Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

Social Determinants of Health Research at NIMHD: An Analysis of Studies Funded During 2019-2023.

INTRODUCTION: Social determinants of health (SDOH) contribute to differences in health outcomes and exacerbate health disparities. This study characterizes the National Institute on Minority Health and Health Disparities' (NIMHD) portfolio of funded grants in SDOH research, identifies gaps, and provides suggestions for future research. METHODS: Using the National Institutes of Health's SDOH Research, Condition, and Disease Categorization, research projects funded from 2019 to 2023 were identified and linked with NIMHD's internal coding system to extract in-depth study characteristics, including sociodemographics of study participants, disease and condition focus, and alignment with strategic priorities. Natural Language Processing methods were used to categorize projects into five Healthy People 2030 SDOH domains. RESULTS: The resulting sample included 675 unique research projects. Most projects included racial and ethnic minority groups (89%), followed by people with lower socioeconomic status (33%), underserved rural communities (16%), and sexual and gender minority groups (13%). Most projects focused on the Etiology of health disparities (61%), followed by Interventions (54%), and Methods and Measurement (39%). Of the Healthy People 2030 domains, Social and Community Context had the greatest representation (61%) whereas Education Access and Quality had the least (6%). Variation in research project characteristics across SDOH domains is also presented. CONCLUSIONS: This study documents characteristics of SDOH research funded by NIMHD and explores how they differ across Healthy People 2030 SDOH domains. Findings highlight how study characteristics and foci align with strategic priorities and suggest opportunities for future research.

The PhenX Toolkit: Recommended Measurement Protocols for Social Determinants of Health Research.

Health disparities are driven by unequal conditions in the environments in which people are born, live, learn, work, play, worship, and age, commonly termed the Social Determinants of Health (SDoH). The availability of recommended measurement protocols for SDoH will enable investigators to consistently collect data for SDoH constructs. The PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a web-based catalog of recommended measurement protocols for use in research studies with human participants. Using standard protocols from the PhenX Toolkit makes it easier to compare and combine studies, potentially increasing the impact of individual studies, and aids in comparability across literature. In 2018, the National Institute on Minority Health and Health Disparities provided support for an initial expert Working Group to identify and recommend established SDoH protocols for inclusion in the PhenX Toolkit. In 2022, a second expert Working Group was convened to build on the work of the first SDoH Working Group and address gaps in the SDoH Toolkit Collections. The SDoH Collections consist of a Core Collection and Individual and Structural Specialty Collections. This article describes a Basic Protocol for using the PhenX Toolkit to select and implement SDoH measurement protocols for use in research studies. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. Basic Protocol: Using the PhenX Toolkit to select and implement SDoH protocols.

Development of trofinetide for the treatment of Rett syndrome: from bench to bedside.

Rett syndrome (RTT) is rare neurodevelopmental disorder caused by mutations in the MECP2 gene that encodes methyl-CpG-binding protein 2 (MeCP2), a DNA-binding protein with roles in epigenetic regulation of gene expression. Functional loss of MeCP2 results in abnormal neuronal maturation and plasticity, characterized by loss of verbal communication and loss of fine and gross motor function, among others. Trofinetide, a synthetic analog of glycine-proline-glutamate, was approved by the US Food and Drug Administration for the treatment of RTT in adult and pediatric patients aged 2 years and older. Here, we present the development of trofinetide from bench research to clinical studies and emphasize how the collaboration between academia, the pharmaceutical industry, and patient advocacy led to the recent approval. The bench-to-bedside development of trofinetide underscores the value of collaboration between these groups in the development and approval of treatments for rare diseases.