The Purpose of the study was to find out the effects of exercise order in a resistance training exercise session on selected speed related variables among women athletes. For this purpose, forty-five (N=45) women athletes who were participated in the inter collegiate athletic meet in Bharathidasan University, Tiruchirappalli, Tamil Nadu, India during the year 2025-2026 were randomly selected as subjects. The age of the subjects was ranged from 18 and 21 years. The subjects were divided into three groups of fifteen in each (n=15). Group-I underwent Large and Progressed toward Small Muscle group Exercises (LG-SM) and Group-II underwent Small and Advanced to Large Muscle group Exercises (SM-LG) and group –III was act as the Control group (CG). Experimental groups underwent their training programme for 12 weeks in addition to the training program designed by the college curriculum. The control group was no underwent any specific training. Speed, Stride Length and Acceleration Speed were selected as dependent variables. Speed and Stride Length were assessed by 50 Meters Sprint Test; and Acceleration Speed was measured by 30 Meters Acceleration Sprint Test. The data collected data from the three groups prior to and immediately after the training programme on the selected criterion variables were statistically analyzed with dependent ‘t’ test and Analysis of Covariance (ANCOVA). Whenever the ‘F’ ratio for adjusted posttest means was found to be significant, Scheffe’s test was followed as a post hoc test to determine which of the paired mean differences were significant. In all the cases 0.05 level of confidence was fixed as a level of confidence to test the hypotheses. The results of the study showed that there was a significant difference was found among the experimental groups. Small and advanced to large muscle group exercises (SM-LG) group is found to be better than other groups in developing Speed, Stride Length and Acceleration Speed.

Background: Anaemia is a common and clinically significant complication of chronic kidney disease (CKD) that contributes to cardiovascular morbidity and accelerated disease progression. Diabetes mellitus (DM), a leading cause of CKD has been independently associated with a higher prevalence and greater severity of anaemia. Objective: To compare the prevalence and severity of anaemia between diabetic and non-diabetic CKD patients and to identify independent predictors of moderate-to-severe anaemia in this population. Methods: This comparative cross-sectional study was conducted in the Department of Nephrology, Tangail Medical College and Hospital, Tangail, Bangladesh, from June 2024 to May 2025. A total of 348 patients with CKD were enrolled, including 174 diabetic CKD patients and 174 age- and sex-comparable non-diabetic CKD patients. Anaemia was defined according to World Health Organization (WHO) sex-specific hemoglobin (Hb) cut-offs (<13 g/dL in males and <12 g/dL in females) and further classified as mild, moderate or severe. Data were analyzed and compared by statistical tests. Results: Diabetic CKD patients were significantly older (59.2±10.2 versus 55.8±11.7 years; p= 0.005) and had a more advanced CKD stage distribution (56.9% versus 42.5% in Stage 4-5; p<0.001). Mean hemoglobin was significantly lower in the diabetic group (10.04±1.89 versus 11.16±2.04 g/dL; p<0.001), and anaemia was significantly more prevalent (87.4% versus 71.3%; p<0.001), with a significant shift toward moderate-to-severe grades (48.9% versus 27.6%; p<0.001). Diabetic status remained an independent predictor of moderate-to-severe anaemia after adjustment for CKD stage, age and disease duration [adjusted odds ratio (AOR) 2.24, 95% CI 1.36–3.68; p= 00.001], with CKD Stage 4-5 the strongest predictor (AOR 6.32, 95% CI 3.81–10.48; p<0.001). Conclusion: Diabetic CKD patients demonstrated significantly higher prevalence and severity of anaemia than non-diabetic CKD patients, which is independent of CKD stages. Routine, regular hemoglobin screening should be incorporated into the clinical management of diabetic CKD patients.

This review synthesizes evidence on the effectiveness of the World Athletics Kids’ Athletics Programme in improving motor competence, physical fitness and psychosocial outcomes among school-aged children (typically aged 6–12 years). The results indicate consistent positive effects of the programme on running speed, agility and object control skills compared to standard physical education or no intervention, with small-to-medium effect sizes. Evidence for improvements in cardiorespiratory fitness and upper-body strength was less robust, with mixed findings. Psychosocially, the programme demonstrated moderate improvements in enjoyment of physical activity and perceived athletic competence, but no significant effects on long-term behavioural outcomes such as sustained participation. Heterogeneity in intervention duration (4–24 weeks), delivery agents (teachers vs. coaches), and outcome measures limited the comparability of some findings. Overall, the World Athletics Kids’ Athletics Programme appears effective for enhancing selected motor and physical fitness components and fostering positive attitudes towards running-based activities in the short term, though longer-term and psychosocial impacts remain less certain. High-quality, cluster-randomized trials with follow-up assessments are needed to strengthen the evidence base.

Social media has become deeply integrated into students’ daily lives, extending beyond social use into informal academic practices, including self-assessment. This study examines how EFL students at a university use social media to assess their own academic abilities, the extent to which they engage in academic social comparison through these platforms, and the difficulties they encounter in doing so. A mixed-methods approach was employed, using an online questionnaire comprising closed and open-ended questions administered to 133 students. Quantitative findings revealed that the majority of students used social media for academic self-assessment on a frequent basis, with YouTube and WhatsApp emerging as the most commonly used platforms. While social comparison was a common practice among students, it was not strongly associated with increased motivation or academic confidence. Qualitative findings further revealed that students primarily used social media for comprehension checks, language practice, and peer feedback, while also reporting challenges related to distraction, unreliable information, and negative social comparison. These findings suggest that social media functions as an informal, self-directed space for academic self-assessment, one that offers meaningful opportunities for reflection and feedback but also carries risks that may undermine effective learning if left unaddressed. The study is limited by its focus on EFL students at a single university and its reliance on self-reported data, and future research should extend to larger, more diverse samples across multiple institutions and disciplines. The findings nonetheless highlight the need for greater digital literacy support and suggest that educators consider ways to intentionally integrate informal social media practices into formal academic guidance.

Withaferin A (WA), a bioactive compound derived from the Ashwagandha plant, has been recognized for its anticancer properties. We tested various concentrations of WA, Fluvastatin (FLU), and their combinations (ranging from 0 to 160 µM) for their potential regulatory effects on colon cancer cells (Caco-2 cell line) and non-tumorigenic colon cells (NCM-460). Our results showed that at lower concentrations (around10 µM), WA significantly impacted colon cancer cells, showing minimal toxicity to normal cells (NCM-460). However, at higher concentrations, FLU selectively inhibited cancer cell proliferation, with noticeable toxicity to both cancerous and normal cells. Additionally, WA treatment led to a time and dose-dependent decrease in the production of IL-1β and TNF-α. Along with these effects, the downregulation of ERK and EGF gene expression was observed across all treatments. Additionally, docking analysis revealed the potential regulatory role of WA and its interaction with aspartate aminotransferase, in comparison to the docking data for FLU, which serves as a standard inhibitor for aspartate aminotransferase. These findings suggest that WA can inhibit cell proliferation signaling by targeting ERK and EGF, thereby promoting programmed cell death (PCD) in treated cells. These data also demonstrate that WA, whether alone or in combination with other compounds, can regulate the production of pro-inflammatory cytokines in treated cells.

Steel fibre-reinforced concrete (SFRC) is generally modelled for compressive strength; nevertheless, almost all published models assume fibres are added to a fixed mix and stop at predicting mean strength, neglecting both the cement-replacement scenario and reliability-based design. This study develops a mechanistic, interpretable model for SFRC in which steel fibres replace cement by mass, a composition that raises the effective water-to-cement ratio while incorporating crack-bridging benefit. Compressive strength is expressed as the sum of a paste-weakening term decaying with the surviving cement fraction and a Rayleigh-type bridging term that peaks before balling degrades dispersion. Across seven fibre dosages (0–12% of cement mass) at two curing ages (224 specimens), the model reproduced the non-monotonic strength response with R² = 0.887 at 28 days and independently recovered the bridging optimum near 6–7% fibre without that value being imposed, indicating that it demonstrates the governing physics rather than merely fitting the data. Hardened density showed no reliable dosage trend and stayed within the normal-weight band. Extending the study to characteristic strength and reliability indices, the model showed that only the control mix cleared the design target, every fibre mix falling below it. The framework links predictive accuracy to structural usability, with external validation identified as the priority next step.

Background: Artificial intelligence (AI), particularly convolutional neural networks (CNNs) and vision transformers (ViTs), is transforming dental radiographic diagnosis across multiple clinical domains. Methods: A narrative review searched PubMed, PubMed Central, BMC Oral Health, and Google Scholar for systematic reviews, meta-analyses, and original studies published between 2019 and 2025, covering ten domains: caries detection, periapical lesion identification, alveolar bone loss, peri-implant assessment, tooth detection and segmentation, cone-beam computed tomography (CBCT) analysis, vertical root fracture (VRF) detection, cephalometric landmark analysis, dental anomaly detection, and AI-versus-clinician comparison. Results: Pooled sensitivity was 0.94 and specificity 0.91 for caries detection on bitewing radiographs. Periapical AI sensitivity was 92.9% with specificity of only 58.6%, yielding a positive predictive value of 15.3%. Peri-implant bone loss assessment achieved AUC of 0.94. Vision transformers outperformed CNNs in 58% of dental imaging studies. VRF detection accuracy ranged from 75% to 97.8%. Cephalometric landmark detection rate reached 98.29%. AI diagnosed radiographs in 1.5 seconds versus 53.8 seconds for clinicians. ANSI/ADA Standard 1110-1:2025 provides the first formal dental AI validation framework. Conclusions: AI achieves substantial and reproducible diagnostic accuracy across dental radiographic tasks. High false-positive rates, demographic dataset bias, limited multi-centre external validation, and regulatory gaps must be resolved before broad clinical implementation.