Results 81 to 90 of about 18,707,175 (333)
Subpar reporting of pre‐analytical variables in RNA‐focused blood plasma studies
Pre‐analytical variables strongly influence the analysis of extracellular RNA (cell‐free RNA; exRNA) derived from blood plasma. Their reporting is essential to allow interpretation and replication of results. By evaluating 200 exRNA studies, we pinpoint a lack of reporting pre‐analytical variables associated with blood collection, plasma preparation ...
Céleste Van Der Schueren+16 more
wiley +1 more source
Cancer‐associated fibroblasts (CAFs) promote cancer growth, invasion (metastasis), and drug resistance. Here, we identified functional and diverse circulating CAFs (cCAFs) in patients with metastatic prostate cancer (mPCa). cCAFs were found in higher numbers and were functional and diverse in mPCa patients versus healthy individuals, suggesting their ...
Richell Booijink+6 more
wiley +1 more source
D-optimal Design for Polynomial Regression: Choice of Degree and Robustness [PDF]
In this paper we show that for D-optimal design, departures from the design are much less important than a depar-ture from a model. As a consequence, we propose, based on D-optimality, a rule for choosing the regression degree.
Antille, Gerard, Weinberg Allen, Anna
core
Surfaceome: a new era in the discovery of immune evasion mechanisms of circulating tumor cells
In the era of immunotherapies, many patients either do not respond or eventually develop resistance. We propose to pave the way for proteomic analysis of surface‐expressed proteins called surfaceome, of circulating tumor cells. This approach seeks to identify immune evasion mechanisms and discover potential therapeutic targets. Circulating tumor cells (
Doryan Masmoudi+3 more
wiley +1 more source
Semi-bayesian D-optimal designs and estimation procedures for mean and variance functions. [PDF]
Semi-Bayesian D-optimal designs for fitting mean and variance functions are derived for some prior distributions on the variance function parameters. The impact of the mean of the prior and of the uncertainty about this mean is analyzed.
Goos, Peter, Vandebroek, Martina
core
Improving D-Optimality in Nonlinear Situations
Experimental designs based on the classical D-optimal criterion minimize the volume of the linear-approximation inference regions for the parameters using local sensitivity coefficients. For nonlinear models, these designs can be unreliable because the linearized inference regions do not always provide a true indication of the exact parameter inference
openaire +2 more sources
A comparative study of circulating tumor cell isolation and enumeration technologies in lung cancer
Lung cancer cells were spiked into donor blood to evaluate the recovery rates of the following circulating tumor cell (CTC) enrichment technologies: CellMag™, EasySep™, RosetteSep™, Parsortix® PR1, and Parsortix® Prototype systems. Each method's advantages and disadvantages are described.
Volga M Saini+11 more
wiley +1 more source
On the Equivalence of Optimality Design Criteria for the Placebo-Treatment Problem [PDF]
We consider a class of optimality criteria and show that each crite- rion has its unique and equivalent dual within the class. This property can be used to find a variety of optimal designs, including a class of compound optimal designs and their ...
Dette, Holger, Wong, Weng Kee, Zhu, Wei
core
On a Multiplicative Algorithm for Computing Bayesian D-optimal Designs [PDF]
We use the minorization-maximization principle (Lange, Hunter and Yang 2000) to establish the monotonicity of a multiplicative algorithm for computing Bayesian D-optimal designs. This proves a conjecture of Dette, Pepelyshev and Zhigljavsky (2008)
Yu, Yaming
core
Sparsely Sampling the Sky: A Bayesian Experimental Design Approach
The next generation of galaxy surveys will observe millions of galaxies over large volumes of the universe. These surveys are expensive both in time and cost, raising questions regarding the optimal investment of this time and money.
Jaffe, A. H., Paykari, P.
core +2 more sources