Sort   by:  
 Page size 
UnknownBeyond depression symptoms: the default mode network as a predictor of antidepressant response.
Antidepressant efficacy for major depressive disorder (MDD) remains limited, with the neural mechanisms underlying treatment response poorly understood. The default mode network (DMN), particularly the connectivity between the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC), has...
S-EPMC12811245 | biostudies-literature
UnknownTranscriptomic decoding of regional cortical vulnerability to major depressive disorder.
Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined...
S-EPMC11310478 | biostudies-literature
UnknownDynamic changes in hemispheric lateralization in major depressive disorder correlate with neurotransmitter and genetic profiles: a DIRECT consortium study.
Hemispheric lateralization, recognized as a pivotal feature in both the structural and functional organization of the human brain, may undergo alterations in specific psychiatric disorders. However, the time-varying patterns of hemispheric lateralization in individuals with major depressive disorder...
S-EPMC12660689 | biostudies-literature
UnknownPrediction of postoperative infection in elderly using deep learning-based analysis: an observational cohort study.
Elderly patients are susceptible to postoperative infections with increased mortality. Analyzing with a deep learning model, the perioperative factors that could predict and/or contribute to postoperative infections may improve the outcome in elderly. This was an observational cohort study with 2014...
S-EPMC10014765 | biostudies-literature
UnknownGuidelines for the use and interpretation of assays for monitoring autophagy (3rd edition).
Not available
S-EPMC4835977 | biostudies-literature
UnknownElective surgery cancellations due to the COVID-19 pandemic: global predictive modelling to inform surgical recovery plans.

Background

The COVID-19 pandemic has disrupted routine hospital services globally. This study estimated the total number of adult elective operations that would be cancelled worldwide during the 12 weeks of peak disruption due to COVID-19.

Methods

A global expert response study was co...
S-EPMC7272903 | biostudies-literature
Sort   by:  
 Page size