Results 91 to 100 of about 273,362 (259)
Design and analysis strategies for robust microbiome ageing research
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Federated Multi-Stage Attention Neural Network for Multi-Label Electricity Scene Classification
Privacy-sensitive electricity scene classification requires robust models under data localization constraints, making federated learning (FL) a suitable framework.
Lei Zhong +8 more
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta +3 more
wiley +1 more source
Multi-label arrhythmias classification is of great significance to the diagnosis of cardiovascular disease, and it is a challenging task as it requires identifying the label subset most related to each instance.
Pan Xia +12 more
doaj +1 more source
Although too much iron in the brain promotes neurodegeneration, iron ion chelators have had mixed effects in clinical trials. This review explains why; some chelators do not render the iron redox‐inactive (e.g., L1) whereas others do (e.g., desferrioxamine).
Barry Halliwell
wiley +1 more source
Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas +4 more
wiley +1 more source
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Updating Correlation-Enhanced Feature Learning for Multi-Label Classification
In the domain of multi-label classification, label correlations play a crucial role in enhancing prediction precision. However, traditional methods heavily depend on ground-truth label sets, which can be incompletely tagged due to the diverse backgrounds
Zhengjuan Zhou +4 more
doaj +1 more source
Epigenetic reprogramming of lineage switching in cancer
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı +4 more
wiley +1 more source

