Preterm birth was associated with a profound reduction in connectivity between multiple brain regions and with the reconfiguration of the organization of functional brain networks.
Teens who have self-harmed five or more times in their lives have a significantly higher pain threshold than those who have never self-harmed.
NfL, a single biomarker in the blood, can accurately predict the presence of underlying neurodegenerative disorders, such as FTD and ALS, in people with cognitive problems.
Mouse study reveals intermittent fasting improves long-term memory retention and promotes hippocampal neurogenesis. The findings could help to slow cognitive decline in older adults.
Brain scans revealed, compared to women with low risk for postpartum psychosis, new mothers in high-risk groups had altered brain connectivity in networks associated with goal-orientated behaviors.
A new study reveals people who experience larger dips in blood sugar hours after eating end up feeling hungrier and eat hundreds of more calories a day than those who experience lower blood sugar dips.
MRI imaging is more adept at detecting fetal abnormalities than conventional ultrasound imaging.
Genetic analysis of almost 195,000 people helped researchers identify 50 novel genes associated with eye color.
Over 60s with poor appetite were found to have less variety of gut bacteria than those with healthier appetites. Additionally, those with good appetites had more microbes associated with diets rich in fruits and vegetables.
Identical twins were more likely to have similar sun-seeking behaviors than non-identical twins, suggesting genetics play a key role in sun-seeking behaviors. Researchers identified five genes associated with sun-seeking behavior, some of which have previously been associated with behavioral traits linked to risk-taking and addiction.
Gene expression study reveals it is possible to distinguish between those with treatment-resistant depression and those with major depressive disorder who respond to antidepressants based on levels of inflammation and the presence of molecular mechanisms that spark inflammation into action.
A new artificial intelligence algorithm can accurately predict whether a person is infected with coronavirus based on a range of symptoms a person experiences. Researchers say the technology will help identify those with COVID-19 in populations that are experiencing limited clinical testing.
