Dynamic human gut microbiome and immune shifts during an immersive psychosocial intervention program.

Background: Although depression is a leading cause of disability worldwide, the pathophysiological mechanisms underlying this disorder-particularly those involving the gut microbiome-are poorly understood.

Method: To investigate, we conducted a community-based observational study to explore complex associations between changes in the gut microbiome, cytokine levels, and depression symptoms in 52 participants (M = 49.56, SD = 13.

Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population, subsequently developing machine learning models to predict clinical outcomes based on baseline characteristics and symptom measures. The study analyzed approximately 15,000 clients aged 18-89 in a real-world clinical setting, treated for up to 180-days between 2015 and 2020.

Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis.

Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected persons and is an ideal model to study transitions of early precancer states to colorectal cancer (CRC). We performed deep multiomic profiling of 93 samples, including normal mucosa, benign polyps and dysplastic polyps, from six persons with FAP. Transcriptomic, proteomic, metabolomic and lipidomic analyses revealed a dynamic choreography of thousands of molecular and cellular events that occur during precancerous transitions toward cancer formation.

Evaluation of X-ray fluorescence for analysing critical elements in three electronic waste matrices: A comprehensive comparison of analytical techniques.

As the drive towards recycling electronic waste increases, demand for rapid and reliable analytical methodology to analyse the metal content of the waste is increasing, e.g. to assess the value of the waste and to decide the correct recycling routes.

Weight Update in Ferroelectric Memristors with Identical and Nonidentical Pulses.

Ferroelectric tunnel junctions (FTJs) are a class of memristor which promise low-power, scalable, field-driven analog operation. In order to harness their full potential, operation with identical pulses is targeted. In this paper, several weight update schemes for FTJs are investigated, using either nonidentical or identical pulses, and with time delays between the pulses ranging from 1 μs to 10 s.