Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma by Qiang Liu, Huiguo Chen, Dongfang Tang, Huibiao Zhang, Shaogeng Chen, Yiran Meng, Boying Zheng, Fei Liu, Jing Zhou, Wen Zhang

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”
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Root-Zone Salinity in Irrigated Arid Farmland: Revealing Driving Mechanisms of Dynamic Changes in China’s Manas River Basin over 20 Years by Guang Yang, Xuejin Qiao, Qiang Zuo, Jianchu Shi, Xun Wu, Alon Ben-Gal

“…The driving mechanisms behind root-zone <i>SSC</i> distributions were analyzed using an approach combined with two machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP), to identify influential factors and quantify their impacts. …”
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Epidemiological surveillance of HIV-1 transmitted drug resistance among newly diagnosed individuals in Shijiazhuang, northern China, 2014-2015. by Xianfeng Wang, Xiaosong Liu, Feng Li, Hong Zhou, Jiefang Li, Yingying Wang, Lihua Liu, Shujun Liu, Yi Feng, Ning Wang

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Development of ultra-short PCR assay to reveal BRAF V600 mutation status in Thai colorectal cancer tissues. by Nunthawut Chat-Uthai, Pichpisith Vejvisithsakul, Sutthirat Udommethaporn, Puttarakun Meesiri, Chetiya Danthanawanit, Yannawan Wongchai, Chinachote Teerapakpinyo, Shanop Shuangshoti, Naravat Poungvarin

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Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

“…Additional explainable AI analyses revealed that several top predictive features in KDpredictor are consistent with prior clinical findings. …”
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Effects of trap confinement on personality measurements in two terrestrial rodents. by Allison M Brehm, Sara Tironi, Alessio Mortelliti

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Detecting cognitive motor dissociation by functional near-infrared spectroscopy by Yan Wang, Yan Wang, Yan Wang, Wentao Zeng, Wentao Zeng, Wentao Zeng, Leyao Zou, Leyao Zou, Leyao Zou, Qijun Wang, Bingkai Ren, Bingkai Ren, Bingkai Ren, Qi Xiong, Yang Bai, Yang Bai, Yang Bai, Zhen Feng, Zhen Feng, Zhen Feng

“…The support vector machine combined with genetic algorithm was employed to classify and predict the brain's response to spoken commands and to identify CMD patients among prolonged DOC individuals.ResultsWe identified seven CMD patients using fNIRS, of whom four were in VS/UWS and three were in MCS–. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…More research is needed to quantitatively examine different contribution of sample sizes, modeling algorithms, variables from different sources, and stratification factors on modeling results, so that we can design an optimal procedure for GSV modeling using airborne Lidar data.…”
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Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing by Zhiyuan Ren, Shijie Zhou, Dong Liu, Qihe Liu

“…The contributions include threefold: First, identifying the co-evolutionary path of algorithmic architectures from adaptive optimization (neural tangent kernel-guided weighting achieving 230% convergence acceleration in Navier-Stokes solutions) to hybrid numerical-deep learning integration (5× speedup via domain decomposition) and second, constructing bidirectional theory-application mappings where convergence analysis (operator approximation theory) and generalization guarantees (Bayesian-physical hybrid frameworks) directly inform engineering implementations, as validated by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>72</mn><mo>%</mo></mrow></semantics></math></inline-formula> cost reduction compared to FEM in high-dimensional spaces (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.01</mn><mo>,</mo><mi>n</mi><mo>=</mo><mn>15</mn></mrow></semantics></math></inline-formula> benchmarks). …”
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Microstate Co-Occurrence Matrices-Based Brain Activity Pattern Changes Analysis on Chronic Tinnitus Subjects by Yingying Wang, Gui Yang, Hongyu Liu, Xin Huang, Shuqing Han, Zhixiang Gu, Liyang Shao, Lei Zhang, Yuan Tao

“…Unlike healthy individuals, tinnitus patients exhibit minimal changes between OE and CE, indicating the reduction of brain flexibility. This study advances EEG microstate analysis by integrating co-occurrence matrix algorithms, offering a direct and comprehensive assessment of microstate stability and interactions. …”
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Randomised controlled trial to evaluate the effectiveness of using the RD-1-based C-Tb skin test as a replacement for blood-based interferon-γ release assay for detection of, and i... by Marc Lipman, Ibrahim Abubakar, Chris Griffiths, Penny Whiting, Robert Horne, Alex Ghanouni, Heinke Kunst, Mike Mandelbaum, Molebogeng X Rangaka, Karen Sanders, Peter J White, Angela Crook, Dominik Zenner, Trinh Duong, Vanessa Hack, Julian Surey, Yohhei Hamada, Henry Bern, Joanna Calvert, Marie Francis, Amy Louise Clarke, Ellen Owen-Powell, Helen L Booth

“…Introduction The predictive utility for incident tuberculosis (TB) of the purified protein derivative tuberculin skin test and region of difference 1 (RD1)-based interferon-gamma release assays (IGRA) is comparable; and either is recommended to test for latent TB infection (LTBI). …”
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Effect of Faricimab versus Aflibercept on Hyperreflective Foci in Patients with Diabetic Macular Edema from the YOSEMITE/RHINE Trials by Usha Chakravarthy, FRCOphth, PhD, Varun Chaudhary, MD, FRCS(C), Srinivas R. Sadda, MD, Colin S. Tan, FRCOphth, FRCSEd (Ophth), Stela Vujosevic, MD, PhD, Sascha Fauser, MD, Kara Gibson, PhD, Carl Glittenberg, MD, Nancy Holekamp, MD, FASRS, Ben Lanza, PhD, Andreas Maunz, PhD, Jeffrey R. Willis, MD, PhD, Rishi P. Singh, MD

“…Methods: A deep learning–based algorithm was used to automatically quantify HRF in spectral-domain OCT volume scans from YOSEMITE/RHINE. …”
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Systematic elucidation of the effective constituents and potential mechanisms of Scrophulariae Radix against neoplasm based on LC-MS, network pharmacology, and molecular docking ap... by Shu-jie Yu, Xiao-bin Kong, Xin Jin, Meng-yi Shan, Gang Cheng, Pei-lu Wang, Wen-long Li, Pei-yuan Zhao, Yun-jie Sheng, Bing-qian He, Qi Shi, Hua-qiang Li, Qi-ming Zhao, Lu-ping Qin, Lu-ping Qin, Xiong-yu Meng, Xiong-yu Meng

“…As a result, the material–liquid ratio was significantly reduced from 100 g/mL to 32 g/mL, and the extraction efficiency was 1.332%, which was close to the predicted value of 1.346% in the response surface method, indicating that the algorithm model had a good fit. …”
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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Methods and Results This study analyzed 8,119 HER2‐positive HR‐negative breast cancer patients from the SEER database, randomly allocated to training/validation/test cohorts (7:1:2 ratio). Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics by Yuexi Yu, Huiru Liu, Kaipeng Liu, Meiqi Zhao, Yiyan Zhang, Runci Jiang, Fengmei Wang

“…Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. …”
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Association between hemoglobin glycation index and the risk of cardiovascular disease in early-stage cardiovascular-kidney-metabolic syndrome: evidence from the China health and re... by Huiyi Liu, Shuai Mao, Shuai Mao, Yunzhang Zhao, Yunzhang Zhao, Lisha Dong, Lisha Dong, Yifan Wang, Yifan Wang, Chao Lv, Tong Yin, Tong Yin

“…Extreme gradient boosting (XGBoost) algorithm was applied, with the Shapley additive explanation (SHAP) method used to determine feature importance. …”
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Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease by I-Wen Wu, Yu-Chieh Liao, Tsung-Hsien Tsai, Chieh-Hua Lin, Zhao-Qing Shen, Yun-Hsuan Chan, Chih-Wei Tu, Yi-Ju Chou, Chi-Jen Lo, Chi-Hsiao Yeh, Chun-Yu Chen, Heng-Chih Pan, Heng-Jung Hsu, Chin-Chan Lee, Mei-Ling Cheng, Wayne Huey-Herng Sheu, Chi-Chun Lai, Huey-Kang Sytwu, Ting-Fen Tsai

“…Secondly, 13 gut microbiota biomarkers, which are strongly correlated with anthropometric, metabolic and/or renal indexes, concomitantly identified by the ML algorithm and the differential abundance method were highly discriminatory. …”
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High-Resolution Mapping of Litter and Duff Fuel Loads Using Multispectral Data and Random Forest Modeling by Álvaro Agustín Chávez-Durán, Miguel Olvera-Vargas, Inmaculada Aguado, Blanca Lorena Figueroa-Rangel, Ramón Trucíos-Caciano, Ernesto Alonso Rubio-Camacho, Jaqueline Xelhuantzi-Carmona, Mariano García

“…A set of vegetation indices and texture metrics derived from the multispectral data, optimized by a “Variable Selection Using Random Forests” (VSURF) algorithm, were used to train random forest (RF) models, enabling the modeling of high-resolution maps of litter and duff fuel loads. …”
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Directed disruption of IL2 aggregation and receptor binding sites produces designer biologics with enhanced specificity and improved production capacity by Amy Dashwood, Ntombizodwa Makuyana, Rob van der Kant, Arman Ghodsinia, Alvaro R. Hernandez, Stephanie Lienart, Oliver Burton, James Dooley, Magda Ali, Lubna Kouser, Francisco Naranjo, Matthew G. Holt, Frederic Rousseau, Joost Schymkowitz, Adrian Liston

“…Here we use SolubiS and dTANGO, computational algorithm-based methods, to predict mutations within the IL2 structure to improve protein production yield in muteins with altered cellular selectivity, to generate combined muteins with elevated therapeutic potential. …”
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Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule by Fanfan Wang, Fanfan Wang, Jianting Wen, Jianting Wen, Jian Liu, Jian Liu, Ling Xin, Yanyan Fang, Yanyan Fang, Yue Sun, Mingyu He, Mingyu He

“…Bioinformatics prediction, MeRIP-qPCR, RIP, and RNA pull-down assays were employed to identify the m6A modification sites of ENST00000619282 and their interactions with FTO/YTHDF1. …”
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