Tag: nevin manimala

Sci Rep. 2025 Sep 26;15(1):33092. doi: 10.1038/s41598-025-16712-z.

ABSTRACT

With the promotion of AI applications, people have undergone various changes, especially high school students who have a strong sense of engagement in AI-related activities. In order to explore the interactive mechanism and influencing factors between AI literacy and computing thinking level of high school students in H city, this study focuses on the relationship between student background, AI literacy, and computational thinking. By conducting a questionnaire survey of hundreds of high school students and using SPSS for descriptive statistics, analysis of variance, and correlation analysis, the focus is on exploring the impact and interrelationships between the three dimensions of AI literacy and the five dimensions of computational thinking. A structural equation model (SEM) was constructed by using AMOS software to further explore its internal complex correlation relationship. The results show that parental education and daily use of AI tools significantly affect students’ AI knowledge and skills, while factors such as gender and family location have different degrees of positive or negative effects on creativity, algorithmic thinking, and critical thinking. In addition, artificial intelligence literacy is moderately positively correlated with some dimensions of computational thinking. This study provides empirical support for the rational planning of AI courses in the basic education stage, strengthening the cultivation of students’ computational thinking and optimizing teaching practice.

PMID:41006537 | DOI:10.1038/s41598-025-16712-z

Sci Rep. 2025 Sep 26;15(1):33277. doi: 10.1038/s41598-025-18925-8.

ABSTRACT

Protein glycation is crucial in the pathogenesis of diabetes and its cardiovascular complications. Little is known about the antiglycation properties of amlodipine, a long-acting calcium channel blocker used to treat high blood pressure. In our study, amlodipine’s antiglycoxidant activity was assayed in sugars (glucose, fructose, and ribose), aldehydes (glyoxal), and chloramine T-modified bovine serum albumin (BSA). Aminoguanidine and N-acetylcysteine were used as standard glycation/oxidation inhibitors. The content of oxidation, glycoxidation, and glycation protein products was measured colorimetrically and fluorimetrically. A one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was used for statistical analysis. The mechanism of amlodipine’s antiglycoxidant activity was also evaluated using in-silico molecular docking. Amlodipine protects against BSA oxidation, as evidenced by enhanced total thiol content and mitigated protein carbonyls/advanced oxidation protein products. Amlodipine also increased the fluorescence of tryptophan and decreased the contents of kynurenine, N-formylkynurenine, and dityrosine. In addition, amlodipine effectively prevents protein glycation, as evidenced by a reduction in amyloid-beta structure, Amadori products, and advanced glycation end products (AGEs). In in silico analysis, amlodipine’s antiglycation properties were indicated during its interaction with BSA, glycosidases, and AGEs/receptor for AGEs (RAGE) pathway proteins. Among all proteins, amlodipine docked best with c-Jun N-terminal kinases. Summarizing, we have demonstrated the anti-glycation and antioxidant activity of amlodipine in vitro. This effect may be particularly important in patients with diabetes and atherosclerosis, where excessive glycation accelerates the development of vascular complications. Further studies are needed to confirm the antidiabetic activity of amlodipine in vivo.

PMID:41006534 | DOI:10.1038/s41598-025-18925-8

Sci Rep. 2025 Sep 26;15(1):32972. doi: 10.1038/s41598-025-17303-8.

ABSTRACT

Brain metastases occur in 20-30% of patients with malignant tumors. While stereotactic radiosurgery (SRS) offers an effective treatment option for limited brain metastases, managing symptomatic patients with multiple metastases remains challenging due to prolonged treatment times and potential neurological complications. The dynamic conformal arc (DCA) SRS technique using a single-isocenter multi-target (DCA-SIMT) approach facilitates efficient treatment of numerous lesions. This study evaluates survival outcomes and symptom control in patients treated with DCA-SIMT SRS for multiple brain metastases. A registry based analysis was conducted on 123 patients with 560 metastatic CNS lesions treated with DCA-SIMT SRS at the Franciszek Lukaszczyk Oncology Center, Poland, between August 2018 and September 2020. The median survival time was 7.17 months. Patients were assessed for survival, local control, and treatment-related symptoms. Statistical analyses included Cox regression and Kaplan-Meier survival analysis. The 6-month and 12-month survival rates were 57% and 29%, respectively. Local control was achieved in 93% of lesions. The total planning target volume (PTV) was a significant prognostic factor (p = 0.008), with an increase in PTV associated with decreased survival. Patients with PTV ≤ 10 cm³ had significantly longer survival (p = 0.007). Histopathological subtype also influenced outcomes, with sqamous non-small cell lung cancer associated with poorer survival (p = 0.003). Neurological symptoms stabilized or improved in 61% of patients post-treatment, despite a median global V12 of 11.6 cm³, which was not associated with increased toxicity. DCA-SIMT SRS is a viable option for symptomatic patients with multiple brain metastases, offering rapid, precise treatment with significant clinical benefits.

PMID:41006529 | DOI:10.1038/s41598-025-17303-8

Sci Rep. 2025 Sep 26;15(1):33216. doi: 10.1038/s41598-025-17866-6.

ABSTRACT

The SPUR tool measures the risk of non-adherence for patients with chronic disease, as well as measuring the relative importance of thirteen behavioral drivers contributing to that risk. Over a period of four years, five different cohorts of patients in three countries and three different pathologies were studied to contribute to the elaboration and refinement of two patient-reported adherence measures: SPUR 6 and SPUR 24. This article examines the results of retrofitting of both of these tools to earlier patient cohorts as well as analyzing the pooled dataset via the use of both tools in order to further study the predictive potential of both. A further analysis was carried out using structural equation modeling both to test the structural validity of the SPUR tools and to examine both indirect and direct influence of the thirteen drivers on patient behavior.Direct comparisons of the SPUR tools to other patient-reported adherence measures across datasets and across the pooled dataset was carried out by analysis of Spearman’s ranked correlation coefficients. The structural equation modeling was carried out using path analysis based on the decision-making schema hypothesized in the foundational SPUR article.The retrofitted analysis and the pooled data analysis both support the use of SPUR 6 and SPUR 24 to assess the risk of non-adherence of patients with chronic disease with respect to other widely used patient reported adherence measures. The structural equation modeling reinforced the hypothesis that the social and psychological drivers of SPUR have a significant indirect impact on non-adherence risk via the rational and usage drivers as well as their direct impact on non-adherence risk.SPUR 6 and SPUR 24 have demonstrated predictive value in assessing the risk of patient non-adherence as compared to their predecessors as well as to other widely-used patient adherence measures, across countries and pathologies. The social and psychological drivers of SPUR seem to drive behavior largely through their influence on rational and usage factors, indicating a cognitive rationalization process . These insights have direct implications for communication strategy towards patients in efforts to enhance medication adherence.

PMID:41006489 | DOI:10.1038/s41598-025-17866-6

Sci Rep. 2025 Sep 26;15(1):33088. doi: 10.1038/s41598-025-17657-z.

ABSTRACT

This study investigates the relationship between dietary patterns and psoriasis severity using advanced machine learning (ML) techniques. The dataset, comprising 37 features including demographic, clinical and dietary features from 142 Thai psoriasis patients, exhibits moderately high dimensionality typical of clinical studies. To address limitations posed by the small sample size, a hybrid resampling strategy integrating bootstrapping with K-fold Cross-Validation (CV) was implemented. Using Random Forest (RF) and eXtreme Gradient Boosting (XGB), a total of 60 classification models were evaluated by varying train/test splits and applying multiple feature selection methods, including Least Absolute Shrinkage and Selection Operator (LASSO), Mean Decrease Accuracy (MDA), and Mean Decrease Impurity (MDI). Although bootstrapping alone sometimes resulted in overfitting, its combination with K-fold CV improved generalizability. In optimal configurations, both RF and XGB achieved sensitivity, specificity, and F1-scores exceeding 90%, alongside area under the curve (AUC) values above 95%. SHapley Additive exPlanations (SHAP) analysis revealed key dietary factors associated with increased psoriasis severity, including high-sodium foods, processed meats, alcohol, red meats, fermented products, and dark-colored vegetables. Clinically, prioritizing weight management is essential, as Body Mass Index (BMI) arose as the strongest feature of psoriasis severity. Dietary triggers identified in this study should inform comprehensive care plans. Popular Thai cuisines, especially Tom Yum Kung emerged as a potentially suitable option, while Som Tum, Pad Thai, Moo Kratha, and Khao Niao Mamuang were identified as potential triggers when consumed excessively. These findings highlight the importance of dietary moderation and personalized guidance, supporting health literacy, patient management, and smart healthcare innovations in Thailand.

PMID:41006473 | DOI:10.1038/s41598-025-17657-z

Sci Rep. 2025 Sep 26;15(1):33202. doi: 10.1038/s41598-025-17413-3.

ABSTRACT

This study aimed to investigate the biological properties of probiotic and synbiotic Lactobacillus gasseri SM 05 (L. gasseri) and Lactobacillus casei subsp. casei (L. casei) in the black raspberry (BR) matrix. A distinctive aspect of this research was its assessment of both fermented and non-fermented raspberry juices as active components in chitosan-based edible coatings, supplemented by coconut sap at concentrations of 5% and 10%, along with the application of high hydrostatic pressure (HHP) processing. These interventions were evaluated for their synergistic potential in enhancing the antioxidant capacity of coatings applied to Lates calcarifer (barramundi) fillets. What distinguishes this study from prior works is the integration of cutting-edge HHP technology, the deliberate exclusion of essential oils and synthetic preservatives, and the novel incorporation of coconut sap across coating formulations. Experimental outcomes revealed that synbiotic formulations-specifically L. gasseri combined with Oligofructose-Enriched Inulin (LG-OEI) and L. casei with OEI (LC-OEI)-exerted the most pronounced bioactivity. The key findings underscore the efficacy of Oligofructose-Enriched Inulin in promoting lactic acid bacterial metabolism and metabolite production within fruit juice substrates. Additionally, the deployment of 10% coconut sap in conjunction with HHP treatment-rather than conventional VAT pasteurization-yielded superior coating performance, effectively preserving the quality of fish samples over a 15-day period. In conclusion, the LG-OEI formulation, when used in chitosan coatings augmented with 10% coconut sap and processed via HHP, demonstrated the highest preservation efficacy.

PMID:41006467 | DOI:10.1038/s41598-025-17413-3

Sci Rep. 2025 Sep 26;15(1):33102. doi: 10.1038/s41598-025-17008-y.

ABSTRACT

This study presents a forensic diagnostic framework aimed at enhancing the early detection, fault classification and remaining useful life (RUL) prediction of rolling bearing failures. The proposed network integrates a novel three-stage machine learning formulation – (1) identification of health state using voting ensemble, (2) prognostic analysis via a hybrid convolutional neural network and gated recurrent unit (CNN-GRU), and (3) fault type identification through the segment anything model (SAM) based on time-frequency representations. The ensemble and CNN-GRU models are trained on both time- and frequency-domain features from vibration signals, while SAM leverages this data in visual sense through iterative masking for zero-shot spatial-temporal fault segmentation. Pre-processing techniques, including piecewise aggregate approximation and singular spectrum analysis, are used to denoise and compress the vibration response without impacting key statistical traits. The proposed e-CNN-GRU-SAM network demonstrates better accuracy in diagnosing fault types, predicting RUL and identifying root causes under different operational conditions. This is established using diverse operating benchmark datasets that simulate induced and real-world degradation scenarios for generalization. Thus, the proposed framework offers a comprehensive forensic analysis toolkit for diagnosis and prognosis of bearings.

PMID:41006465 | DOI:10.1038/s41598-025-17008-y

Sci Rep. 2025 Sep 26;15(1):32952. doi: 10.1038/s41598-025-09011-0.

ABSTRACT

This cross-sectional observational study involved 1052 non-pregnant women aged 18-65 who had undergone TCC and sought care at a tertiary-level gynecology clinic. We documented participants’ medical histories, Pap smear results, and TCC histories. Pap smear results were analyzed using the 2014 Bethesda classification, and obstetric outcomes, including pregnancies, deliveries, miscarriages, and preterm births (PTD), were evaluated. Data analysis was performed using SPSS 22.0, with statistical significance set at p < 0.05. This cross-sectional observational study involved 1052 non-pregnant women aged 18-65 who had undergone TCC and sought care at a tertiary-level gynecology clinic. We documented participants’ medical histories, Pap smear results, and TCC histories. Pap smear results were analyzed using the 2014 Bethesda classification, and obstetric outcomes, including pregnancies, deliveries, miscarriages, and preterm births (PTD), were evaluated. Data analysis was performed using SPSS 22.0, with statistical significance set at p < 0.05. The mean age of participants was 34.4 ± 7.4 years. Abnormal Pap smear results were observed in 11.5% of patients, with a higher prevalence (29.9%) among those who underwent TCC within the last year. The frequency of TCC was inversely related to the rate of abnormal smear results (p < 0.005). However, frequent TCC procedures were associated with significantly increased rates of abortion (18.9%) and PTD (10.3%) (both p < 0.005). While the time elapsed since the last TCC procedure influenced abortion and PTD rates, both were statistically significant (p = 0.016 and p = 0.029, respectively). TCC is associated with a higher incidence of cervical abnormalities and adverse pregnancy outcomes, particularly when performed more frequently. These findings suggest a potential link between TCC and disruptions in cervical health, which may increase the risk of pregnancy complications, underscoring the need for cautious use and further research. Educating communities about the potential risks and advocating for safer medical practices are crucial steps towards improving gynecological and obstetric care in regions where TCC is still prevalent.

PMID:41006449 | DOI:10.1038/s41598-025-09011-0

Sci Rep. 2025 Sep 26;15(1):33015. doi: 10.1038/s41598-025-18500-1.

ABSTRACT

In this study, the biochemical and cytogenetic toxicity induced by the antibiotic active ingredient ornidazole in the non-target organism Allium cepa L. was investigated. In the toxicity assessment, the level of malondialdehyde (MDA), a biochemical marker of lipid peroxidation; genotoxicity indicators such as micronucleus (MN) frequency and mitotic index (MI); the incidence of chromosomal abnormalities (CAs); activities of antioxidant defense enzymes catalase (CAT) and superoxide dismutase (SOD); and the levels of chlorophyll a and b pigments reflecting photosynthetic capacity were analyzed. Additionally, DNA damage was assessed using the Comet test method, and the interaction of ornidazole with macromolecules-particularly DNA-was examined using the molecular docking approach. Four groups of A. cepa bulbs-one control and three treatments-were created. Three distinct dosages (0.0179, 0.0357 and 0.0714 mg/L) of ornidazole were used to germinate the bulbs in the treatment group, while tap water was used to germinate the bulbs in the control group. Following germination, samples from the roots and leaves were gathered and ready for examination. As a result, there was no cytogenetic damage or biochemical alteration that was statistically significant (p > 0.05) in the control group (Group I). MI value, DNA, and chlorophyll levels significantly (p < 0.05) decreased with ornidazole treatment, while MN frequency, CAs, MDA levels, SOD, and CAT activities significantly (p < 0.05) increased. At the ornidazole dosage of 0.0714 mg/L, these rises and declines were shown to be more noticeable. Ornidazole promoted several CAs in root meristem cells, the most common being the sticky chromosome. DNA damage was highlighted by the comet assay results, which indicated a drop in head DNA and an increase in tail DNA. In the control group, the Tail DNA was 1.00 ± 1.05 (%), whereas in the group treated with 0.0714 mg/L ornidazole, it increased to 72.0 ± 1.63 (5), indicating high DNA fragmentation. Molecular docking results showed ornidazole-DNA, ornidazole-tubulin, ornidazole-topoisomerase, ornidazole-glutamate-1-semialdehyde aminotransferase and ornidazole-protochlorophyllide reductase interaction supporting the biochemical and cytogenetic toxicity results. In conclusion, ornidazole exposure induced significant toxic effects in the non-target organism Allium cepa. The study further validated the efficacy of the Allium test as a reliable bioassay for detecting such toxicity. These findings underscore the urgent need for implementing appropriate environmental management strategies to mitigate pharmaceutical contamination and protect non-target organisms from drug-induced toxicity.

PMID:41006444 | DOI:10.1038/s41598-025-18500-1

Sci Rep. 2025 Sep 26;15(1):33276. doi: 10.1038/s41598-025-18097-5.

ABSTRACT

Minimizing ionizing radiation is crucial in paediatric imaging due to children’s increased radiation sensitivity, especially at younger ages. To evaluate a CT attenuation-based Auto Prescription protocol for paediatric head imaging, testing whether it provides image quality and radiation dose comparable to age-based protocols. Auto Prescription was implemented on a 256-slice scanner for axial volumetric head CT, adjusting kV and mAs based on attenuation data from scout images. Radiation dose parameters (CTDIvol, SSDE, ED, DLP) and image quality metrics (SNR, CNR, subjective Likert scale from 1-unacceptable to 4-higher than needed) were assessed in 79 consecutive studies using Auto Prescription protocols. These were compared to 68 studies obtained with age-based protocols using non-parametric tests. A total of 147 patients (60 females, mean age 6.7 ± 5.1 years) were included. The auto prescription group included 29 patients aged 0-5, 20 aged 5-10, 25 aged 10-15, and 5 over 15 years; the age-based group included 36, 18, 9, and 5 patients respectively in the same age groups. The Auto Prescription protocol achieved a more balanced radiation dose distribution across age and water-equivalent diameter. The greatest dose reduction was observed in the 0-1 year (48.2%, p < 0.001) and 10-15 year (40.4%, p < 0.001) age groups. While diagnostic image quality was adequate in both settings, it was lower with the auto prescription protocols (mean image quality 3.0 ± 0.2 versus 2.8 ± 0.2; SNR 7.2 ± 1.5 vs. 5.1 ± 1.1; CNR 0.9 ± 0.5 vs. 0.7 ± 0.2; all p < 0.001). All subjective image quality parameters were statistically non-inferior to the age- based protocol (p < 0.05). Attenuation-based Auto Prescription resulted in a more homogeneous and head density adapted radiation dose across paediatric patients, with non-inferior image quality. Dose reduction was a secondary benefit of individualized scan settings based on patient attenuation rather than age alone.

PMID:41006436 | DOI:10.1038/s41598-025-18097-5