Results 141 to 150 of about 1,084,074 (266)

Structured low-rank approximation with missing data

The approach of SIAM J. Matrix Anal. Appl., 26(4):1083--1099 for solving structured total least squares problems is generalized to weighted structured low-rank approximation with missing data. The method proposed is based on elimination of the correction
Markovsky, Ivan, Usevich, Konstantin
core   +1 more source

Cigarette smoke-induced RANKL expression enhances MMP-9 production by alveolar macrophages

International Journal of COPD, 2018
Lu Zhou,1 Yanqing Le,1 Jieyu Tian,2 Xia Yang,2 Rong Jin,3 Xiaoyan Gai,1 Yongchang Sun1 1Department of Respiratory Medicine, Peking University Third Hospital, Beijing, China; 2Department of Respiratory Medicine, Beijing Tongren Hospital, Capital Medical ...
Zhou L, Le Y, Tian J, Yang X, Jin R, Gai X, Sun Y   +6 more
doaj  

IGF2 knockout reduces but does not abolish osteosarcoma growth in vitro and in vivo

FEBS Open Bio, EarlyView.
To test whether endogenous IGF2 promotes osteosarcoma growth, IGF2 was knocked out in Saos2 cells via CRISPR‐Cas9. KO cells showed reduced proliferation in vitro, and knockout xenografts in mice reached only ~25% of wild‐type tumor volume. Insulin‐like growth factor 2 (IGF2) is implicated in osteosarcoma, but direct functional evidence of its role is ...
Shun Yao, Marco Archetti
wiley   +1 more source

Chronobiology of Cancer: How Aging Fuels Oncogenesis at the Molecular Level

Aging and Cancer, EarlyView.
This graphical abstract illustrates the key biological pathways linking aging with cancer development and progression. In the upper left, cumulative exposure to ultraviolet radiation, toxins, and reactive oxygen species (ROS) causes DNA damage and genomic instability, whereas age‐related decline in repair mechanisms, such as ATM/ATR, BER, and NER ...
Anu Singh, Aroonima Misra, Sufian Zaheer
wiley   +1 more source

RANK-ligand and osteoprotegerin as biomarkers in the differentiation between periprosthetic joint infection and aseptic prosthesis loosening. [PDF]

World J Orthop, 2017
Friedrich MJ, Wimmer MD, Schmolders J, Strauss AC, Ploeger MM, Kohlhof H, Wirtz DC, Gravius S, Randau TM.   +8 more
europepmc   +1 more source

Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

RANK-ligand inhibition to combat sarcopenia with underlying osteoporosis: a study protocol for a randomized, double-blind, double-dummy, active-controlled trial. [PDF]

Trials
Wong RMY, Wong PY, Liu C, Tang N, Wan RCW, Liu WH, Cui C, Zhang N, Kwok TCY, Law SW, Cheung WH.   +10 more
europepmc   +1 more source

Baseline Neuroinflammation Stratifies TSPO‐PET Response to Disease‐Modifying Therapy in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch, Markus Matilainen, Giulia N. Baldrighi, Marjo Nylund, Maija Saraste, Laura Airas   +5 more
wiley   +1 more source

RANK Ligand Modulation of Autophagy in Oral Squamous Cell Carcinoma Tumor Cells. [PDF]

J Cell Biochem, 2016
Sambandam Y, Sakamuri S, Balasubramanian S, Haque A.   +3 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source