Results 121 to 130 of about 4,225,561 (321)
The role and implications of mammalian cellular circadian entrainment
At their most fundamental level, mammalian circadian rhythms occur inside every individual cell. To tell the correct time, cells must align (or ‘entrain’) their circadian rhythm to the external environment. In this review, we highlight how cells entrain to the major circadian cues of light, feeding and temperature, and the implications this has for our
Priya Crosby
wiley +1 more source
Crosstalk between the ribosome quality control‐associated E3 ubiquitin ligases LTN1 and RNF10
Loss of the E3 ligase LTN1, the ubiquitin‐like modifier UFM1, or the deubiquitinating enzyme UFSP2 disrupts endoplasmic reticulum–ribosome quality control (ER‐RQC), a pathway that removes stalled ribosomes and faulty proteins. This disruption may trigger a compensatory response to ER‐RQC defects, including increased expression of the E3 ligase RNF10 ...
Yuxi Huang +8 more
wiley +1 more source
A Perspective on the Missing at Random Problem: Synthetic Generation and Benchmark Analysis
Progressively more advanced and complex models are proposed to address problems related to computer vision, forecasting, Internet of Things, Big Data and so on. However, these disciplines require preprocessing steps to obtain meaningful results.
Juan-Francisco Cabrera-Sanchez +3 more
doaj +1 more source
Missing data patterns in runners’ careers: do they matter? [PDF]
Mattia Stival +3 more
openalex +1 more source
Peptide‐based ligand antagonists block a Vibrio cholerae adhesin
The structure of a peptide‐binding domain of the Vibrio cholerae adhesin FrhA was solved by X‐ray crystallography, revealing how the inhibitory peptide AGYTD binds tightly at its Ca2+‐coordinated pocket. Structure‐guided design incorporating D‐amino acids enhanced binding affinity, providing a foundation for developing anti‐adhesion therapeutics ...
Mingyu Wang +9 more
wiley +1 more source
Methods and implications of addressing missing data in health-care research
Missing data can introduce biases and affect the generalizability of research findings, undermining the scientific rigor of studies and impeding the development of evidence-based practices.
Varun Agiwal, Sirshendu Chaudhuri
doaj +1 more source
Deep Learning Applications in Vessel Dead Reckoning to Deal with Missing Automatic Identification System Data [PDF]
Atefe Sedaghat +3 more
openalex +1 more source
This perspective highlights emerging insights into how the circadian transcription factor CLOCK:BMAL1 regulates chromatin architecture, cooperates with other transcription factors, and coordinates enhancer dynamics. We propose an updated framework for how circadian transcription factors operate within dynamic and multifactorial chromatin landscapes ...
Xinyu Y. Nie, Jerome S. Menet
wiley +1 more source

