Memory efficient algorithm for solving the inverse gravimetry problem of finding several boundary surfaces in multilayered medium

For solving the inverse gravimetry problem of finding several boundary surfaces in a multilayered medium, the parallel algorithm was constructed and implemented for multicore CPU using OpenMP technology. The algorithm is based on the modified nonlinear conjugate gradient method with weighting factors previously proposed by authors. To reduce the memory requirements and computation time, the modification was constructed on the basis of utilizing the Toeplitz-block-Toeplitz structure of the Jacobian matrix of the integral operator. The model problem of reconstructing three surfaces using the quasi-real gravitational data was solved on a large grid. It was shown that the proposed implementation reduces the computation time by 80% in comparison with the earlier algorithm based on calculating the entire matrix. The parallel algorithm shows good scaling of 94% on 8-core processor. © 2019 Author(s).Ministry of Education and Science of the Republic of Kazakhstan: AP 05133873This work was financially supported by the Ministry of Education and Science of the Republic of Kazakhstan (project AP 05133873)

Characterization of tularemia foci in the Republic of Kazakhstan from 2000 to 2020

The wide distribution of tularemia in the territory of Kazakhstan is associated with landscape and geographical characteristics. This is explained by a combination of natural factors: the presence of certain types of rodents—reservoirs and sources, ectoparasites—carriers of the causative agent of tularemia. The study of the current spatial and temporal characterization of tularemia in Kazakhstan from 2000 to 2020 will determine the epidemiological status of tularemia and improve the monitoring system in Kazakhstan. In this work we demonstrated the results of a retrospective survey of natural foci of tularemia: analysis of vector, small mammal and human data. The spatial and temporal characteristics of tularemia from 2000 to 2020 in the territory of Kazakhstan were studied in comparison with historical data, including the description of tularemia outbreaks, the clinical picture, and the source of infection, transmission factors, and geographical coordinates of outbreak registration. Sampling was carried out by trapping rodents on snap traps and collecting ticks by rodent combing and by "flagging" methods. For the last 20 years, 85 human cases of tularemia have been reported. During the period from 2000 to 2020, more than 600 strains of F. tularensis were isolated from field rodents and ticks in the natural foci of tularemia. MLVA typing of F. tularensis strains isolated from natural foci of tularemia in Kazakhstan over the past 20 years. The results of retrospective monitoring indicate that currently active foci of tularemia include the Aktobe, West Kazakhstan, Almaty, East Kazakhstan, and Pavlodar regions. Low-activity natural foci are located in the territory of the Akmola, Karaganda, North Kazakhstan, Kostanay, Atyrau, Zhambyl, and Kyzylorda regions. There are no active natural foci of tularemia in the Mangystau and Turkestan regions. The widespread occurrence of tularemia in the country is associated with landscape and geographical features that contribute to the circulation of the pathogen in the natural focus. An analysis of natural foci of tularemia showed that it is necessary to continue monitoring studies of carriers and vectors for the presence of the causative agent of the F. tularensis, in order to prevent mass cases of human disease

DEVELOPMENT AND VALIDATION OF HYBRID BRILLOUIN-RAMAN SPECTROSCOPY FOR NONCONTACT ASSESSMENT OF MECHANO-CHEMICAL PROPERTIES OF URINE PROTEINS AS BIOMARKERS OF KIDNEY DISEASES

Background Proteinuria is a major marker of chronic kidney disease (CKD) progression and the predictor of cardiovascular mortality. The rapid development of renal failure is expected in those patients who have higher level of proteinuria however, some patients may have slow decline of renal function despite lower level of urinary protein excretion. The different mechanical (visco-elastic) and chemical properties, as well as the proteome profiles of urinary proteins might explain their tubular toxicity mechanism. Brillouin light scattering (BLS) and surface enhanced Raman scattering (SERS) spectroscopies are non-contact, laser optical-based techniques providing visco-elastic and chemical property information of probed human biofluids. We proposed to study and compare these properties of urinary proteins using BLS and SERS spectroscopies in nephrotic patient and validate hybrid BLS-SERS spectroscopy in diagnostic of urinary proteins as well as their profiling. The project ultimately aims for the development of an optical spectroscopic sensor for rapid, non-contact monitoring of urine samples from patients in clinical settings. Methods BLS and SERS spectroscopies will be used for non-contact assessment of urinary proteins in proteinuric patients and healthy subjects and will be cross-validated by Liquid Chromatography-Mass Spectrometry (LC-MS). Participants will be followed-up during the 1 year and all adverse events such as exacerbation of proteinuria, progression of CKD, complications of nephrotic syndrome, disease relapse rate and inefficacy of treatment regimen will be registered referencing incident dates. Associations between urinary protein profiles (obtained from BLS and SERS as well as LC-MS) and adverse outcomes will be evaluated to identify most unfavored protein profiles. Discussion This prospective study is focused on the development of non-contact hybrid BLS - SERS sensing tool and its clinical deployment for diagnosis and prognosis of proteinuria. We will identify the most important types of urine proteins based on their visco-elasticity, amino-acid profile and molecular weight responsible for the most severe cases of proteinuria and progressive renal function decline. We will aim for the developed hybrid BLS - SERS sensor, as a new diagnostic & prognostic tool, to be transferred to other biomedical applications. Trial registration The trial has been approved by ClinicalTrials.gov (Trial registration ID NCT04311684). The date of registration was March 17, 2020

Datasheet1_Characterization of tularemia foci in the Republic of Kazakhstan from 2000 to 2020.xls

The wide distribution of tularemia in the territory of Kazakhstan is associated with landscape and geographical characteristics. This is explained by a combination of natural factors: the presence of certain types of rodents—reservoirs and sources, ectoparasites—carriers of the causative agent of tularemia. The study of the current spatial and temporal characterization of tularemia in Kazakhstan from 2000 to 2020 will determine the epidemiological status of tularemia and improve the monitoring system in Kazakhstan. In this work we demonstrated the results of a retrospective survey of natural foci of tularemia: analysis of vector, small mammal and human data. The spatial and temporal characteristics of tularemia from 2000 to 2020 in the territory of Kazakhstan were studied in comparison with historical data, including the description of tularemia outbreaks, the clinical picture, and the source of infection, transmission factors, and geographical coordinates of outbreak registration. Sampling was carried out by trapping rodents on snap traps and collecting ticks by rodent combing and by "flagging" methods. For the last 20 years, 85 human cases of tularemia have been reported. During the period from 2000 to 2020, more than 600 strains of F. tularensis were isolated from field rodents and ticks in the natural foci of tularemia. MLVA typing of F. tularensis strains isolated from natural foci of tularemia in Kazakhstan over the past 20 years. The results of retrospective monitoring indicate that currently active foci of tularemia include the Aktobe, West Kazakhstan, Almaty, East Kazakhstan, and Pavlodar regions. Low-activity natural foci are located in the territory of the Akmola, Karaganda, North Kazakhstan, Kostanay, Atyrau, Zhambyl, and Kyzylorda regions. There are no active natural foci of tularemia in the Mangystau and Turkestan regions. The widespread occurrence of tularemia in the country is associated with landscape and geographical features that contribute to the circulation of the pathogen in the natural focus. An analysis of natural foci of tularemia showed that it is necessary to continue monitoring studies of carriers and vectors for the presence of the causative agent of the F. tularensis, in order to prevent mass cases of human disease.</p

Vectors, molecular epidemiology and phylogeny of TBEV in Kazakhstan and central Asia

BACKGROUND: In the South of Kazakhstan, Almaty Oblastʼ (region) is endemic for tick-borne encephalitis, with 0.16–0.32 cases/100,000 population between 2016–2018. The purpose of this study was to determine the prevalence and circulating subtypes of tick-borne encephalitis virus (TBEV) in Almaty Oblastʼ and Kyzylorda Oblastʼ. METHODS: In 2015 we investigated 2341 ticks from 7 sampling sites for the presence of TBEV. Ticks were pooled in 501 pools and isolated RNA was tested for the presence of TBEV by RT-qPCR. For the positive samples, the E gene was amplified, sequenced and a phylogenetic analysis was carried out. RESULTS: A total of 48 pools were TBEV-positive by the RT-qPCR. TBEV-positive ticks were only detected in three districts of Almaty Oblastʼ and not in Kyzylorda Oblastʼ. The positive TBEV pools were found within Ixodes persulcatus, Haemaphysalis punctata and Dermacentor marginatus. These tick species prevailed only in Almaty Oblastʼ whereas in Kyzylorda Oblastʼ Hyalomma asiaticum and D. marginatus are endemic. The minimum infection rates (MIR) in the sampling sites were 4.4% in Talgar, 2.8% in Tekeli and 1.1% in Yenbekshikazakh, respectively. The phylogenetic analysis of the generated sequences indicates that TBEV strains found in Almaty Oblastʼ clusters in the Siberian subtype within two different clades. CONCLUSIONS: We provided new data about the TBEV MIR in ticks in Almaty Oblastʼ and showed that TBEV clusters in the Siberian Subtype in two different clusters at the nucleotide level. These results indicate that there are different influences on the circulating TBEV strains in south-eastern Kazakhstan. These influences might be caused by different routes of the virus spread in ticks which might bring different genetic TBEV lineages to Kazakhstan. The new data about the virus distribution and vectors provided here will contribute to an improvement of monitoring of tick-borne infections and timely anti-epidemic measures in Kazakhstan