Hippocampal neurogenesis in adult primates: a systematic review.

It had long been considered that no new neurons are generated in the primate brain beyond birth, but recent studies have indicated that neurogenesis persists in various locations throughout the lifespan. The dentate gyrus of the hippocampus is of particular interest due to the postulated role played by neurogenesis in memory. However, studies investigating the presence of adult hippocampal neurogenesis (AHN) have reported contradictory findings, and no systematic review of the evidence has been conducted to date.

Exploratory Cost-Utility Analysis of a 37-Gene Panel Versus Usual Care to Guide Therapy for Patients with Intermediate-Risk Myeloid Malignancies.

Objective: Genomic risk stratification methods for myeloid malignancies have moved beyond conventional karyotyping and single gene approaches to better define disease behaviour. Next-generation sequencing has been established as the new standard-of-care tool to accurately define prognosis at diagnosis and guide therapy decisions. We aimed to determine the economic value of a 37-gene panel test for informing subsequent care for patients with intermediate-risk myeloid malignancies.

Engagement in a virtual group-based walking intervention for persons with schizophrenia: a qualitative study.

Background: Exercise is beneficial for persons with schizophrenia; however, high dropout rates limit the impact of interventions. Virtual exercise programs have the potential to improve engagement; however, few intervention studies of virtual programs have been conducted in this population.

Methods: This study examined qualitative data from 15 adults with schizophrenia who participated in a pilot randomized controlled trial of Virtual PACE-Life, a live, video-delivered group walking intervention guided by self-determination theory.

Machine Learning in Pain Neuromodulation.

This chapter highlights the intersection of pain neuromodulation and machine learning (ML), exploring current limitations in pain management and how ML techniques can address these challenges. Neuromodulation technologies, such as spinal cord stimulation (SCS), have emerged as promising interventions for chronic pain, but limitations such as patient selection have resulted in high rates of failure and costly removal of these devices. ML offers a powerful approach to augment pain management outcomes by leveraging predictive modeling for enhanced patient selection, adaptive algorithms for programming optimization, and identification of objective biomarkers for improved outcome assessment.