Results 221 to 230 of about 452,858 (310)

A Computational Strategy for Identifying Self‐Assembling Food‐Derived Molecules for Antiparasitic Nanotherapy

Advanced Science, EarlyView.
An integrated computational screening strategy identified ursolic acid (UA) and 18β‐glycyrrhetinic acid (18βGA) as a self‐assembling food‐derived molecular pair. The resulting carrier‐free nanoparticles (UA‐18βGA) showed synergistic antiparasitic activity, reduced combined toxicity, and host‐protective anti‐inflammatory effects in zebrafish and murine ...
Shenye Qu, Ting Wang, Jietao Liu, Jiacheng Qin, Bin Yang, Yihang Liu, Pengfei Li, Gaoxue Wang, Fei Ling   +8 more
wiley   +1 more source

Risk prediction for chronic atrophic gastritis using a random forest model: A multicenter study. [PDF]

World J Gastrointest Oncol
Cao H, Han JL, Wu H, Si SP, Ding LJ, Ji L, Zhang HZ, Yin J, Zhou ZY, Zhang YN, Lv ZF, Tian WY, Zhan Q, Wang H, An FM.   +14 more
europepmc   +1 more source

Feature Selection with the Boruta Package

This article describes a R package Boruta, implementing a novel feature selection algorithm for finding \emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm.
Witold R. Rudnicki, Miron B. Kursa
core  

A Hydrogen‐Releasing Nanozyme Engineers a Mitochondrial ROS Amplifier for Self‐Sustaining Catalytic Immunotherapy

Advanced Science, EarlyView.
We developed a RhPd‐H nanozyme that integrates enhanced POD‐mimetic catalytic activity with thermally triggered H2 release. H2 shields and reprograms mitochondria to continuously leak endogenous ·O2−. This dual‐path ROS spatially and temporally disrupts redox homeostasis, inducing persistent oxidative stress for tumor suppression and antitumor immunity,
Mingfan Shi, Jingrui Cao, Tong Wu, Guang Yang, YaWen Yang, Shixin Zhang, Wenwen Su, Hongyu Chu, Yangyang Zhao, Shan Jiang, Qiong Wu, Dongxu Jiao, Fangfang Chen   +12 more
wiley   +1 more source

BRMDA: prediction model for potential microbe-drug associations based on bilinear attention networks and random forest. [PDF]

Front Genet
Yu G, Chen F, Chen H, Tang S, Liang M, Liu X, Zeng B, Wang L.   +7 more
europepmc   +1 more source

Deciphering Short‐Range Order in 2D Transition Metal Dichalcogenides: From Origin to Multi‐Scale Property Modulation

Advanced Science, EarlyView.
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu, Linggang Zhu, Jian Zhou, Zhimei Sun   +3 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Application of XGBoost and Random Forest algorithms for body weight prediction in Blackbelly sheep using biometric measurements. [PDF]

BMC Vet Res
Delgado MÁG, Tırınk C, Parra-Cortés RI, Martínez IV, Gomez-Vazquez A, Cruz-Hernandez A, Camacho-Pérez E, Dzib-Cauich DA, Önder H, Şen U, Chekirov K, Aksoy Y, Çelik HT, Odu O, Chay-Canul AJ.   +14 more
europepmc   +1 more source

Forecasting Renewable Energy Generation Using Random Forest Analysis

Renewable energy forecasting is critical for sustainable energy development and grid stability. This study applies a Random Forest model to analyze the contribution of different renewable energy sources to total energy generation in Taiwan.
Wu, Chien Hsin;Tseng, Yao Ting;Lo, Wen Fang;Haung, Yu Hsiang
core  

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 more
wiley   +1 more source