Single-cell multiomic analyses reveal known and new genes and pathways involved in the development of germ cells and provide a discovery platform for the scientific community.

Multi-dimensional social relationships dynamically shape attentional biases toward in-group and out-group conspecifics in monkeys, with oxytocin modulating these interactions to reveal neurobiological ...

This fundamental study reports the effects of the psychedelic drug psilocin on iPSC-derived human cortical neurons, analyzing different aspects of structural and functional neuronal plasticity. The ...

According to the latest information released by the Fungicide Resistance Action Committee (FRAC), over 30 fungicide selective targets have been identified and acknowledged in the field of fungicide ...

The intrinsic factor of cell senescence, PCBP2, was identified by unlabeled quantitative proteomics, and its biological role in in vitro replication senescence of human bone marrow mesenchymal stromal ...

Plectin drives hepatocellular carcinoma progression and metastasis through cytoskeletal reorganization and oncogenic signaling, making it a promising therapeutic target for overcoming therapy ...

Advocates of responsible science practices representing over 30 countries have joined the programme to learn from each other ...

How is the eLife Model driving change in research? We explore some key milestones and accomplishments of the first two years ...

This manuscript addresses the role of alpha oscillations in sensory gain control. The authors use an attention-cuing task in an initial EEG study followed by a separate MEG replication study to ...

Shah and colleagues take advantage of the presence of maternal and somatic ribosomes in zebrafish and confirm their differential expression during development. The authors convincingly show that ...

The ThermoMaze behavioral paradigm enables the collection of extensive physiological data while animals remain at distinct experimenter-controlled locations during rest.

Recurrent spiking networks that process input stimuli with optimal efficiency have key emerging properties that are similar to those of biological neural networks.