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1.
Phys Rev Lett ; 115(26): 265303, 2015 Dec 31.
Article in English | MEDLINE | ID: mdl-26765001

ABSTRACT

We study the dynamics of counterflowing bosonic and fermionic lithium atoms. First, by tuning the interaction strength we measure the critical velocity v(c) of the system in the BEC-BCS crossover in the low temperature regime and we compare it to the recent prediction of Castin et al., C. R. Phys. 16, 241 (2015). Second, raising the temperature of the mixture slightly above the superfluid transitions reveals an unexpected phase locking of the oscillations of the clouds induced by dissipation.

2.
Biomed Pharmacother ; 100: 501-508, 2018 Apr.
Article in English | MEDLINE | ID: mdl-29477914

ABSTRACT

In our previous studies, we have demonstrated that a novel water-soluble derivative of limonin, (12S,12aS,Z)-8-((2-(diethylamino)ethoxy)imino)-12-(furan-3-yl)-6,6,8a,12a-tetramethyldodecahydro-1H,3H-oxireno[2,3-d]pyrano[4',3':3,3a]isobenzofuro[5,4-f]isochromene-3,10(9aH)-dione (V-A-4), exhibited strong anti-inflammatory activity both in vitro and in vivo. The purpose of this study was to further explore the underlying mechanisms of such activity demonstrated by V-A-4. The protective effect of V-A-4 on the alleviation of xylene-induced ear swelling and carrageenan-induced subcutaneous air pouch model was detected in vivo. Furthermore, the in vitro effects of V-A-4 and its mechanisms of action were determined by colorimetric COX (ovine) inhibitor-screening assay and in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. This study showed that V-A-4 does not exert anti-inflammatory effect through the inhibition of COX-1 or COX-2. Rather, it is exerted through the suppression of the secretion of nitric oxide (NO) and tumor necrosis factor-α (TNF-α), as well as through the infiltration of inflammatory cells. V-A-4 demonstrated strong inhibition of NF-κB activation through repression of IKKα and IKKß phosphorylations, which in turn leads to the phosphorylation and degradation of IκBα in LPS-induced RAW264.7 cells. Moreover, toll-like receptor 4 (TLR4) pathway was involved in the anti-inflammatory effect of V-A-4, which also played an important role in the down-regulation of LPS-mediated miR-146a and miR-155 expressions. These results encourage further development of V-A-4 as a potential candidate for the treatment of inflammatory diseases.


Subject(s)
Anti-Inflammatory Agents/pharmacology , Inflammation Mediators/antagonists & inhibitors , Limonins/pharmacology , NF-kappa B/antagonists & inhibitors , Signal Transduction/drug effects , Toll-Like Receptor 4/antagonists & inhibitors , Animals , Anti-Inflammatory Agents/chemistry , Dose-Response Relationship, Drug , Inflammation Mediators/metabolism , Limonins/chemistry , Male , Mice , Mice, Inbred ICR , NF-kappa B/metabolism , RAW 264.7 Cells , Signal Transduction/physiology , Toll-Like Receptor 4/metabolism
3.
IET Syst Biol ; 10(3): 107-15, 2016 Jun.
Article in English | MEDLINE | ID: mdl-27187989

ABSTRACT

A number of different gene selection approaches based on gene expression profiles (GEP) have been developed for tumour classification. A gene selection approach selects the most informative genes from the whole gene space, which is an important process for tumour classification using GEP. This study presents an improved swarm intelligent optimisation algorithm to select genes for maintaining the diversity of the population. The most essential characteristic of the proposed approach is that it can automatically determine the number of the selected genes. On the basis of the gene selection, the authors construct a variety of the tumour classifiers, including the ensemble classifiers. Four gene datasets are used to evaluate the performance of the proposed approach. The experimental results confirm that the proposed classifiers for tumour classification are indeed effective.


Subject(s)
Algorithms , Gene Expression Profiling/methods , Neoplasm Proteins/metabolism , Neoplasms/diagnosis , Neoplasms/metabolism , Pattern Recognition, Automated/methods , Animals , Humans , Neoplasms/classification , Reproducibility of Results , Sensitivity and Specificity
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