Morphological profiling allows accurate identification of cell types in dense iPSC-derived cultures, allowing its use for quality control and differentiation monitoring.

In this valuable study, Roiuk et al employed a combination of ribosome profiling and reporter assays to provide convincing evidence that eIF2A is not involved in translational regulation in cultured ...

Understanding bacterial growth mechanisms can potentially help uncover novel drug targets that are crucial for maintaining cellular viability, particularly for bacterial pathogens. In this important ...

In vivo perturbations and single-cell RNA-seq reveal cell-type-specific STAT1-IFNg signaling in regulation of trained immunity in tissue-resident immune cells.

Dentate nucleus neurons can dynamically modulate their activity during a visual attention task, comprising not only sensorimotor but also cognitive attentional components.

As Editor-in-Chief, Behrens is responsible for the editorial direction and vision of the journal, providing leadership to ...

This manuscript describes the identification and characterization of 12 specific phosphomimetic mutations in the recombinant full-length human tau protein that trigger tau to form fibrils. This ...

The bacterial cell wall is crucial to maintain viability. It has previously been suggested that Gram-positive bacteria have a periplasmic region between the cell membrane and peptidoglycan cell wall ...

This important study reveals a role for IκBα in the regulation of embryonic stem cell pluripotency. The solid data in mouse embryonic stem cells include separation of function mutations in IκBα to ...

This valuable study investigates how the proteins of the Cdv division system in Metallosphaera sedula archaea sequentially interact with curved membranes in vitro, extending our understanding of this ...

The current human tissue-based study provides convincing evidence correlating hippocampal expressions of RNA guanine-rich G-quadruplexes with aging and with Alzheimer's Disease presence and severity.

This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be replaced with ...