Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning.

Image-based cell profiling is a powerful tool that compares perturbed cell populations by measuring thousands of single-cell features and summarizing them into profiles. Typically a sample is represented by averaging across cells, but this fails to capture the heterogeneity within cell populations. We introduce CytoSummaryNet: a Deep Sets-based approach that improves mechanism of action prediction by 30-68% in mean average precision compared to average profiling on a public dataset.

Prediction of Hepatocellular Carcinoma and Liver-related Events in Anti-hepatitis D Virus-positive Individuals.

Background & Aims: Chronic hepatitis D (CHD) is the most severe form of chronic viral hepatitis, with a high risk of developing hepatocellular carcinoma (HCC) and liver-related mortality. Risk stratification is needed to guide HCC surveillance strategies and to prioritize treatment with antiviral agents.

Methods: We conducted a multicenter retrospective cohort of anti-hepatitis D virus (HDV)-positive individuals managed at sites in the Netherlands and the United Kingdom.

Daily and Half-yearly Associations between Boundary Diffusion and Parent-adolescent Relationship Quality after Divorce.

Boundary diffusion is a particular risk after divorce and has been associated with adolescents' adjustment problems. Yet, its potential impact on parent-adolescent relationship quality is less straightforward, as previous findings support both an alienation and conflict perspective. Therefore these associations (daily and half-yearly) were examined in recently divorced families, addressing both within-dyad changes and between-dyad differences.

Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning.

Image-based cell profiling is a powerful tool that compares perturbed cell populations by measuring thousands of single-cell features and summarizing them into profiles. Typically a sample is represented by averaging across cells, but this fails to capture the heterogeneity within cell populations. We introduce CytoSummaryNet: a Deep Sets-based approach that improves mechanism of action prediction by 30-68% in mean average precision compared to average profiling on a public dataset.

Circular RNAs regulate neuron size and migration of midbrain dopamine neurons during development.

Midbrain dopamine (mDA) neurons play an essential role in cognitive and motor behaviours and are linked to different brain disorders. However, the molecular mechanisms underlying their development, and in particular the role of non-coding RNAs (ncRNAs), remain incompletely understood. Here, we establish the transcriptomic landscape and alternative splicing patterns of circular RNAs (circRNAs) at key developmental timepoints in mouse mDA neurons in vivo using fluorescence-activated cell sorting followed by short- and long-read RNA sequencing.