Nevin Manimala

Lasers Med Sci. 2025 Aug 12;40(1):332. doi: 10.1007/s10103-025-04578-6.

ABSTRACT

To evaluate the safety and efficacy of fractional carbon dioxide (CO₂) laser combined with recombinant bovine basic fibroblast growth factor (rb-bFGF) gel for treating mature scars secondary to facial scald burns. In this retrospective cohort study, we analyzed 123 patients with mature facial scald burn scars treated with fractional CO₂ laser. According to whether the rb-bFGF gel was used during the treatment, patients were divided into CO₂ + rb-bFGF group (n = 56) and CO₂ group (n = 67). The modified Patient and Observer Scar Assessment Scale (POSAS) scar score was used to evaluate the clinical effect. Patient satisfaction and adverse events were also assessed. At the last follow-up visit, the PSAS score (mean ± SD) was statistically different between the two groups (7.74 ± 2.15 vs. 9.41 ± 1.97; P < 0.01), including color (1.79 ± 0.77 vs. 2.80 ± 1.15; P < 0.01), stiffness (1.75 ± 0.62 vs. 2.00 ± 0.50; P < 0.01), and thickness (1.96 ± 0.48 vs. 2.16 ± 0.51; P < 0.01); the OSAS score (mean ± SD) was statistically different between the two groups (11.34 ± 3.21 vs. 12.96 ± 3.12; P < 0.01), including pigmentation (1.75 ± 0.78 vs. 2.61 ± 1.20; P < 0.01), thickness (1.92 ± 0.51 vs. 2.10 ± 0.42; P < 0.05), relief (1.64 ± 0.60 vs. 1.86 ± 0.50; P < 0.05), and pliability (1.96 ± 0.62 vs. 2.24 ± 0.52; P < 0.05). For patient satisfaction and adverse events, the CO₂ + rb-bFGF group demonstrated accelerated wound healing (4 days vs. 7 days, P < 0.01), reduced incidences of persistent erythema (5.36% vs. 19.40%, P < 0.05) and hyperpigmentation (0% vs. 8.96%, P < 0.05), and higher patient global assessment score (8.09 ± 0.60 vs. 7.02 ± 1.01; P < 0.01). Combination therapy with fractional CO₂ laser and rb-bFGF gel demonstrates superior clinical outcomes compared to laser monotherapy for mature facial scald burn scars, with significant improvements in scar characteristics, fewer complications, and better patient acceptance.

PMID:40789953 | DOI:10.1007/s10103-025-04578-6

Eur J Pediatr. 2025 Aug 11;184(9):545. doi: 10.1007/s00431-025-06374-4.

ABSTRACT

Hypogonadotropic hypogonadism(HH) and constitutional delay in growth and puberty (CDGP) account for the underlying aetiology of delayed puberty with overlapping clinical and hormonal features. The present study aims to evaluate the pubertal development and final height(FH) outcome in patients presenting with delayed puberty due to HH and CDGP. The hospital files of 1654 boys older than 14 years of age who were evaluated for delayed puberty between 01.01.2002 and 01.04.2022 in Hacettepe University İhsan Doğramacı Children’s Hospital Pediatric Endocrinology Department were reviewed retrospectively. 191 patients who met the inclusion criteria were included in the study. The mean age of admission was 14.6 ± 0.9 years. Of those, 149 patients had CDGP and 42 patients had HH. The mean FH-SDS of patients with HH (- 0.09 ± 1.0) was higher than those with CDGP (- 0.64 ± 0.91) (p = 0.003). In total, 118 out of 128 patients (92.2%) with CDGP and 36 out of 39 patients (92.3%) with HH had reached an FH consistent with their target height(TH). There was no statistically significant difference between the FH-SDS of patients with CDGP who received testosterone therapy for induction of puberty and those who did not receive (- 0.46 ± 0.97 SD vs. – 0.74 ± 0.87 SD; p = 0.094). Conclusion: Individuals presented with delayed puberty due to both CDGP and HH have reached an FH consistent with their TH to a large extent. Patients with HH had a higher presenting and final height than those with CDGP, which was attributed to the higher TH. Induction of puberty with testosterone in boys with CDGP seems not to have a clinically meaningful impact on the FH and long-term pubertal progression.

PMID:40789950 | DOI:10.1007/s00431-025-06374-4

Sci Rep. 2025 Aug 11;15(1):29376. doi: 10.1038/s41598-025-15057-x.

ABSTRACT

This study investigates emergent behaviors in multi-agent pursuit-evasion games within a bounded 2D grid world, where both pursuers and evaders employ multi-agent reinforcement learning (MARL) algorithms to develop adaptive strategies. We define six fundamental pursuit actions-flank, engage, ambush, drive, chase, and intercept-which combine to form 21 types of composite actions during two-pursuer coordination. After training with MARL algorithms, pursuers achieved a 99.9% success rate in 1,000 randomized pursuit-evasion trials, demonstrating the effectiveness of the learned strategies. To systematically identify and measure emergent behaviors, we propose a K-means-based clustering methodology that analyzes the trajectory evolution of both pursuers and evaders. By treating the full set of game trajectories as statistical samples, this approach enables the detection of distinct behavioral patterns and cooperative strategies. Through analysis, we uncover emergent behaviors such as lazy pursuit, where one pursuer minimizes effort while complementing the other’s actions, and serpentine movement, characterized by alternating drive and intercept actions. We identify four key cooperative pursuit strategies, statistically analyzing their occurrence frequency and corresponding trajectory characteristics: serpentine corner encirclement, stepwise corner approach, same-side edge confinement, and pincer flank attack. These findings provide significant insights into the mechanisms of behavioral emergence and the optimization of cooperative strategies in multi-agent games.

PMID:40789927 | DOI:10.1038/s41598-025-15057-x

Nat Genet. 2025 Aug 11. doi: 10.1038/s41588-025-02286-z. Online ahead of print.

ABSTRACT

Mixed-model association analysis (MMAA) is the preferred tool for performing genome-wide association studies. However, existing MMAA tools often have long runtimes and high memory requirements. Here we present LDAK-KVIK, an MMAA tool for analysis of quantitative and binary phenotypes. LDAK-KVIK is computationally efficient, requiring less than 10 CPU hours and 5 Gb memory to analyze genome-wide data for 350,000 individuals. Using simulated phenotypes, we show that LDAK-KVIK produces well-calibrated test statistics for both homogeneous and heterogeneous datasets. When applied to real phenotypes, LDAK-KVIK has the highest power among all tools considered. For example, across 40 quantitative UK Biobank phenotypes (average sample size 349,000), LDAK-KVIK finds 16% more independent, genome-wide significant loci than classical linear regression, whereas BOLT-LMM and REGENIE find 15% and 11% more, respectively. LDAK-KVIK can also be used to perform gene-based tests; across the 40 quantitative UK Biobank phenotypes, LDAK-KVIK finds 18% more significant genes than the leading existing tool. Last, LDAK-KVIK produces state-of-the-art polygenic scores.

PMID:40789918 | DOI:10.1038/s41588-025-02286-z

Npj Ment Health Res. 2025 Aug 11;4(1):37. doi: 10.1038/s44184-025-00150-w.

ABSTRACT

The aim was to assess the effectiveness of an intervention comprising a teacher-training program and the implementation of a ten-session mindfulness-based intervention (MBI) in regular classroom teaching for 16- to 24-year-old students in Denmark. In a cluster-randomized trial (2019-2021), upper secondary schools and vocational schools for social and health care were randomly assigned 1:1 to receive the intervention (21 schools, 35 teachers, 438 students) or teaching-as-usual (22 schools, 38 teachers, 551 students). Eighteen self-report measures of mental health were collected at baseline, three, and six months, with the Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) as the primary outcome. Intention-to-treat analyses were conducted using mixed-effects linear regression and bootstrapping. Fourteen intervention schools (n = 277) and 17 teaching-as-usual schools (n = 419) provided follow-up data. No statistically significant effect on the primary outcome (SWEMWBS) was found in the total population. However, a small positive effect on SWEMWBS was observed among females in upper secondary schools at three months, but not sustained at six months. Trial Registration: ClinicalTrials.gov Identifier: NCT04610333, registered October 26, 2020, https://clinicaltrials.gov/ct2/results?cond=&term=NCT04610333&cntry=&state=&city=&dist= .

PMID:40789917 | DOI:10.1038/s44184-025-00150-w

Sci Rep. 2025 Aug 11;15(1):29439. doi: 10.1038/s41598-025-14784-5.

ABSTRACT

With the rapid growth in the exchange of digital data, the problem of protecting images has become essential, particularly in sectors such as medicine, surveillance and secure communications. Traditional encryption techniques, such as DES, AES and RSA, are effective for text, but often ineffective for images, due to high redundancy and high correlation between pixels. We suggest a novel image encryption algorithm based on chaotic maps and the variable-step Josephus problem to get over these restrictions and increase the encryption resilience. This algorithm uses Kepler Chaotic Optimisation Algorithm (CKOA) to select the most suitable chaotic maps, guaranteeing optimal diffusion and complex pixel confusion. Key generation is enhanced with MD5 and SHA-256 hash functions, providing increased resistance to collisions and attacks. In addition, Discrete Wavelet Transform (DWT) is integrated to compress images and reduce processing time, while maintaining a high average entropy of 7.999 for encrypted images. Experimental tests demonstrate strong resistance against cryptographic attacks, including 99.6% as pixel change rate and 33.31% as unified average change intensity, ensuring optimum security. Compared with other image-based encryption schemes, our method stands out for its speed and reduced computational complexity, while offering superior security.

PMID:40789914 | DOI:10.1038/s41598-025-14784-5

Sci Rep. 2025 Aug 11;15(1):29420. doi: 10.1038/s41598-025-15388-9.

ABSTRACT

Early prediction of academic performance is vital for reducing attrition in online higher education. However, existing models often lack comprehensive data integration and comparison with state-of-the-art techniques. This study, which involved 2,225 engineering students at a public university in Ecuador, addressed these gaps. The objective was to develop a robust predictive framework by integrating Moodle interactions, academic history, and demographic data using SMOTE for class balancing. The methodology involved a comparative evaluation of seven base learners, including traditional algorithms, Random Forest, and gradient boosting ensembles (XGBoost, LightGBM), and a final stacking model, all validated using a 5-fold stratified cross-validation. While the LightGBM model emerged as the best-performing base model (Area Under the Curve (AUC) = 0.953, F1 = 0.950), the stacking ensemble (AUC = 0.835) did not offer a significant performance improvement and showed considerable instability. SHAP analysis confirmed that early grades were the most influential predictors across top models. The final model demonstrated strong fairness across gender, ethnicity, and socioeconomic status (consistency = 0.907). These findings enable institutions to identify at-risk students using state-of-the-art interpretable and fair models. These findings enable institutions to identify at-risk students using state-of-the-art, interpretable, and fair models, advancing learning analytics by validating key success predictors against contemporary benchmarks.

PMID:40789907 | DOI:10.1038/s41598-025-15388-9

Clin Nutr. 2025 Aug 5;52:215-224. doi: 10.1016/j.clnu.2025.07.034. Online ahead of print.

ABSTRACT

BACKGROUND & AIMS: Anorexia nervosa (AN) is a severe eating disorder with significant somatic complications, potentially involving an altered intestinal barrier. Prior studies yielded heterogeneous results, ranging from decreased to increased intestinal permeability in AN. This study aimed to assess intestinal permeability in adolescent patients with AN by comparing serum markers Zonulin, Lipopolysaccharide-binding protein (LBP), and intestinal Fatty acid-binding protein (iFABP) with healthy controls (HC) over time.

METHODS: We conducted a longitudinal study on 60 female adolescent patients with AN and 36 age-matched HC. Blood samples were collected at admission to inpatient treatment, at discharge, and at a one-year follow-up. Zonulin, LBP, iFABP and inflammation marker Interleukin 6 levels were measured alongside clinical parameters. Linear mixed models were applied to assess group differences and longitudinal changes. Pearson correlations were used to explore clinical associations.

RESULTS: Zonulin levels were significantly decreased in the AN group at admission and again at the follow-up compared to HC. LBP levels were consistently reduced in AN across all three time points. These alterations thus persisted despite weight recovery. No significant differences were observed in iFABP levels between the groups or over time. Zonulin and LBP positively correlated with Interleukin 6, linking gut permeability to inflammatory processes.

CONCLUSION: Decreased Zonulin and LBP levels suggest reduced paracellular intestinal permeability in adolescent AN while transcellular permeability (iFABP) appears to be rather unaffected. The persistence of these alterations despite weight recovery suggests that reduced intestinal permeability may be a trait rather than a state marker in AN. Our findings challenge the concept of a “leaky gut” in adolescent AN.This highlights the need for further research on the intestinal barrier in AN, while also integrating the role of nutritional intake, gut microbiome interaction and immune reactions, to support the development of gut-targeted therapies.

PMID:40789230 | DOI:10.1016/j.clnu.2025.07.034

Poult Sci. 2025 Jul 23;104(10):105596. doi: 10.1016/j.psj.2025.105596. Online ahead of print.

ABSTRACT

Poultry farming in Gujarat faces persistent challenges from infectious diseases, foodborne pathogens, and the growing threat of antimicrobial resistance (AMR), necessitating the adoption of stringent biosecurity measures encompassing isolation, traffic control, and sanitation. The study aimed to evaluate the knowledge and effectiveness of biosecurity practices among line supervisors involved in contractual commercial broiler farming in Gujarat. This study evaluated the socio-economic characteristics and biosecurity knowledge of 33 line supervisors through a one-day capacity-building training program. Pre- and post-training assessments, including structured questionnaires and Likert scales, were analyzed using descriptive statistics, and Factor Analysis of Mixed Data (FAMD) in R (v4.0.2). Results revealed that most participants were young (mean age 33.94), married males with higher secondary or graduate education and over a decade of poultry farming experience. Post-training evaluations showed a significant improvement in biosecurity knowledge and practices, with 75.76 % rating the training as excellent and was recognized as useful by 90.91 % of respondents. Furthermore, for the non-implementation of comprehensive biosecurity measures by the farmers, lack of awareness was the major attribute given by line supervisors (57.58 %) for the farmers, followed by inadequate control (51.52 %) and insufficient knowledge (48.48 %). Additionally, FAMD identified 76 epidemiological points across breeding farms, commercial broiler farms, and markets, offering insights into zoonotic risk and poultry distribution network (PDN) structure. The findings investigated the need for structured training and advisory support, along with government-led financial incentives, to strengthen biosecurity implementation in poultry systems.

PMID:40789226 | DOI:10.1016/j.psj.2025.105596

J Proteome Res. 2025 Aug 11. doi: 10.1021/acs.jproteome.4c01114. Online ahead of print.

ABSTRACT

Motivated by the lack of adequate tools to perform pathway enrichment analysis, this work presents an approach specifically tailored to SomaScan data. Starting from annotated gene sets, we developed a greedy, top-down procedure to iteratively identify strongly intracorrelated SOMAmer modules, termed “SomaModules”, based on 11K SomaScan data. We generated two repositories based on the latest MSigDB and MitoCarta releases, containing more than 40,000 SOMAmer-based gene sets combined. These repositories can be utilized by any unstructured pathway enrichment analysis tool. We validated our results with two case examples: (i) Alzheimer’s disease specific pathways in a 7K SomaScan case-control study, and (ii) mitochondrial pathways using 11K SomaScan data linked to physical performance outcomes. Using gene set enrichment analysis (GSEA), we found that, in both examples, SomaModules had significantly higher enrichment than the original gene set counterparts. These findings were robust and not significantly affected by the choice of enrichment metric or the Kolmogorov enrichment statistic used in the GSEA procedure. We provide users with access to all code, documentation and data needed to reproduce our current repositories, which also will enable them to leverage our framework to analyze SomaModules derived from other sources, including custom, user-generated gene sets.

PMID:40789203 | DOI:10.1021/acs.jproteome.4c01114