In this important manuscript, the authors provide evidence for this mechanism in two different mechanically gated channels. The experiments were carried out in the same membranes, but the evidence is ...

Why do authors choose the eLife Model? We spoke to Hironori Funabiki at the Rockefeller University to learn his reasons.

The authors examine the role of Numb, a Notch inhibitor, in intestinal stem cell self-renewal in Drosophila during homeostasis and regeneration. This is an important study providing evidence of a Numb ...

This is a useful study that seeks to address the role of the TET family of DNA demethylation enzymes in pancreatic beta cell senescence in the context of type 2 diabetes (T2DM). Although the concepts ...

Mackie and colleagues present a valuable comparison of lateralized gustation in two well-studied nematodes. The evidence they present that ASEL/R lateralization exists and is achieved by different ...

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

Unveiling the circuit organization and functional roles of endopiriform neurons projecting to the ventral CA1.

Frizzled (FZD) proteins are the principal receptors of the Wnt signaling pathway. However, whether Wnt ligands induce FZD endocytosis and degradation remains elusive. The transmembrane E3 ubiquitin ...

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 ...

This study addresses a novel and interesting question about how the rise of the Qinghai-Tibet Plateau influenced patterns of bird migration, employing a multi-faceted approach that combines species ...

The transcription factor regulatory network in Pseudomonas aeruginosa is complex and involves multiple regulators that respond to various environmental signals and physiological cues by regulating ...

This valuable study tests a methodology for the discovery of new honey bee-repellent odorants via machine learning. The conclusions of the study are supported by solid evidence, with predicted ...