Results 91 to 100 of about 120,420 (290)

On the modeling of neural cognition for social network applications

open access: yes, 2017
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

open access: yesMolecular Oncology, EarlyView.
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]

open access: yes
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

open access: yes, 2015
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

EDNRB‐dependent endothelin signaling reduces proliferation and promotes proneural‐to‐mesenchymal transition in gliomas

open access: yesMolecular Oncology, EarlyView.
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

Hypoxic pre-conditioning increases the infiltration of endothelial cells into scaffolds for dermal regeneration pre-seeded with mesenchymal stem cells

open access: yesFrontiers in Cell and Developmental Biology, 2015
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

open access: yes, 2016
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  

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

open access: yesMolecular Oncology, EarlyView.
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

open access: yesScientific Reports
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]

open access: yes
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  

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