Cognitive ability in early life and risk of depression in adulthood: A systematic review and meta-analysis.

BACKGROUND: There is an established association between cognitive ability and risk of depression, though the direction of this association is unclear. Measuring cognitive ability in childhood, prior to the diagnosis of depression, could help to understand whether childhood cognitive ability is associated with a later diagnosis of depression. This systematic review and meta-analysis explored the association between childhood cognitive ability and risk of depression in adulthood. METHODS: We searched five databases to January 2024. We included studies that assessed cognitive ability in childhood (<18 years) and depression in adulthood. We excluded studies with very specific populations. We pooled each study's most-adjusted correlation coefficient in a random-effects meta-analysis. When studies reported a dichotomous outcome (depression/no depression), we converted the effect size to a correlation coefficient. Subgroup analyses were performed to explore sources of heterogeneity. RESULTS: 18 articles (19 cohorts) were included. There was no association between childhood cognitive ability and depression in adulthood (20 sample populations, N = 45,786, r = -0.04, 95 % CI = -0.09 to 0.01, p = 0.09). Neither age at cognitive assessment, length of follow-up, using a continuous/categorical measure of depression, or sex, significantly influenced the association. We rated most studies as having moderate risk of bias. LIMITATIONS: We limited the literature search to studies written in English. Existing studies were also heterogeneous, often adjusting for a variety of covariates. CONCLUSIONS: Our meta-analysis found no association between childhood cognitive ability and depression in adulthood. Future, longitudinal population-level studies should endeavour to control for potential mediators across the life-course (e.g., demographic and environmental factors).

Pressurized Liquid (PLE) Truffle Extracts Have Inhibitory Activity on Key Enzymes Related to Type 2 Diabetes (α-Glucosidase and α-Amylase).

An optimized PLE method was applied to several truffle species using three different solvent mixtures to obtain bioactive enriched fractions. The pressurized water extracts contained mainly (1 → 3),(1 → 6)-ß-D-glucans, chitins, and heteropolymers with galactose and mannose in their structures. The ethanol extracts included fatty acids and fungal sterols and others such as brassicasterol and stigmasterol, depending on the species. They also showed a different fatty acid lipid profile depending on the solvent utilized and species considered. Ethanol:water extracts showed interesting lipids and many phenolic compounds; however, no synergic extraction of compounds was noticed. Some of the truffle extracts were able to inhibit enzymes related to type 2 diabetes; pressurized water extracts mainly inhibited the α-amylase enzyme, while ethanolic extracts were more able to inhibit α-glucosidase. Tuber brumale var. moschatum and T. aestivum var. uncinatum extracts showed an IC50 of 29.22 mg/mL towards α-amylase and 7.93 mg/mL towards α-glucosidase. Thus, use of the PLE method allows o bioactive enriched fractions to be obtained from truffles with antidiabetic properties.