Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/BF02456758 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodetector.
Ecotoxicol Environ Saf
January 2025
College of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, China.
Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation.
View Article and Find Full Text PDFRetrospective evaluation of a novel ultrasound-based imaging analysis software for predicting radiofrequency ablation areas.
PLoS One
January 2025
Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Objective: This study aimed to introduce and evaluate a novel software-based system, BioTrace, designed for real-time monitoring of thermal ablation tissue damage during image-guided radiofrequency ablation for hepatocellular carcinoma (HCC).
Methods: BioTrace utilizes a proprietary algorithm to analyze the temporo-spatial behavior of thermal gas bubble activity during ablation, as seen in conventional B-mode ultrasound imaging. Its predictive accuracy was assessed by comparing the ablation zones it predicted with those annotated by radiologists using contrast-enhanced computed tomography (CECT) 24 hours post-treatment, considered the gold standard.
Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks.
PLoS One
January 2025
Rice Department, Bangkok, Thailand.
Bacterial Leaf Blight (BLB) usually attacks rice in the flowering stage and can cause yield losses of up to 50% in severely infected fields. The resulting yield losses severely impact farmers, necessitating compensation from the regulatory authorities. This study introduces a new pipeline specifically designed for detecting BLB in rice fields using unmanned aerial vehicle (UAV) imagery.
View Article and Find Full Text PDFCellular Senescence Genes as Cutting-Edge Signatures for Abdominal Aortic Aneurysm Diagnosis: Potential for Innovative Therapeutic Interventions.
J Cell Mol Med
January 2025
State Key Laboratory of Frigid Zone Cardiovascular Diseases, Cardiovascular Research Institute and Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, China.
Abdominal aortic aneurysm (AAA) is the most prevalent dilated arterial aneurysm that poses a significant threat to older adults, but the molecular mechanisms linking senescence to AAA progression remain poorly understood. This study aims to identify cellular senescence-related genes (SRGs) implicated in AAA development and assess their potential as therapeutic targets. Four hundred and twenty-nine differentially expressed genes (DEGs) were identified from the GSE57691 training set, and 867 SRGs were obtained.
View Article and Find Full Text PDFImmunoinfiltration Analysis of Mitochondrial Damage-Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms.
Cancer Med
January 2025
Department of Respiratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Background: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-derived biomarkers for LUAD classification and prognosis, remains unexplored.
Aims: The objective of our research is to identify gene modules closely related to the clinical stages of LUAD using the WGCNA method.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!