Physiological impact of Trichoderma viride agents on the quality and production of melon that is grown on soils continuously cropped to melon by Jingyi Liu, Hua Lian, Jingwei Dou, Jingjing Li, Guangliang Zhu, Jiatong Wang, Guangshu Ma, Mei Li

“…Melon quality and yield was also enhanced by the use of T. viride agents, with the treatment of 6.4 × 105 CFU/g T. viride agents having the best boosting effects. The melon fruit’s transverse diameter, vertical diameter, single fruit weight, and yield all increased. …”
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Identification of multiple complications as independent risk factors associated with 1-, 3-, and 5-year mortality in hepatitis B-associated cirrhosis patients by Duo Shen, Ling Sha, Ling Yang, Xuefeng Gu

“…Eight machine learning techniques were employed to construct predictive models, including C5.0, linear discriminant analysis (LDA), least absolute shrinkage and selection operator (LASSO), k-nearest neighbour (KNN), gradient boosting decision tree (GBDT), support vector machine (SVM), generalised linear model (GLM) and naive Bayes (NB), utilising variables such as medical history, demographics, clinical signs, and laboratory test results. …”
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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

“…This study explores a range of commonly used ML models, including artificial neural network (ANN), support vector machine (SVM), decision tree, random forest, and extreme gradient boosting (XGBoost). These models have been used to predict waste characteristics, classify diverse types of OSW, and optimize treatment parameters across various processes, such as thermochemical conversion, anaerobic digestion, and aerobic composting. …”
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The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

“…Six predictive models were constructed using 15 key influencing factors, including Classification and Regression Trees (CART), C5.0, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), Random Forest (RF), and Nomogram. …”
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Wzmianki o muzyce z czasów Stanisława Augusta w gazetach pisanych ze zbiorów biblioteki im. Wróblewskich Litewskiej Akademii Nauk w Wilnie by Ryszard Mączyński

“…Muzykalia nie są w nim zbyt obfite, zaledwie dziesięć doniesień odnoszących się wyłącznie trzech lat: 1780 (sześć adnotacji), 1782 (jedna), 1784 (trzy). …”
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Economic and environmental sustainability of agriculture production at the crop level by A.Z. Bi, K.B. Umesh, B. Md Abdul, D. Sivakumar, P. Srikanth

“…Moreover, using drones and global positioning system-guided tractors maximizes input application, lowers fuel consumption, and boosts overall agricultural productivity. Beneficial insects, birds, and other animals find a home when hedgerows, buffer strips, and wildlife corridors are kept up around and inside fields at crop level.  …”
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Risk Factors for Gastrointestinal Bleeding in Patients With Acute Myocardial Infarction: Multicenter Retrospective Cohort Study by Yanqi Kou, Shicai Ye, Yuan Tian, Ke Yang, Ling Qin, Zhe Huang, Botao Luo, Yanping Ha, Liping Zhan, Ruyin Ye, Yujie Huang, Qing Zhang, Kun He, Mouji Liang, Jieming Zheng, Haoyuan Huang, Chunyi Wu, Lei Ge, Yuping Yang

“…A total of 7 ML algorithms—logistic regression, k-nearest neighbors, support vector machine, decision tree, random forest (RF), extreme gradient boosting, and neural networks—were trained using 10-fold cross-validation. …”
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Intranasal delivery of hMSC-derived supernatant for treatment of ischemic stroke by inhibiting the pro-inflammatory polarization of neutrophils by Yixiang Jiang, Ning Wang, Jingyi Liu, Haoran Ren, Wenkang Jiang, Yanting Lei, Xidan Fu, Miao Hao, Xiujuan Lang, Yumei Liu, Xijun Liu, Rui Li, Hulun Li

“…Intranasal delivery of hMSC-L and hMSC-M significantly reduces neutrophil infiltration in the brain post-stroke and increases the proportion of anti-inflammatory N2-subtype neutrophils, boosting the expression levels of IL-10 and TGF-β. …”
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Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm by Dong Jiang, Yi Qian, Yijun Gu, Ru Wang, Hua Yu, Zhenmeng Wang, Hui Dong, Dongyu Chen, Yan Chen, Haozheng Jiang, Yiran Li

“…This model, derived from machine learning frameworks including Support Vector Machine (SVM), Logistic Regression (LR), Multilayer Perceptron (MLP), k-Nearest Neighbors (KNN), and eXtreme Gradient Boosting (XGBoost) with fivefold cross-validation, showed AUCs of 0.95 (95% CI: 0.90–0.99) and 0.87 (95% CI: 0.72–1.0) in internal validation. …”
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Mitochondrial reactive oxygen species trigger metformin-dependent antitumor immunity via activation of Nrf2/mTORC1/p62 axis in tumor-infiltrating CD8T lymphocytes by Kazuhiro Kakimi, Hirokazu Matsushita, Masaaki Komatsu, Eiryo Kawakami, Mikako Nishida, Nahoko Yamashita, Taisaku Ogawa, Keita Koseki, Eiji Warabi, Tomoyuki Ohue, Katsuyuki Shiroguchi, Heiichiro Udono

“…In synergy with the effect of anti-PD-1 Ab, Met boosts CD8TIL proliferation and IFN-γ secretion, resulting in decreased glycolysis and oxidative phosphorylation in tumor cells. …”
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Supplementation of Nodulisporium sp. KT29 induced by Vibrio harveyi as an immunostimulant for controlling vibriosis in vannamei white shrimp under marine culture system by Dinamella Wahjuningrum, Teuku Reza Efianda, Kustiariyah Tarman, Munti Yuhana, Irzal Effendi, Fazril Saputra

“…It could be concluded that providing NM 20 mL treatment boosted the resistance and the immune system in vaname shrimp to control vibriosis reared at the sea. …”
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Fibrinogen-albumin ratio predicts treatment response in phospholipase A2 receptor-associated membranous nephropathy with nephrotic syndrome by Suyan Duan, Si Chen, Chen Chen, Fang Lu, Ying Pan, Yifei Lu, Qing Li, Simeng Liu, Bo Zhang, Huijuan Mao, Changying Xing, Yanggang Yuan

“…When combining FAR and anti-PLA2R Ab, the AUC was boosted to 0.766.Conclusions FAR was significantly correlated with proteinuria and anti-PLA2R Ab in PMN. …”
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Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model de... by Hayeon Lee, Seung Ha Hwang, Seoyoung Park, Yunjeong Choi, Sooji Lee, Jaeyu Park, Yejun Son, Hyeon Jin Kim, Soeun Kim, Jiyeon Oh, Lee Smith, Damiano Pizzol, Sang Youl Rhee, Hyunji Sang, Jinseok Lee, Dong Keon Yon

“…Findings: In the discovery cohort, the ensemble model using voting with logistic regression and adaptive boosting achieved a balanced accuracy of 72.6% and an area under the receiver operating characteristics curve (AUROC) of 0.792. …”
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Bisphenol B restrains rat leydig cell function via H3K27me3/H3K9me3 histone modifications by Jiayi He, Huiqian Zhang, Hehua Quan, Qingyuan Wang, Congcong Wen, Yiyan Wang, Yang Zhu, Ren-Shan Ge, Xiaoheng Li

“…Notably, BPB significantly boosted the expressions of histone methylation markers like EEF1A1, SUZ12, EED, EZH2, H3K27me3, and H3K9me3 in vivo. …”
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Evaluation of the adherence of municipalities and states to the Ministry of Health’s microplanning for high-quality vaccination activities and the increase in vaccination coverage... by Ana Catarina de Melo Araújo, Thales Philipe Rodrigues da Silva, Gustavo Velasquez-Melendez, Luciana Maiara Diogo Nascimento, Carla Conceição Ferraz, Fernanda Penido Matozinhos, Eder Gatti Fernandes

“…This analysis suggests that higher adherence to OM improves VC outcomes, emphasizing the role of OM in these metrics and shows that comprehensive implementation of OM improves vaccination efforts and significantly boosts VC, particularly in states fully adhering to guidelines.…”
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Enhancing reproductive capacity in hybrid Red Tilapia (Oreochromis niloticus ×‎ O. mossambicus) via dietary administration of date palm pollen (Phoenix dactylifera L.)‎ by Nashi K. Alqahtani, Hesham S. Ghazzawy, Roshmon Thomas Mathew, Yousef‎ Ahmed Alkhamis, Rashid Saleh Alngada, Moaheda E.H. Eissa, Sameh A. Abdelnour, Sara F. Ghanem, Layla A. Almutairi, El-Sayed Hemdan Eissa

“…The gonadal histology demonstrated that DPP boosted gonad maturation histo-structure in both genders of Tilapia fish. …”
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Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: Insights for enhancing breeding programs and herd management by Alessio Cecchinato, Hugo Toledo-Alvarado, Lucio Flavio Macedo Mota, Vittoria Bisutti, Erminio Trevisi, Riccardo Negrini, Sara Pegolo, Stefano Schiavon, Luigi Gallo, Giovanni Bittante, Diana Giannuzzi

“…The blood metabolites (15 blood biomarkers related to hepatic damage and function, oxidative stress, inflammation, and innate immunity) were predicted using milk Fourier-transform mid-infrared (MIR) spectroscopy. A gradient boosting machine approach with leave-one-batch-out cross-validation (R2 range from 0.45 to 0.82) was implemented to an independent calibration database of 1,367 lactating cows reared in 5 herds. …”
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Global research trends in Chinese medicine for the treatment of non-alcoholic fatty liver disease (NAFLD): A bibliometric study by Kangjie li, Jie Wang, Ming Dang, Runxin Ren, Maomao Fu, Jing Wang, Qiao Zhang, Chongbo Zhao

“…The top 10 key journals account for 49.02 % of the publications, with Frontiers in Pharmacology being the most prolific, while the World Journal of Gastroenterology boasts the highest average number of citations. The most frequently cited journals are Hepatology, Journal of Hepatology, and Journal of Ethnopharmacology. …”
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Effect of Sunflower (Helianthus annus L.) Hulls with Different Particle Sizes on Growth Performance and Physiological Responses of Broiler Chickens Fed Different Levels of Protein by Najibeh Beigzadeh, Smayyeh Salari, Faegheh Zaefarian, Shima Hosseinifar

“…This improvement is achieved by increasing the digestibility of crude protein, as well as boosting the Lactobacillus population. Additionally, using coarse sunflower hulls led to an increase in the relative weight of the carcass and thighs.…”
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Development, validation, and clinical application of a machine learning model for risk stratification and management of cervical cancer screening based on full-genotyping hrHPV tes... by Binhua Dong, Zhen Lu, Tianjie Yang, Junfeng Wang, Yan Zhang, Xunyuan Tuo, Juntao Wang, Shaomei Lin, Hongning Cai, Huan Cheng, Xiaoli Cao, Xinxin Huang, Zheng Zheng, Chong Miao, Yue Wang, Huifeng Xue, Shuxia Xu, Xianhua Liu, Huachun Zou, Pengming Sun

“…Methods: We developed, compared and validated four machine learning models (eXtreme gradient boosting [XGBoost], support vector machine [SVM], random forest [RF], and naïve bayes [NB]) for cervical cancer prediction, using data from a national cervical cancer screening project conducted in 267 healthcare centers in China. …”
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