The Narrative Coherence of Autistic Children's Accounts of an Experienced Event in Response to Different Interviewer Prompts: A Longitudinal Study.

Purpose: This study explored the narrative coherence of the accounts of an experienced event produced by autistic and neurotypical children (ages 6-15 years) after delays of two weeks and two months.

Methods: The sample comprised 27 autistic children and 32 neurotypical peers, who were interviewed about the event using the Revised National Institute of Child Health and Human Development (NICHD) Investigative Interview Protocol. The study focused on assessing the narrative coherence of children's reports, emphasizing key story grammar elements and temporal features in their narratives.

Assessment of community readiness to address malnutrition in rural southwest Guatemala.

Background: Malnutrition is prevalent throughout southwest Guatemala, where >40% of children suffer from chronic undernutrition. Evidence supports that assessing a community's awareness and readiness to address malnutrition is a critical first step in improving the success of a nutrition intervention program. The objective of this study was to apply the community readiness model (CRM) to assess community readiness to address childhood malnutrition in a rural southwest region of Guatemala.

Postnatal Zika and Dengue Infection and their Effects on Neurodevelopment Among Children Living in Rural Guatemala.

Background: Prenatal Zika virus (ZIKV) infection leads to microcephaly and adverse neurodevelopment. The effects of postnatal ZIKV infection on the developing brain are unknown. We assessed the neurodevelopmental outcomes of children exposed postnatally during the ZIKV epidemic.

Accurate design of high-affinity protein binding macrocycles using deep learning.

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest.

Discovery of the most stable form of an adenosine receptor antagonist through virtual polymorph screening and targeted crystallization.

An innovative approach was developed to identify the optimal crystalline form, usually the thermodynamically most stable form. This method involves using virtual polymorph screening and targeted crystallization based on in silico solid-state modeling. By utilizing advanced crystal structure prediction (CSP) technology, the virtual polymorph screening method helps confirm whether the most stable crystalline form has been identified in actual crystallization experiments.