Comparing the efficacy of different methods in assessing cervical stromal invasion in endometrial carcinoma: a retrospective study of 2,020 patients by Ying Yang, Ying Yang, Zhijun Ye, Zhijun Ye, Yifei Zhao, Yifei Zhao, Zhengyu Li, Zhengyu Li

“…Combining MRI and biopsy could improve diagnostic sensitivity, aiding in clinical decision making and prognostic prediction. Comprehensive consideration of high-risk factors for the occurrence of CSI may aid the diagnosis. …”
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Profiling of pathogenic variants in Japanese patients with sarcoglycanopathy by Rui Shimazaki, Yoshihiko Saito, Tomonari Awaya, Narihiro Minami, Ryo Kurosawa, Motoyasu Hosokawa, Hiroaki Ohara, Shinichiro Hayashi, Akihide Takeuchi, Masatoshi Hagiwara, Yukiko K. Hayashi, Satoru Noguchi, Ichizo Nishino

“…The structures of transcripts with aberrant splicing were also determined by RT-PCR, RNA-seq, and in silico prediction. Results We identified biallelic variants in SGC genes in 53 families, including three families with LGMDR6, which had not been identified in Japan so far. …”
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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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Risk, incidence and predictors of venous thromboembolism among patients attending the emergency department of tertiary care hospitals in Addis Ababa city, Ethiopia: a multicentre p... by Desalew Mekonnen, Alemseged Beyene Berha, Worku Degefa, Minyahil Alebachew Woldu

“…More than two-thirds (70.64%) of patients were at high risk of developing VTE according to the Padua Risk Prediction Score. Eighteen patients (4.3%) were diagnosed with VTE during their emergency stay. …”
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Pivotal role of MiRNA's in malignant transformation of Oral Submucous Fibrosis by J.H. Shazia Fathima, Selvaraj Jayaraman, Asma Abdullah Nurul, Ramya Sekar, Inamul Hasan Madar, Logalakshmi Thirumani, Nazmul Huda Syed

“…Artificial Intelligence contributes to miRNA research, enhancing target prediction and understanding disease mechanisms. Continued research is crucial for identifying additional OSMF-related miRNAs and refining diagnostic and therapeutic strategies. …”
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Mechanism of <italic>Hindu Datura</italic> in the Treatment of Rheumatoid Arthritis from the Perspective of Network Pharmacology by Changlong FU, Yangyang MEI, Xihai LI, Zhiwei QIU, Changxing CHEN, Chunsong ZHENG

“…Objective:To construct the active component target of <italic>Hindu datura</italic> and the disease target of rheumatoid arthritis by using network pharmacology, to predict the specific molecular signal and pathway of <italic>hindu datura</italic> in the treatment of rheumatoid arthritis, and to analyze its potential therapeutic target and molecular mechanism.Methods:All the chemical components of <italic>hindu datura</italic> were summarized and screened through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)database, retrieval was performed with the preset oral bioavailability(OB)≥30%and drug like(DL)≥0.18.Uniprot database was used to screen the entire correlation basis of the effective chemical compound.After screening the disease target with"rheumatoid arthritis"as the retrieval word using GeneCards and OMIM database, the superimposed target area between the drug target of <italic>hindu datura</italic> and the disease target of rheumatoid arthritis was summarized and analyzed, and it could be used as the prediction target gene of <italic>hindu datura</italic> for treating rheumatoid arthritis.Network targets were constructed and analyzed for the exported data based on Cytoscape 3.7.1 software and STRING 7.8 database.Finally, GO functional enrichment analysis and KEGG signal pathway analysis were performed to further screen the main targets and signal pathways.Results:①Through screening and analysis, 27 effective compounds, 318 corresponding target genes and 125 predicted target genes were obtained for the treatment of rheumatoid arthritis.②The core genes in PPI network mainly included JUN, AKT1, RELA, MAPK1, etc.③GO functional enrichment analysis showed that the biological process(BP)for the treatment of rheumatoid arthritis by <italic>hindu datura</italic> mainly involves response to lipopolysaccharide, response to lipopolysaccharide, response to molecule of bacterial origin, response to metalion, response to oxidative stress, response to steroid hormone, cellular response to oxidative stress, reactive oxygen species metabolic process, response to oxygen levels, etc..The cell component(CC)consisted of membrane raft, membrane region, plasma membrane raft and presynaptic membrane; molecular functions(MF)mainly involved the nuclear receptor activity, transcription factor activity(direct ligand regulated sequence-specific DNA binding), steroid hormone receptor activity, cytokine receptors, cytokine activity, DNA-binding transcription activator activity, RNA polymeraseⅡtranscription factor binding, kinase regulator activity, receptor ligand activity, etc.The analysis of KEGG signaling pathway showed that the obvious pathway of <italic>hindu datura</italic> in the treatment of rheumatoid arthritis may involve IL-17 signaling pathway, TNF signal pathway, HIF-1signalpathway, Toll-like receptor signal pathway, etc.Conclusion:The potential mechanism of <italic>hindu datura</italic> for the treatment of rheumatoid arthritis is to exert anti-inflammatory, analgesic and antioxidant effects, which involve a number of interactive signal pathways.…”
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The triglyceride–glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with... by Chenyang Li, Zixi Zhang, Xiaoqin Luo, Yichao Xiao, Tao Tu, Chan Liu, Qiming Liu, Cancan Wang, Yongguo Dai, Zeying Zhang, Cheng Zheng, Jiafeng Lin

“…The incorporation of the TyG index or its derivatives into predictive models modestly improved the prediction performance for mortality outcomes. …”
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Neuroimaging predictors of malignant brain oedema after thrombectomy in ischemic stroke: a systematic review and meta-analysis by Linrui Huang, Xindi Song, Jingjing Li, Yanan Wang, Xing Hua, Meng Liu, Ming Liu, Simiao Wu

“…We included studies investigating neuroimaging predictors or prediction models for MBE after thrombectomy. We estimated effect size for the association between predictors and MBE by odds ratios (ORs) or standardized mean differences (SMDs), and pooled results using random-effects modelling.Results We included 19 studies (n = 6007) with 17 neuroimaging factors and 5 models. …”
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Rapid Detection of Hybrid Maize Parental Lines Using Stacking Ensemble Machine Learning by M. Aqil, M. Azrai, M. J. Mejaya, N. A. Subekti, F. Tabri, N. N. Andayani, Rahma Wati, S. Panikkai, S. Suwardi, Z. Bunyamin, E. Roy, M. Muslimin, M. Yasin, E. Prakasa

“…This indicates that the prediction errors were caused by highly similar data features among female and off-type images. …”
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High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity by Meihan Liu, Huimin Lei, Xingwang Wang, Paula Paredes

“…These findings enable more accurate ET modeling and prediction in arid regions and provide valuable insights for water resource management, particularly irrigation scheduling, in areas affected by salt-induced stress. …”
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Alleviating small sample problem in continuous forest monitoring with remote sensing-assisted Copulas by Xinjie Cheng, Zhengyang Hou, Annika Kangas, Jean-Pierre Renaud, Hao Tang, Weisheng Zeng, Qing Xu

“…Four main conclusions are relevant: for both Burkina Faso (BF) and Genhe (GH) study area, (1) Copulas outperforms WLS in modeling and prediction, both in terms of mean values and maximum/minimum values; (2) Copulas consistently demonstrates superior performance and precision across varying sample sizes compared to the WLS with MA estimators; (3) a straightforward sample size optimization approach reveals that variance estimates of Copulas remain lower than those of WLS as the sample size decreases in monitoring surveys; (4) Copulas requires about 20% smaller sample size than WLS does when achieving a specified precision, suggesting enhanced efficiency. …”
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Unveiling Cuproptosis-Driven Molecular Clusters and Immune Dysregulation in Ankylosing Spondylitis by Wei B, Wang S, Li S, Gu Q, Yue Q, Tang Z, Zhang J, Liu W

“…The eXtreme Gradient Boosting (XGB) model showed the highest predictive accuracy, achieving an area under the receiver operating characteristic curve (AUC) of 0.725, and 5-gene prediction models were established. …”
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Two new strains of Streptomyces with metabolic potential for biological control of pear black spot disease by Yi-Huang Chen, Jia-Xing Zhang, Yan Min, Yang Liu, Jian-Ming Wang, Lin-Quan Bai, Xiao-Xia Luo

“…The resistance genes of strain TRM 76172 were classified as macrolides, and genomic prediction revealed the biosynthetic pathway of the active compound Candidin. …”
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Efficacy and safety of dexamethasone or triamcinolone in combination with anti-vascular endothelial growth factor therapy for diabetic macular edema: A systematic review and meta-a... by Bo Zhou, Hua Liu, Feng Xiong

“…The assessment of heterogeneity was conducted via Cochran's Q test, I2 statistics, and the implementation of a 95% prediction interval (PI). All analyses were performed by R 4.3.1, Stata 12.0, and TSA v0.9.5.10 Beta software.…”
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Identification of Five m6A-Related lncRNA Genes as Prognostic Markers for Endometrial Cancer Based on TCGA Database by Li Shan, Ye Lu, Cheng-Cheng Xiang, Xiaoli Zhu, Er-Dong Zuo, Xu Cheng

“…Five major lncRNAs associated with m6A were screened out, and risk score modeling was used for UCEC prognosis prediction. High risk scores were associated with a shorter OS. …”
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Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals&#x2019; Electroencephalography Signals by Illia Pidvalnyi, Anna Kostenko, Oleksandr Sudakov, Dmytro Isaev, Oleksandr Maximyuk, Oleg Krishtal, Olena Iegorova, Ievgen Kabin, Zoya Dyka, Steffen Ortmann, Peter Langendorfer

“…Detection and prediction of the onset of seizures are among the most challenging problems in epilepsy diagnostics and treatment. …”
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Discovery of robust and highly specific microbiome signatures of non-alcoholic fatty liver disease by Emmanouil Nychas, Andrea Marfil-Sánchez, Xiuqiang Chen, Mohammad Mirhakkak, Huating Li, Weiping Jia, Aimin Xu, Henrik Bjørn Nielsen, Max Nieuwdorp, Rohit Loomba, Yueqiong Ni, Gianni Panagiotou

“…We identified highly specific microbiome signatures through building accurate machine learning models (accuracy = 0.845–0.917) for NAFLD with high portability (generalizable) and low prediction rate (specific) when applied to other metabolic diseases, as well as through a community approach involving differential co-abundance ecological networks. …”
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Modelos de perfil de velocidad para evaluación de consistencia del trazado en carreteras de la provincia de Villa Clara, Cuba Speed profile models for evaluation of design consiste... by René A. García Depestre, Domingo E. Delgado Martínez, Eduardo E. Díaz García

“…Cuba does not have proprietary models that consider the characteristics of the roads and drivers, so it is necessary to develop predictive models for the evaluation of design consistency. …”
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A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity by Victoria Shevchenko, R. Austin Benn, Robert Scholz, Wei Wei, Carla Pallavicini, Ulysse Klatzmann, Francesco Alberti, Theodore D. Satterthwaite, Demian Wassermann, Pierre-Louis Bazin, Daniel S. Margulies

“…Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. …”
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The Impact of Amniotic Fluid Interleukin-6, Interleukin-8, and Metalloproteinase-9 on Preterm Labor: A Narrative Review by Theodoros Karampitsakos, Despoina Mavrogianni, Nikolaos Machairiotis, Anastasios Potiris, Periklis Panagopoulos, Sofoklis Stavros, Panos Antsaklis, Peter Drakakis

“…MMP-9 gene variations and protein levels showed significant predictive value for membrane rupture and labor onset. …”
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