Results 181 to 190 of about 253,519 (319)

An M-Estimator for Tail Dependence in Arbitrary Dimensions

Consider a random sample in the max-domain of attraction of a multivariate extreme value distribution such that the dependence structure of the attractor belongs to a parametric model.
Krajina, A., Segers, J., Einmahl, J.H.J.
core   +1 more source

The weak instrument problem of the system GMM estimator in dynamic panel data models [PDF]

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms
Frank Windmeijer, Maurice Bun
core  

Integrating preliminary test and Stein-type techniques to improve estimation in the time-dependent Cox model. [PDF]

PLoS One
Ramezani R, Rabiei MR, Arashi M.
europepmc   +1 more source

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

Covariate adjustment in randomized clinical trials: From general theory to practical insights. [PDF]

Clin Trials
Bannick MS, Yi Y, Ye T.
europepmc   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source

CD47 promotes mitogen‐activated protein kinase and epithelial‐to‐mesenchymal transition molecular programs to drive prometastatic phenotypes in non‐small cell lung cancer

Molecular Oncology, EarlyView.
Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau, Lilian G. Zhai, Ryunosuke Hoshi, Zackary Rousseau, Abraam Zakhary, Yin Fang Wu, Rola M. Saleeb, Heyu Ni, Kelsie L. Thu   +8 more
wiley   +1 more source

A Repeated Block Perturbation Subsampling for Large-Scale Longitudinal Data. [PDF]

J Stat Theory Pract
Yao Y, Lee JH, Jin Z.
europepmc   +1 more source

KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer

Molecular Oncology, EarlyView.
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan, Veronika M Metzler, Simone de Brot, Corinne L Woodcock, Anna E Harris, Jennifer Lothion‐Roy, Emeli M Nilsson, Atara Ntekim, Michael S Toss, Jenny L Persson, Francesca Khani, Brian D Robinson, Lorraine J Gudas, Emad Rakha, David M Heery, Catrin S Rutland, Nigel P Mongan   +16 more
wiley   +1 more source

Simulation based new method for population variance using auxiliary information. [PDF]

Sci Rep
Ahmadini AAH, Semary HE, Ahmad S, Ullah K, Zahid E, Al-Moisheer AS.   +5 more
europepmc   +1 more source