructive vigour assessment. Specifically, we selected 244 rice accessions covering seven sub-populations and originating from six continents. After 0, 10 and 15 days of accelerated ageing, standard germination tests combined with multi-spectral image analysis were conducted to determine the germination rate, germination potential and vigour index. The results showed that accelerated ageing significantly inhibited the germination ability of all seeds, and this effect exhibited significant sub-population specificity. Among the sub-populations, aus and Asian-origin accessions displayed the strongest ageing tolerance, while the temperate japonica sub-population and European-origin accessions were highly sensitive, with vigour almost completely lost after 10 days of ageing. Multi-spectral data analysis revealed that reflectance in the 780–970 nm wavelength band was highly significantly correlated with the vigour index. In conclusion, the genetic background and geographical ecotype may be key determinants of seed storability in rice; the aus sub-population and Asian-origin accessions appear to be promising sources of ageing tolerance; and multi-spectral imaging can serve as an effective high-throughput, non-destructive tool for seed vigour evaluation. It should be noted that, given the limited sample size in this study and the fact that geographic origin and sub-population composition may not be independent in the evaluated germplasm panel, the conclusions are only representative of this particular set of accessions. The generalisability of the results therefore requires further validation with additional and more balanced samples. Full article

Heat stress is an increasing constraint on leaf mustard production (Brassica juncea); however, methods for screening heat tolerance and evaluating genotype stability across environments remain limited. This study established a rapid screening method for heat tolerance based on relative injury (RI, %), expressed as cell membrane thermostability (CMT) under heat treatments. A preliminary temperature-response experiment showed a sigmoidal increase in RI, with 45 °C providing the greatest discrimination among genotypes; therefore, it was selected as the evaluation temperature for heat tolerance. Six leaf mustard accessions from Myanmar and Japan were evaluated under five sowing conditions. The combined ANOVA revealed significant effects of genotype, environment and genotype-by-environment interaction, indicating that heat tolerance is genetically controlled but is also influenced by environmental conditions. Genotype stability across environments was evaluated using the additive main effects and multiplicative interaction (AMMI) and genotype plus genotype-by-environment (GGE) biplot. The analysis showed that JP256550 (M3) had the lowest and most favorable genotype selection index (GSI) for CMT, whereas Yamagata seisai and Miike takana, with the lowest AMMI stability value (ASV), showed the most stable CMT across environments. In contrast, JP256560 (M1) and JP256554 (M4) exhibited greater environmental sensitivity and specific adaptation. Different sowing times also accelerated plant development and flowering, with the Myanmar accessions bolting earlier than the Japanese accessions. The results indicated that CMT measured at 45 °C is an effective phenotyping tool for heat tolerance screening in combination with multi-environment stability analysis, providing a practical approach to identify stable genotypes and suggesting that M3 is a promising candidate for future heat-tolerance breeding. Full article

Sparse and heterogeneous plastic-related data complicate the construction of analytical datasets and the evaluation of predictive models. This study presents AUDA, a workflow that organizes human-reviewed records extracted by PRISM into country–year analytical tables and supports descriptive analysis, interpolation, and forecasting. The analytical database contains over 28,000 records from 195 countries and regions. The case studies use smaller datasets constructed from available observations, along with an external global plastic-production series. Correlation and random-forest feature-importance analyses describe associations with plastic waste generation. Predictive evaluations compare interpolation, statistical, and machine-learning methods using repeated masking and rolling-origin forecasting. Cubic spline interpolation and Gaussian process regression achieved the lowest mean weighted absolute percentage error in the Japan and United States resin-consumption interpolation tasks, respectively. Theil–Sen regression achieved the lowest error using this metric in global plastic-production forecasting, while persistence and ARIMA tied for the lowest error in forecasting Japanese plastic-waste generation. These rankings are specific to the evaluated series and data partitions. An exploratory sensitivity analysis also examines how a standard-error tolerance coefficient and the chosen complexity ordering affect hyperparameter selection; it does not establish improved performance on unseen data. AUDA provides workflows for analyzing available records but does not reconcile differences in source measurement methods or estimate policy effects. Full article

The Salem Black goat is an indigenous Indian breed valued for its premium Black leather and high twinning rate, yet its genomic diversity and adaptive potential remain unexplored. We characterised genomic diversity, population structure, demographic history and selection signatures using whole-genome sequence data from 11 Salem Black goats (7 unrelated individuals retained after kinship filtering) analysed alongside 157 individuals from five global breeds (Red Sokoto/Maradi, Tanzania Toggenburg, Omani Jabal Akhdar, Pakistani Kachan and Madagascar Diana), yielding a final dataset of 120 unrelated animals and 36,584 autosomal SNPs. Genomic inbreeding was estimated via runs of homozygosity; population structure was assessed using principal component analysis, ADMIXTURE, phylogenetic reconstruction, and genetic differentiation. Historical effective population size was inferred, and selection signatures were identified using the de-correlated composite of multiple signals (DCMS) approach. Salem Black goats showed the highest genomic inbreeding ($F_{ROH}$ = 0.41), lowest observed heterozygosity (9.6%), and smallest recent effective population size ($N_e\approx 15$), indicating severe recent inbreeding and genetic erosion. Population structure analyses identified Salem Black as a distinct lineage most closely related to Pakistani Kachan goats. Significant selection signals emerged only in Madagascar Diana, Omani Jabal Akhdar, and Tanzania Toggenburg goats, highlighting genes linked to heat tolerance, immunity, DNA repair, metabolism, and reproduction. These findings provide the first genomic characterization of Salem Black goats and identify their urgent conservation priority. Full article