Results 201 to 210 of about 19,373 (299)

Disruption of the SNRPF–DDX24–E2F4 Feedback Loop Uncouples Splicing and Transcriptional Regulation to Suppress Ovarian Cancer Progression

open access: yesAdvanced Science, EarlyView.
This study identifies SNRPF as a critical oncogenic driver in ovarian cancer. By regulating a self‐sustaining SNRPF–DDX24–E2F4 feedback loop through intron retention and nonsense‐mediated decay, SNRPF couples RNA splicing with transcriptional regulation to promote tumor progression.
Yingwei Li   +4 more
wiley   +1 more source

BIN1 and ALDH1B1 Deficiency in Colonic Smooth Muscle Drives Mitochondrial Dysfunction and Fibrosis in Slow‐Transit Constipation

open access: yesAdvanced Science, EarlyView.
Slow‐transit constipation (STC) is a disabling motility disorder with unclear smooth‐muscle mechanisms. Spatial proteomic analysis of STC patient colon reveals both the central pathogenic role of smooth muscle cells (SMCs) in STC and novel regulators of intestinal motility, BIN1 and ALDH1B1.
Jianbo Liu   +10 more
wiley   +1 more source

The rhetoric of sincerity

open access: yes, 2009
Alphen, E.J. van, Bal, M.G., Smith, C.E.
openaire   +2 more sources

Ethical Precision in Nanoscale Brain Interfacing

open access: yesAdvanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

Temporal Interference Stimulation Enhances Neural Regeneration

open access: yesAdvanced Science, EarlyView.
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti   +15 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

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