Insights into the Driving Factors of Methane Emission from Double-Season Rice Field Under Different Fertilization Practices in South China by Jin Zheng, Yusheng Lu, Peizhi Xu, Kaizhi Xie, Changmin Zhou, Yaying Li, Haoyang Geng, Qianyuan Wang, Wenjie Gu

“…The results showed that CH₄ emission fluxes exhibited seasonal variations, with consistent patterns of change observed across all treatments for both early- and late-season rice. …”
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Results of replacing fish meal with insect protein in carp feeds by O. Deren, O. Bernakevych, L. Bobeliak, N. Hrytsyshyna, M. Koryliak

“…Substantiation of the prospects for replacing fish meal in the composition of carp feeds with black soldier fly meal (Hermetia illucens) based on the analysis of studies of productive and individual functional parameters of the body of experimental groups of fish. …”
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Impact mechanism of anaerobic digestion of sulfur-rich coal to H2S by graphene by Wenjie ZHAO, Xianbo SU, Weizhong ZHAO, Yixuan ZHOU

“…Using high-sulfur coal extracted from Jincheng as a carbon and sulfur source, an anaerobic fermentation system is constructed with graphene as the conductive material. The anaerobic fermentation process will be analyzed to investigate the evolutionary patterns in gas composition, morphological sulfur in coal, coal molecular structure liquid-phase substances and microbial community structure. …”
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Systematic phenotype and genotype characterization of Moebius syndrome by Bryn D. Webb, Julie A. Jurgens, Narisu Narisu, Zhongyang Zhang, Brenda J. Barry, Carol Van Ryzin, Lori L. Bonnycastle, Wai-Man Chan, Tingfen Yan, Silvio Alessandro Di Gioia, Amy J. Swift, Sarah E. MacKinnon, Darren T. Oystreck, Janet C. Rucker, Tamiesha Frempong, Mary C. Whitman, Edmond J. FitzGibbon, Janice S. Lee, Ke Hao, Caroline Andrews, Monica Erazo, Flavia M. Facio, Sherin Shaaban, Thomas P. Naidich, Peter S. Chines, Tanya J. Lehky, Camilo Toro, Andrea L. Gropman, John A. Butman, Christopher K. Zalewski, Carmen C. Brewer, Audrey Thurm, Joseph Snow, Scott M. Paul, Brian P. Brooks, Carlo Pierpaoli, Caroline D. Robson, David G. Hunter, Francis S. Collins, Ethylin Wang Jabs, Elizabeth C. Engle, Irini Manoli

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Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

“…The inclusion of HCs provides evidence that rTMS-induced changes align with normative network patterns, and the responder analysis suggests that connectivity modulation is linked to clinical improvement. …”
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Potential influence of geomagnetic activity on blood pressure statistical fluctuations at mid-magnetic latitudes by Pengzhi He, Chen Li, Minlan Xu, Ruilong Guo, Alexander William Degeling, Timo Pitkänen, Yude Bu, Xiangyun Zheng, Yue Zhang, Xianghong Jia, Anmin Tian, Chenyao Han, Shifeng Wang, Tianlu Chen, Jiangping Fang, Shaowei Sun, Wenlong Liu, Jinbin Cao, Kimmen Quan, Zhiyuan Cong, Dedong Ma, Qiugang Zong, Suiyan Fu, Shutao Yao, Huanhu Zhang, Quanqi Shi

“…Both BP and the GMA index exhibit similar annual bimodal patterns and multiple periodicities, including 12-month and 6-month cycles, and an intermittent 3-month cycle. …”
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Genome-wide identification of the regulatory network of mitogen-activated protein kinase signaling cascades gene families in Hevea Brasiliensis by Xiaojuan Huang, Manman Sun, Xiaoyu Du, Lin Quan, Jinquan Chao, Xiaomin Deng, Hongze Liao

“…Integrating the interaction network and gene expression patterns, 12 potential HbMPK cascade signaling modules including HbMPKKK6/41/79-HbMPKK1-HbMPK9/12/15 and HbMPKKK6/14/21/41/79-HbMPKK9-HbMPK9/15 might involve in NR production and stress responses. …”
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Assessing the prognostic and therapeutic value of cuproptosis-related genes in colon adenocarcinoma patients by Zhanhui Ye, Yixian Song, Mengqing Zhu, Fuying Zheng, Wenjie Qin, Wenjie Qin, Xue Li, Pei Wang, Zihua Li, Kequan Chen, Aimin Li

“…Using the Weighted Gene Co-expression Network Analysis (WGCNA) method, we identified the gene module most strongly linked to cuproptosis and conducted functional enrichment analysis to explore the roles of genes within this module in COAD tumorigenesis. …”
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CD9 regulates proliferation, invasion, migration and radioresistance of esophageal squamous cell carcinoma by activating AKT/GSK3β signaling pathway by Liubing Hou, Liubing Hou, Zengyao Hao, Ge Zhang, Jiayuan Li, Yu Wang, Xiaoying Xue, Xiaoying Xue, Huandi Zhou, Huandi Zhou, Huandi Zhou

“…This study aims to systematically elucidate the molecular mechanisms by which CD9 regulates malignant phenotypes and radiosensitivity through the AKT/GSK3β signaling pathway in ESCC.MethodsTCGA data, ESCC tissues microarray, in vitro experiments, and patient cohorts were utilized to investigate the expression patterns, functional mechanisms, and clinical relevance of CD9 in ESCC. …”
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Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review by Alex Federman, Yufei Wang, Jalayne J Arias, Catherine E A Scipion, Margaret A Manchester

“…Objectives This study aimed to systematically map the evidence and identify patterns of barriers and facilitators to clinician artificial intelligence (AI) acceptance and use across the types of AI healthcare application and levels of income of geographic distribution of clinician practice.Design This scoping review was conducted in accordance with the Joanna Briggs Institute methodology for scoping reviews and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guideline.Data sources PubMed and Embase were searched from 2010 to 21 August 2023.Eligibility criteria This scoping review included both empirical and conceptual studies published in peer-reviewed journals that focused on barriers to and facilitators of clinician acceptance and use of AI in healthcare facilities. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…<b>Methods</b>: A cross-sectional case-control study was conducted involving 42 individuals aged 60 years or older. …”
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Vestibular Atelectasis: A Narrative Review and Our Experience by Andrea Tozzi, Andrea Castellucci, Salvatore Martellucci, Pasquale Malara, Michael Eliezer, Giuseppe Ferrulli, Rosanna Rita Ruberto, Pasquale Brizzi, Enrico Armato, Alessio Marchetti, Daniele Marchioni, Angelo Ghidini, Claudio Moratti

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CLU, FOS, and CXCL8 as diagnostic biomarkers for heart failure progression post-acute myocardial infarction: an integrated RNA-Seq and multi-machine learning study by Jingjing Wei, Peng Yu, Peng Yu, Yucai Hu, Lijie Qiao, Lijie Qiao, Bin Li, Bin Li, Haitao Li, Shiyang Xie, Zhengwei Dong, Aolong Wang, Yilin Zhang, Xinlu Wang, Yongxia Wang, Mingjun Zhu

“…Functional enrichment analysis was used to explore the biological roles of DEGs. …”
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Altered Expression of Cell Cycle Regulators and Factors Released by Aged Cells in Skeletal Muscle of Patients with Bone Fragility: A Pilot Study on the Potential Role of SIRT1 in M... by Angela Falvino, Roberto Bonanni, Beatrice Gasperini, Ida Cariati, Angela Chiavoghilefu, Amarildo Smakaj, Virginia Veronica Visconti, Annalisa Botta, Riccardo Iundusi, Elena Gasbarra, Virginia Tancredi, Umberto Tarantino

“…However, knowledge about expression patterns of factors potentially involved in aging and senescence at the tissue level remains limited. …”
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Exploring Mortality and Prognostic Factors of Heart Failure with In-Hospital and Emergency Patients by Electronic Medical Records: A Machine Learning Approach by Yu CS, Wu JL, Shih CM, Chiu KL, Chen YD, Chang TH

“…To improve the explainability of the AI models, Shapley Additive Explanations methods were also conducted.Conclusion: Exploring HF mortality and its patterns related to clinical risk factors by machine learning models can help physicians make appropriate decisions when monitoring HF patients’ health quality in the hospital.Keywords: mortality, risk factor, cardiovascular disease, multivariate statistical analysis, machine learning, artificial intelligence…”
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Identification of single nucleotide polymorphisms (SNPs) associated with heat stress and milk production traits in Chinese holstein cows by Jingyi Xu, Lirong Hu, Jingyang Ning, Fan Zhang, Qing Xu, Yachun Wang

“…Results In this study, we further validated the gene expression patterns and genetic effects of the three candidate genes on HS response and milk production in Chinese Holstein cows. …”
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The effect of dual inflammation on the acute phase clinical outcomes of schizophrenia patients with comorbid COVID-19 by Jiahui Zhu, Jiamin Shao, Peng Wang, Yuan Liu, Gangming Cheng, Qi Zhou, Zhuoran Li, Jiayi Li, Mingqia Wang, Zhuokai Zhang, Xuan Dong, Chuan Shi

“…Then clinical symptoms, cognitive performance, and functional assessments were conducted at recruitment. …”
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Transcriptome sequencing and Mendelian randomization analysis identified biomarkers related to neutrophil extracellular traps in diabetic retinopathy by Linlin Hao, Songhong Wang, Lian Zhang, Lian Zhang, Jie Huang, Yue Zhang, Xuejiao Qin

“…The qRT-PCR results revealed that the results of GBP2, PSAP and P2RY12 exhibited consistent expression patterns with the dataset.ConclusionThis study identified GBP2, P2RY12 and PSAP as NETs-associated biomarkers in the development of PDR, offering new insights for clinical diagnosis and potential treatment strategies for DR.…”
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Comparative metagenomics highlights the habitat-related diversity in taxonomic composition and metabolic potential of deep-sea sediment microbiota by Rui Lu, Denghui Li, Yang Guo, Zhen Cui, Zhanfei Wei, Guangyi Fan, Weijia Zhang, Yinzhao Wang, Ying Gu, Mo Han, Shanshan Liu, Liang Meng

“…Additionally, we analyzed the metabolic patterns of microbial communities in different deep-sea sediments. …”
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Maize Herbivore-Induced Volatiles Enhance Xenobiotic Detoxification in Larvae of <i>Spodoptera frugiperda</i> and <i>S. litura</i> by Peng Wang, Qiyue Zeng, Yi Zhao, Xiaomin Sun, Yongqiang Han, Rensen Zeng, Yuanyuan Song, Dongmei Chen, Yibin Lin

“…In addition, the expression of four genes encoding uridine diphosphate (UDP)-glycosyltransferases (<i>UGT33F28</i>, <i>UGT40L8</i>) and P450s (<i>CYP4d8</i>, <i>CYP4V2</i>) showed similar induction patterns in <i>S. frugiperda.</i> Cis-3-hexen-1-ol, an important component in maize HIPVs, also showed the same functions as maize HIPVs, and its exposure increased larval xenobiotic tolerance and induced the detoxification enzymes and gene expression. …”
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