Hepatitis E virus infection among blood donors in Zhengzhou by ZHAO Hongna, WEI Yueguang, YAN Lumin, TU Tiantian, WANG Shumin, WEI Yihui, WANG Yifang, ZHAO Lei, CHEN Mingjun

“…[Objective] To analyze the infection status of hepatitis E virus (HEV) among blood donors in Zhengzhou, so as to provide data support for formulating local blood screening strategies. [Methods] Random samples from blood donors from January to December 2022 were tested for HEV RNA using PCR technology. …”
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Chaetoceros muelleri sulfated polysaccharides: chain conformation, physical characteristics, and morphology by Valeria Miranda-Arizmendi, Jorge Marquez-Escalante, Agustin Rascon-Chu, Karla Martínez-Robinson, Francisco Brown-Bojorquez, Elizabeth Carvajal-Millan

“…These values suggest a flexible and compact random coil structure in CMSP. The sample's zeta potential (ζ), conductivity, and diffusion coefficient (D) were −26.43 mV, −2.07 µm cm/s V, 1.25 mS/cm, and 1.8 × 10−8 cm2/s, correspondingly. …”
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The Effect of Waxing Options on Shelf Life and Postharvest Quality of “ngowe” Mango Fruits under Different Storage Conditions by Benson Maina, Jane Ambuko, Margaret J. Hutchinson, Willis O. Owino

“…The waxed fruits were then packed in carton boxes and stored either at ambient room temperature (25°C) or cold room (12°C). Random samples of three fruits from each treatment and storage conditions were taken for measurement of attributes associated with ripening after every 3 and 7 days for ambient and cold storage, respectively. …”
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GH, IGF-1, and Age Are Important Contributors to Thyroid Abnormalities in Patients with Acromegaly by Xia Wu, Lu Gao, Xiaopeng Guo, Qiang Wang, Zihao Wang, Wei Lian, Wei Liu, Jian Sun, Bing Xing

“…The thyroid gland volume was significantly increased in patients with higher random GH (p=0.01), higher nadir GH (p=0.008), and higher IGF-1 level (p=0.018). …”
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The financial toxicity of cancer: unveiling global burden and risk factors – a systematic review and meta-analysis by Addisu Getie, Alemu Birara Zemariam, Befkad Derese Tilahun, Ribka Nigatu Haile, Tegene Atamenta Kitaw, Molla Azmeraw Bizuayehu

“…Statistical analysis was performed using STATA V.17, with catastrophic health expenditures (CHEs) pooled via a random-effects model. Heterogeneity was explored to understand variations in study outcomes. …”
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Safety profile of EZH2 inhibitors for cancer: a systematic review and meta-analysis by Zhou Zhao, Xiufeng Chen, Huayang Pang, Yan Shi, Hao Sun

“…Data on all-grade TRAEs, grade 3 or higher TRAEs, and severe TRAEs were extracted and analyzed using random-effects models. Results Our systematic review and meta-analysis included 22 studies encompassing 1,002 patients who met the inclusion criteria. …”
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Narrow Dietary Niche With High Overlap Between Snow Leopards and Himalayan Wolves Indicates Potential for Resource Competition in Shey Phoksundo National Park, Nepal by Sandesh Lamichhane, Bikram Shrestha, Bhumi Prakash Chaudhary Tharu, Raj Kumar Koirala, Bishnu Prasad Bhattarai, Pratigyan Poudel, Binaya Adhikari, Gopal Khanal

“…However, the interspecific difference in prey selection was apparent, with significant deviations between observed and expected prey use indicating non‐random prey selection relative to availability: Snow leopards exhibited a higher occurrence of wild prey items in their diet (55.28%), primarily blue sheep (Pseudois nayaur) (24.83%), whereas wolves relied predominantly on domestic livestock (67.89%), with goats (Capra hircus) accounting for over one‐fourth of their diet (29.15%). …”
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Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study by Yanfei Chen, Bing Wang, Yankai Shi, Wenhao Qi, Shihua Cao, Bingsheng Wang, Ruihan Xie, Jiani Yao, Xiajing Lou, Chaoqun Dong, Xiaohong Zhu, Danni He

“…We selected personal characteristics, clinical data and psychosocial factors as baseline predictors for AD (March 2015 to December 2021). The study utilised Random Forest and Extreme Gradient Boosting (XGBoost) algorithms alongside traditional logistic regression for modelling. …”
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Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study by Shiben Zhu, Wanqin Hu, Zhi Yang, Jiani Yan, Fang Zhang

“…Seven LLMs were evaluated on these multiple-choice questions, and 9 machine learning models, including Logistic Regression, Support Vector Machine, Multilayer Perceptron, k-nearest neighbors, Random Forest, LightGBM, AdaBoost, XGBoost, and CatBoost, were used to optimize overall performance through ensemble techniques. …”
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Prediction of Length of Stay After Colorectal Surgery Using Intraoperative Risk Factors by Daitlin Esmee Huisman, MD, Erik Wouter Ingwersen, MD, Joanna Luttikhold, MD, PhD, Gerrit Dirk Slooter, MD, PhD, Geert Kazemier, MD, PhD, Freek Daams, MD, PhD, LekCheck Study Group, Audrey Jongen, Carlo V. Feo, Simone Targa, Hidde M. Kroon, Emmanuel A. G. L. Lagae, Aalbert K. Talsma, Johannes A. Wegdam, Bob van Wely, Dirk J. A. Sonneveld, Sanne C. Veltkamp, Emiel G. G. Verdaasdonk, Rudi M. H. Roumen, Freek Daams

“…This study included patients who underwent colorectal surgery in 14 different hospitals between January 2016 and December 2020. Two distinct random forest models were developed: one solely based on preoperative variables (preoperative prediction model [PP model]) and the other incorporating both preoperative and intraoperative variables (intraoperative prediction model [IP model]). …”
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Perbedaan Status Gizi, Pola Makan, Riwayat Diare, dan Pengetahuan Gizi Seimbang pada Anak Autisme dan Non-Autisme di Jakarta by Andini Rizky Aulia, Sintha Fransiske Simanungkalit, Firlia Ayu Arini

“…Metode: Penelitian ini menggunakan desain case-control dengan 102 sampel (51 ASD dan 51 Non-ASD) yang dikumpulkan melalui cluster random sampling. Data status gizi diperoleh dari pengukuran antropometri, pola makan melalui kuesioner SQ-FFQ, dan pengetahuan gizi pengasuh serta riwayat diare dari kuesioner. …”
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A meta-analysis of risk factors for cardiovascular adverse events with anthracycline based chemotherapy in lymphoma patients by Bo Dai, Jingjing Xu, Baiyan Wang

“…Anthracyclines, hypertension, radiation therapy, diabetes, smoking, age, gender, hyperlipidemia, and obesity were meta-analyzed using a fixed or random effects model. Result Sixteen studies were included in this meta-analysis. …”
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Study on the loss of ductility of the API 5L grade b steel using the isothermal aging process by Julio César Velázquez, Manuela Diaz-Cruz, Noé Eliseo González-Arévalo, Ulises Oswaldo Solis, Arturo Cervantes-Tobón, Selene Capula-Colindres, Roman Cabrera-Sierra

“…These variables were analyzed as random variables and were fitted to a theoretical probability function. …”
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Clinical Comparative Study of Intravitreal Injection of Triamcinolone Acetonide and Aflibercept in the Treatment of Diabetic Retinopathy Cystoid Macular Edema by Yanxia Zhu, Jun Li, Songping Yu, Bangxun Mao, Jia Ying

“…Methods A total of 102 patients with DR cystoid macular edema admitted to the hospital were enrolled between July 2018 and July 2021. According to random number table method, they were divided into the control group (intravitreal injection of triamcinolone acetonide) and the observation group (intravitreal injection of aflibercept), 51 cases in each group. …”
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Outcome in patients undergoing postponed elective surgery during the COVID-19 pandemic (TRACE II): study protocol for a multicentre prospective observational study by Markus W Hollmann, Gert Jan Scheffer, Wolfgang Buhre, Sander van Kuijk, Seppe Koopman, Dianne de Korte-de Boer, Peter G Noordzij, Alice C Werger, Jennifer Breel, Carolien S E Bulte, Bas A in ‘t Veld, Carin G C L Wensing

“…Multivariable logistic mixed-effects regression analysis with a random intercept for hospital will be used to test group differences on the primary outcome.Ethics and dissemination Ethical approval was obtained from the Institutional Review Board of Maastricht University Medical Centre+ and Amsterdam UMC. …”
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Multi-model Evaluation and Bayesian Model Averaging in Quantitative Air Quality Forecasting in Central China by Haixia Qi, Shuangliang Ma, Jing Chen, Junping Sun, Lingling Wang, Nan Wang, Weisi Wang, Xiefei Zhi, Hao Yang

“…., meteorological fields, emission sources and the initial concentrations of pollutants) and therefore their forecast results tend to have large systematic and random errors. We evaluated the concentrations of six pollutants in Henan Province predicted by three air quality models—the China Meteorological Administration Unified Atmospheric Chemistry Environment (CUACE) model, the Nested Air Quality Prediction (NAQP) model and the Community Multiscale Air Quality (CMAQ) model. …”
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Smartphone applications for physical activity and sedentary behaviour change in people with cardiovascular disease: A systematic review and meta-analysis. by Kacie Patterson, Rachel Davey, Richard Keegan, Nicole Freene

“…Study quality was assessed using validated tools appropriate for each study design. Random effects model was used and the pooled mean difference between post scores were calculated. …”
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Experimental Setup and Machine Learning-Based Prediction Model for Electro-Cyclone Filter Efficiency: Filtering of Ship Particulate Matter Emission by Aleksandr Šabanovič, Jonas Matijošius, Dragan Marinković, Aleksandras Chlebnikovas, Donatas Gurauskis, Johannes H. Gutheil, Artūras Kilikevičius

“…Advances in air purification technologies, including hybrid electrostatic filtration systems, have shown promising efficiency in removing submicron particles and toxic gases, reducing energy costs. In this paper, a random forest machine learning model developed to predict particulate concentrations post-cleaning demonstrated robust performance (MAE = 0.49 P/cm³, <i>R</i>² = 0.97). …”
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Motor Learning Deficits in a Neonatal Mouse Model of Hypoxic-Ischemic Injury by Maria Marlicz, Weronika Matysik, Emily Zucker, Sarah Lee, Hannah Mulhern, Jennifer Burnsed

“…However, when navigating a wheel with a random pattern of spokes removed (complex task), HI mice took longer than sham mice to reach a plateau in performance (n = 5/group; day 1, <i>p</i> = 0.02; day 4, <i>p</i> = 0.77). …”
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Association of urban green and blue space with accelerated ageing: A cohort Study in the UK Biobank by YiNi Wang, XinYu Shi, Fei Yang, ShengYuan Wang, TianShu Han, Kun Ma

“…Results: After controlling for random effects and various types of covariates, we found that 1) populations with higher levels of UGBS exposure are associated with accelerated ageing and slowing down; 2) UGBS has the greatest impact on accelerated ageing within a 1000-m street network buffer distance; 3) Participants living in heavily polluted areas should pay more attention to UGBS; 4) Intermediary analysis found that UGBS mainly accelerates aging by reducing harm, rather than affecting the population's ability to recover and build. …”
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