TECTB Variants Reveal Tectorial Membrane Vulnerability in Dominant Non‐Syndromic Hearing Loss
TECTB is a non‐collagenous protein of the tectorial membrane – an extracellular matrix of the cochlea. This study identifies dominant missense variants in TECTB linked to human hereditary deafness in two unrelated families. Genetically engineered mice homozygous for one of the variants are profoundly deaf, whereas heterozygous mice have normal hearing ...
Evan B. Hale +23 more
wiley +1 more source
Average distance between the processors of biswapped networks. [PDF]
Prabhu S +3 more
europepmc +1 more source
Structural Divergence Between the Moltbook AI‐Agent Network and Human Social Networks
Analysis of the Moltbook AI‐agent network reveals a striking combination of familiar global scaling and distinct internal organization. Attention is highly concentrated, reciprocity is limited, connected triads are suppressed, and communities are strongly modular.
Wenpin Hou, Zhicheng Ji
wiley +1 more source
Enhancing bioinformatics engineering by utilizing graph therapeutic properties for clinically approved antitoxin drugs in zoonotic diseases. [PDF]
Imran M, Aqib M, Malik MA, Jutt S.
europepmc +1 more source
On Zagreb coindices and Mostar index of [Formula: see text] nanotubes. [PDF]
Imran M +4 more
europepmc +1 more source
The GPX3‐VCAM1 Axis Gates Pro‐Fibrotic Tubule Cell Fate in Hyperuricemic Nephropathy
Hyperuricemia induces NLRP3 inflammasome signaling activation and downregulation of GPX3 in proximal tubular epithelial cells, leading to oxidative stress–driven VCAM1 upregulation, emergence of pro‐fibrotic proximal tubule cells, macrophage recruitment, and renal fibrosis.
Yunfei Qi +11 more
wiley +1 more source
A Dynamic Mechanism for Prevalence of Triangles in Competitive Networks. [PDF]
Mooij MN +4 more
europepmc +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
Cover-free families on hypergraphs and combinatorial group testing. [PDF]
Idalino TB, Moura L.
europepmc +1 more source

