Dystonia in children with acquired brain injury.

AIM: To quantify the proportion of children who develop dystonia after acquired brain injury (ABI) admitted to a tertiary paediatric intensive care unit (PICU) and analyse the trajectory of dystonia over a 6 month period. METHODS: Children's Health Ireland at Temple Street PICU electronic database was searched for key terms related to ABI from January 1, 2016 to March 14, 2021. Individuals meeting inclusion criteria were analysed, and clinical data pertinent to ABI, dystonia, treatment and outcomes were reviewed. RESULTS: Six-hundred and forty-three PICU episodes (580 patients) met search criteria for ABI, with 379 included in the final analysis. Twelve patients developed dystonia following ABI, giving an incidence of 3.2%. The incidence was higher in the hypoxia/anoxia and TBI cohort at 8.3% and 6.2%, respectively. All patients developed dystonia within the first month following ABI (50% by a week). Patients who developed dystonia compared to non-dystonia cohort had a median lower GCS on admission (4.5 versus 7.0, p value 0.032), longer median length of PICU stay (14.0 versus 3.0 days, p value < 0.001) and were older (median age 9.08 versus 4.68 years, p value 0.06). Dystonia persisted in the majority at 6 months (10/11), requiring on-going medical therapies. CONCLUSION: In our retrospective study, the estimated incidence of dystonia following ABI admitted to the PICU was 3.2%, highest in the hypoxia/anoxia (8.3%) and TBI (6.2%) cohorts. Dystonia emerged early and persisted at 6 months in the majority. This is the first review of dystonia, clinical trajectory and outcomes conducted post-PICU admission for ABI. Future prospective studies are required to determine the true prevalence and burden of disease in the PICU setting.

The plant proteome folding project: structure and positive selection in plant protein families.

Despite its importance, relatively little is known about the relationship between the structure, function, and evolution of proteins, particularly in land plant species. We have developed a database with predicted protein domains for five plant proteomes (http://pfp.bio.nyu.edu) and used both protein structural fold recognition and de novo Rosetta-based protein structure prediction to predict protein structure for Arabidopsis and rice proteins. Based on sequence similarity, we have identified ~15,000 orthologous/paralogous protein family clusters among these species and used codon-based models to predict positive selection in protein evolution within 175 of these sequence clusters. Our results show that codons that display positive selection appear to be less frequent in helical and strand regions and are overrepresented in amino acid residues that are associated with a change in protein secondary structure. Like in other organisms, disordered protein regions also appear to have more selected sites. Structural information provides new functional insights into specific plant proteins and allows us to map positively selected amino acid sites onto protein structures and view these sites in a structural and functional context.