Comparison of Th1 and Th2 responses in non-healing and healing patients with cutaneous leishmaniasis

Background:

Cutaneous leishmaniasis is an endemic disease in many regions of Iran, including the city of Mashhad. In recent years, some cases have not responded to Glucantime, the usual treatment for this disease. The cellular immune response caused by T-helper type 1 (Th1) cells has an important role in protection against leishmaniasis, and activation of the T-helper type 2 (Th2) response causes progression of the disease. By analyzing these responses we hope to find a more effective treatment than that currently in use for leishmaniasis patients.

Methods:

The cellular immune responses in 60 cases of non-healing and healing cutaneous leishmaniasis, and individuals in a control group, were analyzed by measuring cytokines released by peripheral blood mononuclear cells (PBMCs) when stimulated with Leishmania major antigens by Enzyme Linked Immuno Sorbent Assay (ELISA).

Results:

Subjects from the healing group secreted more interleukin-12 (IL-12) and interferon gamma (IFN-γ) (p<0.05) and less interleukins -4, -5, -10 (IL-4, IL-5, and IL-10) (p<0.005) and -18 (IL-18) (p=0.003) than the non-healing group.

Conclusions:

The results demonstrate that secretion of cytokines that activate Th2 response including IL-4, IL-5 and IL-10 in non-healing subjects was higher than healing subjects and secretion of cytokines that activate Th1 response including IL-12 and IFN-γ in healing subjects was higher relative to the non-healing subjects. In this study it has been shown that the level of IL-18 progresses disease in non-healing patients when the level of IL-12 gets decreased. Key Words: Cytokines, Cutaneous leishmaniasis, Glucantime     

Study of PKRBD in HCV genotype 3a infected patients in response to interferon therapy in Pakistani population

Background

Hepatitis C virus (HCV) is a major cause of liver cirrhosis and hepatocellular carcinoma and infects about 3% world population. Response to interferon therapy depends upon the genotype of the virus and factors associated with the host. Despite a good response to interferon therapy, a considerable number of genotype 3a infected patients remains unalleviated.

Results

In total forty-nine patients including twenty-five non-responders (non-SVR) and twenty-four responders (SVR) were recruited. Patients were tested for viral status at different intervals and the isolated RNA was sequenced for the NS5A region in both groups. The comparison of PKRBD of HCV between the SVR and non-SVR patients did not confirm any significant difference in the number of mutations. However, when the sequence downstream to the PKRBD of NS5A was compared, two important statistically significant mutations were observed; at positions 2309 (Ala to Ser) and 2326 (Gly to Ala). These mutations were then analysed for tertiary protein structure and important structural changes were observed. Statistically significant difference was also observed when age groups of patients were compared; younger patients showed better response than the older ones.

Conclusions

The region between PKRBD and IRRDR may be important for prediction of response to IFN therapy for genotype 3a. ISDR and PKRBD have not shown any involvement in treatment response. Further functional analyses of these findings can help in understanding the involvement of the NS5A region in interferon treatment of HCV-3a infected patients.

     

Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks

The ensemble modeling (EM) approach has shown promise in capturing kinetic and regulatory effects in the modeling of metabolic networks. Efficacy of the EM procedure relies on the identification of model parameterizations that adequately describe all observed metabolic phenotypes upon perturbation. In this study, we propose an optimization-based algorithm for the systematic identification of genetic/enzyme perturbations to maximally reduce the number of models retained in the ensemble after each round of model screening. The key premise here is to design perturbations that will maximally scatter the predicted steady-state fluxes over the ensemble parameterizations. We demonstrate the applicability of this procedure for an Escherichia coli metabolic model of central metabolism by successively identifying single, double, and triple enzyme perturbations that cause the maximum degree of flux separation between models in the ensemble. Results revealed that optimal perturbations are not always located close to reaction(s) whose fluxes are measured, especially when multiple perturbations are considered. In addition, there appears to be a maximum number of simultaneous perturbations beyond which no appreciable increase in the divergence of flux predictions is achieved. Overall, this study provides a systematic way of optimally designing genetic perturbations for populating the ensemble of models with relevant model parameterizations.     

Performance of Multiplex Cytokine Assays in Serum and Saliva among Community-Dwelling Postmenopausal Women

Multiplexing arrays increase the throughput and decrease sample requirements for studies employing multiple biomarkers. The goal of this project was to examine the performance of Multiplex arrays for measuring multiple protein biomarkers in saliva and serum. Specimens from the OsteoPerio ancillary study of the Women’s Health Initiative Observational Study were used. Participants required the presence of at least 6 teeth and were excluded based on active cancer and certain bone issues but were not selected on any specific condition. Quality control (QC) samples were created from pooled serum and saliva. Twenty protein markers were measured on five multiplexing array panels. Sample pretreatment conditions were optimized for each panel. Recovery, lower limit of quantification (LLOQ) and imprecision were determined for each analyte. Statistical adjustment at the plate level was used to reduce imprecision estimates and increase the number of usable observations. Sample pre-treatment improved recovery estimates for many analytes. The LLOQ for each analyte agreed with manufacturer specifications except for MMP-1 and MMP-2 which were significantly higher than reported. Following batch adjustment, 17 of 20 biomarkers in serum and 9 of 20 biomarkers in saliva demonstrated acceptable precision, defined as <20% coefficient of variation (<25% at LLOQ). The percentage of cohort samples having levels within the reportable range for each analyte varied from 10% to 100%. The ratio of levels in saliva to serum varied from 1∶100 to 28∶1. Correlations between saliva and serum were of moderate positive magnitude and significant for CRP, MMP-2, insulin, adiponectin, GM-CSF and IL-5. Multiplex arrays exhibit high levels of analytical imprecision, particularly at the batch level. Careful sample pre-treatment can enhance recovery and reduce imprecision. Following statistical adjustments to reduce batch effects, we identified biomarkers that are of acceptable quality in serum and to a lesser degree in saliva using Multiplex arrays.     

The Chemical Diversity of Lantana camara: Analyses of Essential Oil Samples from Cuba,Nepal, and Yemen

The aerial parts of Lantana camara L. were collected from three different geographical locations: Artemisa (Cuba), Biratnagar (Nepal), and Sana'a (Yemen). The essential oils were obtained by hydrodistillation and analyzed by gas chromatography/mass spectrometry. A cluster analysis of 39 L. camara essential oil compositions revealed eight major chemotypes: β‐caryophyllene, germacrene D, ar‐curcumene/zingiberene, γ‐curcumen‐15‐al/epi‐β‐bisabolol, (E)‐nerolidol, davanone, eugenol/alloaromadendrene, and carvone. The sample from Cuba falls into the group dominated by (E)‐nerolidol, the sample from Nepal is a davanone chemotype, and the sample from Yemen belongs to the β‐caryophyllene chemotype. The chemical composition of L. camara oil plays a role in the biological activity; the β‐caryophyllene and (E)‐nerolidol chemotypes showed antimicrobial and cytotoxic activities.     

Optimization of staged bioleaching of low-grade chalcopyrite ore in the presence and absence of chloride in the irrigating lixiviant: ANFIS simulation

In this investigation, copper was bioleached from a low-grade chalcopyrite ore using a chloride-containing lixiviant. In this regard, firstly, the composition of the bacterial culture media was designed to control the cost in commercial application. The bacterial culture used in this process was acclimated to the presence of chloride in the lixiviant. Practically speaking, the modified culture helped the bio-heap-leaching system operate in the chloridic media. Compared to the copper recovery from the low-grade chalcopyrite by bioleaching in the absence of chloride, bioleaching in the presence of chloride resulted in improved copper recovery. The composition of the lixiviant used in this study was a modification with respect to the basal salts in 9 K medium to optimize the leaching process. When leaching the ore in columns, 76.81 % Cu (based on solid residues of bioleaching operation) was recovered by staged leaching with lixiviant containing 34.22 mM NaCl. The quantitative findings were supported by SEM/EDS observations, X-ray elemental mapping, and mineralogical analysis of the ore before and after leaching. Finally, Adaptive neuro-fuzzy inference system (ANFIS) was used to simulate the operational parameters affecting the bioleaching operation in chloride–sulfate system.     

Unmasking Heavily O-Glycosylated Serum Proteins Using Perchloric Acid: Identification of Serum Proteoglycan 4 and Protease C1 Inhibitor as Molecular Indicators for Screening of Breast Cancer

Heavily glycosylated mucin glycopeptides such as CA 27.29 and CA 15–3 are currently being used as biomarkers for detection and monitoring of breast cancer. However, they are not well detected at the early stages of the cancer. In the present study, perchloric acid (PCA) was used to enhance detection of mucin-type O-glycosylated proteins in the serum in an attempt to identify new biomarkers for early stage breast cancer. Sensitivity and specificity of an earlier developed sandwich enzyme-linked lectin assay were significantly improved with the use of serum PCA isolates. When a pilot case-control study was performed using the serum PCA isolates of normal participants (n = 105) and patients with stage 0 (n = 31) and stage I (n = 48) breast cancer, higher levels of total O-glycosylated proteins in sera of both groups of early stage breast cancer patients compared to the normal control women were demonstrated. Further analysis by gel-based proteomics detected significant inverse altered abundance of proteoglycan 4 and plasma protease C1 inhibitor in both the early stages of breast cancer patients compared to the controls. Our data suggests that the ratio of serum proteoglycan 4 to protease C1 inhibitor may be used for screening of early breast cancer although this requires further validation in clinically representative populations.