The study of H. pylori putative candidate factors for single- and multi-component vaccine development

Helicobacter pylori has grown to colonize inside the stomach of nearly half of the world’s population, turning into the most prevalent infections in the universe. Medical care failures noticeably confirm the need for a vaccine to hinder or deal with H. pylori. This review is planned to discuss the most known factors as a vaccine candidate, including single (AhpC, BG, CagA, KatA, Fla, Hsp, HWC, Lpp, LPS, NAP, OMP, OMV, SOD, Tpx, Urease, VacA) and multi-component vaccines. Many promising results in the field of single and multivalent vaccine can be seen, but there is no satisfactory outcome and neither a prophylactic nor a therapeutic vaccine to treat or eradicate the infection in human has been acquired. Hence, selecting suitable antigen is an important factor as an appropriate adjuvant. Taken all together, the development of efficient anti-H. pylori vaccines relies on the fully understanding of the interactions between H. pylori and its host immune system. Therefore, more work should be done on epitope mapping, analysis of molecular structure, and determination of the antigen determinant region as well due to design a vaccine, preferably a multi-component vaccine to elicit specific CD4 T-cell responses that are required for H. pylori vaccine efficacy.     

Cytotoxic lesions of the corpus callosum (CLOCCs) associated with SARS-CoV-2 infection

Journal of Neurology -     

Toll-Like Receptor (TLR)-9 rs352140 Polymorphism is an Immunopathology Protective Factor in Parkinson's Disease in the Northern Iranian Population

Background: Neuroinflammation and immunopathology in Parkinson's disease (PD) are believed to be associated with genetic and environmental factors. Objective: We conducted the current study to evaluate the Toll-like receptors (TLR4 and TLR9) genes polymorphism in patients with Parkinson's disease in northern Iran. Methods: We extracted DNA from peripheral blood samples of 100 sporadic cases of Parkinson's disease and 100 healthy-matched controls with the mean age of 69.98 and 71.94 years, respectively. Subsequently, single-nucleotide polymorphisms (SNPs) of TLR4 and TLR9 were genotyped using restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR). Results were confirmed employing Sanger sequencing. For the analysis of our data, we used SNPStats and SPSS 22 software. Results: Our findings indicated that the allele distribution for rs352140 of TLR9 gene was significantly different in the PD group compared with the healthy controls (p=0.02). Moreover, rs352140 T allele was observed to be correlated with PD reduced risk (TT + TC vs. CC). The dominant rs352140 model was approved as the most acceptable inheritance model for fitting the data (OR 0.41, 95% CI 0.23-0.75, p=0.0031). Additionally, haplotype analysis revealed a significant correlation between TLR9 polymorphisms and Parkinson's disease. Conclusion: The results of this study indicated that rs352140T of TLR9 gene was a protective factor in Parkinson's disease. Furthermore, this SNP could be regarded as a prognostic factor. However, this conclusion should be confirmed by further investigations.     

Effect of melatonin supplementation on sleep quality: a systematic review and meta-analysis of randomized controlled trials

Journal of Neurology - The Present study was conducted to systematically review the effect of the melatonin on sleep quality. We summarized evidence from randomized clinical trials (RCTs) that...     

Prediction of drug‐drug interactions using physiologically‐based pharmacokinetic models of CYP450 modulators included in Simcyp software

In recent years, physiologically based PharmacoKinetic (PBPK) modeling has received growing interest as a useful tool for the assessment of drug pharmacokinetics. It has been demonstrated to be informative and helpful to quantify the modification in drug exposure due to specific physio‐pathological conditions, age, genetic polymorphisms, ethnicity and particularly drug–drug interactions (DDIs). In this paper, the prediction success of DDIs involving various cytochrome P450 isoenzyme (CYP) modulators namely ketoconazole (a competitive inhibitor of CYP3A), itraconazole (a competitive inhibitor of CYP3A), clarithromycin (a mechanism‐based inhibitor of CYP3A), quinidine (a competitive inhibitor of CYP2D6), paroxetine (a mechanism‐based inhibitor of CYP2D6), ciprofloxacin (a competitive inhibitor of CYP1A2), fluconazole (a competitive inhibitor of CYP2C9/2C19) and rifampicin (an inducer of CYP3A) were assessed using Simcyp^® software. The aim of this report was to establish confidence in each CYP‐specific modulator file so they can be used in the future for the prediction of DDIs involving new victim compounds. Our evaluation of these PBPK models suggested that they can be successfully used to evaluate DDIs in untested scenarios. The only noticeable exception concerned a quinidine inhibitor model that requires further improvement. Additionally, other important aspects such as model validation criteria were discussed.