Role of oxidative stress and intracellular glutathione in the sensitivity to apoptosis induced by proteasome inhibitor in thyroid cancer cells

<p>Abstract</p> <p>Background</p> <p>The proteasome inhibitor bortezomib has shown impressive clinical activity alone and in combination with conventional and other novel agents for the treatment of multiple myeloma (MM) and some solid cancers. Although bortezomib is known to be a selective proteasome inhibitor, the downstream mechanisms of cytotoxicity and drug resistance are poorly understood.</p> <p>Methods</p> <p>Proteasome activity, intracellular glutathione (GSH) and ROS levels, as well as activities of GSH synthesis enzymes were measured using spectrophotometric methods. Cell death was analyzed using flow cytometry and caspase activity assay. The expression level of GSH synthesis enzymes were measured using real-time RT-PCR.</p> <p>Results</p> <p>At concentrations that effectively inhibited proteasome activity, bortezomib induced apoptosis in FRO cells, but not in ARO cells. Bortezomib elevated the amount of glutathione (GSH) and the treatment with bortezomib increased the level of mRNA for GCL, a rate-limiting enzyme in glutathione synthesis. Furthermore, depletion of GSH increases apoptosis induced by bortezomib, in contrast, repletion of GSH decreases bortezomib-mediated cell death.</p> <p>Conclusion</p> <p>GSH protects cells from proteasome inhibition-induced oxidative stress and glutathione-dependent redox system might play an important role in the sensitivity to proteasome inhibition-induced apoptosis.</p

Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries

Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available

PI-88 and related heparan sulfate mimetics

The heparan sulfate mimetic PI-88 (muparfostat) is a complex mixture of sulfated oligosaccharides that was identified in the late 1990s as a potent inhibitor of heparanase. In preclinical animal models it was shown to block angiogenesis, metastasis and tumor growth, and subsequently became the first heparanase inhibitor to enter clinical trials for cancer. It progressed to Phase III trials but ultimately was not approved for use. Herein we summarize the preparation, physicochemical and biological properties of PI-88, and discuss preclinical/clinical and structure-activity relationship studies. In addition, we discuss the PI-88-inspired development of related HS mimetic heparanase inhibitors with improved properties, ultimately leading to the discovery of PG545 (pixatimod) which is currently in clinical trials

The Control of Heparanase Through the Use of Small Molecules

Despite the enormous progress made in recent years with antibodies, vaccines, antisense oligonucleotides, etc., the so-called “biological” approaches for tackling the control of various diseases, medicinal chemistry remains a bulwark to refer to for the development of new drugs. Also in the case of heparanase, medicinal chemistry has always been in the forefront to identify new inhibitors, through modification of natural macromolecules, e.g., sulfated polysaccharides like heparin, or of natural compounds isolated from bacteria or plants, or through rational design. In this chapter, the reader will find a detailed description of the most relevant small-molecule heparanase inhibitors reported so far in the scientific literature and in patent applications, with mention to the design strategy and to structure-activity relationships. Starting from heparanase inhibitors of natural origin and the attempts to improve their potency and selectivity, the reader will be guided through the major chemical classes of synthetic inhibitors, with representation of the structure of the most relevant compounds. The last paragraph is dedicated to a brief description of inhibitors that have reached clinical trials, highlighting their structure, mechanism, and improved derivatives

Spatial and temporal patterns of dengue infections in Timor-Leste, 2005–2013

Abstract Background Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease. Methods Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling. Results The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72–76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6–0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29–59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables. Conclusions Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection