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Nevin Manimala Statistics

Differences in different reconstruction algorithms for coronary CTA demonstrating pericoronary adipose tissue attenuation

Sci Rep. 2025 Dec 29;15(1):44876. doi: 10.1038/s41598-025-28914-6.

ABSTRACT

The Fat Attenuation Index (FAI) surrounding the coronary arteries, a sensitive biomarker for coronary inflammation, can be measured through standard Coronary Computed Tomography Angiography (CCTA). The aim of this study is to evaluate the differences in FAI as displayed on CCTA using three different reconstruction algorithms: high-level Deep Learning Image Reconstruction (DLIR-H), adaptive statistical iterative reconstruction-Veo at a level of 50% (ASiR-V50%), and Filtered Back Projection (FBP). Based on the presence or absence of plaque, the population was divided into the following groups: normal, no plaque, non-calcified plaque, mixed plaque, and calcified plaque. Each group was then further analysed according to the reconstruction algorithm, with three subgroups for each: DLIR-H, ASiR-V50%, and FBP. Attenuation values for pericardial adipose tissue, image noise, and the Fat Attenuation Index (FAI) of the three proximal coronary arteries were measured and evaluated for each of the three reconstruction algorithms. The attenuation values of pericardial adipose tissue measured by the three algorithms were not statistically different. However, the FAI measured by DLIR-H was the highest, followed by ASiR-V50%, with FBP yielding the lowest value; all differences were statistically significant. Meanwhile, DLIR-H demonstrated the strongest ability to reduce image noise, whereas FBP showed the weakest ability to do so. FAI varies significantly depending on the algorithm used. Therefore, standardised reconstruction protocols are essential in multicentre and longitudinal studies to ensure accurate, reproducible, and comparable FAI results.

PMID:41461810 | DOI:10.1038/s41598-025-28914-6

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Nevin Manimala Statistics

Factors associated with male involvement in postpartum reversible contraceptive use in Shebedino Woreda, Southern Ethiopia

Sci Rep. 2025 Dec 29;15(1):44824. doi: 10.1038/s41598-025-29227-4.

ABSTRACT

Background Men’s participation in long-acting reversible contraceptives during the postpartum period is a determinant of reproductive health outcomes and for achieving national and sustainable development goals. Most research findings on male participation in family planning are concerned with short-acting family planning in Africa, including Ethiopia. Despite this, little is known about male involvement in postpartum long-acting reversible contraceptive use of their wife in Africa, particularly in Ethiopia. Objective To assess the magnitude of male involvement in postpartum long-acting reversible contraceptive use and association factors among married males in Shebedinno woreda, Sidama regional state, Southern Ethiopia, 2023. Methods A community-based cross-sectional study was conducted among 633 randomly selected married men from July 30 to August 30, 2023. Data were collected using pretested, questionnaires. Bivariable and multivariable logistic regression analyses were conducted. Multicollinearity and model fitness were examined. The crude and adjusted odds ratios, together with their corresponding 95% confidence intervals, were computed. A P-value < 0.05 was considered a level of statistical significance. Result A total of 623 married men responded to the questionnaires, yielding a response rate of 98.4%. Out of these, 197 (31.6%, 95% CI: 28.6, 36.0) participants were involved in postpartum long-acting reversible contraceptive use. Men with a secondary school education (AOR = 2.35, 95% CI: 1.12, 4.93) and those with a diploma or higher education (AOR = 4.42, 95% CI: 1.80, 10.83), heard information about long-acting reversible contraceptives (AOR = 2.77, 95% CI: 1.07, 7.16), having good knowledge (AOR = 1.84, 95% CI: 1.24, 2.74) and a positive attitude towards the use of postpartum long-acting reversible contraceptives (AOR = 2.18, 95% CI: 1.47, 3.24) all proved to be positive significant factors. Conclusion and recommendations Overall, men’s participation in postpartum long-acting reversible contraceptive use of their spouse was relatively low. Therefore, promoting male participation in postpartum long-acting reversible contraceptives requires effective community awareness, dissemination of information, education, and communication, and fostering a positive attitude towards long-acting reversible contraceptives.

PMID:41461797 | DOI:10.1038/s41598-025-29227-4

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Nevin Manimala Statistics

Effectiveness of an educational intervention based on the common-sense model of self-regulation for lung cancer patients after thoracoscopic surgery

Sci Rep. 2025 Dec 29;15(1):44833. doi: 10.1038/s41598-025-29106-y.

ABSTRACT

This study constructed an educational intervention based on the common-sense model of self-regulation for lung cancer patients after thoracoscopic surgery and evaluated the effects of the educational intervention. From July 2023 to January 2024, ninety patients with lung cancer after initial thoracoscopic surgery were divided into an intervention group (N = 45) and a control group (N = 45). Patients in the intervention group received a nursing intervention based on the common-sense model of self-regulation. Patients in the control group received usual care. The intervention group received face-to-face and telephone counselling for 4 weeks, and they had a manual. Pulmonary exercise compliance, frailty, and illness perception were assessed before and after the intervention. After the implementation of the nursing intervention based on the common-sense model of self-regulation, there were statistically significant differences in lung function exercise compliance scores and illness perception scores between the intervention group and the control group, but there was no statistically significant difference in frailty scores between the two groups after the intervention. This educational intervention is effective for the rehabilitation behaviour of lung cancer patients following thoracoscopic surgery. Clinical trial registration: This study has been registered in the Chinese Clinical Trial Registry through this website www.chictr.org.cn , and the registration number is ChiCTR2400087033. The first registration date was 17 July 2024.

PMID:41461796 | DOI:10.1038/s41598-025-29106-y

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Nevin Manimala Statistics

Acute Finnish sauna heating and cold water immersion effects on cardiovascular dynamic response in normotensive women

Sci Rep. 2025 Dec 29;15(1):44881. doi: 10.1038/s41598-025-29035-w.

ABSTRACT

The study aims to evaluate the acute effects of sauna heating and cold immersion on cardiovascular dynamic response in normotensive women. Twenty-eight healthy females underwent a sauna protocol comprising three consecutive 10-min exposures, each separated by a 10-min cooling interval. Blood pressure and heart rate (HR) were measured immediately after leaving the sauna room and in the last minute of the cooling period. Three acute responses after heating in the sauna and three cooling responses had a statistically significant effect on SBP (systolic blood pressure) (p < 0.001), DBP (diastolic blood pressure) (p < 0.001), and HR (p < 0.001). SBP was significantly higher in the first heating session compared to the baseline measurement, while DBP was significantly lower. HR was significantly higher in all three heating sessions compared to the baseline measurement (p < 0.001). Progression analysis revealed a decreasing trend in SBP across heating sessions, whereas no significant trend was observed during cooling sessions. DBP and HR remained stable across heating and cooling cycles. SBP shows high sensitivity to repeated sauna stress, suggesting adaptive cardiovascular effects. However, it is still a preliminary study in young, healthy women, and in the future, more longitudinal studies are needed to identify cardiovascular responses in different age and sex groups, as well as the impact of sauna cycles on individuals with coexisting cardiovascular diseases.

PMID:41461792 | DOI:10.1038/s41598-025-29035-w

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Spatiotemporal trends and machine learning-based prediction of temperature variability during the T. Aman rice-growing season in Bangladesh

Sci Rep. 2025 Dec 29;15(1):44883. doi: 10.1038/s41598-025-28804-x.

ABSTRACT

Climate change poses significant risks to food security, especially in agriculture-dependent countries like Bangladesh. This study analyzes temperature trends from 1961 to 2023 using data from the Bangladesh Meteorological Department (BMD) across three climatic regions: Barind, Coastal, and Haor. The Mann-Kendall test revealed statistically significant warming trends in both maximum and minimum temperatures, with the most pronounced increase in the Haor region. Moran’s analysis detected clear spatial clustering of high-risk zones, with Barind districts facing severe maximum temperature risks (> 40 °C) and Sylhet showing heightened minimum temperature risks. The MLP model achieved the lowest errors across ecosystems, with MSEs of 0.82 (Barind), 1.47 (Coastal), and 1.50 (Haor) for maximum temperature and with MSEs of 0.48 (Barind), 0.44 (Coastal), and 0.48 (Haor) for minimum temperature, outperforming SVM, CNN, LSTM, ANN, RF, and Ensemble models. This is the first region-specific application of machine learning models along with Mann-Kendall trend analysis, Moran’s I spatial statistics for rice production in Bangladesh which provides a multidimensional framework that is rarely applied in Bangladesh. These findings underscore the urgent need for region-specific climate adaptation strategies, as rising temperatures threaten rice production and agricultural resilience.

PMID:41461780 | DOI:10.1038/s41598-025-28804-x

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Automatic classification of uveal melanoma response patterns following ruthenium-106 plaque brachytherapy using ultrasound images and deep convolutional neural network

Sci Rep. 2025 Dec 29;15(1):44835. doi: 10.1038/s41598-025-28995-3.

ABSTRACT

Following uveal melanoma (UM) affected treatment using ruthenium-106 brachytherapy, tumor thickness patterns fall into one of four categories: decrease (regression), increase (recurrence), stop (stable), or other, which are assessed in follow-up A-mode and B-mode images. These patterns are critical indicators of the tumor’s response to therapy. This study aims to apply deep learning (DL) models for predicting post-brachytherapy tumor response patterns. A cohort of 192 patients participated in this study. B-Mode images taken at the time of diagnosis were collected, and the ophthalmologists labeled the images into four response patterns based on the results of the treatment. DenseNet121 and ResNet34 models were trained and evaluated using performance metrics. DenseNet121 achieved a macro-average AUC of 0.933 (0.95% CI [0.905-0.957]), compared to 0.916 (95%CI [0.884-0.945]) for the ResNet34. The per-class evaluation showed that DenseNet121 excelled in predicting all categories, providing superior predictive accuracy. This difference in classification performance was statistically significant based on the DeLong test (p < 0.05). The ablation study revealed that the best performance was achieved without pretrained weights, using dropout layers and a batch size of 32. Both models demonstrated strong classification capabilities, with DenseNet121 providing the highest overall accuracy. This study highlights the potential of DL models in predicting response patterns in UM patients undergoing brachytherapy. Further validation and exploration of their integration into clinical practice are warranted.

PMID:41461779 | DOI:10.1038/s41598-025-28995-3

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Nevin Manimala Statistics

Causal machine learning uncovers conditions for convective intensification driven by organic and sulfate aerosols

Sci Rep. 2025 Dec 29;15(1):44806. doi: 10.1038/s41598-025-28939-x.

ABSTRACT

Aerosols are often hypothesized to invigorate deep convective clouds (DCCs), but observational evidence remains limited and inconclusive. Clarifying this hypothesis is critical for regions vulnerable to thunderstorms and flooding, particularly highly polluted coastal cities. Leveraging a novel causal discovery-inference pipeline and high-resolution observations near Houston, TX, we identify multiple causal pathways among aerosols (mostly organic and sulfate), DCCs, and meteorological factors. However, a direct causal link from aerosols to DCCs is found to be uncommon, occurring in less than 35% of analyzed scenarios, and is characterized by strong conditionality and nonlinearity. When aerosol impacts on DCCs do occur, they can be substantial, enhancing DCC core heights by approximately 1.7 km, with 92% of this effect concentrated in warmer-phase cloud regions. Notably, the presence of sea breezes and the inclusion of all measured aerosol particles each enhance DCCs in over 95% of aerosol-sensitive cases.

PMID:41461776 | DOI:10.1038/s41598-025-28939-x

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Validation of a modified oxygen nebulized inhalation method in airway surface anesthesia by comparative analysis via scalable broad learning

Sci Rep. 2025 Dec 29;15(1):44813. doi: 10.1038/s41598-025-28908-4.

ABSTRACT

In clinical practice for the diagnosis of pulmonary tuberculosis (PTB), bronchoscopy is typically performed under airway surface anaesthesia. The effectiveness of this anaesthesia is closely associated with the smoothness of bronchoscopy diagnosis, as well as the incidence and severity of related adverse events. To enhance the efficacy of airway surface anaesthesia, the modified oxygen nebulized inhalation (MONI) method is developed. Derived from the traditional oxygen nebulized inhalation (ONI) procedure, this modified method improves the refined selection of a nebulizer and precise control of the oxygen flowing speed.To validate the advantages of the MONI method, this study compared it with the traditional ONI method through data experiments. Patients undergoing bronchoscopic operation were divided into two groups: one group received MONI for anaesthesia, and the other received ONI. Six key clinical items were recorded during the procedure. A comparative analysis was then conducted on the grouped data using machine learning models. A parameter-scalable broad learning system (BLS) architecture is proposed for feature extraction from raw data, with the optimal analytical model determined by minimizing the loss function value. Both the number of virtual input nodes and the number of neurons in the hidden layer are set as tunable parameters to optimize the model. Scoring data for the target clinical items were input into the system, transformed for BLS network training, and then used to generate predictions. Comparative analysis of the BLS output predictions showed that the data recorded from the MONI group performed better than that from the ONI group.Furthermore, the optimal models were validated to be significant for prediction and could explain how the network output data correlates with each of the six clinical items. Thus, we conclude that the proposed MONI method can practically enhance the effect of airway surface anaesthesia, which will facilitate the diagnosis of pulmonary tuberculosis (PTB). The scalable BLS model is prospective to provide advanced artificial intelligence support to detection procedures, thereby contributing to the effective prevention of infectious diseases.

PMID:41461769 | DOI:10.1038/s41598-025-28908-4

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Molecular characterization of bovine leukemia virus detected in dairy cattle herds from the Emirate of Abu Dhabi, United Arab Emirates

Sci Rep. 2025 Dec 29;15(1):44915. doi: 10.1038/s41598-025-28570-w.

ABSTRACT

Enzootic bovine leukosis (EBL) is an economically important disease of cattle caused by the bovine leukemia virus (BLV). Although BLV-seropositive dairy cattle were previously reported in the Emirate of Dhabi, UAE (EAD), molecular characterization of circulating BLV strains has not been undertaken. Therefore, the objectives of this study were to reassess the seroprevalence along with evaluating the genetic diversity of BLV strains circulating in dairy cattle in the EAD. Sera from 782 dairy cattle distributed across 11 farms were ELISA-screened and RT-qPCR testing of seropositive samples was followed by Sanger sequencing of the partial BLV env-gp51 gene (~ 423 bp) and phylogenetic analysis. The overall BLV herd seroprevalence was 27.3% (CI: 6.03%-61.00%), mean animal seroprevalence 33.5% (CI:30.20%-36.93%), and individual farm seroprevalence 28.00% (CI:19.00%-36.00%), 70.00% (CI:56.00%-84.00%), and 64.00% (59.00%-70.00%) for Farms 7, 11, and 14 respectively. Viral RNA was detected in 107 of 205 (52.2%) seropositive cattle, and phylogenetic analysis revealed a high genetic relatedness (~ 99.3-100.0%) among the BLV strains from the EAD. Additionally, study BLV isolates cluster under BLV-genotype 4 along with strains from Belgium, Russia and Vietnam. BLV infection is confirmed in EAD cattle, with circulating genotype 4 strains closely related to those from Europe and Asia, suggesting potential transboundary connections and underscoring the need for coordinated regional control measures. Future studies should focus on characterizing BLV infection risk factors in dairy cattle farms in the EAD. In the meantime, UAE livestock health authorities should urgently consider developing a national EBL control policy.

PMID:41461764 | DOI:10.1038/s41598-025-28570-w

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In vitro and in silico evaluation of synergistic antioxidant potential in a polyherbal formulation from Abelmoschus esculentus and Telfairia occidentalis

Sci Rep. 2025 Dec 29;15(1):44771. doi: 10.1038/s41598-025-28672-5.

ABSTRACT

Polyherbal formulations are increasingly investigated for their synergistic antioxidant potential against oxidative stress-related disorders. This study evaluated a polyherbal ethanol extract derived from Abelmoschus esculentus pods and Telfairia occidentalis leaves (AETO-PHF) through integrated in vitro and in silico approaches. GC-MS analysis identified 37 compounds, with dodecanoic acid (16.24%) and 9-octadecenoic acid (Z)-,2,3-dihydroxypropyl ester (16.41%) as predominant constituents. Antioxidant assays revealed potent dose-dependent radical scavenging, with IC₅₀ values of 61.39 ± 0.17 µg/mL (DPPH), 11.15 ± 0.15 µg/mL (H₂O₂ scavenging), 61.75 ± 0.00 µg/mL (FRAP), and 38.97 ± 2.66 µg/mL (NO inhibition). These results were statistically comparable (p > 0.05) to ascorbic acid (61.38 ± 0.58, DPPH; 61.71 ± 0.20, FRAP; and 38.94 ± 0.00, NO inhibition µg/mL) and gallic acid (11.30 ± 0.84 µg/mL, H₂O₂ scavenging). Molecular docking against cytochrome c peroxidase showed strong interactions of dodecanoic acid (- 5.7 kcal/mol) and 9-octadecenoic acid ester (- 6.2 kcal/mol), both surpassing the binding affinity of the reference antioxidant ascorbic acid (- 5.5 kcal/mol). Molecular dynamics simulations confirmed stable protein-ligand complexes with favorable RMSD, RMSF, and hydrogen-bond interaction profiles. These findings validate the traditional use of A. esculentus and T. occidentalis, demonstrate synergistic antioxidant efficacy of their polyherbal blend, and provide molecular-level insights into their mechanism of action. AETO-PHF represents a promising candidate for nutraceutical and therapeutic applications against oxidative stress-related diseases, meriting further in vivo and clinical studies.

PMID:41461761 | DOI:10.1038/s41598-025-28672-5