A chromosome-level, haplotype-resolved genome assembly and annotation for the Eurasian minnow (Leuciscidae: Phoxinus phoxinus) provide evidence of haplotype diversity.

Background: In this study, we present an in-depth analysis of the Eurasian minnow (Phoxinus phoxinus) genome, highlighting its genetic diversity, structural variations, and evolutionary adaptations. We generated an annotated haplotype-phased, chromosome-level genome assembly (2n = 50) by integrating high-fidelity (HiFi) long reads and chromosome conformation capture data (Hi-C).

Results: We achieved a haploid size of 940 megabase pairs (Mbp) for haplome 1 and 929 Mbp for haplome 2 with high scaffold N50 values of 36.

Health and Experiences During the COVID-19 Pandemic Among Children and Young People: Analysis of Free-Text Responses From the Children and Young People With Long COVID Study.

Background: The literature is equivocal as to whether the predicted negative mental health impact of the COVID-19 pandemic came to fruition. Some quantitative studies report increased emotional problems and depression; others report improved mental health and well-being. Qualitative explorations reveal heterogeneity, with themes ranging from feelings of loss to growth and development.

Highly Optimized CNS Penetrant Inhibitors of EGFR Exon20 Insertion Mutations.

Despite recent advances in the inhibition of EGFR (epidermal growth factor receptor), there remains a clinical need for new EGFR Exon20 insertion (Ex20Ins) inhibitors that spare EGFR WT. Herein, we report the discovery and optimization of two chemical series leading to ether and biaryl as potent, selective, and brain-penetrant inhibitors of Ex20Ins mutants. Building on our earlier discovery of alkyne which allowed access to CNS property space for an Ex20Ins inhibitor, we utilized structure-based design to move to lower lipophilicity and lower CL compounds while maintaining a WT selectivity margin.

Explainable artificial intelligence for neuroimaging-based dementia diagnosis and prognosis.

Introduction: Artificial intelligence and neuroimaging enable accurate dementia prediction, but 'black box' models can be difficult to trust. Explainable artificial intelligence (XAI) describes techniques to understand model behaviour and the influence of features, however deciding which method is most appropriate is non-trivial. Vision transformers (ViT) have also gained popularity, providing a self-explainable, alternative to traditional convolutional neural networks (CNN).

Identifying Opportunities for Fluid Balance Optimization in Critically Ill Children.

Introduction: Fluid overload (FO), a state of pathologic positive cumulative fluid balance (CFB), is common in Pediatric Intensive Care Units (PICU) and associated with morbidity and mortality. Because different PICUs may have unique needs, barriers, and limitations to accurately report fluid balance (FB) and reduce FO, understanding the drivers of positive FB is needed. We hypothesize CFB >5% and >10% is common within initial days of PICU admission, but that reasons for high %CFB will vary across sites, as will barriers to accurate FB recording and opportunities to improve FB recording and management.