Results 71 to 80 of about 5,269,728 (309)
Pseudo-marginal algorithms with multiple CPUs [PDF]
, 2014 The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables.
Drovandi, Christopher C.
core
Molecular Oncology, EarlyView.The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Loss of proton‐sensing TDAG8 increases tumor progression in mouse models of colon cancer
Molecular Oncology, EarlyView.Loss of the pH‐sensing receptor TDAG8 accelerates colorectal cancer progression in mice. Animals lacking TDAG8 expression had increased tumor growth, DNA damage, and recruitment of tumor‐associated immune cells, including macrophages, neutrophils, and monocytes.
Ermanno Malagola +11 more
wiley +1 more source
Marginal and conditional distributions of singular distributions
Publications of the Research Institute for Mathematical Sciences, 1965 This note derives marginal and conditional means and covariances when the joint distribution may be singular and discusses the resulting invariants.
Harris, W. A. jun., Helvig, T. N.
openaire +2 more sources
Pharmacological chromatin remodeling enhances response to estrogen therapy in ER+ breast cancer
Molecular Oncology, EarlyView.Estrogen therapy elicits clinical benefit in ~ 30% of patients with endocrine‐resistant estrogen receptor (ER)‐positive breast cancer. Based on findings that ER transcriptional activation underlies response to estrogen therapy, we tested the effects of epigenetic dysregulation via pharmacological inhibition of histone deacetylases (HDACi).
Anneka L. Johnson Thomas +16 more
wiley +1 more source
A Kernel Method for the Optimization of the Margin Distribution [PDF]
, 2008 Recent results in theoretical machine learning seem to suggest that nice properties of the margin distribution over a training set turns out in a good performance of a classifier. The same principle has been already used in SVM and other kernel based methods as the associated optimization problems try to maximize the minimum of these margins.
AIOLLI, FABIO +2 more
openaire +1 more source
Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known [PDF]
At the heart of the copula methodology in statistics is the idea of separating marginal distributions from the dependence structure. However, as shown in this paper, this separation is not to be taken for granted: in the model where the copula is known ...
Werker, B.J.M. +2 more
core
Molecular Oncology, EarlyView.Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
A New Approach to Testing Marginal Productivity Theory [PDF]
We address the long standing question of whether production factors are paid their marginal products. We propose a new approach that circumvents the need to specify production functions and to compare marginal products to factor payments. Our approach is
Weiser, Constantin, Biewen, Martin
core
Molecular Oncology, EarlyView.Incomplete microwave ablation (iMWA) of liver cancer triggers a biphasic progression in residual tumors. At Day 3, the microenvironment is characterized by acute inflammatory responses and extracellular matrix (ECM) remodeling. By Day 14, a profound shift occurs toward oncogenic signal transduction and immunosuppression, marked by macrophage ...
Yu Liu +9 more
wiley +1 more source