AIMC Topic: Iron
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Predicting the governing factors for the release of colloidal phosphorus using machine learning.
Chemosphere
Jun 27, 2024
Predicting the parameters that influence colloidal phosphorus (CP) release from soils under different land uses is critical for managing the impact on water quality. Traditional modeling approaches, such as linear regression, may fail to represent th...
Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose.
Environmental geochemistry and health
Jun 26, 2024
This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characteriza...
Enhanced wastewater treatment by catalytic persulfate activation with protonated hydroxylamine-assisted iron: Insights from a deep learning-based numerical investigation.
Chemosphere
May 25, 2024
Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.
Respiratory research
May 14, 2024
BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures.
Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation.
Molecular biotechnology
Apr 13, 2024
Ferroptosis is a unique form of cell death reliant on iron and lipid peroxidation. It disrupts redox balance, causing cell death by damaging the plasma membrane, with inducers acting through enzymatic pathways or transport systems. In cancer treatmen...
Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach.
Chemosphere
Apr 7, 2024
Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamet...
Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.
ACS sensors
Mar 26, 2024
Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Cur...
Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis.
ACS sensors
Mar 12, 2024
A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identificati...
Lactoferrin: A Promising New Player in Treatment of Iron Deficiency Anemia in Patients on Regular Hemodialysis: A Randomized Controlled Trial.
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Jan 17, 2024
Hepcidin is secreted in inflammatory states as in patients on regular hemodialysis (HD). Therefore, novel agents modulating hepcidin secretion may have the potential to effectively reverse anemia in HD patients. Bovine milk derivative lactoferrin (BL...
Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning.
Frontiers in public health
Jan 8, 2024
INTRODUCTION: This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutritional status, household income levels, and allergic disease occurrence.
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