نتایج جستجو برای: mir155

تعداد نتایج: 277  

2017
Carol M. Artlett Sihem Sassi-Gaha Jennifer L. Hope Carol A. Feghali-Bostwick Peter D. Katsikis

BACKGROUND Despite the important role that microRNAs (miRNAs) play in immunity and inflammation, their involvement in systemic sclerosis (SSc) remains poorly characterized. miRNA-155 (miR-155) plays a role in pulmonary fibrosis and its expression can be induced with interleukin (IL)-1β. SSc fibroblasts have activated inflammasomes that are integrally involved in mediating the myofibroblast phen...

1997
Chen Xi PharmClint Co Eli Lilly

1 Dr. Chen Xi worked at Eli Lilly and Company, and he is currently working at Pfizer, Inc. as a consultant specialized in clinical trial analysis and SAS programming support. His view does not reflect the business practice of any of his client firms. He can be reached through E-Mail at [email protected] or [email protected]. Information theoretic model selection criteria such as AIC, BIC and ICOM...

2016
Manuel Tsiang Gregg S. Jones Joshua Goldsmith Andrew Mulato Derek Hansen Elaine Kan Luong Tsai Rujuta A. Bam George Stepan Kirsten M. Stray Anita Niedziela-Majka Stephen R. Yant Helen Yu George Kukolj Tomas Cihlar Scott E. Lazerwith Kirsten L. White Haolun Jin

Bictegravir (BIC; GS-9883), a novel, potent, once-daily, unboosted inhibitor of HIV-1 integrase (IN), specifically targets IN strand transfer activity (50% inhibitory concentration [IC50] of 7.5 ± 0.3 nM) and HIV-1 integration in cells. BIC exhibits potent and selective in vitro antiretroviral activity in both T-cell lines and primary human T lymphocytes, with 50% effective concentrations rangi...

2012
Peter J. Waddell Xi Tan

The purpose of this article is to look at how information criteria, such as AIC and BIC, interact with the g%SD fit criterion derived in Waddell et al. (2007, 2010a). The g%SD criterion measures the fit of data to model based on a normalized weighted root mean square percentage deviation between the observed data and model estimates of the data, with g%SD = 0 being a perfectly fitting model. Ho...

2017
Camila Macedo da Luz Matthew Samuel Powys Boyles Priscila Falagan-Lotsch Mariana Rodrigues Pereira Henrique Rudolf Tutumi Eidy de Oliveira Santos Nathalia Balthazar Martins Martin Himly Aniela Sommer Ilse Foissner Albert Duschl José Mauro Granjeiro Paulo Emílio Corrêa Leite

BACKGROUND Poly-lactic acid nanoparticles (PLA-NP) are a type of polymeric NP, frequently used as nanomedicines, which have advantages over metallic NP such as the ability to maintain therapeutic drug levels for sustained periods of time. Despite PLA-NP being considered biocompatible, data concerning alterations in cellular physiology are scarce. METHODS We conducted an extensive evaluation o...

2016
Aziza Elmesmari Alasdair R. Fraser Claire Wood Derek Gilchrist Diane Vaughan Lynn Stewart Charles McSharry Iain B. McInnes Mariola Kurowska-Stolarska

OBJECTIVE To test the hypothesis that miR-155 regulates monocyte migratory potential via modulation of chemokine and chemokine receptor expression in RA, and thereby is associated with disease activity. METHODS The miR-155 copy-numbers in monocytes from peripheral blood (PB) of healthy (n = 22), RA (n = 24) and RA SF (n = 11) were assessed by real time-PCR using synthetic miR-155 as a quantit...

2011
Jui-Chen Hsu Gregory R. Hancock Jeffrey R. Harring Jeffrey Harring George Macready Paul J. Hanges Tien-Liang Hsu I-Jen Wang Hsu

Title of the ESTIMATION AND MODEL SELECTION FOR Dissertation FINITE MIXTURES OF LATENT INTERACTION MODELS Jui-Chen Hsu, Doctor of Philosophy, 2011 Directed by Professor Gregory R. Hancock, Department of Measurement, Statistics and Evaluation Professor Jeffrey R. Harring, Department of Measurement, Statistics and Evaluation Latent interaction models and mixture models have received considerable ...

2004
Tadeusz Inglot Teresa Ledwina

The data driven Neyman statistic consists of two elements: a score statistic in a finite dimensional submodel and a selection rule to determine the best fitted submodel. For instance, Schwarz BIC and Akaike AIC rules are often applied in such constructions. For moderate sample sizes AIC is sensitive in detecting complex models, while BIC works well for relatively simple structures. When the sam...

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