Chemicals with developmental and reproductive toxicity (DART) pose significant risks to human health, particularly exposure during critical windows of embryonic and fetal development. Therefore, rapid and accurate identification of DART chemicals is ...
Due to the diverse molecular structures of chemical compounds and their intricate biological pathways of toxicity, predicting their reproductive and developmental toxicity remains a challenge. Traditional Quantitative Structure-Activity Relationship ...
Using mark-resight data, we investigated fidelity to territory and mate as well as breeding dispersal rates and the causes and consequences of breeding dispersal in a 20-year study of American goshawks (Astur atricapillus) in Arizona, USA. Generalize...
Environmental science and pollution research international
Dec 10, 2024
The striped snakehead, Channa striata, is commercially and nutritionally important due to its medicinal properties, such as wound healing and antimicrobial abilities. This study investigated the reproductive biology of C. striata in relation to hydro...
The use of artificial intelligence (AI) in human reproduction is a rapidly evolving field with both exciting possibilities and ethical considerations. This technology has the potential to improve success rates and reduce the emotional and financial b...
IN BRIEF: Clinical drug trials often do not include pregnant people due to health risks; therefore, many medications have an unknown effect on the developing fetus. Machine learning QSAR models have been used successfully to predict the fetal risk of...
International journal of biometeorology
Nov 14, 2024
In an era where global climate change is shifting plant phenology, global meta-analyses of multiple species are required more than ever. Common language or references for enhanced data compatibility are key for such analyses. Although the Plant Pheno...
Egg production rate and egg weight are core indicators for evaluating the production performance of broiler breeders. The accurate prediction of these indicators can significantly enhance farm economic efficiency and can provide a basis for future pr...
Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive tox...
Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen receptors (AR) are costly, time-consuming, and low-throughput. This study developed a knowledge-based deep neural network model (AR-DNN) to predict AR-me...
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