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Fall armyworm (Spodoptera frugiperda) is a major invasive pest threatening soybean production, and identifying resistant genotypes is essential for sustainable crop protection. This study evaluated 36 soybean genotypes for their resistance to S. frugiperda based on leaf damage intensity and frequency, resistance classification, morphophysiological traits, and yield components. The research was conducted under field conditions using a randomized complete block design (RCBD) with three replications. Armyworm damage was assessed at 36 and 41 days after planting (DAP), and all quantitative data were analyzed using ANOVA followed by the Scott-Knott test at a 5% significance level. Data were presented as mean ± standard deviation (SD). Significant variation was evident among genotypes, with attack intensity at 41 DAP ranging from 18.31 ± 10.64% to 61.20 ± 11.39%, and attack frequency from 33.38 ± 16.92% to 95.49 ± 5.35%. Based on mean intensity values, one genotype was categorized as strongly resistant (SR) (UB 2), four as resistant (R) (UBASK24, UBASK35, GBG, TGM), and a broader set as moderately resistant (MR), while highly susceptible (HS) genotypes included UBASK15, UBASK62, UBASK64, UBASK32, UBASK36, and UBASK14. Morphophysiological traits exhibited wide variation, including leaf trichome density (13.56-42.11 trichomes 0.25 cm^-2), plant height (38.42-78.67 cm), and flowering time (31-47 DAP), while yield traits identified TGM, UBASK35, UBASK24, and GBG as the highest-performing genotypes. Overall, UB 2, UBASK24, UBASK35, GBG, and TGM are promising parental candidates for breeding soybean resistance against S. frugiperda, integrating strong resistance expression with favorable agronomic performance.

Background: Tropomyosin 4 (TPM4) regulates neurite outgrowth and vascular pathology but its role as a biomarker for predicting outcomes in stroke patients is unclear. This study investigated the association between serum TPM4 levels and 1-year functional outcomes in acute ischemic stroke (AIS) patients.

Methods: AIS patients admitted within 24 h post-onset from the Chengdu Stroke Registry were included. Serum TPM4 levels were measured by enzyme-linked immunosorbent assay (ELISA). Poor functional outcomes were defined as a modified Rankin Scale (mRS) score >2 at 1 year after stroke onset. Multivariate logistic regression assessed TPM4's association with outcomes, with its predictive incremental value evaluated by discrimination, reclassification, and overall performance metrics.

Results: Among 181 patients (median age 66 years, 64.1% male), 59 (32.6%) experienced poor outcomes at 1 year, including 16 deaths (8.8%). Serum TPM4 levels on admission were negatively correlated with the National Institutes of Health Stroke Scale (NIHSS) score (r = -0.185, p = 0.013). Adjusted for confounders, lower serum TPM4 levels were independently associated with 1-year poor functional outcomes (adjusted OR 0.045, 95% CI [0.005-0.393], p = 0.005). Serum TPM4 levels had acceptable discriminative ability for predicting poor outcomes (AUROC 0.706, 95% CI [0.621-0.791], p < 0.0001). Incorporating TPM4 into the basic model significantly improved the predictive power for poor functional outcomes (net reclassification index: 31.87%, p = 0.041; integrated discrimination improvement: 5.01%, p = 0.008; Brier score decreased from 0.16 to 0.15, p = 0.012).

Conclusions: Lower serum TPM4 levels on admission were independently associated with poor functional outcomes at 1 year in AIS patients, suggesting that TPM4 may serve as a potential biomarker for long-term outcomes and offer insights into its potential role in stroke pathophysiology. These findings need to be further verified in external cohorts.

Background: Physiotherapy services are often integrated within the broader healthcare system in India. Unlike in developed countries, physiotherapy is still limited to indirect access and needs a referral from other healthcare providers, which potentially limits physiotherapists. The purpose of this study was to explore the knowledge or skill, attitude, and behavior towards the implementation of evidence-based practice (EBP) in physiotherapy care. In addition, the physiotherapist's perception of barriers in the implementation of EBP was inquired.

Methods: A cross-sectional study was conducted through an online survey involving two thousand nine hundred and ninety-six physiotherapists from 22 states/union territories in India. A 24-item EBP questionnaire (EBPQ) investigating knowledge, attitude, and behavior domains with a 1 to 7 Likert scale response for each item, with a higher score indicating a favorable response. A linear regression model was used to analyze the relationship between factors and evidence-based practice behavior among physiotherapists.

Results: The mean age of the participants was 35.8 ± 6.2 years, with a work experience of 13.25 ± 6.38 years. The overall EBPQ mean score of Indian physiotherapists was 3.6 ± 0.38, and the mean scores of the domains-knowledge, attitude, and implementation of EBP-were 3.59 ± 0.53, 4.29 ± 0.79, and 3.20 ± 0.62, respectively. The EBP domains were mainly determined by the educational attainment and workplace, which explained 46.1% of the variance. Lack of time and skills was identified as the top barrier influencing EBP among physiotherapists in India. The behavior dimension score of EBPQ is determined by 8 knowledge items and 2 attitude items, which explain 61.2% of the variance.

Conclusions: The Indian physiotherapists reported a positive attitude toward evidence-based practice; however, their knowledge and behavior were observed to be insufficient. Lack of time, limited skills, a shortage of resources, and limitations in applying EBP were reported as the main barriers.

Objectives: This study aims to investigate the effects of variable resistance training (VRT) on athletes' lower limb explosive power through assessments of jumping, sprinting, and change of direction (COD) performance.

Methods: A systematic search was conducted across four electronic databases (Web of Science, PubMed, Scopus, ProQuest) from their inception until March 23, 2025. Study eligibility was assessed against the Population, Intervention, Comparison, Outcomes, Study design (PICOS) framework. Following data extraction, the methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool. Data analysis was performed using Stata 15 software, with standardized mean differences (SMD) and 95% confidence intervals calculated as the pooled effect size measure.

Results: Fifteen articles involving 442 participants were included in the final analysis. The overall meta-analysis demonstrated that VRT was an effective method for enhancing athletes' jumping performance (SMD = 0.81 cm, p < 0.001), sprint performance (SMD = -1.13 s, p < 0.001), and COD performance (SMD = -1.66 s, p < 0.001). Subgroup analyses indicated significant positive effects of VRT on vertical jump (VJ: SMD = 0.31 cm, p = 0.027), squat jump (SJ: SMD = 0.94 cm, p < 0.001), countermovement jump (CMJ: SMD = 1.01 cm, p < 0.001), 5-m sprint (SMD = -1.18 s, p < 0.001), 10-m sprint (SMD = -1.18 s, p < 0.001), 30-m sprint (SMD = -1.08 s, p = 0.013), T-test (SMD = -2.01 s, p < 0.001), repeated change of direction (RCOD: SMD = -2.01 s, p < 0.001), and Illinois test (SMD = -1.85 s, p < 0.001).

Conclusion: This systematic review suggests that VRT may serve as an effective training strategy for enhancing lower-limb explosive power in athletes. However, due to significant heterogeneity among the included studies and potential publication bias, the definitive benefits of VRT require further validation through additional high-quality research.

Objectives: The objective of the study was to quantify seed flow consistency and in-row spacing accuracy when using a conveyor belt-style metering device under varying operational parameters, to develop mathematical models, and to optimize the uniformity of seed placement for black cumin seeding.

Methods: Seed flow properties and the uniformity of in-row seed distribution uniformity were evaluated through weighing tests and sticky belt methods, respectively. The uniformity of the flow was assessed using coefficient of variation (CV) values, while the in-row seed distribution uniformity was evaluated by using the variation factor (V_f) and the goodness criterion (λ). The experiments were conducted based on Central Composite Design (CCD) under laboratory conditions. The forward speed, seed rate, and seed falling angle were chosen as independent variables. The experiments were conducted at five levels of forward speed (1.01, 1.4, 2.0, 2.6, and 3.01 m s^-1), five levels of seed rate (6.6, 10, 15, 20 and 23.4 kg ha^-1), and five levels of seed falling angle (1.36, 15, 35, 55 and 68.64°).

Results: The polynomial functions were developed and the V_f and λ models were optimized. Optimization reduced the variation factor (V_f) to 0.53 and improved the goodness criterion (λ) to 91.67%, indicating a substantial enhancement in seed placement uniformity. For the V_f model, the optimum forward speed was found to be 1.05 m s^-1, with a seed rate of 12.35 kg ha^-1 and a seed falling angle of 35°; whereas for the λ model, the corresponding values were calculated 1.55 m s^-1, 21.1 kg ha^-1, and 28.5°, respectively. The developed models showed high predictive accuracy, with an R ² value of 95.96% for the λ model. Based on the findings of this work, the seed rate was determined as the most important parameter for all models considered.

Conclusions: The results of the experiments also revealed that the conveyor belt metering unit could be used for the seeding process of black cumin seeds with great success, without encountering significant problems. The comparison of R ² value of the λ and V_f models indicated that the λ model had a better variable prediction. Therefore, the optimum values from the λ model may be more useful than those from the V_f model.

This meta-analysis aimed to assess the cardioprotective effect of resveratrol (RES) against myocardial ischemia/reperfusion injury (MIRI) and myocardial infarction (MI) in the animal. PubMed, Web of Science, and EMBASE were searched. Primary outcomes included myocardial infarct size (IS) and cardiac function. Secondary outcomes included cardiac injury enzyme, oxidative stress level, inflammatory cytokine, and apoptosis rate. Subgroup analysis, publication bias, sensitivity analysis, meta-regression, and dosage-efficacy analysis were used to evaluate the risk of bias. Fifty-seven studies were included involving 1,125 animals. The results showed that RES treatment decreased IS in animal models of MIRI (SMD: -5.44; 95% CI [-6.42 to -4.45]; P < 0.01; I² = 86%) and MI (SMD: -3.41; 95% CI [-4.44 to -2.38]; P < 0.01; I² = 75%). Moreover, RES treatment improved cardiac function, decreased cardiac injury enzymes, down-regulated oxidative stress levels, alleviated inflammatory cytokine levels, and reduced apoptosis rate in animal models of MIRI and MI. This meta-analysis of preclinical animal studies suggested that RES may have potential in alleviating MIRI and MI. However, the translational potential of RES remains uncertain, and additional preclinical studies with standardized protocols, comorbid models, and eventual clinical trials are needed to confirm these results.

Background: Transcranial direct current stimulation (tDCS) has been reported to enhance explosive strength in lower limb skeletal muscles. Nevertheless, findings regarding the impact of tDCS on jump performance remain inconclusive, potentially due to variations in stimulation montage and current intensity. Therefore, we aimed to elucidate the effects of multifocal tDCS on lower limb jump kinetics and neuromuscular adaptation.

Methods: Fourteen female collegiate basketball players were enrolled in a randomized, crossover, controlled trial. Each participant underwent three intervention sessions in a randomized sequence: 2 mA tDCS, 4 mA tDCS, and sham tDCS, all targeting the primary motor cortex (M1). After each stimulation session, countermovement jump (CMJ), squat jump (SJ), drop jump (DJ), and surface electromyography (EMG) data were collected. Statistical analysis was performed using one-way repeated measures ANOVA.

Results: The 4 mA multifocal tDCS condition produced a significant increase in jump height compared to baseline, sham, and the 2 mA condition. Similarly, the concentric impulse was markedly higher in the 4 mA group relative to all other conditions. Relative peak force was significantly improved in the 4 mA group versus baseline, and relative peak power was significantly greater under 4 mA tDCS compared to sham stimulation. The modified reactive strength index (RSImod) was also enhanced considerably following 4 mA tDCS, relative to both baseline and sham conditions. However, EMG analysis indicated that none of the tDCS interventions significantly affected the root mean square (RMS) values of lower limb muscle activation, including the rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), semitendinosus/semimembranosus (SEM), medial gastrocnemius (MG), lateral gastrocnemius (GL), and tibialis anterior (TA).

Conclusion: Multifocal anodal tDCS at an intensity of 4 mA significantly improves lower limb jump performance in female collegiate basketball athletes. Integrating multifocal anodal tDCS into routine training regimens may serve as a practical and effective adjunct for enhancing performance in this population.

Background: Imaging advantages have raised intracranial aneurysm (IA) detection rates but have also increased radiologists' workloads. Coupled with visual fatigue, this heavier burden heightens the risk of missed or erroneous diagnoses. Concurrently, artificial intelligence (AI) has shown great promise for analyzing medical images. This study aims to evaluate the diagnostic performance of AI software for IAs and to provide an initial, single-centre validation of its potential as a supportive tool in future deployment.

Methods: Between January 2019 and September 2023, 452 patients with 544 IAs diagnosed by head and neck computed tomography angiography (CTA) who also underwent digital subtraction angiography (DSA) were included. The AI's ability to detect the presence, location, and size of IAs was recorded. Its results were compared with DSA, and the agreement between AI and radiologists in measuring IA size was evaluated.

Results: The AI software demonstrated a sensitivity of 88.97% (95% CI [0.861-0.963]) and an accuracy of 75.04% (95% CI [0.715-0.783]) for detecting IAs. Specifically, the accuracy and sensitivity of AI in detecting IAs that are smaller than three mm, between 3-5 mm, and larger than five mm are 58.46% (95% CI [0.462-0.698]) and 66.67% (95% CI [0.537-0.775]), 76.68% (95% CI [0.714-0.813]) and 88.93% (95% CI [0.843-0.924]), 77.10% (95% CI [0.720-0.816]) and 94.24% (95% CI [0.906-0.966]), respectively. There was good agreement between radiologists and DSA, between AI and DSA, and between radiologists and AI for identifying the location of IAs, with kappa values all greater than 0.75. The radiologists and AI also showed good consistency in measuring depth, width, height, and maximum diameter, with intraclass correlation coefficients (ICCs) all greater than 0.75, except for the neck width, which had an ICC of 0.492.

Conclusions: The AI software performs well in terms of detecting IAs that are larger than three mm and shows good agreement with radiologists in localizing positions and extracting their morphometric parameters (except for neck width measurements). The AI software has proved to be a reliable adjunct for IA detection and measurement tasks.

Background: Investigating the carbon sequestration potential of wetlands and the dynamics of net primary productivity (NPP) on the Tibetan Plateau of China enhances understanding of their contributions to global carbon emission reduction and their role in maintaining biodiversity and ecosystem stability. Vegetation NPP is a key indicator of carbon sequestration; however, existing research has largely focused on historical dynamics, with limited studies projecting future trends. This gap impedes proactive conservation and climate mitigation strategies.

Methods: Here, we predicted the spatial distribution of normalized difference vegetation index (NDVI) on the Tibetan Plateau for 2025-2030, employing a backpropagation neural network and Kriging interpolation fitting. We estimated spatial and temporal dynamics of NPP and wetland carbon sequestration potentials during the same period using the Carnegie-Ames-Stanford Approach model. Furthermore, we investigated the effects of land use and climate on NPP.

Results: Key findings were: (1) NDVI distribution was higher in the southeast than in the northwest, with temperature influencing its value. (2) Spatial distribution of NPP on the Tibetan Plateau exhibits a typical landscape pattern of "patch-corridor-matrix." The maximum NPP of vegetation was 1,112.82 gC ⋅ m^-2 ⋅ a^-1 for 2025-2030. Projections of NPP for 2025-2030 suggest an increase of approximately 50% relative to current levels by 2045, indicating a substantial enhancement of the carbon sink potential over the coming two decades. (3) Carbon sequestration potential of wetlands on the Plateau ranges from 0 to 100 gC ⋅ m^-2 ⋅ a^-1, with high carbon sink potential concentrated near Palong Tsangpo, the largest tributary of the Yarlung Tsangpo River. (4) Woodland NPP has the highest mean value and rate of change. Furthermore, analysis of 2025 land use data shows that forestland and grassland are the dominant land cover types in the Yunnan, Sichuan, and Southeastern Xizang Sections of the Qinghai-Tibet Plateau. Their high proportions correspond significantly to high regional NDVI values, indicating the spatial heterogeneity of NDVI distribution is driven by land cover changes rather than directional factors. (5) Correlation analysis indicated strong positive correlations between precipitation and solar radiation with NPP. NPP does not increase or decrease with increasing temperature; instead, it tends to increase within suitable temperature ranges.

Genotyping-in-Thousands by sequencing (GT-seq) is a promising tool for genetic monitoring. For the past 25 years, genetic monitoring of Rio Grande silvery minnow (Hybognathus amarus) has been conducted annually by surveying variation at microsatellite loci. This is the first study describing the development of a GT-seq panel using archived samples that maintains the analytical and inferential continuity of long-term genetic monitoring. A total of 2,983 microhaplotypes in 373 individuals were identified using nextRAD-seq from samples spanning 20 years and a conspecific reference genome. Using this data, estimates of genetic diversity and temporal genetic structure across the time-series were used as a baseline to test subsets of loci that effectively tracked those changes. A panel including 250 loci with higher F_ST across temporal samples and 250 loci selected randomly offered the highest power and was used for GT-seq optimization. A sex-linked marker validated previously was also included for sex assignment. The optimized GT-seq panel included 284 loci. Comparisons of genotypes from those loci obtained for the same samples with nextRAD-seq and GT-seq revealed high genotype accuracy (98.3%). Estimates of genetic diversity and patterns of temporal genetic structure were similar between datasets and accuracy of sex assignment was 100%. The utility of using a conspecific genome for both loci identification and primer design in the face of reduced genetic diversity, and the importance of temporal metrics representative of ongoing genetic monitoring is explored. The strategy used here, effectively preserved the long-term genetic monitoring of the endangered Rio Grande silvery minnow while transitioning to a more efficient and cost-effective marker system.