Results 131 to 140 of about 28,952 (292)
ABSTRACT Liver metastasis is a leading cause of mortality in colorectal cancer (CRC), where the inflammatory tumor microenvironment, specifically neutrophil infiltration, significantly promotes metastatic colonization. This study reveals a pro‐metastatic role for alpha‐1 antitrypsin (A1AT) in CRC liver metastasis via a dual mechanism involving ...
Qian Fei +11 more
wiley +1 more source
A novel deep learning technique for medical image analysis using improved optimizer
Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth.
Vertika Agarwal +2 more
doaj +1 more source
Lactate in cervical cancer induces HNRNPU K181 lactylation, opposed by NAA50‐mediated acetylation and suppressed by Pazopanib. This lactylation enhances HNRNPU binding to PHGDH pre‐mRNA exon 1, maintaining exon 1‐containing transcripts and mRNA stability, thereby activating serine metabolism.
Chang Zhang +6 more
wiley +1 more source
Stochastic gradient descent optimisation for convolutional neural network for medical image segmentation. [PDF]
Nagendram S +7 more
europepmc +1 more source
This study constructed the first spatiotemporal multi‐omics map of peach fruit and discovered a key candidate gene that synergistically regulates trichome development and drought tolerance through the jasmonic acid signaling pathway, providing insights into the coupling mechanism between development and stress resistance.
Zhixin Liu +9 more
wiley +1 more source
A SIEVE STOCHASTIC GRADIENT DESCENT ESTIMATOR FOR ONLINE NONPARAMETRIC REGRESSION IN SOBOLEV ELLIPSOIDS. [PDF]
Zhang T, Simon N.
europepmc +1 more source
Nonparametric budgeted stochastic gradient descent
One of the most challenging problems in kernel online learning is to bound the model size. Budgeted kernel online learning addresses this issue by bounding the model size to a predefined budget.
V Nguyen (9860309) +3 more
core
Convergence of Hyperbolic Neural Networks Under Riemannian Stochastic Gradient Descent
We prove, under mild conditions, the convergence of a Riemannian gradient descent method for a hyperbolic neural network regression model, both in batch gradient descent and stochastic gradient descent.
Wang, Bao, Whiting, Wes, Xin, Jack
core +1 more source
In rheumatoid arthritis, synovial Tregs accumulate but are functionally impaired due to iron overload‐induced ferroptosis. This triggers mitochondrial dysfunction and TXK tyrosine kinase‐mediated signaling, leading to Treg destabilization and inflammation.
Jingrong Chen +19 more
wiley +1 more source
Random coordinate descent: A simple alternative for optimizing parameterized quantum circuits
Variational quantum algorithms rely on the optimization of parameterized quantum circuits in noisy settings. The commonly used back-propagation procedure in classical machine learning is not directly applicable in this setting due to the collapse of ...
Zhiyan Ding +4 more
doaj +1 more source

