Results 31 to 40 of about 1,776,687 (293)
Evolutionary interplay between viruses and R‐loops
FEBS Letters, EarlyView.Viruses interact with specialized nucleic acid structures called R‐loops to influence host transcription, epigenetic states, latency, and immune evasion. This Perspective examines the roles of R‐loops in viral replication, integration, and silencing, and how viruses co‐opt or avoid these structures.
Zsolt Karányi +4 more
wiley +1 more source
Warm Cores around Regions of Low-Mass Star Formation
, 2010 Warm cores (or hot corinos) around low-mass protostellar objects show a rich chemistry with strong spatial variations. This chemistry is generally attributed to the sublimation of icy mantles on dust grains initiated by the warming effect of the stellar ...
André +39 more
core +1 more source
FEBS Letters, EarlyView.Exposure to common noxious agents (1), including allergens, pollutants, and micro‐nanoplastics, can cause epithelial barrier damage (2) in our body's protective linings. This may trigger an immune response to our microbiome (3). The epithelial barrier theory explains how this process can lead to chronic noncommunicable diseases (4) affecting organs ...
Can Zeyneloglu +17 more
wiley +1 more source
FEBS Letters, EarlyView.Three‐dimensional (3D) biological systems have become key tools in lymphoma research, offering reliable in vitro and ex vivo platforms to explore pathogenesis and support precision medicine. This review highlights current 3D non‐Hodgkin lymphoma models, detailing their features, advantages, and limitations, and provides a broad perspective on future ...
Carla Faria +3 more
wiley +1 more source
, 2015 In this review we focus on the idea of establishing connections between the mechanical properties of DNAligand complexes and the physical chemistry of DNA-ligand interactions.
Rocha, M. S.
core +1 more source
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
FEBS Letters, EarlyView.Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan +2 more
wiley +1 more source
Heads and Tails: Molecular Imagination and the Lipid Bilayer, 1917–1941 [PDF]
, 2018 Today, the lipid bilayer structure is nearly ubiquitous, taken for granted in even the most rudimentary introductions to cell biology. Yet the image of the lipid bilayer, built out of lipids with heads and tails, went from having obscure origins deep in ...
Liu, Daniel
core
REVIEW OF PHYSICAL CHEMISTRY. [PDF]
Journal of the American Chemical Society, 1905 n ...
openaire +2 more sources
FEBS Letters, EarlyView.In this work, we reveal how different enzyme binding configurations influence the fluorescence decay of NAD(P)H in live cells using time‐resolved anisotropy imaging and fluorescence lifetime imaging microscopy (FLIM). Mathematical modelling shows that the redox states of the NAD and NADP pools govern these configurations, shaping their fluorescence ...
Thomas S. Blacker +8 more
wiley +1 more source