Results 131 to 140 of about 6,852,071 (351)

Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression

Molecular Oncology, EarlyView.
Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park, Jae Won Oh, Hyewon Chung, Jung Won Kwon, Yi Rang Na, Kwang Pyo Kim, Seung Hyeok Seok   +6 more
wiley   +1 more source

Large Deviations in Renewal Models of Statistical Mechanics

, 2019
In Ref. [1] the author has recently established sharp large deviation principles for cumulative rewards associated with a discrete-time renewal model, supposing that each renewal involves a broad-sense reward taking values in a separable Banach space ...
Zamparo, Marco
core   +1 more source

Goodness-of-fit statistics for approximate Bayesian computation [PDF]

arXiv, 2016
Approximate Bayesian computation is a statistical framework that uses numerical simulations to calibrate and compare models. Instead of computing likelihood functions, Approximate Bayesian computation relies on numerical simulations, which makes it applicable to complex models in ecology and evolution.
arxiv  

Adverse prognosis gene expression patterns in metastatic castration‐resistant prostate cancer

Molecular Oncology, EarlyView.
We aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression‐based pathways with clinical outcomes. Loss of AR signaling, high proliferation, and a glycolytic phenotype were independently prognostic for poor outcomes, and an adverse transcriptional feature score incorporating these pathways ...
Marina N. Sharifi, Eric Feng, Nicholas R. Rydzewski, Amy K. Taylor, Jamie M. Sperger, Yue Shi, Kyle T. Helzer, Matthew L. Bootsma, Viridiana Carreno, Alex H. Chang, Luke A. Nunamaker, Grace C. Blitzer, Tianfu Andy Shang, Aishwarya Subramanian, Anders Bjartell, Andreas Josefsson, Pernilla Wikström, Emily Feng, Manish Kohli, Rendong Yang, Scott M. Dehm, Eric J. Small, Rahul Aggarwal, David A. Quigley, Joshua M. Lang, Shuang G. Zhao, Martin Sjöström   +26 more
wiley   +1 more source

Comments on “Cloud Droplet Coalescence: Statistical Foundations and a One-Dimensional Sedimentation Model” [PDF]

, 1968
Elizabeth Berry
openalex   +3 more sources

Statistical Mechanics of Shell Models for 2D-Turbulence

, 1994
We study shell models that conserve the analogues of energy and enstrophy, hence designed to mimic fluid turbulence in 2D. The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach
Aurell, E., Boffetta, G., Crisanti, A., Frick, P., Paladin, G., Vulpiani, A.   +5 more
core   +1 more source

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus

Renal Failure
Background Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD prediction are urgently needed.
Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu   +4 more
doaj   +1 more source

A statistical decision model for sensory discrimination which predicts Weber’s law and other sensory laws: Some results of a computer simulation [PDF]

, 1966
Michel Treisman
openalex   +1 more source

TOMM20 as a driver of cancer aggressiveness via oxidative phosphorylation, maintenance of a reduced state, and resistance to apoptosis

Molecular Oncology, EarlyView.
TOMM20 increases cancer aggressiveness by maintaining a reduced state with increased NADH and NADPH levels, oxidative phosphorylation (OXPHOS), and apoptosis resistance while reducing reactive oxygen species (ROS) levels. Conversely, CRISPR‐Cas9 knockdown of TOMM20 alters these cancer‐aggressive traits.
Ranakul Islam, Megan E. Roche, Zhao Lin, Diana Whitaker‐Menezes, Victor Diaz‐Barros, Eurico Serrano, Maria Paula Martinez Cantarin, Nancy J. Philp, Atrayee Basu Mallick, Ubaldo Martinez‐Outschoorn   +9 more
wiley   +1 more source

Statistics of a Vortex Filament Model

Electronic Journal of Probability, 2005
A random field composed by Poisson distributed Brownian vortex filaments is constructed. The filament have a random thickness, length and intensity, governed by a measure $ $. Under appropriate assumptions on $ $ we compute the scaling law of the structure function and get the multifractal scaling as a particular case.
Flandoli, Franco, Gubinelli, Massimiliano   +1 more
openaire   +6 more sources