Results 201 to 210 of about 274,417 (276)
Nuclear pore links Fob1‐dependent rDNA damage relocation to lifespan control
Damaged rDNA accumulates at a specific perinuclear interface that couples nucleolar escape with nuclear envelope association. Nuclear pores at this site help inhibit Fob1‐induced rDNA instability. This spatial organization of damage handling supports a functional link between nuclear architecture, rDNA stability, and replicative lifespan in yeast.
Yamato Okada +5 more
wiley +1 more source
The structural heterogeneity of AKT autoinhibition. [PDF]
Xu L +6 more
europepmc +1 more source
The inhibition of mitochondrial dihydroorotate dehydrogenase (DHODH) impairs syncytialization and induces cellular senescence via mitochondrial and endoplasmic reticulum stress in human trophoblast stem cells, elevating sFlt1/PlGF levels, a hallmark of placental dysfunction in hypertensive disorders of pregnancy.
Kanoko Yoshida +6 more
wiley +1 more source
Activity-based chemoproteomic profiling reveals the active kinome of <i>Leishmania</i>. [PDF]
Porta EOJ, Kalesh K, Steel PG.
europepmc +1 more source
Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu +8 more
wiley +1 more source
Formononetin ameliorates SP-induced urticaria in mice via suppressing TAK1/MAK signaling pathway. [PDF]
Wu Y, Li C.
europepmc +1 more source
SNUPN‐Related Muscular Dystrophy: Novel Phenotypic, Pathological and Functional Protein Insights
ABSTRACT Objective SNUPN‐related muscular dystrophy or LGMDR29 is a new entity that covers from a congenital or childhood onset pure muscular dystrophy to more complex phenotypes combining neurodevelopmental features, cataracts, or spinocerebellar ataxia. So far, 12 different variants have been described.
Nuria Muelas +18 more
wiley +1 more source
DyVarMap: Integrating Conformational Dynamics and Interpretable Machine Learning for Cancer-Associated Missense Variant Classification in FGFR2. [PDF]
Lian Y, Shehu A.
europepmc +1 more source

