Results 91 to 100 of about 120,420 (290)
On the modeling of neural cognition for social network applications
In this paper, we study neural cognition in social network. A stochastic model is introduced and shown to incorporate two well-known models in Pavlovian conditioning and social networks as special case, namely Rescorla-Wagner model and Friedkin-Johnsen ...
Cvetkovic, Vladimir +4 more
core +1 more source
COMP–PMEPA1 axis promotes epithelial‐to‐mesenchymal transition in breast cancer cells
This study reveals that cartilage oligomeric matrix protein (COMP) promotes epithelial‐to‐mesenchymal transition (EMT) in breast cancer. We identify PMEPA1 (protein TMEPAI) as a novel COMP‐binding partner that mediates EMT via binding to the TSP domains of COMP, establishing the COMP–PMEPA1 axis as a key EMT driver in breast cancer.
Konstantinos S. Papadakos +6 more
wiley +1 more source
An Alternative Methodology for Estimating Credit Quality Transition Matrices [PDF]
This study presents an alternative way of estimating credit transition matrices using a hazard function model. The model is useful both for testing the validity of the Markovian assumption, frequently made in credit rating applications, and also for ...
Fernando Pineda +3 more
core
OCReP: An Optimally Conditioned Regularization for Pseudoinversion Based Neural Training
In this paper we consider the training of single hidden layer neural networks by pseudoinversion, which, in spite of its popularity, is sometimes affected by numerical instability issues.
Cancelliere, Rossella +3 more
core +1 more source
Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau +36 more
wiley +1 more source
Many therapies using mesenchymal stem cells (MSC) rely on their ability to produce and release paracrine signals with chemotactic and pro-angiogenic activity.
Fernando Antonio Fierro +9 more
doaj +1 more source
Preconditioning Kernel Matrices
The computational and storage complexity of kernel machines presents the primary barrier to their scaling to large, modern, datasets. A common way to tackle the scalability issue is to use the conjugate gradient algorithm, which relieves the constraints ...
Cunningham, John P. +3 more
core
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +1 more source
Macroscale coupling between structural and effective connectivity in the mouse brain
Exploring how the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the major goals of modern neuroscience.
Danilo Benozzo +5 more
doaj +1 more source
Model-Free Estimation of Large Variance Matrices [PDF]
This paper introduces a new method for estimating large variance matrices. Starting from the orthogonal decomposition of the sample variance matrix, we exploit the fact that orthogonal matrices are never ill-conditioned and therefore focus on improving ...
Filip Žikeš +2 more
core

