Comparison of Population Pharmacokinetic Modeling and Machine Learning Approaches for Predicting Voriconazole Trough Concentrations in Critically Ill Patients.

Despite the widespread use of voriconazole in antifungal treatment, its high pharmacokinetic and pharmacodynamic variability may lead to suboptimal efficacy, especially in intensive care unit (ICU) patients. Machine learning (ML), an artificial intelligence modeling approach, is increasingly being applied to personalized medicine. The effectiveness of ML models for predicting voriconazole blood concentrations in ICU patients, compared to traditional population pharmacokinetics (popPK) models, has been uncertain until now.

Genome-wide association studies identify miRNA-194 as a prognostic biomarker for gastrointestinal cancer by targeting ATP6V1F, PPP1R14B, BTF3L4 and SLC7A5.

Background: The dysregulated genes and miRNAs in tumor progression can be used as biomarkers for tumor diagnosis and prognosis. However, the biomarkers for predicting the clinical outcome of gastrointestinal cancer (GIC) are still scarce.

Methods: Genome-wide association studies were performed to screen optimal prognostic miRNA biomarkers.

Correction to: Community environmental satisfaction: its forms and impact on migrants' happiness in urban China.

The original article [1] contains errors in the presentation of Table 5 & Table 6 whereby values are displayed in an incorrect format leading to potential misinterpretation.

Community environmental satisfaction: its forms and impact on migrants' happiness in urban China.

Background: The great number of internal migrants has become an important part of China's urban population. Improving migrants' well-being is emerging as a key to the state policy emphasized in China's New-type Urbanization Plan. Previous studies on subjective well-being (SWB) have primarily focused on the impacts of objective measures of community environment and consider migrants as a homogeneous group.