Combined Analysis of Transcriptome and Mendelian Randomization Reveals AKT1 and PPARG as Biomarkers Related to Glucose Metabolism in Sepsis by Ma J, Li W, Ma Q, Ding L, Wang Z, Wang R, Huang Y, Ma G, Gao J

“…Jie Ma,1,2,* Wendi Li,3 Qianqian Ma,1 Liying Ding,4 Zhaoyun Wang,1 Rong Wang,1 Yanan Huang,1 Gang Ma,2,* Jun Gao1,* 1Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China; 2Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China; 3Department of Child Rehabilitation Education, Ningxia Rehabilitation Center for the Disabled, Yinchuan, Ningxia, 750002, People’s Republic of China; 4Department of Gynecology, Gynecology Clinic of Li Ying, Wuzhong, Ningxia, 751100, People’s Republic of China*These authors contributed equally to this workCorrespondence: Gang Ma, Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China, Email magang2671@163.com Jun Gao, Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China, Email gaojun1605@sina.comIntroduction: This study aimed to identify diagnostic and therapeutic biomarkers related to glucose metabolism in sepsis, as hyperglycemia and blood glucose fluctuations influence sepsis progression.Methods: Datasets from public databases were analyzed using various methods, including differential expression analysis, PPI network screening, machine learning algorithms and Mendelian randomization. …”
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Long-term risk of de novo malignancy with tumor necrosis factor alpha (TNF) inhibitor immunosuppression: a multicenter, retrospective cohort study by Conor B. Driscoll, Jordan M. Rich, Christopher Yang, Joseph Nicolas, Dylan Isaacson, Philip Silberman, Xinlei Mi, Sai Kaushik Shakar Ramesh Kumar, Hui Zhang, Steven Belknap, William H. Temps, Edward M. Schaeffer, Shilajit D. Kundu

“…There may need to be differential cancer screening algorithms for patients with different inflammatory conditions and TNF-I exposure.…”
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Integrating health equity in artificial intelligence for public health in Canada: a rapid narrative review by Samantha Ghanem, Marielle Moraleja, Danielle Gravesande, Jennifer Rooney

“…Several health equity considerations for applying AI in public health were identified, including gaps in AI epistemology, algorithmic bias, accessibility of AI technologies, ethical and privacy concerns, unrepresentative training datasets, lack of transparency and interpretability of AI models, and challenges in scaling technical skills.ConclusionWhile AI has the potential to advance public health in Canada, addressing equity is critical to preventing inequities. …”
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Bioinformatic analysis, clinical implications and experimental validation of ferroptosis-related feature gene in IgA nephropathy: focus on DUSP1 by Tingting Liu, Tingting Pan, Mingxin Chang, Shaojie Fu, Hongzhao Xu, Hao Wu, Zhonggao Xu, Yanli Cheng

“…Among them, dual specificity phosphatase 1 (DUSP1) was screened as FFG by three machine learning algorithms. …”
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Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila. by Jean-Baptiste Masson, François Laurent, Albert Cardona, Chloé Barré, Nicolas Skatchkovsky, Marta Zlatic, Tihana Jovanic

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Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study by Jaclyn A Pagliaro, Lauren K Wash, Ka Ly, Jenny Mathew, Alison Leibowitz, Ryan Cabrera, Jolie B Wormwood, Varsha G Vimalananda

“…ResultsOf the 7714 who were mailed a study invitation, 560 were screened. Of the screened patients, 203 were enrolled (2.9% enrollment yield) and 166 completed the study (82% retention rate). …”
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Association between impaired sensitivity to thyroid hormones and sedentary behavior: a cross-sectional study by Hangzhou Yang, Jie Kang, Lingkang Dong, Zihan Lin, Qixian Lin, Bo Wu

“…The Least Absolute Shrinkage and Selection Operator (LASSO) regression and the Boruta algorithm were employed to screen out confounding factors closely associated with sedentary time and the parametric thyroid feedback quantile-based index (PTFQI). …”
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Relationship between stress hyperglycemia ratio and the incidence of atrial fibrillation in patients after coronary artery bypass grafting: a retrospective study based on the MIMIC... by Runjia Liu, Jiatong Li, Jing Zeng, Yuxuan Tao, Dong Chen, Haixia Li

“…We employed logistic regression models, restricted cubic splines (RCS), threshold effect analysis, ubgroup analysis, Boruta algorithm, lasso algorithm, and receiver operating characteristics (ROC) to analyze the relationship between SHR and POAF incidence comprehensively. …”
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PRKDC regulates cGAMP to enhance immune response in lung cancer treatment by Zhanghao Huang, Zhanghao Huang, Zhanghao Huang, Runqi Huang, Runqi Huang, Runqi Huang, Jun Zhu, Jun Zhu, Youlang Zhou, Youlang Zhou, Jiahai Shi, Jiahai Shi

“…This study aimed to investigate the antitumor effects of 2’,3’-cGAMP in LUAD.MethodHerein, patients with LUAD were screened for prognostic biomarkers, which were then assessed for sensitivity to immunotherapy and chemotherapy utilizing the “TIDE” algorithm and CellMiner database. …”
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Analysis and Validation of Autophagy-Related Gene Biomarkers and Immune Cell Infiltration Characteristic in Bronchopulmonary Dysplasia by Integrating Bioinformatics and Machine Lea... by Xiao S, Ding Y, Du C, Lv Y, Yang S, Zheng Q, Wang Z, Zheng Q, Huang M, Xiao Q, Ren Z, Bi G, Yang J

“…Subsequently, the hub genes were identified by Lasso and Cytoscape with three machine-learning algorithms (MCC, Degree and MCODE). In addition, hub genes were validated with ROC, single-cell sequence and IHC in hyperoxia mice. …”
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Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. …”
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Integrating Artificial Intelligence and Microfluidics Technology for Psoriasis Therapy: A Comprehensive Review for Research and Clinical Applications by Ibrahim Shaw, Yimer Seid Ali, Changhong Nie, Kexin Zhang, Chuanpin Chen, Yin Xiao

“…Integrating artificial intelligence (AI) with microfluidics promises to overcome these barriers by leveraging AI algorithms to automate device design, streamline experimentation, and enhance diagnostic and therapeutic outcomes. …”
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Big data transfer service architecture for cloud data centers: problems, methods, applications, and future trends by Muhammad Umar Majigi, Ismaila Idris, Shafi’i Muhammad Abdulhamid, Richard A. Ikuesan

“…Key issues identified in the context of big data transfer services for cloud data centers include storage, big data transfer, service transfer architecture, data processing, bandwidth, and security, all of which demand extensive research. After thoroughly screening selected peer-reviewed articles, the primary open issues are: incorporating a data placement module in the data transfer service, providing end-to-end safeguards for packet delivery, improving data transfer time and speed, minimizing costs and implementation overhead, ensuring secure data transfer between servers in the cloud, demonstrating effective big data transfer architectures, considering topology-specific extensions to reduce the busty nature of data centers, and enhancing data transfer services using machine learning algorithms during upload and download operations. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…We evaluate their performance on regression and optimization molecular tasks using docking scores, finding them to outperform classical single-task and transfer-learning models. We examine the issue of generalization to divergent test tasks, which is a general concern of meta-learning algorithms in science, and propose strategies to alleviate it.…”
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Biophysical and nutritional combination treatment for myosteatosis in patients with sarcopenia: a study protocol for single-blinded randomised controlled trial by Maoyi Tian, Ling Qin, Simon Kwoon Ho Chow, Wing Hoi Cheung, A A Welch, Can Cui, Parco M Siu, Meng Chen Michelle Li, Yu Kin Cheng, Ronald Man Yeung Wong, Timothy CY Kwok, Minghui Yang, Clinton Rubin, Sheung Wai Law

“…The findings of this study will demonstrate the effect of combination treatment as an alternative for managing sarcopenia.Methods and analysis In this single-blinded randomised controlled trial, subjects will be screened based on the Asian Working Group for Sarcopenia (AWGS) 2019 definition. 200 subjects who are aged 65 or above and identified sarcopenic according to the AWGS algorithm will be recruited. …”
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Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait loci, a... by Guoqing Liu, Xiangwen Lv, Jiahui Qin, Xingqing Long, Miaomiao Zhu, Chuwen Fu, Jian Xie, Peichun He

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…This work compares and reports a classification of malware detection work based on deep learning algorithms. The 2011–2025 articles were considered, and the latest work focused on the literature for the 2018–2025 years; after screening, 72 articles were selected for the initial study. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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A portable retina fundus photos dataset for clinical, demographic, and diabetic retinopathy prediction by Chenwei Wu, David Restrepo, Luis Filipe Nakayama, Lucas Zago Ribeiro, Zitao Shuai, Nathan Santos Barboza, Maria Luiza Vieira Sousa, Raul Dias Fitterman, Alexandre Durao Alves Pereira, Caio Vinicius Saito Regatieri, Jose Augusto Stuchi, Fernando Korn Malerbi, Rafael E. Andrade

“…The mBRSET dataset serves as a resource for developing AI algorithms and investigating real-world applications, enhancing ophthalmological care in resource-constrained environments.…”
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RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

“…In this study, the combined roles of m7G methylation regulators were explored in COPD for the first time by integrated bioinformatic methods. The machine algorithms screened 7 disease signature genes relevant to clinical indicators, including CYFIP2, EIF3D, EIF4G3, GEMIN5, METTL1, SNUPN and NCBP2, and METTL1 was related to the progression in COPD. …”
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