Where do "chemical imbalance" beliefs come from? Evaluating the impact of different sources.

Introduction: Although the etiology of depression is incredibly complex, the narrative that it is caused by a simple "chemical imbalance" persists in lay settings. We sought to understand where people are exposed to this explanation (i.e.

Extracellular matrix turnover in severe COVID-19 is reduced by corticosteroids.

Background: Severe and critical COVID-19 is characterized by pulmonary viral infection with SARS-CoV-2 resulting in local and systemic inflammation. Dexamethasone (DEX) has been shown to improve outcomes in critically ill patients; however, its effect on tissue remodeling, particularly collagen turnover, remains unclear. This study investigated the association between circulating extracellular matrix (ECM) remodeling neo-epitopes and COVID-19 severity, their relationship with mortality, and the effect of DEX on these markers.

Managing emotions in everyday life: Why a toolbox of strategies matters.

Emerging research indicates that people use multiple strategies to manage their emotions in everyday life. Yet, we know little about what these strategy combinations look like, how they function, or how individual differences influence these phenomena. We addressed these issues in two, 2-week daily diary studies performed during the height of the COVID-19 pandemic ( = 422; data collected April and September 2020).

Basal cell of origin resolves neuroendocrine-tuft lineage plasticity in cancer.

Neuroendocrine and tuft cells are rare, chemosensory epithelial lineages defined by expression of ASCL1 and POU2F3 transcription factors, respectively. Neuroendocrine cancers, including small cell lung cancer (SCLC), frequently display tuft-like subsets, a feature linked to poor patient outcomes. The mechanisms driving neuroendocrine-tuft tumour heterogeneity, and the origins of tuft-like cancers are unknown.

Predictive learning shapes the representational geometry of the human brain.

Predictive coding theories propose that the brain constantly updates internal models to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link prediction error encoding and optimization of sensory representations remain unclear. Here, we provide evidence how predictive learning shapes the representational geometry of the human brain.