Assessing the causal effect of inflammation‐related genes on myocarditis: A Mendelian randomization study by Huazhen Xiao, Hongkui Chen, Wenjia Liang, Yucheng Liu, Kaiyang Lin, Yansong Guo

“…Univariable MR (UVMR) analysis revealed that IRF7 was a risk factor for myocarditis [IVW: odd ratio (OR) = 1.041, 95% confidence interval (CI) = 1.018–1.955, P = 0.039], while ADORA2B was a protective factors for myocarditis (IVW: OR = 0.799, 95% CI = 0.640–0.997, P = 0.047). …”
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Identification and Validation of Ferritinophagy-Related Biomarkers in Periodontitis by Yi-Ming Li, Chen‑Xi Li, Reyila Jureti, Gulinuer Awuti

“…ABSTRACT: Objective: While ferritinophagy is believed to play a significant role in the development of periodontitis, the exact mechanisms remain unclear. …”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…Early detection and accurate prediction of ARDS can significantly improve patient outcomes. While machine learning (ML) models are increasingly being used for ARDS prediction, there is a lack of consensus on the most effective model or methodology. …”
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Prognostic analysis of sepsis-induced myocardial injury patients using propensity score matching and doubly robust analysis with machine learning-based risk prediction model develo... by Pan Guo, Pan Guo, Li Xue, Fang Tao, Kuan Yang, YuXia Gao, Chongzhe Pei

“…A web-based application was subsequently developed for real-world use.ConclusionSIMI significantly worsens patient prognosis, while the XGBoost model demonstrated excellent predictive performance. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

“…At Xiaotangshan Station, the correlation between modelled ET and SIFsu is 0.71, while the correlation between modelled ET and SIFsh is 0.65. …”
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Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography by Yujie Ma, Maged Ali Al-Aroomi, Yutian Zheng, Wenjie Ren, Peixuan Liu, Qing Wu, Ye Liang, Canhua Jiang

“…This study evaluates the efficacy of deep learning algorithms for detecting and diagnosing dental caries using cone-beam computed tomography (CBCT) with the Mask R-CNN architecture while comparing various hyperparameters to enhance detection. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Conclusion The e4Quant assay is a novel alternative for genotyping to determine APOE ε4 carrier status, while also providing quantitative measurements of ApoE4 levels. …”
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Current and Future Trends of the Automotive Industry by Dieter Hermann Schramm

“…This, in addition to continued research on high-efficiency batteries which also includes the development of vehicles that offer a good compromise between coverage, costs and consumption while satisfying the mobility needs of their users.…”
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Exploring Brain Activity in Different Mental Cognitive Workloads by Sahar Oftadeh Balani, Ali Fawzi Al-Hussainy, Alhan Abd Al-Hassan Shalal, Mohammed Ubaid, Zinab Aluquaily, Jaafar Alamoori, Saeid Motevalli

“…Method: We employed a publicly accessible EEG dataset consisting of a cohort of 36 healthy volunteers (75% female), aged 18 to 26 years, while the participants were at rest or engaged in an arithmetic task to explore mental cognitive workload. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…Radiomic models were established based on extracted features from tumor-dominant regions of interest (ROI) on CT images, while clinical models were developed using demographic characteristics and preoperative laboratory examinations. …”
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The Persistent Threat of Chronic Inflammation on the Mortality Among Cervical Cancer Survivors: A Mendelian Randomization and Machine Learning Analysis Using UK Biobank and Chinese... by Wang J, Chen Z, Guan M, Ma Z, Peng L, Chen J, Fiori PL, Carru C, Capobianco G, Coradduzza D, Zhou L

“…After feature selection with 3 algorithms (LASSO regression, Boruta and Support vector machines), the gradient boosting machine (GBM) model outperformed other models by achieving an area under the curve (AUC) of 0.930 and a Brier score of 0.027 in 1-year overall survival (OS) prediction. …”
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Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment by L. M. Sheridan, D. Duplyakin, C. Phillips, H. Tinnesand, H. Tinnesand, R. K. Rai, J. E. Flaherty, L. K. Berg

“…</p> <p>Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. …”
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Examining the Role of Social Media in New Social Movements A Case Study of the Black Lives Matter Movement by Ali Davari, Mostafa Ghaffari

“…The findings suggest that future research should adapt Melucci’s framework to address contemporary challenges such as platform governance, algorithmic amplification, and activist burnout in digital environments. …”
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Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study by Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

“…Among 46,225 patients of the Seoul National University Bundang Hospital, MACCE occurred in 4.9% (2256/46,225), including myocardial infarction (907/46,225, 2%) and stroke (799/46,225, 1.7%), while in-hospital mortality was 0.9% (419/46,225). …”
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EEG microstate analysis in children with prolonged disorders of consciousness by Yi Zhang, Zhichong Hui, Yuwei Su, Weihang Qi, Guangyu Zhang, Liang Zhou, Jiamei Zhang, Kaili Shi, Yonghui Yang, Lei Yang, Gongxun Chen, Sansong Li, Mingmei Wang, Dengna Zhu

“…HC showed stronger connectivity for MS A, C, and D, while MCS exhibited stronger functional connectivity for MS C and D compared to VS/UWS. …”
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A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective by Dung Nguyen Tien, Huong Thi Thu Bui, Tram Hoang Thi Ngoc, Thuy Thi Pham, Dac Trung Nguyen, Huyen Nguyen Thi Thu, Thi Thu Hang Vu, Thi Lan Anh Luong, Lan Thu Hoang, Ho Cam Tu, Nina Körber, Tanja Bauer, Lam Khanh Ho

“…MethodsThis study used decision tree algorithms—ID3 and CART—on a data set of 60 hepatitis B surface antigen (HBsAg)–positive pregnant women. …”
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Detection of Coffee Leaf Miner Using RGB Aerial Imagery and Machine Learning by Emerson Ferreira Vilela, Cileimar Aparecida da Silva, Jéssica Mayara Coffler Botti, Elem Fialho Martins, Charles Cardoso Santana, Diego Bedin Marin, Agnaldo Roberto de Jesus Freitas, Carolina Jaramillo-Giraldo, Iza Paula de Carvalho Lopes, Lucas de Paula Corrêdo, Daniel Marçal de Queiroz, Giuseppe Rossi, Gianluca Bambi, Leonardo Conti, Madelaine Venzon

“…A set of four machine learning algorithms was utilized: Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD). …”
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Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes by Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang

“…Mechanistic pathways governing gene-metabolite-lipid interactions were inferred via random walk with restart algorithms and validated by gene set enrichment analysis (GSEA). …”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…These findings are important for the timing of electrophysiology-supported DBS programming, such as contact selection or adaptive algorithms.…”
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Discovery of a novel binding pocket in PPARγ for partial agonists: structure-based virtual screening identifies ginsenoside Rg5 as a partial agonist promoting beige adipogenesis by Zhen Wang, Kexin Shui, Zehui Zhang, Yihan Chen, Nanfei Yang, Shiliang Ji, Pingping Shen, Qiang Tian, Qiang Tian

“…Here, we employed six computational algorithms (Fpocket, DeepSite, CavityPlus, DoGSiteScorer, CASTpFold, POCASA) to identify a novel allosteric pocket (pocket 6–5) in the PPARγ ligand-binding domain (LBD), localized at the helix 3 (H3), helix 2 (H2), helix 2'(H2′), and β-sheet interface. …”
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