Category: Nevin Manimala

BMC Nephrol. 2025 Aug 23;26(1):486. doi: 10.1186/s12882-025-04420-9.

ABSTRACT

BACKGROUND: Nephrotic syndrome is a common glomerular disorder. Treatment typically begins with corticosteroids, but patient response varies. Differentiating between steroid-sensitive nephrotic syndrome (SSNS) and steroid-resistant nephrotic syndrome (SRNS) early in the disease course is important, as SRNS is associated with a higher risk of poor long-term outcomes. Neutrophil gelatinase-associated lipocalin (NGAL), a biomarker released in response to tubular injury, has emerged as a potential non-invasive marker for renal damage.

METHODS: We conducted a systematic review and meta-analysis of studies reporting NGAL levels in SSNS and SRNS, based on the PRISMA guidelines. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, ScienceDirect, and the WHO Virtual Health Library Regional. The statistical analysis was performed using a random-effects model to estimate the standardized mean difference (SMD) with a 95% confidence interval.

RESULTS: A total of 16 studies were included. Meta-analyses revealed significantly higher urinary NGAL levels in both SSNS and SRNS patients compared to healthy controls. Urinary NGAL levels were significantly higher in SSNS and SRNS patients compared to healthy controls, with SMD = 0.78 (95% CI: 0.434-1.128, P < .001) and SMD = 2.56 (95% CI: 1.152-3.971, P < .001), respectively. Patients with SRNS had markedly higher urinary NGAL levels than those with SSNS (SMD = 1.889, 95% CI: 0.819-2.959, P < .001). ROC analyses across several studies demonstrated moderate to strong discriminative ability of urinary NGAL in distinguishing between SRNS and SSNS.

CONCLUSION: Urinary NGAL demonstrated strong potential as a non-invasive biomarker for distinguishing between SRNS and SSNS, supporting its clinical utility in early diagnosis, risk stratification, and management.

PMID:40849613 | DOI:10.1186/s12882-025-04420-9

BMC Pregnancy Childbirth. 2025 Aug 23;25(1):881. doi: 10.1186/s12884-025-07902-8.

ABSTRACT

BACKGROUND: Modern medicine has significantly transformed the process of childbirth among women. The preferred mode of childbirth has become of global interest to many researchers due to the steady rise in recent caesarean section (CS) rates. While CS is often viewed as a life-saving intervention, it is associated with both immediate and long-term complications for the mother, newborn, and future pregnancies. To better understand the medical and non-medical reasons for CS among women, this study was conducted to identify the socio-demographic and obstetric factors that influence CS in the Tamale Metropolis.

METHODOLOGY: A retrospective cross-sectional study was conducted among 318 postpartum mothers at the Tamale Teaching Hospital. Descriptive analysis, univariate logistic regression and stepwise multivariate logistic regression model were conducted, with a p-value < 0.05 considered statistically significant.

RESULTS: The majority of respondents (63.5%) were below 30 years. Almost all respondents (95.3%) were enrolled in the National Health Insurance Scheme (NHIS). The majority (95.91%) had single births. Most respondents (91.2%) had spontaneous vaginal delivery. The prevalence of CS was 8.8%. Significant factors influencing the preference for CS were maternal age above 30 years (aOR = 2.27, 95% CI = 1.01-5.12), rural settlement (aOR = 0.31, 95% CI = 0.10-0.92), twin delivery (aOR = 6.88, 95% CI = 1.64-28.95), and obstetric complication (aOR = 10.55, 95% CI = 2.42-46.04).

CONCLUSION: There is a need to focus on initiatives that address regional disparities, enhance access to comprehensive maternal healthcare services, and promote informed decision-making regarding mode of delivery to ultimately improve maternal and infant health outcomes.

PMID:40849612 | DOI:10.1186/s12884-025-07902-8

BMC Cardiovasc Disord. 2025 Aug 23;25(1):629. doi: 10.1186/s12872-025-05070-3.

ABSTRACT

BACKGROUND: Acute coronary syndrome (ACS) remains a leading cause of global cardiovascular morbidity and mortality, with elevated low-density lipoprotein cholesterol (LDL-C) being a key modifiable risk factor. Despite statin therapy, many patients fail to achieve optimal LDL-C targets, highlighting the need for adjunctive treatments such as PCSK9 inhibitors (e.g., Evolocumab and Alirocumab). However, comparative evidence on their efficacy and safety in ACS patients remains limited.

OBJECTIVE: To systematically evaluate the efficacy and safety of PCSK9 inhibitors (Evolocumab and Alirocumab) in patients with ACS, focusing on LDL-C reduction and major adverse cardiovascular events (MACE).

METHODS: A comprehensive search was conducted in PubMed, Embase, Cochrane Library, ClinicalTrials.gov, and the WHO International Clinical Trials Registry. Eligible randomized controlled trials (RCTs) assessed PCSK9 inhibitors in ACS patients and reported outcomes on LDL-C and MACE. Both direct and network meta-analyses were performed to compare effect sizes across interventions. No direct head-to-head trials between Evolocumab and Alirocumab were identified.

RESULTS: Nine RCTs involving 37,934 patients were included. Direct meta-analysis showed that PCSK9 inhibitors significantly reduced LDL-C (mean difference [MD]: – 52.7 mg/dL; 95% CI: – 61.2 to – 44.1) and lowered the risk of MACE (odds ratio [OR]: 0.79; 95% CI: 0.68-0.93). In subgroup analysis, Evolocumab produced greater LDL-C reductions, while Alirocumab showed a stronger trend toward MACE reduction, though not statistically significant (OR: 0.84; 95% CI: 0.68-1.03). Network meta-analysis confirmed these patterns but revealed no statistically significant differences between the two agents.

CONCLUSION: PCSK9 inhibitors significantly improve lipid profiles and reduce cardiovascular event risk in ACS patients. While Evolocumab and Alirocumab offer similar overall benefits, their differential effects on LDL-C and MACE warrant further investigation. These findings support the role of PCSK9 inhibitors in secondary prevention strategies for high-risk cardiovascular populations.

PMID:40849610 | DOI:10.1186/s12872-025-05070-3

Discov Oncol. 2025 Aug 23;16(1):1601. doi: 10.1007/s12672-025-03336-y.

ABSTRACT

BACKGROUND: The causal relationship between interleukin-7 levels and neuroblastoma risk remains unclear, and optimal radiation therapy timing lacks definitive evidence. This study investigated causal associations using Mendelian randomization while examining radiation therapy timing effects.

METHODS: We conducted two-sample Mendelian randomization analysis using GWAS summary statistics for interleukin-7 levels and neuroblastoma with three SNPs as instrumental variables. Multiple MRmethods included inverse variance weighted (IVW), MR-Egger, weighted median, and mode approaches. Additionally, 1,007 neuroblastoma patients from SEER database (2000-2018) were analyzed comparing preoperative (n = 416) versus postoperative (n = 591) radiation therapy using propensity score matching and Cox regression models.

RESULTS: Mendelian randomization revealed significant positive causal association between elevated interleukin-7 levels and increased neuroblastoma risk. The IVW method showed higher interleukin-7 levels associated with 3.6-fold increased odds (OR = 3.585, 95% CI: 1.216-10.575, p = 0.021). In clinical analysis, preoperative radiation demonstrated superior survival outcomes with 27% mortality reduction (HR = 0.73, 95% CI: 0.55-0.97, p = 0.031). Subgroup analysis revealed significant racial differences, with White patients deriving greatest benefit from preoperative radiation (HR = 0.57, 95% CI: 0.42-0.78, p < 0.001).

RESULTS: This study provides evidence for causal relationship between interleukin-7 levels and neuroblastoma risk, suggesting inflammatory pathways’ role in pathogenesis.

PMID:40849609 | DOI:10.1007/s12672-025-03336-y

Sci Rep. 2025 Aug 23;15(1):31065. doi: 10.1038/s41598-025-17115-w.

ABSTRACT

This prospective study aimed to investigate changes in corneal higher-order aberrations (HOAs) in myopic children using orthokeratology (ortho-k) lenses and their relationship with myopia progression. A total of 112 children aged 8-13 years were divided into group A (axial elongation ≤ 0.1 mm/y with ortho-k) and group B (axial elongation > 0.1 mm/y with ortho-k). At baseline, 1, 6, and 12 months following the initiation of lens wear, HOAs and corneal peripheral defocus were evaluated. Ninety-three patients completed the 1-year follow-up. The mean axial elongation was – 0.07 ± 0.15 mm/y in group A, versus 0.32 ± 0.17 mm/y in group B. No statistical differences were observed in HOAs and corneal peripheral defocus at 1, 6, and 12 months (F = 0.653, 0.878; P > 0.05). Multivariate linear regression showed axial elongation was negatively correlated with ∆HOAs, peripheral defocus, and ∆horizontal coma (standardized beta=-0.331, -0.318, -0.209; P = 0.006, 0.001, 0.010, respectively) and positively correlated with the treatment zone diameter (standardized beta = 0.261, P = 0.003). Multivariate logistic regression identified ∆HOAs, peripheral defocus, ∆horizontal coma, and treatment zone as key factors distinguishing group A from group B (OR = 0.009, 0.455, 0.123, 12.172; P = 0.036, 0.003, 0.032, 0.019, respectively). The ROC curve for ∆HOAs had an area of 0.803 with a cut-off value of 0.834 μm. The ∆HOAs were more effective independent predictors of axial elongation than corneal peripheral defocus in children using ortho-k lenses. The ∆HOAs greater than 0.834 μm may lead to axial elongation ≤ 0.1 mm/y. These findings can be beneficial to fitting and optimizing ortho-k lenses.

PMID:40849596 | DOI:10.1038/s41598-025-17115-w

Surg Today. 2025 Aug 23. doi: 10.1007/s00595-025-03118-7. Online ahead of print.

ABSTRACT

PURPOSE: To compare the safety and efficacy of barbed and non-barbed sutures for fascial closure in abdominal surgery.

METHODS: A systematic literature search through February 2025 identified studies comparing overall surgical site infections (SSI), fascial complications, and hospital stays between barbed and non-barbed sutures. A meta-analysis using random-effects models calculated odds ratios (ORs) or mean differences (MDs) with 95% confidence intervals (CIs).

RESULTS: Seven studies involving 12,278 patients (barbed group, n = 4912; non-barbed group, n = 7366) were included. The overall SSI rates were 1.9% and 4.0% in the barbed and non-barbed groups, respectively. Barbed sutures significantly reduced overall SSIs (OR, 0.41; 95% CI: 0.31-0.53; P < 0.001) without statistical heterogeneity. Barbed suture also significantly reduced the length of hospital stay (MD, – 1.13; 95% CI: – 1.42- – 0.83, P < 0.001) without statistical heterogeneity. No significant difference was observed in fascial complications between the groups (OR, 0.66; 95% CI: 0.36-1.22, P = 0.19).

CONCLUSIONS: This is the first meta-analysis to focus specifically on barbed sutures for abdominal fascial closure. Barbed sutures significantly reduce SSI and hospital stay without increasing fascial complications, thus suggesting that they are safe and efficient options for abdominal wall closure.

PMID:40849594 | DOI:10.1007/s00595-025-03118-7

Sci Rep. 2025 Aug 23;15(1):31012. doi: 10.1038/s41598-025-16539-8.

ABSTRACT

In multi-objective particle swarm optimization, achieving a balance between solution convergence and diversity remains a crucial challenge. To cope with this difficulty, this paper proposes a novel multi-objective particle swarm algorithm, called ASDMOPSO, which aims to improve the optimization efficiency through the angular division of the archive and the dynamic update strategy. The algorithm efficiently classifies non-dominated solutions by dividing the external archive region into equal angles, thus achieving fine management and diversity maintenance of solutions during the optimization process. When the external archive overflows, the algorithm removes the solution in the highest density region using the congestion distance metric. At the same time, the research presents a multi-stage initialization approach. This method splits the random population into two subpopulations. Subsequently, a genetic algorithm and a differential evolutionary algorithm are utilized for optimization purposes in each subpopulation, respectively. As a result, the quality of the initial population is enhanced. To explore the solution space more efficiently, this paper designs a dynamic flight parameter adjustment technique. This technique balances exploration and exploitation by adjusting the optimization algorithm parameters in real time. The proposed algorithm is compared with several representative multi-objective optimization algorithms on 22 benchmark functions, and statistical tests, sensitivity analysis, and complexity analysis are conducted. The experimental results show that the ASDMOPSO algorithm is more competitive than other comparison algorithms, with significantly improved optimization efficiency. For example, on the ZDT4 test function, its average IGD value is 0.032, outperforming the standard PSO algorithm and surpassing all other comparison algorithms, thereby validating the algorithm’s superiority in complex multi-objective optimization problems.

PMID:40849576 | DOI:10.1038/s41598-025-16539-8

Sci Rep. 2025 Aug 23;15(1):31017. doi: 10.1038/s41598-025-16221-z.

ABSTRACT

The Physical Unclonable Function (PUF) is a security mechanism that generates secret keys by capitalizing on inherent physical variations in a device to produce a distinctive response. Given the prevalent incorporation of power management units (PMUs) in current System-on-Chip devices to meet the rising demands for energy efficiency and optimal power utilization, this study proposes the utilization of existing components, specifically the voltage regulator within the PMU, to enhance the PUF. The system has been designed in 22-nm FDSOI technology. The statistical analyses are founded on silicon measurements comprising 8K challenge-response pairs obtained from three distinct chips. It reveals that the proposed system attains a 50% diffuseness, indicating an improvement of approximately 31%, while achieving a relatively consistent 48% uniformity when compared to stand alone PUF. Moreover, the system exhibits higher resiliency against machine learning-based modeling attacks, as evidenced by a prediction accuracy of 50.5% in comparison to the 67.1% reported in the stand alone employed PUF implementation.

PMID:40849572 | DOI:10.1038/s41598-025-16221-z

Sci Rep. 2025 Aug 23;15(1):31053. doi: 10.1038/s41598-025-15720-3.

ABSTRACT

Antenatal Care, use of skilled delivery attendants, Institutional delivery and postnatal care services are key maternal health services that can significantly reduce maternal mortality. The objective of this study was to identify spatial distribution and factors that affect full package utilization of maternal health services in Ethiopia. Sampling weights were applied, and analyses were conducted using STATA version 17. Spatial statistics, including Moran’s I and Getis-Ord Gi*, were performed in ArcGIS to assess spatial autocorrelation and identify FPMHSU clusters. SaTScan software detected purely spatial clusters. Multilevel binary logistic regression identified individual- and community-level factors. Model selection was based on a significant log-likelihood ratio test and Variables with p < 0.05 were deemed significant, with adjusted odds ratios and 95% confidence intervals quantifying associations. The prevalence of in Ethiopia was 56.96% (95% CI: 55.41%, 58.51%) and exhibited significant spatial clustering (Moran’s Index = 0.686, P < 0.001). Women aged 20-24 years [AOR = 0.65, 95% CI: 0.44-0.97], high parity [AOR = 0.52, 95% CI: 0.40-0.69] and urban residents [AOR = 0.53, 95% CI: 0.31-0.89] reduce the outcome, while being married [AOR = 1.54, 95% CI: 1.04-2.30], Muslim religion [AOR = 2.25, 95% CI: 1.45-3.48], primary education [AOR = 2.04, 95% CI: 1.65-2.52], secondary education [AOR = 2.30, 95% CI: 1.53-3.45], higher education [AOR = 6.10, 95% CI: 2.43-15.07], awareness of pregnancy complications [AOR = 3.62, 95% CI: 3.00-4.36], poorer households [AOR = 1.77, 95% CI: 1.32-2.37], middle wealth category [AOR = 1.56, 95% CI: 1.13-2.14], richer households [AOR = 2.61, 95% CI: 1.84-2.71], and the richest households [AOR = 6.70, 95% CI: 3.96-11.56] increase the outcome. This study revealed significant disparities in in Ethiopia, with spatial clustering (Moran’s I = 0.686) and hotspots in Addis Ababa, Dire Dawa, Harari, and East Gojam. Women with higher education (primary, secondary, and higher), Muslim religion, awareness of pregnancy complications, better economic status (poorer, middle, richer, and richest wealth categories), and urban residence were more likely to utilize maternal health services. Addressing these disparities is crucial for improving maternal health outcomes and ensuring equitable access.

PMID:40849569 | DOI:10.1038/s41598-025-15720-3

Sci Rep. 2025 Aug 23;15(1):31039. doi: 10.1038/s41598-025-15292-2.

ABSTRACT

The increasing reliance on Human-centric Internet of Things (H-IoT) systems in healthcare and smart environments has raised critical concerns regarding data integrity, real-time anomaly detection, and adaptive access control. Traditional security mechanisms lack dynamic adaptability to streaming multimodal physiological data, making them ineffective in safeguarding H-IoT devices against evolving threats and tampering. This paper proposes a novel trust-aware hybrid framework integrating Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) models, and Variational Autoencoders (VAE) to analyze spatial, temporal, and latent characteristics of physiological signals. A dynamic Trust-Aware Controller (TAC) is introduced to compute real-time trust scores using anomaly likelihood, context entropy, and historical behavior. Access decisions are enforced via threshold-based logic with a quarantine mechanism. The system is evaluated on benchmark datasets and proprietary H-IoT signals under diverse attack and noise scenarios. Experiments are conducted on edge devices including Raspberry Pi and Jetson Nano to assess scalability. The proposed framework achieved an average F1-score of 94.3% for anomaly detection and a 96.1% accuracy in access decision classification. Comparative results against rule-based and statistical baselines showed a 12-18% improvement in detection sensitivity. Real-time inference latency was maintained under 160 ms on edge hardware, validating feasibility for critical H-IoT deployments. Trust scores exhibited high stability under adversarial data fluctuations. This research delivers a scientifically grounded, practically scalable solution for adaptive security in H-IoT networks. Its novel fusion of deep learning and trust modeling enhances both responsiveness and resilience, paving the way for next-generation secure health and wearable ecosystems.

PMID:40849566 | DOI:10.1038/s41598-025-15292-2