Results 131 to 140 of about 1,691,919 (306)
Molecular Oncology, EarlyView.Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
wiley +1 more source
Median Estimation with Quantile Transformations: Applications to Stratified Two-Phase Sampling
EntropyMost traditional estimators assume normality and remain sensitive to extreme observations, which limits their usefulness in practical applications. To improve accuracy, we introduce quintile-based median estimators using transformation methods in a ...
Fatimah A. Almulhim, Hassan M. Aljohani
doaj +1 more source
Incorporating measurement error and density gradients in distance sampling surveys [PDF]
, 2007 Distance sampling is one of the most commonly used methods for estimating density and abundance. Conventional methods are based on the distances of detected animals from the center of point transects or the center line of line transects.
Marques, Tiago Andre Lamas Oliveira
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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
Enhanced log ratio calibration methods for stratified variance estimation in survey sampling
Scientific ReportsSurvey sampling is a widely used technique for collecting data from a subset of a bigger population. Among its methods, stratified random sampling is particularly valuable for yielding precise inferences about distinct subgroups within a population by ...
Azam Zaka +6 more
doaj +1 more source
AbstractConsider first data-based machine learning techniques. They rely on large sets of examples provided during the training stage and do not learn with equations. Dealing with a situation that do not belong to the training set variability, namely an out-of-distribution sample, can be very challenging for these techniques.
David Ryckelynck +2 more
openaire +1 more source
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
Improved estimators for the shape parameter in gamma regression [PDF]
, 1986 A regression model is considered in which the response variables have gamma distributions with a common shape parameter. A review is given of existing estimators for the shape parameter.
Bakir, ST, Al-Abood, AM, Young, DH
core
Molecular Oncology, EarlyView.This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi +6 more
wiley +1 more source
The Empirical Saddlepoint Approximation for GMM Estimators [PDF]
The empirical saddlepoint distribution provides an approximation to the sampling distributions for the GMM parameter estimates and the statistics that test the overidentifying restrictions.
Sowell, Fallaw
core