Results 111 to 120 of about 3,790,217 (289)

Supervised Brain Tumor Segmentation Based on Gradient and Context-Sensitive Features

open access: yesFrontiers in Neuroscience, 2019
Gliomas have the highest mortality rate and prevalence among the primary brain tumors. In this study, we proposed a supervised brain tumor segmentation method which detects diverse tumoral structures of both high grade gliomas and low grade gliomas in ...
Junting Zhao   +6 more
doaj   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

open access: yesMolecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric   +10 more
wiley   +1 more source

TABLE OF GRADIENTS. [PDF]

open access: yesMinutes of the Proceedings of the Institution of Civil Engineers
n ...
openaire   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

open access: yesMolecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh   +12 more
wiley   +1 more source

Grating Lobe Suppression of Non-Uniform Arrays Based on Position Gradient and Sigmoid Function

open access: yesIEEE Access, 2019
A super-multivariate optimization algorithm is proposed to suppress the grating lobes (GLs) of non-uniform arrays. For position-only variable cases of any huge array, it is always difficult to deal with by using clustering algorithm because of thousands ...
Xiaomin Xu   +3 more
doaj   +1 more source

On Policy Gradients

open access: yesCoRR, 2019
The goal of policy gradient approaches is to find a policy in a given class of policies which maximizes the expected return. Given a differentiable model of the policy, we want to apply a gradient-ascent technique to reach a local optimum. We mainly use gradient ascent, because it is theoretically well researched.
openaire   +2 more sources

Heterozygous loss‐of‐function alleles associate the conserved 3′‐5′ exoribonuclease EXOSC10 with hypersensitivity to the anticancer drug 5‐fluorouracil

open access: yesMolecular Oncology, EarlyView.
EXOSC10, an essential nuclear RNA exosome‐associated 3′‐5′ exoribonuclease, is inhibited by the anticancer drug 5‐fluorouracil (5‐FU), and EXOSC10 depletion increases 5‐FU sensitivity. The colon‐cancer variant EXOSC10S402T, located in a proteolysis motif, is stable and nuclear but nonfunctional in vivo.
Radhika Sain   +10 more
wiley   +1 more source

Nonlinear Sherman-type inequalities

open access: yesAdvances in Nonlinear Analysis, 2018
An important class of Schur-convex functions is generated by convex functions via the well-known Hardy–Littlewood–Pólya–Karamata inequality. Sherman’s inequality is a natural generalization of the HLPK inequality.
Niezgoda Marek
doaj   +1 more source

Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer

open access: yesMolecular Oncology, EarlyView.
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley   +1 more source

Reducing Reparameterization Gradient Variance

open access: yes, 2017
Optimization with noisy gradients has become ubiquitous in statistics and machine learning. Reparameterization gradients, or gradient estimates computed via the "reparameterization trick," represent a class of noisy gradients often used in Monte Carlo ...
Adams, Ryan P.   +3 more
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