Bacterial meningitis (BM) is a public health burden in developing countries, including Central Asia. This disease is characterized by a high mortality rate and serious neurological complications. Delay with the start of adequate therapy is associated with an increase in mortality for patients with acute bacterial meningitis. Cerebrospinal fluid culture, as a gold standard in bacterial meningitis diagnosis, is time-consuming with modest sensitivity, and this is unsuitable for timely decision-making. It has been shown that bacterial meningitis differentiation from viral meningitis could be done through different parameters such as clinical signs and symptoms, laboratory values, such as PCR, including blood and cerebrospinal fluid (CSF) analysis. In this study, we proposed the method for distinguishing the bacterial form of meningitis from enteroviral one. The method is based on the machine learning process deriving making decision rules. The proposed fast-and-frugal trees (FFTree) decision tree approach showed an ability to determine procalcitonin and C-reactive protein (CRP) with cut-off values for distinguishing between bacterial and enteroviral meningitis (EVM) in children. Such a method demonstrated 100% sensitivity, 96% specificity, and 98% accuracy in the differentiation of all cases of bacterial meningitis in this study. These findings and proposed method may be useful for clinicians to facilitate the decision-making process and optimize the diagnostics of meningitis.

Objectives To determine the prevalence of Escherichia coli STs and associated resistance mechanisms carried by the community in North-East India. Methods E. coli (108) were isolated from sewage collected from 19 sites across the city of Silchar by plating on MacConkey agar with/without selection (50 mg/L cefotaxime). Species identification was confirmed by MALDI-TOF MS for 82 isolates. Common resistance mechanisms were determined by WGS of pooled E. coli isolates. PFGE combined with specific probes determined the presence of common resistance mechanisms in all isolates. Phylotypes, multilocus STs, core-genome multilocus STs, resistance genes and virulence genes were determined by in silico analysis of 38 genomes. Results and conclusions Analysis of isolates collected without selection (n = 33) indicated that cefotaxime resistance in E. coli was 42% (14/33) and estimated meropenem resistance at 9%. The remaining 58% (19/33) were additionally susceptible to ampicillin, trimethoprim, ciprofloxacin and aminoglycosides. The most common ST among the cefotaxime-resistant E. coli was ST167 (29%), followed by ST410 (17%) and ST648 (10%). E. coli ST131 was absent from the collection. Sixty-three isolates were resistant to cefotaxime and harboured blaCTX-M-15 [54% (34/63)] or blaCMY-42 [46% (29/63)], of which 10% (6/63) harboured both genes. Carbapenem resistance was due to blaNDM-5, found in 10/63 cefotaxime-resistant isolates, and/or blaOXA-181, found in 4/63 isolates. NDM-5 was encoded by IncX3 and/or IncFII plasmids and CMY-42 was mostly encoded by IncI plasmids. NDM-5 appears to have replaced NDM-1 in this region and CMY-42 appears to be in the process of replacing CTX-M-15.

The most prevalent STs were ST394, ST10 and ST648, accounting for 39% of all isolates collected and were found at many sites across Islamabad. Carbapenemase genes were absent and only a single isolate of ST131 was found. The most prevalent resistance mechanisms were qnrS1 and blaCTX-M-15, with blaCTX-M-15 penetrating many STs and found in 31% of all collected isolates. However, the majority of the successful STs were blaCTX-M-15 negative indicating that resistance is not the main driver of prevalence. Twenty-three percent of blaCTX-M-15 genes were chromosomally encoded and large ISEcp1-mediated insertions included qnrS1 and several plasmid genes. In all chromosomally encoded isolates no plasmid copies of blaCTX-M-15 were found. The most prevalent ST (ST394) contained many enteroaggregative E. coli virulence genes and the fimH30 variant allele previously linked to the success of ST131.

Introduction: Giardia intestinalis is the most important and common diarrhea-causing parasitic protozoa worldwide with growing clinical relevance in public health. There are many documented cases of G. intestinalis resistance to metronidazole (MZ). Pyruvate: ferredoxin oxidoreductase (PFOR), the membrane-localized enzyme, plays a key role in the development of resistance to drugs. The aim of the present study was to evaluate the difference in the levels of PFOR gene expression between MZ-resistant and MZ-susceptible strains of G. intestinatlis. Methodology: From 159 samples with G. intestinalis cysts, 48 strains were successfully cultivated. Using specific pair primers, PFOR gene expressions were estimated in different groups of Giardia. The polymerase chain reaction (PCR) data were analyzed with Bayesian analysis of qRT-PCR data using MCMC.qpcr package, with relative expression software tool (REST) and quantitative PCR CopyCount web source. Results: In the group of Giardia with minimum inhibitory concentration (MIC) of 6.3 µM, the level of PFOR gene expression was downregulated and compared with controls, differed by 1.5 to 2.8 times. At the same time, there was no significant difference in PFOR gene expression between the control (susceptible) group and the group with MIC of 3.2 µM. Conclusions: Though there is association between PFOR gene expression and metronidazole resistance of Giardia intestinalis, the level of PFOR gene expression cannot be a strong genetic marker to predict level of resistance to metronidazole based on MICs.

BACKGROUND: The prevalence of rheumatoid arthritis (RA) is 1% in the global population. The lack of epidemiological studies in developing countries makes it difficult to obtain a complete global epidemiological picture of RA. RA develops due to the interaction of multiple genetic and environmental factors, though the contribution of these factors to the various disease occurrence seen in different populations is unclear. AIM: The aim of our study was to analyze the dynamics of the general prevalence and incidence of RA among the population of Kazakhstan in 2017–2019 as well as to investigate the three most common single-nucleotide polymorphisms (SNP) of RA in the Kazakhstan population. METHODS: The analysis of statistical data on Form 12 “On the health of the people and the health care system” was carried out. Prevalence and incidence rates were calculated according to generally accepted rules. Demographic data for the Republic of Kazakhstan were obtained from the official website stat.gov.kz. Our study included 70 RA patients and 113 control subjects. Blood samples were collected and genotyped for peptidylarginine deiminase 4 (PADI4), protein tyrosine phosphatase 22, and human leukocyte antigen (HLA)-DRB9 SNPs by reverse transcription polymerase chain reaction. RESULTS: The prevalence of RA in Kazakhstan in 2017–2019 was 0.36–0.38%, with an incidence rate of 0.085–0.087%, which can be comparable to data of other countries in Central Asia. The allele and genotypes frequency analyses were carried out between patients and controls. The HLA-DRB9 showed significant association of the G allele odds ratio (OR) 1.96 (95% confidence interval [CI]: 1.252–3.081), p= 0.0025 and G/G genotype OR = 3.67 (95% CI: 1.58–8.54), p = 0.00162 with RA in our sample. Strong association between anti-citrullinated protein antibody (ACPA) profile and PADI4 (OR 12.19 [95% CI: 2.19–67.94], p = 0.00115) was found. CONCLUSION: There was an increase in RA prevalence with age among females and a higher crude prevalence and incidence of RA in the southern regions of Kazakhstan. HLA-DRB9 prevailed in Kazakhstani patients with RA, PADI4 showed association with ACPA-positive RA. Further studies on larger samples are required to confirm our obtained results.