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Assessment of waterlogging tolerance in tea genotypes through morpho-physiological and biochemical profiling
Tea is one of the major economic crops in Bangladesh, however, its productivity is severely constrained by waterlogging stress arising from erratic climatic changes. A significant knowledge gap persists regarding the morpho-physiological and biochemical determinants of waterlogging tolerance and post-stress recovery in tea, hindering the development of tolerant genotypes. Therefore, the present study aimed to investigate the integrated morpho-physiological and biochemical responses of tea genotypes under waterlogging stress to identify tolerant genotype(s) based on stress tolerance indices (STIs). Eight pre-screened tea genotypes—P/LAL/08/23, P/LAL/08/62, P/LAL/09/116, P/AFN/11/35, P/AFN/11/46, P/OTI/31, P/AFN/13/90, P/AFN/11/31, with two control clones, BT2 (popular variety) and TV9 (waterlogging-tolerant variety), were evaluated using 23 morpho-physiological and biochemical parameters maintaining a two-factorial completely randomized design experiment. One set of tea genotypes was exposed to a 14-day waterlogging phase, followed by a 14-day recovery phase (total 28 days of stress), while another set of plants was maintained under control (non-stress) conditions, for the same period, to calculate STIs. Root fresh weight (RFW), leaf number (NL), net photosynthesis ( Pn ), transpiration rate ( E ), stomatal conductance ( g s ), relative leaf water content (RWC), and absolute growth rate (AGR) were significantly decreased under waterlogging condition compared to the control. Leaf chlorophyll a (CHA), chlorophyll b (CHB), and total carotenoids (CRTN), were reduced under stress, whereas proline content (of leaf: PRLF and root: PRRT), total antioxidant activity (of leaf: TACL and root: TACR), and lipid peroxidation (of leaf: LOPL and root: LPOR) increased as a part of adaptive responses. The traits such as RFW, NL, Pn , E , g s , RWC, AGR, CHA, CHB, CRTN, and LPOL, were detected as most influential at both phases of stress conditions from principal component analysis. Ultimately, the P/AFN/13/90 was identified as the most waterlogging-tolerant genotype, exhibiting higher STIs for maximum traits during both the waterlogging and recovery phases.
Automated concrete crack detection enhanced by deep learning and generative adversarial networks
Cracks on the surface of concrete structures are an obvious indication of their condition. However, traditional visual inspection methods are significantly influenced by human factors. They are accurate for larger cracks. However, they introduce subjective judgment when detecting smaller cracks. They also pose safety risks. Automated detection methods face challenges in achieving lightweight implementation due to limited annotated data and difficulties in complex environments. This paper proposes a method for detecting and measuring concrete cracks. The method uses a generative adversarial network (GAN) to augment data and a U-Net segmentation network. Conditional GAN (cGAN) is proposed to generate high-fidelity crack images using training-set data only, avoiding data leakage and effectively solving insufficient sample issues. A U-Net segmentation network that has been enhanced performs crack segmentation. This network incorporates channel attention modules and dilated residual blocks. A hybrid loss function that combines the Dice coefficient and binary cross-entropy resolves class imbalance. Fractal theory quantifies the geometric features of the detected cracks. The crack segmentation model that was trained on cGAN-augmented datasets achieved an average precision (AP) of 82.03% and an F1 score of 83.24%, as demonstrated by experimental results. The fractal dimension–based crack measurement method achieves an accuracy of ≤4% error for complex crack networks (fractal dimension >1.6). The proposed method provides a reproducible, automated, high-precision solution for concrete crack detection and quantification, with verified stability and engineering applicability.
Academic and psychological determinants of mental stress among medical students in Dhaka: A multinomial logistic regression approach
As stress among medical students is a global health concern due to comprehensive academic engagements, this study aimed to assess the educational and psychological factors related to mental stress among medical students in Dhaka city. A descriptive type of cross-sectional study was conducted in two medical colleges in Dhaka city among 380 medical students from 3 rd year to 5 th year, using a pre-tested, self-administered, and structured questionnaire. The data obtained were analyzed using IBM SPSS Statistics (version 23) and Stata (version 14.2) employing the chi-square association test for bivariate analysis and subsequent multinomial logistic regression for the significant variables. Among 380 respondents, 68.7% were female, with 51.8% of respondents from Shaheed Suhrawardy Medical College. The mean stress score of medical students was 21.64 (SD = 6.64), with 67.9% and 22.6% as moderately and highly stressed, respectively. In bivariate analysis, 29 academic factors and 09 psychological factors were significantly associated with stress. In multinomial logistic regression analysis, three models were conducted, containing variables related to academic stress in model 1, variables related to psychological stress in model 2, and all stress variables in model 3. From model 1, academic performance, study and exam score anxiety, fear of future uncertainty and new living, administration satisfaction, and lack of entertainment facilities are significantly associated with stress. Additionally, the factors significantly associated with stress are time management, social life perception, and feeling lonely for model 2 and all stress-related variables, including study and exam score worry, difficulty in understanding context, fear of new living, administration and lecture satisfaction, teaching strategy satisfaction, time management, parental support in study, and feeling loneliness for model 3. Proper interventions for stressors of mental stress, further assessment, and rehabilitation for high and moderate-stressed respondents could be a prime concern to lessen the burden of stress among medical students.
Adverse effects of removable orthodontic aligners: A systematic review with single-arm meta-analysis
Background Removable orthodontic aligners are widely used due to their aesthetic appeal, removability, and perceived comfort. However, evidence regarding their potential adverse effects remains limited. Objective To identify and synthesize the adverse effects associated with removable orthodontic aligner therapy. Methods This systematic review with single-arm meta-analysis evaluated adverse effects related to removable orthodontic aligner therapy. Seven electronic databases (Cochrane, Embase, LILACS, Livivo, MEDLINE, Scopus, and Web of Science) and gray literature sources (ProQuest Dissertations and Google Scholar) were searched without language or date restrictions. Two calibrated reviewers independently selected studies. Risk of bias was assessed using RoB 2 for randomized trials and ROBINS-I for non-randomized studies. Due to clinical and methodological heterogeneity, most outcomes were synthesized narratively; meta-analyses were conducted only for pain/discomfort, apical root resorption, and plaque. Results Thirty-four studies met the inclusion criteria, including 10 randomized controlled trials, 6 non-randomized clinical studies, and 18 cohort studies. Randomized trials were predominantly at low risk of bias, whereas most non-randomized and cohort studies were at moderate to high risk. Pain and apical root resorption were the most frequently reported adverse effects. Pain peaked within 24 hours, decreased by day 3, and was minimal by 1 week. Apical root resorption was generally small, with a mean linear loss of −0.33 mm (95% CI −0.55 to −0.11) and a volumetric loss of −4.37 mm³ (95% CI −5.51 to −3.24). Findings on plaque at 3 months were inconclusive. Other reported outcomes included periodontal changes, enamel demineralization, white spot lesions, speech alterations, halitosis, open gingival embrasures, temporomandibular symptoms, and awake bruxism. Conclusion Short-term pain and minor apical root resorption appear to be the most frequently reported adverse effects of removable orthodontic aligners, although the certainty of evidence varies across outcomes. Speech alterations, discomfort, and white spot lesions have also been reported.
Cancer-associated fibroblast subtype signature gene predicts survival and immunotherapy response in sarcoma
Background Sarcomas show heterogeneous responses to immune-checkpoint blockade (ICB), and cancer-associated fibroblasts (CAFs) are considered to shape the tumor immune microenvironment, yet CAF programs that predict ICB outcomes in sarcoma remain unclear. Methods We investigated the interaction between different cell types in the sarcoma tumor microenvironment and their effects on immune-checkpoint blockade response, with a focus on identifying signature genes and molecular mechanisms that distinguish tumor-promoting from tumor-suppressive CAFs at the single-cell level. We analyzed single-cell data from two different sarcoma cohorts, transcriptome profiles of 206 sarcoma patients recruited from The Cancer Genome Atlas, and predicted immune-checkpoint blockade (ICB) response data inferred using the TIDE algorithm from 64 TCGA sarcoma patients. Results We found 134 stem-like CAF-related signature genes in the recurrent group and eight signature genes in the metastasis group, defining three CAF subtypes (myofibroblastic CAF, antigen-presenting CAF, and inflammatory CAF). SIG134 and SIG8 were associated with TIDE-inferred ICB response in subtype-specific analyses: SIG134 in STLMS and ULMS, and SIG8 in MFS, STLMS, and ULMS. In addition, the MDK-NCL ligand-receptor signal transduction pathway was linked to the infCAF subtype and myoCAFs in metastatic sarcoma. Furthermore, SIG4 ( MDK , SDC2 , LRP1 , and NCL ) was highly expressed in inflammatory CAFs. Conclusions Single-cell-derived CAF signatures may reflect sarcoma subtype-specific stromal programs associated with predicted ICB response and clinical outcome. SIG4 is proposed as a candidate prognostic signature that warrants further validation.
Chronic CBD treatment differentially modulates neurobehavioral outcomes and endocannabinoid signaling in an aged HIV-1 Tat transgenic mouse model
As the population of older individuals living with HIV continues to expand, identifying non-euphoric therapeutic interventions for HIV-associated complications is essential. While cannabidiol (CBD) has demonstrated neuroprotective potential, its effects following prolonged exposure in the context of an aging biological environment remain poorly understood. This study utilized aged (15–18 months) male and female HIV-1 Tat transgenic mice to evaluate the impact of chronic CBD (3 mg/kg, s.c., for 12 weeks). A behavioral battery was employed to assess object recognition memory, anxiety-like behavior, spontaneous nociception, and locomotor activity. Subsequently, liquid chromatography-tandem mass spectrometry and Western blotting were used to map endocannabinoid ligands (AEA, 2-AG, AA), metabolic enzymes (FAAH, MAGL), and receptors (CB 1 R, CB 2 R, GPR55) across the prefrontal cortex, amygdala, brainstem, and spinal cord. Results indicated that chronic CBD improved recognition memory specifically in female Tat(+) mice. While CBD treatment did not affect spinal cord-related tail flick sensitivity it universally increased supraspinal hot plate sensitivity. Chronic CBD treatment also elevated baseline body temperature and modulated body mass without impairing general locomotion. Furthermore, chronic CBD restructured the eCB signaling landscape across all examined CNS regions in a highly sex- and genotype-dependent manner. Notably, cannabinoid receptor and GPR55 expression exhibited distinct regulatory shifts governed by significant three-way interactions. These findings demonstrate that chronic CBD intervention interacts with the eCB system of aged mice in a region-specific manner. These results underscore the critical importance of considering age, sex, and treatment duration when evaluating cannabinoid-based therapies for the management of neuroHIV.
HPV vaccination intention and its association with vaccine hesitancy and health beliefs among unvaccinated Chinese medical college students: A cross-sectional study
Background Human papillomavirus (HPV) infection poses a significant public health challenge, and HPV vaccination uptake among Chinese college students remains suboptimal. Therefore, it is essential to conduct ongoing, in-depth investigations into the psychological and cognitive mechanisms of HPV vaccination intention. This study aims to explore the associations among HPV vaccination intention, vaccine hesitancy, and health beliefs among Chinese medical college students. Methods A cross-sectional survey was conducted from June 16 to July 16, 2024, to assess sociodemographic characteristics, vaccine hesitancy, and health belief model (HBM) among college students at Guangdong Medical University. Descriptive statistics, univariate analysis, and binary logistic regression were performed to identify factors associated with HPV vaccination intentions among unvaccinated students. Results Among 3,584 unvaccinated participants, 73.16% expressed willingness to receive the HPV vaccine. The key significant associations identified included gender (male) (OR: 0.26; 95% CI: 0.22 ~ 0.31; p < 0.001), parental occupation (employees in enterprises, commercial, and service industries (including self-employed)) (OR: 1.43; 95% CI: 1.18 ~ 1.75; p < 0.001), and information sources (hospitals or doctors) (OR: 1.37; 95% CI: 1.15 ~ 1.64; p = 0.001). Vaccination intention was also directly associated with the perceived necessity (OR: 0.91; 95% CI: 0.88 ~ 0.94; p < 0.001) and importance (OR: 1.07; 95% CI: 1.03 ~ 1.10; p < 0.001) of vaccine hesitancy, as well as the perceived benefits of behavior for the HBM (OR: 1.21; 95% CI: 1.12 ~ 1.32; p < 0.001). Conclusions In this sample, Chinese medical college students demonstrated a relatively high willingness to receive HPV vaccination. Willingness was positively associated with perceived necessity, importance, and benefits of vaccination. Integrating structured clinician-delivered counseling into curricula, using parental occupation data for targeted subsidies, and embedding classroom sessions comparing personal HPV risk with vaccine safety data may improve uptake. Government evaluation of gender-neutral vaccination policies and provision of male-inclusive campus services are also recommended.
A feature-efficient dual-task machine learning framework for predicting bone mineral density and osteoporosis stratification in resource-constrained environments
Osteoporosis is a chronic skeletal disorder characterized by progressive bone mineral density (BMD) loss and structural deterioration, significantly increasing fracture risk. Despite its high prevalence, early detection remains challenging due to its asymptomatic progression and the limitations of conventional diagnostic techniques, such as Dual-Energy X-ray Absorptiometry (DXA). While DXA remains the clinical benchmark for BMD assessment, its high cost, limited accessibility, and inability to directly detect vertebral fractures necessitate the development of alternative, cost-effective, and widely deployable diagnostic methodologies. A dataset of 159 patient records was collected from NORI and CDA Hospital, incorporating 17 input features spanning demographics, genetic/blood type, clinical history and lab tests parameters. To bridge this gap, we developed a practical machine learning model tailored for clinics with limited resources. Instead of relying on expensive imaging, our framework uses only basic, highly accessible clinical markers—specifically ABO blood groups, serum calcium, and potassium levels. Because these tests are inexpensive and easily processed in standard laboratories, our approach removes the financial and technical hurdles of advanced diagnostics, making early screening possible in remote or underfunded healthcare settings. Data preprocessing involved rigorous feature selection, standardization, hyper-parameters tuning, clinically relevant features derivation and biomarker combinations. For classification, ensemble voting classifier was trained on key biomarkers— Weight, Potassium, Calcium and Total Vitamin D—achieving an accuracy of 90% and an AU-ROC score of 0.93 in predicting osteoporosis severity. In parallel, extreme gradient boosting Regressor trained on Age, Weight, ABO Group and Total Vitamin D demonstrated an R 2 of 0.536 for lumbar spine BMD estimation. The proposed framework demonstrates the viability of leveraging machine learning for non-invasive osteoporosis screening and fracture risk assessment, offering a radiation-free and clinically accessible complementary pre-screening tool.
Retraction: [Pt(O,O’-acac)(γ-acac)(DMS)] Alters SH-SY5Y Cell Migration and Invasion by the Inhibition of Na+/H+ Exchanger Isoform 1 Occurring through a PKC-ε/ERK/mTOR Pathway
The incidence and risk factors of sepsis following ovarian cancer surgery: A retrospective Nationwide Inpatient Sample database study
Background Postoperative sepsis is a significant complication following ovarian cancer surgery. However, limited studies have explored the risk factors associated with postoperative sepsis following ovarian cancer surgery in this context. This study aimed to assess the prevalence of postoperative sepsis and identify its associated risk factors. Methods This study retrospectively analyzed data from patients who underwent ovarian cancer surgery between January 2010 and December 2019 using the Nationwide Inpatient Sample (NIS) database. The age range of the study population is between 18 and 99 years old. Patients were categorized into two groups based on the presence or absence of postoperative sepsis. Data on patient demographics (e.g., race, age), hospital characteristics (e.g., insurance type, bed size, teaching status, region), preoperative comorbidities, and postoperative complications were extracted for comparison. Univariate and multivariable logistic regression analysis were conducted to identify factors associated with postoperative sepsis. Results A total of 39,049 patients were identified in the NIS database. Among them, 1,288 cases of postoperative sepsis were observed, representing an incidence rate of 3.3%. Patients with postoperative sepsis exhibited higher hospital charges, advanced age, prolonged length of stay (LOS), and increased in-hospital mortality. Preoperative risk factors for postoperative sepsis included congestive heart failure, coagulopathy, metastatic cancer, etc. Postoperative sepsis was associated with major complications, including electrolyte imbalance, urinary tract infection, thrombocytopenia, etc. Conclusions The incidence of postoperative sepsis following ovarian cancer surgery has shown a slight increase over time. Postoperative sepsis is associated with advanced age, race, prolonged LOS, higher hospital charges, in-hospital mortality, preoperative comorbidities, and perioperative complications. Recognizing these risk factors is essential for improving patient prognosis.
Engineering of T7 DNA-dependent RNA polymerase with activity at elevated temperature
Bacteriophage T7 RNA polymerase (T7 RNAP) is a key enzyme for in vitro transcription (IVT) and plays a central role in the production of synthetic mRNA for research and therapeutic applications. However, IVT frequently generates double-stranded RNA (dsRNA) as an undesired by-product, which can trigger innate immune responses and compromise mRNA quality. Increasing reaction temperatures reduces dsRNA formation, however, the wild-type T7 RNA polymerase exhibits limited stability under such conditions. Therefore, polymerase variants with enhanced thermotolerance enable more robust transcription at elevated temperatures while minimizing dsRNA generation. To address this limitation, we aimed at obtaining T7 RNA polymerase variants with increased thermotolerance using the Protein Repair One Stop Shop (PROSS) web server. Four crystal structures of T7 RNA polymerase, comprising a promoter complex, an initiation complex, and two elongation complexes were used as input for independent PROSS runs. Mutations shared across all four designs for each PROSS index were then combined to generate multi-structure PROSS Combined Designs (PCDs). In the subset evaluated experimentally, PCD9 retained full-length transcription activity at temperatures up to 48 °C, whereas wild-type T7 RNA polymerase showed strong loss of activity under the same buffer conditions. At 48 °C, PCD9 supported the synthesis of kilobase-length scale transcripts and produced no detectable dsRNA signal in a dot blot assay. In contrast, the wild-type enzyme generated strong dsRNA signals at 37 °C and failed to produce detectable RNA at 48 °C. Additional PROSS variants derived exclusively from the elongation complex structure were inactive at both 37 °C and 48 °C. Together, these results show that multi-structure PROSS design can yield a thermotolerant T7 RNA polymerase with improved performance at elevated temperature and reduced dsRNA byproduct formation. The findings also suggest that restricting stability design to a single structural state may not fully capture the requirements of a highly dynamic enzyme.