A growing body of data suggests that therapies based on Toll-like receptors (TLR) targeting, in particular TLR4, holds promise in curing autoimmune and inflammatory pathologies still lacking specific treatment, included several rare diseases. While TLR4 activators (agonists) have already found successful clinical application as vaccine adjuvants, the use of TLR4 blockers (antagonists) as antisepsis agents or as agents against inflammatory diseases (including arthritis, multiple sclerosis, neuroinflammations) and cancer is still at a preclinical phase of development. This minireview focuses on recent achievements on the development of TLR4 modulators based on lipid A structure simplification, in particular on compounds having disaccharide or monosaccharide structures. As the TLR4 activity of natural TLR4 ligands (lipopolysaccharide, LPS and its biologically active part, the lipid A) depends on both the structure of endotoxin aggregates in solution and on single-molecule interaction with MD-2 and CD14 receptors, the rational design of TLR4 modulators should in principle take into account both these factors. In the light of the most recent advances in the field, in this minireview we discuss the structure–activity relationship in simplified lipid A analogs, with cationic or anionic amphiphilic structures. 相似文献
Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer. 相似文献
Background: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account.
Methods: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs.
Results: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. 相似文献
The aim of the present study was to investigate the effect of gonadotropin-releasing hormone (GnRH) antagonists (GnRH-ant) on follicular fluid (FF) insulin-like growth factor-I (IGF-I) and FF vascular endothelial growth factor (VEGF) levels. Sixty women undergoing assisted reproduction were randomized and assigned to two different GnRH analog regimens: GnRH agonist (GnRH-a) and GnRH-ant. FF VEGF and FF IGF-I concentrations were significantly increased in the patients treated with GnRH-ant (p < 0.001). In the same patients we observed a statistically significant reduction in serum luteinizing hormone (LH) and estradiol (E2) levels (p < 0.001 and p < 0.05, respectively), FF E2 and FF androstenedione levels (p < 0.05 and p < 0.001, respectively), as well as a reduction in the number of pregnancies although this was not statistically significant. In the GnRH-ant group, FF VEGF levels were positively correlated with FF IGF-I levels, and both were negatively correlated with serum LH levels. The increase in FF IGF-I and FF VEGF levels in women treated with GnRH-ant could be explained by a deleterious follicular environment in response to profound suppression of LH and E2 levels. 相似文献