A genome-wide CRISPR/Cas9 knockout screening approach identified C/EBPδ as transcriptional regulator of the alarmins S100A8 and S100A9 during differentiation of monocytes and inflammatory processes in vivo.

Hermaphroditic Caenorhabditis elegans slow the onset of mating-induced death through self-sperm-regulated insulin-like gene expression, which regulates the activity of the IIS/FOXO pathway, mTOR signaling, and the TFEB/HLH-30 transcription factor.

FLEXIQuant-LF provides the framework to enable large-scale identification of differentially modified peptides and quantification of their modification extent in label-free mass spectrometry data without prior knowledge of the modification type.

Spatiotemporal manipulations of insomniac reveal that this gene regulates the birth and development of sleep-regulatory neurons, enabling their proper function in adulthood.

BonVision is an open-source software for real-time rendering and control of 2D and 3D visual environments that also enables easy replication of experiments.

A genetic screening approach identifies RNA binding proteins that enhance or inhibit the accumulation of CD138+ plasma cells in vitro, and chimeric mouse models demonstrate that YTHDF2 promotes the accumulation of antibody secreting cells in vivo.

Increased extramedullary erythropoiesis in spleen compensates for the elevated turnover of red blood cells in mice lacking CD47, but extramedullary erythropoiesis is suppressed in mice lacking the CD47 ligand thrombospondin-1.

Sleep-encoded vocabulary influences awake decision-making 36 hr later, particularly when targeting the vocabulary to slow-wave troughs, which suggests that unconscious episodic memory formation during deep sleep is possible.

The transcription factor, MEF2C, mediates a change in approximately one half of the expressed frontal cortical transcriptome controlling cellular metabolism and synaptic strength in response to acute loss of sleep.

Sound cues that were associated with memories during wake elicit memory reactivations when replayed to human participants during rapid eye movement sleep, those memory reactivations are identifiable by machine learning models that directly relate electroencephalography patterns of wake and sleep.