Biosimilar artificial mucus models that mimic native mucus facilitate efficient, lab-based drug diffusion studies, addressing the costly and challenging preclinical phase of drug development, especially for nano- and micro-scale particle-based coloni...
The accurate diagnosis of pathogenic variants is essential for effective clinical decision making within precision medicine programs. Despite significant advances in both the quality and quantity of molecular patient data, diagnostic rates remain sub...
Panax notoginseng is a well-known research species in China. The issue of continuous crop barriers has led to a reduction in suitable habitats in Wenshan. In the context of global warming, it is far from adequate to merely predict the suitability dis...
Intensive education systems are believed to contribute to high rates of myopia. This study examined whether near-viewing behaviors in college students differ based on their pre-college educational systems and whether these behaviors can be used to cl...
RNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA...
BACKGROUND: Existing biomarkers for epithelial ovarian cancer (EOC) have demonstrated limited sensitivity and specificity. This study aimed to investigate plasma protein and metabolite characteristics of EOC and identify novel biomarker candidates fo...
Fatty acid ethyl esters (FAEEs) are widely used in biofuels, pharmaceuticals, and lubricants, offering an eco-friendly alternative due to their biodegradability and renewable nature, contributing to environmental sustainability. The objective of this...
Cardiotoxicity is the loss of the heart muscle's ability to contract effectively, often due to chemotherapy or radiation therapy. This study uses interpretable machine learning to predict post-chemotherapy cardiotoxicity using radiomics features extr...
Electroencephalography (EEG) recordings with visual stimuli require detailed coding to determine the periods of participant's attention. Here we propose to use a supervised machine learning model and off-the-shelf video cameras only. We extract compu...
This work presents a comprehensive study on the prediction of phenytoin solubility at supercritical state using advanced techniques including machine learning analysis. The solubility of small-molecule pharmaceutical was analyzed and calculated to en...
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