Relative Fat Mass and Physical Indices as Predictors of Gallstone Formation: Insights From Machine Learning and Logistic Regression by Deng L, Wang S, Wan D, Zhang Q, Shen W, Liu X, Zhang Y

“…The models were validated internally through k-fold cross-validation and externally using independent datasets. Furthermore, we substantiated the link between relative fat mass (RFM) and gallstone formation by employing four logistic regression models, conducting subgroup analyses, and applying restricted cubic spline (RCS) curves.Results: The logistic regression algorithm demonstrated superior predictive capability for all risk factors associated with gallstone occurrence compared to other machine learning models. …”
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Using remote sensing and machine learning to generate 100-cm soil moisture at 30-m resolution for the black soil region of China: Implication for agricultural water management by Liwen Chen, Boting Hu, Jingxuan Sun, Y. Jun Xu, Guangxin Zhang, Hongbo Ma, Jingquan Ren

“…However, soil moisture datasets or algorithms fail to simultaneously meet the requirements of multi-layer, high spatiotemporal resolution soil moisture information for large-scale agricultural production areas. …”
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Dual role of Cathepsin S in cutaneous melanoma: insights from mendelian randomization and bioinformatics analysis by Linsa Zhou, Qiang Zhou, Qian Guo, Peng Lai, Chen Rui, Wanqing Li, Xuemei Chen, Yue Zhuo, Xiaoping Zhong, Sen Lin

“…Result Using matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. …”
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Characterizing Tidal Marsh Inundation with Synthetic Aperture Radar, Radiometric Modeling, and In Situ Water Level Observations by Brian T. Lamb, Kyle C. McDonald, Maria A. Tzortziou, Derek S. Tesser

“…These findings have relevance to the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission, as threshold-based classifications of wetland inundation dynamics will be employed to verify that NISAR datasets satisfy associated mission science requirements to map wetland inundation with classification accuracies better than 80% at 1 hectare spatial scales.…”
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Cross-agency working when conducting a pragmatic RCT for older victims of crime: our experiences and lessons learned by Marc Serfaty, Jessica Satchell, Gloria K. Laycock, Chris R. Brewin, Marta Buszewicz, Gerard Leavey, Vari M. Drennan, Jonathan Cooke, Anthony Kessel

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Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings by Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, Jong Wan Hu, Mohamed Elsharawy

“…Two deep learning methods viz deep belief network (DBN) and deep neural network (DNN), and five machine learning methods namely feedforward neural network, extreme learning machine, weighted extreme learning machine, random forest, and gradient boosting machine were evaluated, and compared in predicting the design wind pressures on tall buildings. Wind tunnel datasets, used in the current study to develop the proposed computing models, were collected from testing three tall buildings having the same full-scale horizontal dimensions of (40 m and 80 m) and different heights of (80 m, 120 m and 160 m). …”
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The impact of the COVID-19 pandemic on the research activity and working experience of clinical academics, with a focus on gender and ethnicity: a qualitative study in the UK by Carmen Soto, Jessica Elizabeth Morgan, Paul Crampton, Paul Alexander Tiffin, Gabrielle M Finn, Amelia Kehoe, Ellie Taylor, John AG Buchanan, Abisola Olatokunbo Balogun

“…Objective To investigate the impact of the COVID-19 pandemic on the research activity and working experience of clinical academics, with a focus on gender and ethnicity.Design Qualitative study based on interviews and audio/written diary data.Setting UK study within clinical academia.Participants Purposive sample of 82 clinical academics working in medicine and dentistry across all career stages ranging from academic clinical fellows and doctoral candidates to professors.Methods Qualitative semistructured interviews (n=68) and audio diary data (n=30; including 16 participants who were also interviewed) collected over an 8-month period (January–September 2020), thematically analysed.Results 20 of 30 (66.6%) audio diary contributors and 40 of 68 (58.8%) interview participants were female. …”
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Comprehensive Analysis of Competing Endogenous RNA Network Focusing on Long Noncoding RNA Involved in Cirrhotic Hepatocellular Carcinoma by Yuli Zhang, Dinggui Chen, Miaomiao Yang, Xianfeng Qian, Chunmei Long, Zhongwei Zheng

“…The lncRNA, miRNA, and mRNA expression datasets were obtained from Gene Expression Omnibus and The Cancer Genome Atlas. …”
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Genetic variation reveals the therapeutic potential of BRSK2 in idiopathic pulmonary fibrosis by Zhe Chen, Mingyang Tang, Nan Wang, Jiangjiang Liu, Xiaoyan Tan, Haitao Ma, Jing Luo, Kai Xie

“…Methods We employed Mendelian randomization (MR) with three genome-wide association studies and four quantitative trait loci datasets to identify key driver genes for IPF. Prioritized targets were evaluated for respiratory insufficiency and transplant-free survival. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Performance of the prognostic model, DCRGS, for the prognostic evaluation, was assessed using a multiple time-dependent receiver operating characteristic (ROC) curve, the R package, “timeROC”, and validated using GEO datasets. Results Analysis of scRNA-seq data showed that there is a significant upregulation of LGALS9 expression in DCs isolated from malignant pleural effusion samples. …”
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Characterising melanoma diagnostic pathways for patients in routine practice using administrative health data in Ontario, Canada: a population-based study by Frances C Wright, Timothy P Hanna, Patti A Groome, Nicole J Look Hong, Meaghan E Mavor, Yuka Asai, Hugh Langley

“…Objective To characterise diagnostic pathways for patients with melanoma in routine practice and compare patient, disease and diagnostic interval (DI) characteristics across pathways.Design Descriptive cross-sectional study using administrative health data.Setting Population-based study in Ontario, Canada.Participants Patients with melanoma diagnosed from 2007 to 2019.Main outcome measures We used latent class cluster analysis to create clusters of patients with similar diagnostic experiences to characterise diagnostic pathways in routine practice. …”
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Role of Aging in Ulcerative Colitis Pathogenesis: A Focus on ETS1 as a Promising Biomarker by Ni M, Peng W, Wang X, Li J

“…In this study, we explored the role of aging-related genes (ARGs) in UC pathogenesis and diagnosis prediction.Methods: Gene expression data were obtained from four independent datasets (GSE75214, GSE87466, GSE94648, and GSE169568) in the GEO database, and ARGs were derived from multiple public databases. …”
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Desain Faktorial untuk Pembuktian Teori Masters dalam Penentuan Jumlah Lapisan dan Neuron Tersembunyi pada Peramalan Multivariat dengan Jaringan Syaraf Tiruan by Dwi Ayu Lusia, Awalludiyah Ambarwati

“…The more hidden layers will obtain better RMSE in both training dan testing datasets. Thus, the Masters Theory which states that there is no reason to use more than two hidden layers, proved to be invalid. …”
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Identification and Verification of Novel Biomarkers Involving Rheumatoid Arthritis with Multimachine Learning Algorithms: An In Silicon and In Vivo Study by Fucun Liu, Juelan Ye, Shouli Wang, Yang Li, Yuhang Yang, Jianru Xiao, Aimin Jiang, Xuhua Lu, Yunli Zhu

“…We retrieved RA-related and pan-cancer information datasets from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. …”
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Phylogeography and genetic diversity of Ulmus elongata (Ulmaceae), a Tertiary relict tree with extremely small populations (PSESP) by Yakun Wang, Xiankun Wang, Junyuan Wu, Jun Yang, Yanpei Liu, Peng Guo, Fude Shang, Nan Lin

“…Utilizing chloroplast genome datasets, we found that U. elongata exhibited remarkably low nucleotide diversity and gene flow (π = 0.00013, Nm = 0.03). …”
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A Realistic Approach to Calculating the Nitrogen Use Efficiency Index in Cereals with Winter Wheat (<i>Triticum aestivum</i> L.) as an Example by Witold Grzebisz, Jarosław Potarzycki

“…Two groups of N pools (soil <i>N_min</i> and N mass in the wheat biomass) were determined in BBCH 30, 58, and 89. These core datasets were used to calculate total N input (<i>N_in</i>) to the soil/crop system during the two main periods of WW growth: (1) before (vegetative mega-phase, V) and (2) after wheat flowering (reproductive mega-phase, R, or grain filling period, GFP). …”
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The Impact of Lockdown on Air Quality in Pakistan during the COVID-19 Pandemic Inferred from the Multi-sensor Remote Sensed Data by Rehana Khan, Kanike Raghavendra Kumar, Tianliang Zhao

“…We focused on assessing the significant changes of pollutant concentrations during March–May for the years 2019 and 2020 utilizing the satellite datasets observed from the Moderate Resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounder (AIRS), and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis data. …”
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Insights gained through real-time monitoring of porcine reproductive and respiratory syndrome virus and description of temporal trends based on laboratory data in Ontario, Canada by Tatiana Petukhova, Maria Spinato, Tanya Rossi, Michele T. Guerin, Cathy A. Bauman, Pauline Nelson-Smikle, Davor Ojkic, Zvonimir Poljak

“…The final optimized, aggregated, and anonymized datasets were exported to the Tableau server and were used to design dynamic real-time visualizations with Tableau Desktop v.2021.4. …”
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LURAP1L-AS1 long noncoding RNA promotes breast cancer progression and associates with poor prognosis by Radhakrishnan Vishnubalaji, Dania Awata, Nehad M. Alajez

“…Bioinformatics analysis predicted LURAP1L-AS1 to function as a competitive endogenous RNA (ceRNA), sponging key microRNAs, such as miR-7a-5p, miR-101-3p, miR-181a-5p, and miR-27a-3p, thereby modulating oncogenes including EZH2, MCL1, and KRAS, which are linked to increased cancer cell survival, proliferation, and metastasis.In addition to its role in TNBC, correlation analysis using breast cancer patient datasets revealed a significant association between LURAP1L-AS1 and ESR1 expression, suggesting its broader impact across breast cancer subtypes. …”
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Tumor-Stroma Ratio is a Critical Indicator of Peritoneal Metastasis in Gastric Cancer by Zhong L, Huang H, Hou D, Zhou S, Lin Y, Yu Y, Yu J, Han F, Xie L

“…Additionally, the correlation between TSR and PM in GC was analyzed using Gene Expression Omnibus (GEO) datasets. To validate TSR’s clinical potential in diagnosing PM, 640 GC patients from two medical centers were enrolled. …”
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