Nailfold Capillaroscopy in Early Stages of Mixed Connective Tissue Disease in a Sample of Egyptian Patients by Yasser A Elmotaleb Gazar, Hesham Salah Hamoud, Sherif Mohamed Ismail

“…Therefore, it aids in the recognition of alternations in nailfold capillaries making an early prediction of course of illness in MCTD patients possible and suggests a potential ability to differentiate from early SSc, thus helps in preventing morbidities and sequelae of the disease.…”
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Model Evaluation and Uncertainty Analysis of PM2.5 Components over Pearl River Delta Region Using Monte Carlo Simulations by Qian Wu, Xiao Tang, Lei Kong, Zirui Liu, Duohong Chen, Miaomiao Lu, Huangjian Wu, Jin Shen, Lin Wu, Xiaole Pan, Jie Li, Jiang Zhu, Zifa Wang

“…Abstract Sulfate, nitrate, ammonium, organic carbon (OC) and black carbon (BC) are the key components of PM2.5, but predicting their concentrations remains a challenge because of high uncertainties in the modeling. …”
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Multiomics approach identifies dysregulated lipidomic and proteomic networks in Parkinson’s disease patients mutated in TMEM175 by Federica Carrillo, Marco Ghirimoldi, Giorgio Fortunato, Nicole Piera Palomba, Laura Ianiro, Veronica De Giorgis, Shahzaib Khoso, Tiziana Giloni, Sara Pietracupa, Nicola Modugno, Elettra Barberis, Marcello Manfredi, Teresa Esposito

“…Altogether, these data provide novel insights into the molecular and metabolic alterations underlying TMEM175 mutations and may be relevant for PD prediction, diagnosis and treatment.…”
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Galaxy @Sciensano: a comprehensive bioinformatics portal for genomics-based microbial typing, characterization, and outbreak detection by Bert Bogaerts, Julien Van Braekel, Alexander Van Uffelen, Jolien D’aes, Maxime Godfroid, Thomas Delcourt, Michael Kelchtermans, Kato Milis, Nathalie Goeders, Sigrid C. J. De Keersmaecker, Nancy H. C. Roosens, Raf Winand, Kevin Vanneste

“…These pipelines include quality control, de novo assembly, sequence typing, antimicrobial resistance prediction and several relevant species-specific assays. …”
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Automated on-site broiler live weight estimation through YOLO-based segmentation by Mahmoud Y. Shams, Wael M. Elmessery, Awad Ali Tayoush Oraiath, Ahmed Elbeltagi, Ali Salem, Pankaj Kumar, Tamer M. El-Messery, Tarek Abd El-Hafeez, Mohamed F. Abdelshafie, Gomaa G. Abd El-Wahhab, Ibrahim S. El-Soaly, Abdallah Elshawadfy Elwakeel

“…The YOLOv8 architecture builds a model that demonstrates improved and trustworthy results in broiler weight prediction, achieving a mean average precision across a range of intersection over union thresholds from 50 % to 95 % of 0.829. …”
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Mosaic loss of the Y chromosome in human neurodegenerative and oncological diseases by I. L. Kuznetsova, L. I. Uralsky, T. V. Tyazhelova, T. V. Andreeva, E. I. Rogaev

“…The development of new biomarkers for prediction and early detection of human diseases, as well as for monitoring the response to therapy is one of the most relevant areas of modern human genetics and genomics. …”
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Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network by Zehua Li, Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li

“…This improvement can enhance the feature extraction ability of the Backbone network, as the new modules can fully utilize the information of all dimensions of the convolutional kernel. (2) An Efficient Channel Attention (ECA) module is added to the Neck for improving the network’s capability to extract deep semantic feature information of the detection target. (3) In the Bbox module of the prediction head, the Complete Intersection over Union (CIoU) loss function is replaced by the Weighted Intersection over Union version 3 (WIoUv3) loss function to improve the convergence speed of the bounding box loss function and reduce the convergence value of the loss function. …”
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The Utility of Synovial Fluid Interleukin-10 in Diagnosing Chronic Periprosthetic Joint Infection: A Prospective Cohort Study by Zou Y, Yang Y, Yang J, Zhang Y, Zhao C, Qin L, Hu N

“…Adding SF IL-10 to traditional models improved risk prediction for chronic PJI (net reclassification improvement [NRI]: 0.167 [0.023 ~ 0.312]; integrated discrimination improvement [IDI]: 0.160 [0.096 ~ 0.224]).Conclusion: Higher SF IL-10 levels were significantly associated with chronic PJI in revision surgery patients, and incorporating SF IL-10 into the traditional risk model enhanced its predictive value for chronic PJI in these patients.Keywords: periprosthetic infection, synovial fluid, interleukin-10, C-reactive protein, erythrocyte sedimentation rate…”
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Amorphization and siliconization of silicon carbide as a first wall material by Aritra De, Jerome Guterl, Zachary Bergstrom, Tyler Abrams, Gregory Sinclair, John David Elder, Dmitry Rudakov

“…The understanding and prediction of silicon carbide (SiC) material evolution exposed to SOL plasma conditions is of prime interest because SiC represents a promising main chamber wall plasma-facing material for next-step fusion devices (low hydrogenic diffusion, good mechanical and thermal properties under neutron irradiation). …”
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Identification of quality markers and mechanisms of Anzi Tiaochong Fang in the treatment of antiphospholipid syndrome-related recurrent pregnancy loss: chemical analysis, network p... by Shan He, Fei Ma, Jia Li, Da-yan Liu, Zhi-wei Wang, Peng-dian Chen, Jia-man Wu, Hong Chang, Yan Ning

“…APS-RPL targets were identified using databases such as HERB, similarity ensemble approach, PharmMapper, Swiss Target Prediction, Gene Expression Omnibus, Genecards, and DisGeNET. …”
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Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images by Yida Wang, Ankang Gao, Hongxi Yang, Jie Bai, Guohua Zhao, Huiting Zhang, Yang Song, Chenglong Wang, Yong Zhang, Jingliang Cheng, Guang Yang

“…Abstract Prediction of isocitrate dehydrogenase (IDH) mutation status and epilepsy occurrence are important to glioma patients. …”
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A novel method to determine background concentrations and spatial distributions of heavy metals in soil at large scale using machine learning coupled with remote sensing-terrain at... by Magboul M. Sulieman, Fuat Kaya, Abdullah S. Al-Farraj, Eric C. Brevik

“…. • The proposed method is a novel way to predict soil HMs and their spatial distribution over large areas. • Remote sensing/digital elevation models (DEMs)-derived ECOVs are useful for predicting and digitally mapping soil HMs, thus important for future environmental monitoring studies. • Explainable algorithms (i.e., RF and SMLR) are able to utilize ECOVs for HMs prediction and to establish background concentrations over large areas.Therefore, the combination of machine learning and RS/DEMs-based ECOVs is crucial to overcome the disadvantages of HMs determination via conventional methods.…”
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Validation of the Acute Physiology and Chronic Health Evaluation (APACHE) II and IV Score in COVID-19 Patients by Jeroen Vandenbrande, Laurens Verbrugge, Liesbeth Bruckers, Laurien Geebelen, Ester Geerts, Ina Callebaut, Ine Gruyters, Liesbeth Heremans, Jasperina Dubois, Bjorn Stessel

“…Acute Physiology and Chronic Health Evaluation (APACHE) scoring systems are designed for ICU mortality prediction. This study aims to validate APACHE IV in COVID-19 patients admitted to the ICU. …”
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Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase‐CYP substrates by Nihan Izat, Jayaprakasam Bolleddula, Pasquale Carione, Leticia Huertas Valentin, Robert S. Jones, Priyanka Kulkarni, Darren Moss, Vincent C. Peterkin, Dan‐Dan Tian, Andrea Treyer, Karthik Venkatakrishnan, Michael A. Zientek, Jill Barber, J. Brian Houston, Aleksandra Galetin, Daniel Scotcher

“…In conclusion, this study provides a novel PBPK‐based framework for predicting AO‐mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO‐CYP substrates within a totality‐of‐evidence approach.…”
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Body Composition and Basal Metabolic Rate in Women with Type 2 Diabetes Mellitus by Marina de Figueiredo Ferreira, Filipe Detrano, Gabriela Morgado de Oliveira Coelho, Maria Elisa Barros, Regina Serrão Lanzillotti, José Firmino Nogueira Neto, Emilson Souza Portella, Haydée Serrão Lanzillotti, Eliane de Abreu Soares

“…The aim of this study was to determine which of the seven selected equations used to predict basal metabolic rate most accurately estimated the measured basal metabolic rate. …”
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Clinical analysis and risk factors associated with poor prognosis in nontuberculous mycobacterial infection by Jinjing Chai, Sujie Zhang, Chong Ma, Qimin Mei, Tao Liu, Jihai Liu, Yecheng Liu, Huadong Zhu

“…The area under the curve (AUC) values for NLR and neutrophil-to-monocyte-plus-lymphocyte-ratio (NMLR) were 0.751 and 0.763 with optimal cut-off values of 9.50 and 3.83, respectively, for prediction of mortality in patients with NTM disease.…”
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Artificial intelligence-driven identification and mechanistic exploration of synergistic anti-breast cancer compound combinations from Prunella vulgaris L.-Taraxacum mongolicum Han... by Chunlai Feng, Jiaxi Cheng, Mengqiu Sun, Chunxue Qiao, Qiuqi Feng, Naying Fang, Yingying Ge, Mengjie Rui

“…A deep learning-based prediction model, DeepMDS, was applied to predict synergistic anti-breast cancer multi-compound combinations. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
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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

“…Multi-layer soil moisture is an important factor in predicting agricultural droughts and waterlogging, with significant implications for the growth, development, and yield prediction of rain fed crops. …”
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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

“…Additionally, increased CTSS may provide a basis for biomarker prediction of CM prognosis, immune status and immunotherapy.…”
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