Category: Nevin Manimala

Reprod Biol Endocrinol. 2025 Dec 24;23(1):162. doi: 10.1186/s12958-025-01501-0.

ABSTRACT

OBJECTIVE: The relationship between sedentary behavior and infertility remains ambiguous and contentious. This study seeks to elucidate this association by analyzing data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), coupled with Mendelian randomization (MR) analyses.

METHODS: Our analysis comprised 2904 female participants, aged 20 to 49 years, enrolled in the National Health and Nutrition Examination Survey (NHANES) during the 2013-2018 cycles. Weighted multivariate logistic regression model was employed to examine the association between sedentary behavior and infertility, with sensitivity analysis conducted to validate the robustness of the findings. In addition, we used restricted cubic spline (RCS) curves to explore any non-linear association between sedentary behavior and infertility. A two-sample Mendelian randomization (MR) analysis was subsequently conducted using summary-level data from genome-wide association studies (GWAS) to investigate the potential causal links between self-reported leisure screen time (LST), sedentary commuting, sedentary behavior at work, and infertility. Causal estimates were primarily obtained with the inverse-variance weighted (IVW), while the weighted median, MR-Egger, and weighted mode were applied as complementary analyses. To evaluate the robustness of these results, horizontal pleiotropy was assessed using the MR-Egger intercept, heterogeneity was examined with Cochran’s Q test, and additional sensitivity testing was performed through leave-one-out analyses.

RESULTS: After adjusting for potential confounders, the weighted multivariable logistic regression analysis indicated that although the prevalence of infertility appeared to increase with longer daily sitting time, this association did not reach statistical significance (OR = 1.03, 95% CI: 1.00-1.07, P = 0.066). Results from multiple sensitivity analyses remained largely consistent, supporting the robustness of these findings. In the Mendelian randomization (MR) analysis, no statistically significant causal relationship was observed between genetically predicted sedentary behavior and infertility. Specifically, the inverse variance-weighted (IVW) estimates suggested no robust evidence of causality between leisure screen time (OR = 1.11, 95% CI: 0.10-1.24, P = 0.052), sedentary commuting (OR = 1.19, 95% CI: 0.88-1.62, P = 0.257), or sedentary behavior at work (OR = 0.99, 95% CI: 0.83-1.19, P = 0.930) and infertility.

CONCLUSION: No statistically significant evidence was found to support an association between sedentary behavior and infertility. Future large-scale prospective studies are warranted to further explore this potential relationship.

PMID:41444875 | DOI:10.1186/s12958-025-01501-0

BMC Med Educ. 2025 Dec 24;25(1):1706. doi: 10.1186/s12909-025-08164-w.

ABSTRACT

BACKGROUND: Distal radius fractures (DRFs) are among the most common orthopedic injuries and are often challenging for students to fully understand when taught using only 2D radiographs or healthy models. This study aimed to evaluate the educational impact of tomography-based 3DP DRF models on medical students’ knowledge acquisition and anatomical understanding compared with conventional teaching methods.

METHODS: The study was designed as a parallel-group, single-blinded prospective randomized controlled trial conducted over two days of structured education. Ninety-four second year physiotherapy students (19.62 ± 1.2 years; 45 F, 49 M) were enrolled and randomly assigned into intervention (n = 47) and control (n = 47) groups. The intervention group received tomography-based fracture 3DP training, while the control group received a healthy 3D-printed model. Primary outcomes included theoretical knowledge (MCQs) and practical case-solving. Secondary outcomes were Test-Taking Motivation Questionnaire (TTMQ); Test Anxiety Inventory (TAI), puzzle assembly time, satisfaction, and willingness-to-recommend ratings. Assessments were conducted pre- and post-training, with knowledge retention re-assessed at one month after education. Statistical analyses were performed using independent samples t-tests and chi-square tests for between-group comparisons, paired t-tests for within-group changes.

RESULTS: The intervention group included 47 students (19.51 ± 1.1 years; 36 F, 11 M), while the control group consisted of 47 students (19.74 ± 1.3 years; 33 F, 14 M). Demographic characteristics were similar between the groups. In the 3D group, theoretical knowledge scores improved (50.68 [45.34, 55.93], p < .001), TTMQ scores increased (28.06 [24.22, 31.91], p < .001), and TAI scores decreased (-10.89 [-14.33, – 7.46], p < .001). Similarly, in the control group, theoretical knowledge scores improved (49.46 [44.86, 54.03], p < .001), TTMQ scores increased (21.60 [17.13, 26.06], p < .001), and TAI scores decreased (-9.70 [-14.35, – 5.05], p < .001). Post-training comparisons showed that the intervention group achieved significantly higher scores in case-solving (-18.55 [-23.87, – 13.23], p < .001), MCQ performance (4.17 [0.15, 8.18], p = .042), puzzle assembly time (11.34 [4.24, 18.44], p = .002), TTMQ (8.04 [3.20, 12.87], p = .030), and TAI (-4.42 [-7.54, – 1.30], p = .030). No significant between-group differences were observed for color recognition (p = .301), weight identification (p = .161), detail recognition (p = .669), or knowledge retention (p = .160).

CONCLUSIONS: Within the limits of this study, tomography-based fracture-specific 3D printed models led to greater improvements in knowledge, motivation, reduced anxiety, and better practical performance compared with conventional teaching methods. These models showed educational benefits; further research is needed to confirm long-term and clinical impacts.

TRIAL REGISTRATION: clinicaltrials.gov NCT06061003 24/09/2023.

PMID:41444874 | DOI:10.1186/s12909-025-08164-w

Alzheimers Dement. 2025 Dec;21 Suppl 4:e096826. doi: 10.1002/alz70858_096826.

ABSTRACT

BACKGROUND: A person suffering from dementia will eventually lose the ability to breathe if that part of the brain has been seriously affected. If left untreated, this will cause the victim to die. Continuous breathing assistance is necessary to regulate their breathing. In order to meet this requirement an automatic ventilator support system using artificial neural network (ANN) is proposed for getting the required blood oxygen saturation level (SaO₂).

METHOD: Samples from 325 people with acute respiratory issues, including dementia patients, were collected at ASTER Medcity in Kochi, India, with ethical permission. Parameter identification for model inputs and outputs is done by in cooperating real time patient data including periodical arterial blood gas analysis, continuous pulse oximetry readings and mechanical ventilator settings using statistical R programming. Artificial neural network model was developed using MATLAB programming to predict inspired oxygen (FiO₂) and comparison also undertaken with physician’s prediction.

RESULT: After so many trial and error we got the mean square error of the trained model network as 0.019907 and R value as 0.852. To reduce over fitting hidden layer value must be taken less than twice the input layer size. New data set different from that used for modelling ANN was used for testing. Compared with the predictions of the physicians the artificial neural network model shows 86% accuracy CONCLUSION: Continuous oxygen saturation level monitoring and control is essential for Alzheimer’s disease patient, since persistent respiratory diseases in these people can become a common reason for sudden death. For this a ANN model using MATLAB programming was developed to predict inspired oxygen amount which was given to the patient as life support. The suggested model output was found to be utilized as a suggestive method to assist clinicians because it displays an accuracy of over 80% when compared to the decisions made by physicians.

PMID:41444850 | DOI:10.1002/alz70858_096826

Dig Dis Sci. 2025 Dec 24. doi: 10.1007/s10620-025-09622-7. Online ahead of print.

ABSTRACT

BACKGROUND: Recurrent common bile duct (CBD) stones after endoscopic retrograde cholangiopancreatography (ERCP) is a significant clinical issue. While the association between serum lipid levels and gallstones has been established, its impact on recurrent CBD stone is less clear. This study aims to investigate the association between serum lipid levels and recurrent CBD stone, further subclassified into different subgroups. We also try to explore effective drugs to decrease the occurrence of recurrent CBD stone.

MATERIALS AND METHODS: This multi-institutional study acquired patients’ data from Chang Gung Memorial Hospitals using Chang Gung Research Database (CGRD) from 2002/1/1 to 2020/12/31. We analyzed the association between metabolic risk factors and recurrent CBD stone after ERCP using propensity score matching and then subclassified these patients into cholecystectomy, cirrhosis, and hyperlipidemia. Additionally, medications aimed at controlling serum lipid levels were investigated for their potential to reduce the recurrence rate of CBD stones.

RESULTS: Totally, 5132 patients were enrolled. Our results showed that higher cholesterol level and HbA1C above 6.5% are risk factors of CBD stone recurrence after ERCP when using propensity score matching. However, triglyceride (TG) and high-density lipoprotein (HDL) were presented as protective factors. These metabolic factors may be variable in different subgroups. Additionally, statin and aspirin might be effective drugs to reduce CBD stone recurrence rate.

CONCLUSIONS: Serum lipid level and HbA1C were found to be associated with recurrent CBD stone after ERCP but variable in different subgroups. Statin and aspirin might reduce the risk of CBD stone recurrence.

PMID:41444847 | DOI:10.1007/s10620-025-09622-7

Environ Geochem Health. 2025 Dec 24;48(2):66. doi: 10.1007/s10653-025-02940-9.

ABSTRACT

In recent years, India has witnessed an alarming rise in air pollution levels, raising growing concerns among health and environmental experts. This study evaluates the inhalation cancer risk associated with fine particulate matter (PM_2.5) bound polycyclic aromatic hydrocarbons (PAHs) in two rapidly developing yet under-monitored regions of India. Ambient air samples were analyzed for 16 priority PAHs, and the carcinogenic risk was assessed using Incremental Lifetime Cancer Risk (ILCR) estimates through Monte Carlo simulations for both adults and children. The results indicated season and site-specific variations in PAH concentrations, with winter months showing higher cumulative BaP equivalent (BaPeq) levels. Adults consistently exhibited higher ILCR values than children, exceeding the acceptable risk threshold of 1 × 10^-6 in several scenarios.Global sensitivity analysis using the Sobol’ method revealed that BaPeq concentration, exposure duration, and body weight were the most influential parameters affecting ILCR outcomes. Statistical validation using ANOVA and Tukey’s post-hoc test confirmed significant seasonal and demographic variability. These findings emphasize the need for refined toxicity values and exposure inputs to improve human health risk assessments in India. This work combines field monitoring, probabilistic modelling, and uncertainty-based analysis to support evidence-driven air quality management, aligning with the goals of India’s clean air strategies.

PMID:41444846 | DOI:10.1007/s10653-025-02940-9

Ann Surg Oncol. 2025 Dec 24. doi: 10.1245/s10434-025-18735-2. Online ahead of print.

ABSTRACT

BACKGROUND: Organ preservation is gaining attention, yet primary treatment approaches differ substantially between pT1 and pT2 colon cancer (CC). This study evaluates whether tumor invasion depth affects survival outcomes in patients with pT1-2N0-2 colon cancer.

METHODS: In this nationwide cohort study, patients undergoing surgery for pT1 or pT2 CC between 2014 and 2015 were identified from the Dutch Snapshot Research Group’s SNAPSHOT complex colon cancer database. Five-year disease-free survival (DFS) and overall survival (OS) was analyzed using Kaplan-Meier curves, log-rank tests, and Cox proportional hazard models.

RESULTS: A total of 2312 patients were included (921 pT1 and 1391 pT2). Five-year DFS (83.5% vs. 83.2%, P = 0.79, adjusted HR [HR_adj] pT2 vs. pT1: 0.9; 95% confidence interval [CI] 0.7-1.2) and 5-year OS (84.9% vs. 85.6%, P = 0.72, HR_adj pT2 vs. pT1: 0.8; 95% CI 0.6-1.1) were comparable between pT1N0 and pT2N0 patients. Similarly, in pT1N+ and pT2N+ patients, there was no significant difference in DFS (81% vs. 75.8%, P = 0.31, HR_adj pT2 vs. pT1: 1.3; 95% CI 0.6-2.6) or OS (84% vs. 82.5%, P = 0.73, HR_adj pT2 vs. pT1: 0.9; 95% CI 0.5-1.6). Distant metastases developed in 37 (4%) pT1 patients and 68 (4.9%) pT2 patients (P = 0.33). Among these, 26 of 37 pT1 patients (70.3%) and 40 of 68 pT2 patients (58.8%) did not have lymph node metastases in the initial resection specimen (pN0).

CONCLUSIONS: Tumor invasion depth (pT1 or pT2) had no significant impact on DFS or OS following formal oncological resection. Furthermore, most distant metastases develop in pN0 patients, suggesting a minor influence of surgery on control of distant disease.

PMID:41444843 | DOI:10.1245/s10434-025-18735-2

Tech Coloproctol. 2025 Dec 24. doi: 10.1007/s10151-025-03254-9. Online ahead of print.

ABSTRACT

INTRODUCTION: In sacral neuromodulation (SNM), the stimulation intensity is set at the sensory threshold (ST) level. However, subsensory stimulation as low as 50% of ST has proven effective in reducing faecal incontinence episodes.

AIM: To explore the relationship between functional outcomes and varying subsensory stimulation amplitude in newly implanted patients.

METHOD: This randomised, double-blind study was designed to include patients with ≥ 1 faecal incontinence episodes/week despite maximal conservative therapy. As part of another trial, patients were offered a one-stage procedure. Postoperatively, patients were randomised into two groups. G-1 received stimulation at 0.05 V, at 50% and 90% of the ST in three 4-week periods, followed by 12 weeks of stimulation at the ST. G-2 received stimulation at 90% of the ST in three 4-week periods, followed by 12 weeks of stimulation at ST. Patients were evaluated after each period using St. Marks’s Incontinence Score and a visual analogue scale (VAS) for patient satisfaction regarding social function, bowel function and quality-of-life, along with a bowel habit diary.

RESULTS: In total, 73 patients with a median age of 60 years [interquartile range (IQR: 50-69 years)] completed the trial. Faecal incontinence episodes were significantly reduced at all follow-ups, with no differences between groups. The only statistical difference between groups was deltaVAS for bowel function after 4 weeks. In G-1 with ultra-low stimulation amplitude [0.05 V – equivalent to 9.6% (IQR: 6.5-13.4) of ST], the improvement compared with baseline was 30 points (IQR: 10-50) significantly lower than G-2 with an improvement of 50 points (IQR: 10-70) (p-value: 0.05).

CONCLUSIONS: Subsensory stimulation is feasible in newly implanted patients with faecal incontinence. An amplitude of 0.05 V is as effective on the functional outcomes as stimulation with higher amplitudes.

PMID:41444840 | DOI:10.1007/s10151-025-03254-9

Alzheimers Dement. 2025 Dec;21 Suppl 3:e099806. doi: 10.1002/alz70857_099806.

ABSTRACT

BACKGROUND: Elevated central arterial stiffness is a risk factor for amnestic mild cognitive impairment (aMCI) and dementia, but the pathophysiological mechanisms underlying the relationship between vascular health and cognitive decline in patients with aMCI remain unclear. We examined the cross-sectional relationship between central arterial stiffness, brain default mode network functional connectivity (DMN-FC), and cognitive function in patients with aMCI.

METHOD: Participants aged 55-80 years, either cognitively normal or diagnosed with aMCI, and without major neurological, vascular, metabolic, or psychiatric diseases, were recruited. Data was analyzed from 21 cognitively normal (age 65.9±7.0) and 48 adults with aMCI (age 64.1±5.9). Central arterial stiffness was measured using carotid-femoral pulse wave velocity (cfPWV) and carotid β-stiffness via applanation tonometry and ultrasonography. DMN-FC was assessed with resting-state fMRI and seed-based correlation analysis, using the posterior cingulate cortex (PCC) as the seed. Episodic memory and executive function were evaluated with California Verbal Learning Test (CVLT) and Wisconsin Card Sorting Test (WCST). Data was analyzed using multiple variable linear regression and mediation analysis.

RESULT: Carotid β-stiffness index was slightly higher in aMCI patients (8.9±2.1) compared to cognitively normal older adults (8.0±1.7), but the difference was not statistically significant. Higher carotid β-stiffness index was associated with higher DMN-FC between the PCC and right precentral gyrus (PcG) in the cognitively normal (B=0.02, r² = 0.373, p = 0.003) and aMCI group (r² = 0.260, p = 0.0002). Higher DMN-FC between the PCC and right PcG was associated with worse CVLT performance in the aMCI group (B=-27.10, p = 0.012, 95%CI = -47.91, -6.30). Higher carotid β-stiffness index was associated with worse CVLT performance (B=-1.55, p = 0.045, 95%CI=-3.08, -0.03) and worse WCST performance (B=-2.62, p = 0.068, 95%CI = -5.45, 0.20) in the aMCI group. Higher DMN-FC between the PCC and right PcG mediated the association between higher carotid β-stiffness index and worse CVLT performance in the aMCI group.

CONCLUSION: Our findings suggest that elevated central arterial stiffness may impair cognitive performance in patients with aMCI through alterations in DMN functional connectivity, potentially reflecting compensatory mechanisms. These findings underscore the importance of addressing vascular health as part of efforts to prevent or delay cognitive decline in aging populations, particular those at risk of dementia.

PMID:41444801 | DOI:10.1002/alz70857_099806

Alzheimers Dement. 2025 Dec;21 Suppl 3:e101375. doi: 10.1002/alz70857_101375.

ABSTRACT

BACKGROUND: Neuropsychiatric symptoms (NPS), such as depression and anxiety, are common in the early stages of Alzheimer’s disease (AD). These symptoms often appear before cognitive decline becomes evident, posing significant challenges for patients and caregivers. Despite their prevalence, the underlying mechanisms of NPS remain poorly understood, particularly in underserved populations.

METHOD: A retrospective cohort study will utilize REDGESAM’s electronic clinical records, focusing on patients aged 50 and older diagnosed with mild cognitive impairment (MCI) or subjective cognitive decline (SCD). Data sources include standardized neuropsychiatric scales and brain imaging reports. Advanced statistical analyses, including regression modeling, will assess associations between NPS, imaging findings, and cognitive decline.

RESULT: This study anticipates identifying key correlations between NPS and brain imaging markers such as hippocampal volume and white matter integrity. These findings will provide a deeper understanding of how early psychiatric symptoms align with biological changes in the brain.

CONCLUSION: By leveraging REDGESAM’s robust data, this research will inform targeted interventions for depression and anxiety in AD, improve patient outcomes, and contribute to dementia care strategies worldwide.

PMID:41444800 | DOI:10.1002/alz70857_101375

Sci Rep. 2025 Dec 24. doi: 10.1038/s41598-025-33517-2. Online ahead of print.

ABSTRACT

Short-term rainfall forecasting presents a complex spatiotemporal modeling challenge, critical for adaptation and mitigation of high-impact hydrometeorological events such as flash floods and cloudbursts. This study examines hourly rainfall patterns in the Northwest Himalayan (NWH) region of India, enhancing forecasting accuracy using spatial correlations. The region shows a significant decline in hourly rainfall trends over the period 2019-2024, with approximately 50% of the area exhibiting statistically significant decreasing trends. The analysis reveals that high-elevation regions exhibit stronger initial 1-hour lag correlation (>0.8) and a rapid temporal decay over 9 hours. In contrast, lower-altitude areas (below 600 m) display a more gradual decrease in correlation, suggesting broader spatial influence with less intense propagation. Across all locations, rainfall variability as defined by statistically significant correlations, typically dissipates within 6 to 7 hours. Our analysis further identifies a prominent belt of high rainfall coherence aligned along the central Himalayan zone, highlighting pronounced spatial homogeneity. To improve predictive performance, this study proposes an attention-guided spatial correlation mechanism integrated within a Deformable Convolutional Long Short-Term Memory (DConvLSTM) framework. The proposed model, termed SARITA, processes hourly rainfall and spatial correlations, with the attention mechanism dynamically using spatial dependencies. This integration enhances the model’s ability to generalize across spatial-temporal patterns. Model evaluation using statistical metrics demonstrates that SARITA consistently outperforms baseline models such as ConvLSTM and standard DConvLSTM, achieving a 25% improvement in hourly rainfall forecasts. Furthermore, the model also improves anomaly detection by 3.5% over the standard DConvLSTM model.

PMID:41444798 | DOI:10.1038/s41598-025-33517-2