Results 51 to 60 of about 536,991 (288)
We show that the majority of the 18 analyzed recurrent cancer‐associated ERBB4 mutations are transforming. The most potent mutations are activating, co‐operate with other ERBB receptors, and are sensitive to pan‐ERBB inhibitors. Activating ERBB4 mutations also promote therapy resistance in EGFR‐mutant lung cancer.
Veera K. Ojala +15 more
wiley +1 more source
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns +10 more
wiley +1 more source
Numerical simulation is a powerful technique for slope stability assessment and landslide hazard investigation. However, the physicomechanical parameters of the simulation results are susceptible to uncertainty.
Wujiao Dai, Yue Dai, Jiawei Xie
doaj +1 more source
Jackknifing Weighted Least Squares Estimators
SUMMARY In a heteroscedastic linear regression model, the ordinary jackknife estimator of the asymptotic covariance matrix of the weighted least squares estimator is proved to be inconsistent. A modified jackknife procedure is proposed and shown to produce consistent estimators of the asymptotic covariance matrix.
openaire +2 more sources
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Weighted Least Squares Regression with the Best Robustness and High Computability
A novel regression method is introduced and studied. The procedure weights squared residuals based on their magnitude. Unlike the classic least squares which treats every squared residual as equally important, the new procedure exponentially down-weights
Yijun Zuo, Hanwen Zuo
doaj +1 more source
Conjugate gradient acceleration of iteratively re-weighted least squares methods
Iteratively Re-weighted Least Squares (IRLS) is a method for solving minimization problems involving non-quadratic cost functions, perhaps non-convex and non-smooth, which however can be described as the infimum over a family of quadratic functions. This
Fornasier, Massimo +3 more
core +1 more source
Adaptive weighted least squares algorithm for Volterra signal modeling [PDF]
Published ...
Chan, SCK +2 more
core +1 more source
Tandem VHH targeting distinct EGFR epitopes were engineered into a monovalent bispecific antibody (7D12‐EGA1‐Fc) with more potent ADCC without increasing affinity to EGFR. Structural modeling of 7D12‐EGA1‐Fc showed cross‐linking of separate EGFR domains to enhance CD16a engagement on NK cells.
Yuqiang Xu +5 more
wiley +1 more source
Determination of Personalized IOL-Constants for the Haigis Formula under Consideration of Measurement Precision. [PDF]
The capabilities of a weighted least squares approach for the optimization of the intraocular lens (IOL) constants for the Haigis formula are studied in comparison to an ordinary least squares approach. The weights are set to the inverse variances of the
Simon Schröder +4 more
doaj +1 more source

