Evidence of a Causal Relationship Between Body Mass Index and Immune-Mediated and Inflammatory Skin Diseases and Biomarkers: A Mendelian Randomization Study by Li Z, Zhao Y

“…Zhaoyi Li, Yibin Zhao The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 31000, People’s Republic of ChinaCorrespondence: Yibin Zhao, Email 510496772@qq.comAim: Increasing observational studies are revealing a positive correlation between body mass index (BMI) and the risk of Immune-mediated and Inflammatory Skin Diseases (IMID), however the causal relationship is not yet definite.Objective: The aim of the study was to conduct a two-sample Mendelian randomization (TSMR) to explore the potential causality between BMI, and IMID and biomarkers.Methods: The summary statistics for BMI (n = 322,154), at genome-wide significant level, were derived from the Genetic Investigation of Anthropometric Traits consortium (GIANT). …”
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Maternal PCOS status and metformin in pregnancy: Steroid hormones in 5-10 years old children from the PregMet randomized controlled study. by Liv Guro Engen Hanem, Øyvind Salvesen, André Madsen, Jørn V Sagen, Gunnar Mellgren, Petur Benedikt Juliusson, Sven Magnus Carlsen, Eszter Vanky, Rønnaug Ødegård

“…These were compared in i) placebo-exposed children versus children from the reference population (z-score zero) by the deviation in z-score by one-sample t-tests and ii) metformin versus placebo-exposed children by two-sample t-tests. …”
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Effectiveness of an mHealth Program on Reducing Blood Pressure Among Young Adults With Prehypertension: Protocol of a Pragmatic Cluster Randomized Controlled Trial by Melita Sheilini, H Manjunatha Hande, Nagaraja Ravishankar, Akshay M J, Jyothi Nayak, Ramesh Chandrababu

“…Phase 1 was completed on March 29, 2024, with data collected from 762 samples from 8 randomly selected colleges from Udupi District. …”
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Impact of acute and chronic regular exercise on arterial stiffness and reflection measures in coronary artery disease patients: A Protocol for Randomized Clinical Trial by G. Kapoor, A. Swaroop, S. Singh

“…Patients with CAD (n=105) will be selected using systematic sampling techniques and allocated randomly to one of the four treatment groups using computer-generated, random number sequence for age, sex and health status of CAD (Group-I: aerobic exercise, Group-II: resistance exercise, Group-III: combined aerobic and resistance exercise, and Group-IV: control) as per the inclusion and exclusion criteria. …”
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Stock Market Bubble Warning: A Restricted Boltzmann Machine Approach Using Volatility–Return Sequences by Mauricio A. Valle, Jaime Lavín, Felipe Urbina

“…Our model’s generative nature enables the creation of synthetic samples to analyze market periods prone to forming a bubble. …”
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Feasibility and acceptability of a pilot randomized trial of a single session of imagery rescripting targeting the primary consequences of negative experiences with eating and appe... by Nichole R. Kelly, Kelly Jean Doty, Bonnie H. C. Schrag, Shaylah Bryant, Sammy Plezia, Nicholas J. Parr, Elizabeth L. Budd

“…Single sessions of IR demonstrate promise in shifting the primary negative consequences of NEREAs in clinical samples of women. The primary objectives of this pilot trial were to evaluate the feasibility and acceptability of a remote-delivered, single session of IR and a nutrition education control group in a community sample of adults with NEREAs. …”
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How to map soil organic carbon stocks at field scale in South Africa? by Willie Herman Cloete, Gerhard du Preez, George Munnik Van Zijl

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Évaluation comparative des algorithmes d'apprentissage automatique pour la classification des types de sols à partir de caractéristiques physico-chimiques : application de Random F... by Mamadou Ndiaye, René Boissy, Mbagnick Faye, N’kpomé Styvince Romaric Kouao

“…Using physico-chemical characteristics such as texture (percentages of sand, silt, and clay), pH, organic matter, cation exchange capacity (CEC), bulk density, and water retention, this study evaluates the performance of four algorithms: Random Forest, XGBoost, SVM, and KNN. A set of 1000 random samples was used for training and testing, with cross-validation and confusion matrices to assess performance. …”
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Optimizing Methanol Injection Quantity for Gas Hydrate Inhibition Using Machine Learning Models by Mohammed Hilal Mukhsaf, Weiqin Li, Ghassan Husham Jani

“…Using a dataset of 74,000 samples, with 80% for training and 20% for testing, we enhanced model robustness with 50 Monte Carlo iterations and tenfold cross-validation. …”
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Efficient Swell Risk Prediction for Building Design Using a Domain-Guided Machine Learning Model by Hani S. Alharbi

“…Following hard-limit filtering and Unified Soil Classification System (USCS) screening, 291 valid samples were extracted from a public dataset of 395 cases. …”
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Pregnancy urine biomarkers for effectively preeclampsia prediction: a systematic review and meta-analysis by Juanhong Wu, Yingsha Yao, Ting Wang, Ting Xu, Ruoan Jiang

“…Urine as a source for test samples is noninvasive and easy to obtain. This study followed the Priority Reporting Project for Systematic Evaluation and Meta-Analysis protocol. …”
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Digital mapping of soil organic carbon stocks in the forest lands of Dominican Republic by Efraín Duarte, Erick Zagal, Juan A. Barrera, Francis Dube, Fabio Casco, Alexander J. Hernández

“…The methodology was developed using geospatial datasets available in the Google Earth Engine (GEE) platform combined with a set of 268 soil samples. Twenty environmental covariates were analyzed, including climate, topography, and vegetation. …”
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Assessment of CCMP in Capturing High Winds with Respect to Individual Satellite Datasets by Pingping Rong, Hui Su

“…The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. …”
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Machine learning-based prediction of preterm birth risk using methylation changes in neonatal cord blood CpG sites by Yuxin Feng, Ying Ni, Wenkai Wang, Fen Guo, Liyu Wang, Fan Zhu, Luyao Zhang, Ying Feng

“…Four models, including Random Forest with Lasso and Gradient Boosting with Random Forest, achieved optimal predictive performance, each with a validation accuracy of 93.75%. …”
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Comparison of Artificial Intelligence Algorithms and Remote Sensing for Modeling Pine Bark Beetle Susceptibility in Honduras by Omar Orellana, Marco Sandoval, Erick Zagal, Marcela Hidalgo, Jonathan Suazo-Hernández, Leandro Paulino, Efrain Duarte

“…Data from 5601 pest occurrence sites (2019–2023), 4000 absence samples, and a set of environmental covariates were used, with 70% for training and 30% for validation. …”
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Predictive modelling of sustainable concrete compressive strength using advanced machine learning algorithms by Tejas Joshi, Pulkit Mathur, Parita Oza, Smita Agrawal

“…The results show that ML algorithms are highly effective in predicting CS, with the random forest algorithm achieving the highest accuracy (R² = 0,95; error = 3,74). …”
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Urine Metabolomic Profiling and Machine Learning in Autism Spectrum Disorder Diagnosis: Toward Precision Treatment by Shula Shazman, Julie Carmel, Maxim Itkin, Sergey Malitsky, Monia Shalan, Eyal Soreq, Evan Elliott, Maya Lebow, Yael Kuperman

“…Methods: First-morning urine samples were collected from 52 children (32 with ASD and 20 neurotypical controls), aged 5.04 ± 1.87 and 5.50 ± 1.74 years, respectively. …”
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Investigating omega-3 fatty acids' neuroprotective effects in repetitive subconcussive neural injury: Study protocol for a randomized placebo-controlled trial. by Lauren H Beauregard, Jeffrey J Bazarian, Blair D Johnson, Hu Cheng, Gage Ellis, William Kronenberger, Philip C Calder, Zhongxue Chen, Patricia Silveyra, Patrick D Quinn, Sharlene D Newman, Timothy D Mickleborough, Keisuke Kawata

“…Omega-3 fatty acids, especially docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may have neuroprotective effects, but it remains unclear what aspects of neural health benefit from DHA+EPA when faced with subconcussive head impacts. In a randomized placebo-controlled trial, 208 soccer players will complete baseline measures including demographics, blood sampling, dietary recalls, and psychological assessment. …”
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Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003–2018 by Zu-Ming You, Yuan-Sheng Li, Fan-Shuo Meng, Rui-Xiang Zhang, Chen-Xi Xie, Zhijiang Liang, Ji-Yuan Zhou

“…However, there has been no research on machine learning (ML) modelling between multiple heavy metal exposures and PCA risk. Based on the 8022 samples from the 2003–2018 National Health and Nutrition Examination Survey (NHANES) database, we utilized the information pertaining to the concentrations of 18 blood and urinary heavy metals and minerals as well as 14 covariates. …”
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Effect of trilaciclib administered before chemotherapy in patients with extensive-stage small-cell lung cancer: A pooled analysis of four randomized studies by Ying Liu, Lin Wu, Dingzhi Huang, Qiming Wang, Chen Yang, Li Zhou, Shuguang Sun, Xiaomei Jiang, Ying Cheng

“…Approach taken, including aspects such as the sample size: This pooled analysis included one study in China and three studies in western countries, and the overall sample size was 325. …”
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