Linking childhood allostatic load, early adversity and the emergence of mental health symptoms in early adulthood: Analysis of the ALSPAC longitudinal birth cohort.

Background: It has been well-established that the allostatic load (AL) index, a cumulative score of multi-system dysregulation in response to chronic stress, is significantly increased at the time of a psychiatric diagnosis. However, no studies have investigated if there is an association between the AL index in childhood and the later development of mental health symptoms in young adults.

Methods: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a population cohort from Bristol, United Kingdom, we investigated the AL index at age 9 years and the risks for mental health symptoms at age 24 years.

The mental health impact of climate change on Pacific Islanders: A systematic review focused on sea level rise and extreme weather events.

Objective: This systematic review investigates the impact of climate change on the mental health of Pacific Island Nations (PINs), with a focus on identifying culturally tailored interventions and appropriate research methodologies to address these impacts.

Method: A systematic review of peer-reviewed literature up to May 18, 2024, was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol and the Population, Interest Area, and Context (PICo) framework. Empirical studies on the impact of climate change on mental health in PINs were evaluated by using the Quality Assessment Tool for Studies with Diverse Designs (QATSDD).

Schizophrenia, a disease of impaired dynamic metabolic flexibility: A new mechanistic framework.

Schizophrenia is a chronic, neurodevelopmental disorder with unknown aetiology and pathophysiology that emphasises the role of neurotransmitter imbalance and abnormalities in synaptic plasticity. The currently used pharmacological approach, the antipsychotic drugs, which have limited efficacy and an array of side-effects, have been developed based on the neurotransmitter hypothesis. Recent research has uncovered systemic and brain abnormalities in glucose and energy metabolism, focusing on altered glycolysis and mitochondrial oxidative phosphorylation.

Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices.

Introduction: Advances in wearable sensor technology have enabled the collection of biomarkers that may correlate with levels of elevated stress. While significant research has been done in this domain, specifically in using machine learning to detect elevated levels of stress, the challenge of producing a machine learning model capable of generalizing well for use on new, unseen data remain. Acute stress response has both subjective, psychological and objectively measurable, biological components that can be expressed differently from person to person, further complicating the development of a generic stress measurement model.