Risk Factors for Postoperative Nausea and Vomiting After TACE: A Prospective Cohort Study by Yuzhu Wang, Xin Zhou, Guoping Li, Qianzhou Lv, Xiaoyu Li, Zhiping Yan

“…Chronic gastritis, pain, epirubicin, and the dosage of lipiodol were independent risk factors for PONV. The risk prediction model that was constructed according to the aforementioned factors demonstrated good discriminatory capacity for predicting the risk of post-TACE PONV, which can improve the recognition of medical providers, and has a good ability to prevent and treat nausea and vomiting.…”
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Scrutinizing the evidence of anthracene toxicity on adrenergic receptor beta-2 and its bioremediation by fungal manganese peroxidase via in silico approaches by Muhammad Naveed, Khadija Khatoon, Tariq Aziz, Rida Naveed, Muhammad Nouman Majeed, Maida Salah Ud Din, Tayyab Javed, Ayaz Ali Khan, Abdullah F. Alasmari

“…This study aims to alleviate the adverse environmental effects of anthracene through fungal degradation, focusing on bioremediation approaches using bioinformatics. Toxicity prediction using Pro-Tox 3.0 identified anthracene as a compound of toxicity class 4 with a LD50 of 316 mg/kg. …”
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Constraints of S–Pb–Sr Isotope Compositions and Rb–Sr Isotopic Age on the Origin of the Laoyingqing Noncarbonate-Hosted Pb–Zn Deposit in the Kunyang Group, SW China by Hongsheng Gong, Runsheng Han, Peng Wu, Gang Chen, Lingjie Li

“…This study is aimed at investigating whether the Laoyingqing deposit has the same ore-forming age and type as other Pb–Zn deposits related to the Pb–Zn metallogenic system and prospecting prediction of the deep and peripheral areas of the deposits in the SYGT. …”
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The Bony Density of the Pedicle Plays a More Significant Role in the Screw Anchorage Ability Than Other Regions of the Screw Trajectory by Zan Chen, Yue Chen, Jiajun Zhou, Yanwei He, Jingchi Li

“…Specifically, the AUC of screw loosening prediction was notably higher when using HU values of the pedicle compared to other methods (AUC in the pedicle > 0.9 and in the screw insertion position > 0.7). …”
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Blepharoplasty: historical aspects, terminology, and modern ideas by A.D. Kazantsev, E.P. Kazantseva, I.B. Alekseev

“…Modern, highly effective diagnostic tools and professional medical equipment allow for an accurate prediction of surgical outcome, thereby emphasizing the importance of the conception "desired changes — realistic expectations". …”
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The prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in colorectal cancer and colorectal anastomotic leakage patients: a retrospe... by Nuo Xu, Jian-Xin Zhang, Jia-Jie Zhang, Zhuo Huang, Lian-Chun Mao, Zhi-Yong Zhang, Wei-Dong Jin

“…Nomogram and calibration curve analysis will further improve the accuracy of OS and DFS prediction.…”
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Clinical significance of hyperuricaemia in biopsy-proven diabetic kidney disease ━ a single-centre retrospective study by Jin Yu, Jin Yu, Xiao Tu, Xiao Tu, Kunyue Xu, Xuanli Tang, Xuanli Tang, Yufan Wu, Xue Jiang, Xue Jiang

“…In the testing and training sets, the AUCs at 1, 3, and 5 years were 0.888, 0.939, and 0.886 and 0.947, 0.867, and 0.905, respectively.ConclusionThe clinicopathologic manifestation of DKD patients with hyperuricaemia was much more severe, and hyperuricaemia predicted a worse renal prognosis. A new renal prognosis prediction model including SUA was constructed for DKD with higher accuracy.…”
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Role of B7H4 and Fas in regulation of trophoblast cells and development of pre-eclampsia: a cross-sectional study by Xiujuan Dong, Cuicui Nie, Yanli Yin, Haixia Xu, Yanxia Zhang, Lihua Han, Congcong Xu

“…The upstream regulators of B7H4 in trophoblasts were predicted and estimated using a luciferase reporter assay. …”
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Association of preoperative ultrasonographic parameters of the contralateral kidney with long-term serum creatinine in cats treated for unilateral ureteral obstruction by Diego Pulido Vega, Jérémie Ficheroulle, Jérémie Ficheroulle, Mathieu Manassero, Jeremy Mortier, Christelle Maurey

“…IntroductionPrediction of renal recovery after surgical management of feline unilateral ureteral obstruction (UO) is crucial to guide therapeutic decisions, but predictors of this outcome are still lacking. …”
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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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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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