Results 101 to 110 of about 24,916,518 (300)
FEBS Open Bio, EarlyView.Research is strongest when conducted alongside patients, not just about them. Patient research organizations help integrate patient perspectives into research priorities, study design, and scientific meetings, leading to meaningful patient outcomes and development of relevant therapies.
Jenica H. Kakadia +9 more
wiley +1 more source
FEBS Open Bio, EarlyView.In this study, a novel esterase from the thermoacidophilic archaeon Thermoplasma acidophilum was biochemically and structurally characterized. Our results demonstrate that Ta0887 is a highly thermostable esterase that preferentially hydrolyzes p‐nitrophenyl hexanoate and possesses an α‐helical cap domain that likely contributes to its substrate ...
Alejandro Delgado‐Rey +4 more
wiley +1 more source
Post-l1-penalized estimators in high-dimensional linear regression models [PDF]
In this paper we study post-penalized estimators which apply ordinary, unpenalized linear regression to the model selected by first-step penalized estimators, typically LASSO. It is well known that LASSO can estimate the regression function at nearly the
Victor Chernozhukov, Alexandre Belloni
core
Selective elimination of quiescent cancer cells by dequalinium chloride via ROS‐mediated ferroptosis
FEBS Open Bio, EarlyView.Dequalinium chloride (DQ) selectively eliminates quiescent cancer cells (QCCs) by amplifying mitochondrial ROS. QCCs exhibit elevated basal ROS and limited redox‐buffering capacity, making them vulnerable to further ROS increases. DQ‐induced ROS exceeds the tolerance threshold, triggering lipid peroxidation and ferroptosis, whereas proliferating cells ...
Kotaro Miyamoto +14 more
wiley +1 more source
Sparsity averaging for compressive imaging [PDF]
, 2013 We discuss a novel sparsity prior for compressive imaging in the context of the theory of compressed sensing with coherent redundant dictionaries, based on the observation that natural images exhibit strong average sparsity over multiple coherent frames.
Wiaux, Yves; id_orcid +9 more
core +2 more sources
Social-sparsity brain decoders: faster spatial sparsity [PDF]
, 2016 International audience—Spatially-sparse predictors are good models for brain decoding: they give accurate predictions and their weight maps are interpretable as they focus on a small number of regions.
Thirion, Bertrand +2 more
core +2 more sources
Wide and Deep Model of Multi-Source Information-Aware Recommender System
IEEE Access, 2018 Collaborative filtering recommendation suffers from the problems of high data sparsity, poor expansibility, cold start, and the difficulty of modeling user preferences, among which data sparsity is the greatest issue. Although our previous work on matrix
Weihua Yuan +4 more
doaj +1 more source
Aging and Cancer, EarlyView.Cancer treatment is associated with measurable acceleration of biological aging across epigenetic, telomere, senescence, and immune biomarkers. However, biomarker validation and interventional strategies remain limited, especially in hematologic malignancies, underscoring the need for standardized multi‐omic aging assessments and adequately powered ...
Moataz Ellithi +3 more
wiley +1 more source
On the Sparsity of Wavelet Coefficients for Signals on Graphs
, 2013 A number of new localized, multiscale transforms have recently been introduced to analyze data residing on weighted graphs. In signal processing tasks such as regularization and compression, much of the power of classical wavelets on the real line is ...
Ricaud, Benjamin +5 more
core +1 more source
Multiple-Factor Based Sparse Urban Travel Time Prediction
Applied Sciences, 2018 The prediction of travel time is challenging given the sparseness of real-time traffic data and the uncertainty of travel, because it is influenced by multiple factors on the congested urban road networks.
Xinyan Zhu +5 more
doaj +1 more source