Publications by authors named "I Cristea"
Intercellular communication is fundamental to multicellular life and a core determinant of outcomes during viral infection, where the common goals of virus and host for persistence and replication are generally at odds. Hosts rely on encoded innate and adaptive immune responses to detect and clear viral pathogens, while viruses can exploit or disrupt these pathways and other intercellular communication processes to enhance their spread and promote pathogenesis. While virus-induced signaling can result in systemic changes to the host, striking alterations are observed within the cellular microenvironment directly surrounding a site of infection, termed the virus microenvironment (VME).
View Article and Find Full Text PDFThis paper reviews the scientific evidence on new anti-amyloid monoclonal antibodies for treating Alzheimer's disease as a case study for improving scientific evidence communication. We introduce five guidelines condensed from the biomedical evidence literature but adapted to the short format of science communication in e.g.
View Article and Find Full Text PDFAerobic glycolysis is a hallmark of many viral infections, leading to substantial accumulation of lactate. However, the regulatory roles of lactate during viral infections remain poorly understood. Here, we report that human cytomegalovirus (HCMV) infection leverages lactate to induce widespread protein lactylation and promote viral spread.
View Article and Find Full Text PDFBackground: Males and females exhibit distinct anatomic and functional characteristics of the heart, predisposing them to specific disease states.
Methods: We identified microRNA (miRNAs/miR) with sex-differential expression in mouse hearts.
Results: Four conserved miRNAs are present in a single locus on the X-chromosome and are expressed at higher levels in females than males.
Article Synopsis
- The study utilized machine learning models to identify reliable diagnostic markers for eating disorders, major depressive disorder, and alcohol use disorder, targeting young adults aged 18-25.
- The classification models showed high accuracy rates (AUC-ROC ranging from 0.80 to 0.92) even without considering body mass index and highlighted shared predictors like neuroticism and hopelessness.
- Additionally, the models were moderately successful in predicting future symptoms related to eating disorders, depression, and alcohol use in a longitudinal sample of adolescents, indicating the potential for improved diagnosis and risk assessment in mental health.