scholarly journals ECOLOGICAL CHARACTERISTICS OF ANTIBIOTIC RESISTANCE OF CONDITIONALLY PATHOGENIC MICROORGANISMS PERSISTENT IN HYDROECOSYSTEMS

2018 ◽  
pp. 53-57 ◽  
Author(s):  
Lyubov Vladimirovna Lartseva ◽  
Olga Valentinovna Obukhova
Keyword(s):  
Antibiotic Resistance ◽  
Large Scale ◽  
Anthropogenic Factors ◽  
Pathogenic Microorganisms ◽  
Veterinary Science ◽  
Volga River ◽  
Volga River Delta ◽  
Pike Perch ◽  
Study Results ◽  
Minimum Resistance

The article provides an overview of investigating antibiotic resistance of conditionally pathogenic microflora circulating in different hydroecosystems. It has been stated that the process of spreading antibiotic resistance in bacteria around the world is progressing in a large scale. It has been found that the peculiarities of its manifestation are largely determined by natural, climatic and anthropogenic factors, as well as by the level of urbanization. Mechanisms of microorganism interaction with separate antibiotics are studied. The data obtained show that antibiotics widely used in medicine, veterinary science and aquaculture have caused antibiotic resistance in microflora isolated from hydroecosystems and hydrobionts (fish). The study results of the Russian and foreign scientists on antibiotic resistance of bacteria isolated from water and fish have been brought. Thus, microorganisms isolated from urban watercourses of Astrakhan, the Volga river Delta and pike perch body organs showed multiple antibiotic resistance depending on the season and the studied area. In all cases there have been recorded the minimum resistance of microflora to tobramycin and chloramphenicol and the maximum - to benzylpenicillin and ampicillin. The obtained data can serve as indicators of sanitary and epidemiological and environmental problems of hydroecosystems.

GROWTH OF PIKE-PERCH SANDER LUCIOPERCA (L., 1758) (PERCIDAE) IN RESERVOIRS OF K. SATPAYEV’S CHANNEL

2018 ◽  
pp. 59-68
Author(s):  
Saule Zhangirovna Asylbekova ◽  
Kuanysh Baibulatovich Isbekov ◽  
Vladimir Nickolaevich Krainyuk
Keyword(s):  
Growth Rates ◽  
Growth Dynamics ◽  
High Growth ◽  
Water Bodies ◽  
Volga River ◽  
Trophic Resources ◽  
Pike Perch ◽  
The Amur River ◽  
Back Calculation ◽  
Abiotic And Biotic Factors

Pike-perch is an invader for the water basins of Central Kazakhstan. These species have stable self-reproductive populations in the regional waters. Back calculation method was used to investigate pike-perch growth rates in reservoirs of K. Satpayev’s channel. For comparison, the data from the other water bodies (Vyacheslavsky and Sherubay-Nurinsky water reservoirs) were used, as well as literature data. Pike-perch species from the investigated waters don’t show high growth rates. The populations from the reservoirs of K. Satpayev’s channel have quite similar growth rates with populations from the Amur river, from a number of reservoirs in the Volga river basin and from the reservoir in Spain. Sexual differences in growth have not been observed. Evaluating possible influence of various abiotic and biotic factors on the growth rate of pike-perch in the reservoirs of K. Satpayev’s channel was carried out. It has been stated that the availability of trophic resources cannot play a key role in growth dynamics because of their high abundance. Morphology of water bodies also does not play a role, as well as chromaticity, turbidity and other optical water indicators. It can be supposed that the main factor influencing growth of pike perch is the habitat’s temperature. This factor hardly ever approaches optimal values for the species in reservoirs of K. Satpaev’s channel. The possible influence of fishing selectivity on pike-perch growth rates was also evaluated. Currently, there has been imposed a moratorium on pike-perch catch. However, pike-perch is found in by-catches and in catches of amateur fishermen. It should be said that such seizures have an insignificant role in the dynamics of growth rates.

CHARACTERISTICS OF FREE-RADICAL PROCESSES IN THE ORGANISMS OF SOME PREDATORY FISH SPECIES IN DIFFERENT SEASONS OF THE YEAR

2017 ◽  
pp. 117-123
Author(s):  
Nikolay Aleksandrovich Pudovkin ◽  
Peter Vladimirovich Smutnev
Keyword(s):  
Fish Species ◽  
Catalase Activity ◽  
Perca Fluviatilis ◽  
Selenium Concentration ◽  
The Body ◽  
Predatory Fish ◽  
Volga River ◽  
Silurus Glanis ◽  
Average Value ◽  
Pike Perch

The authors of the article have studied the content of the elements of anti-oxidant system (malondialdehyde, catalase, selenium) in tissues of the internal organs (gills, intestine, muscles, liver, swimbladder, scales) in some species of predatory fish (pike Esox lucius (L., 1758), perch Perca fluviatilis (L., 1758), pike-perch Sander lucioperca (L., 1758), catfish Silurus glanis ) widespread in the basin of the Volga river in the Saratov region. The lowest concentration of malondialdehyde in organisms of the studied fish species is observed in fall and winter; the highest - in spring and summer. Catalase activity in gills tissue of a pike raised in 11.8%, cat-fish - 9.1%, pike-perch - 7.5%, perch - 7.8%. In fall (compared to winter) enzyme activity lowering in gonads of pike-perch makes 16.3%, in gonads of perch - 14.4%. In other tissues there were not observed any evident changes of catalase activity. Fish species under consideration are listed according to the average value of selenium concentration in organisms, µg/g: pike (0.208) > catfish (0.207) > pike-perch (0.196) > perch (0.178). According to the average value of the selenium accumulation in the body in different season all the studied species can be placed in the following order, µg/g: winter-pike (0.132) > pike-perch (0.136) > perch and catfish (0.142); spring - pike-perch (0.190) > perch (0.191) > pike (0.208) > catfish (0.209); summer - perch (0.186) > pike-perch (0.190) > catfish and pike (0.203); autumn - perch (0.193) > pike-perch (0.268) > > catfish (0.274) > pike (0.289).

The gut microbiota resistome provides development of drug resistance in causative agents of human infectious diseases

2017 ◽  
pp. 20-32 ◽  
Author(s):  
Е.Н. Ильина ◽  
Е.И. Олехнович ◽  
А.В. Павленко
Keyword(s):  
Drug Resistance ◽  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Integrated Approach ◽  
Modern Medicine ◽  
Pathogenic Microorganisms ◽  
Human Pathogens ◽  
Potential Source ◽  
Causative Agents ◽  
Bacterial Genes

С течением времени подходы к изучению резистентности к антибиотикам трансформировались от сосредоточения на выделенных в виде чистой культуры патогенных микроорганизмах к исследованию резистентности на уровне микробных сообществ, составляющих биотопы человека и окружающей среды. По мере того, как продвигается изучение устойчивости к антибиотикам, возникает необходимость использования комплексного подхода для улучшения информирования мирового сообщества о наблюдаемых тенденциях в этой области. Все более очевидным становится то, что, хотя не все гены резистентности могут географически и филогенетически распространяться, угроза, которую они представляют, действительно серьезная и требует комплексных междисциплинарных исследований. В настоящее время резистентность к антибиотикам среди патогенов человека стала основной угрозой в современной медицине, и существует значительный интерес к определению ниши, в которых бактерии могут получить гены антибиотикорезистентности, и механизмов их передачи. В данном обзоре мы рассматриваем проблемы, возникшие на фоне широкого использования человечеством антибактериальных препаратов, в свете формирования микрофлорой кишечника резервуара генов резистентности. Over the time, studies of antibiotic resistance have transformed from focusing on pathogenic microorganisms isolated as a pure culture to analysis of resistance at the level of microbial communities that constitute human and environmental biotopes. Advancing studies of antibiotic resistance require an integrated approach to enhance availability of information about observed tendencies in this field to the global community. It becomes increasingly obvious that, even though not all resistance genes can geographically and phylogenetically spread, the threat they pose is indeed serious and requires complex interdisciplinary research. Currently, the antibiotic resistance of human pathogens has become a challenge to modern medicine, which is now focusing on determining a potential source for bacterial genes of drug resistance and mechanisms for the gene transmission. In this review, we discussed problems generated by the widespread use of antibacterial drugs in the light of forming a reservoir of resistance genes by gut microflora.

Analysis of the modern use of natural territorial complex of the Volga river Delta landscape for the agricultural purposes

2020 ◽  
Vol 64 (2) ◽  
pp. 186-195
Author(s):  
Zanozin V.V. ◽  
◽  
Barmin A.N. ◽  
Keyword(s):  
River Delta ◽  
Volga River ◽  
Volga River Delta

Transformation of periphyton communities in reservoirs of the Volga river delta

2016 ◽  
Vol 54 (1) ◽  
pp. 013-017
Author(s):  
B.M. Nasibulina ◽  
◽  
T.F. Kurochkina ◽  
A.A. Istelyueva ◽  
◽  
...  
Keyword(s):  
River Delta ◽  
Volga River ◽  
Volga River Delta

scholarly journals Tu1497 NATIONWIDE SURVEY OF HELICOBACTER PYLORI ANTIBIOTIC RESISTANCE IN HIGH PREVALENCE OF GASTRIC CANCER COUNTRY (BHUTAN): A LARGE-SCALE COMMUNITY-BASED STUDY

2020 ◽  
Vol 91 (6) ◽  
pp. AB591-AB592
Author(s):  
Ratha-Korn Vilaichone ◽  
Natsuda Aumpan ◽  
Tomohisa Uchida ◽  
Thawee Ratanachu-ek ◽  
Lotay Tshering ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Helicobacter Pylori ◽  
Antibiotic Resistance ◽  
Large Scale ◽  
Nationwide Survey ◽  
Community Based ◽  
High Prevalence

Prevalence and distribution analysis of antibiotic resistance genes in a large-scale aquaculture environment

2020 ◽  
Vol 711 ◽  
pp. 134626 ◽  
Author(s):  
Xiaoxiao Shen ◽  
Guangqiu Jin ◽  
Yongjun Zhao ◽  
Xiaohou Shao
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Large Scale ◽  
Antibiotic Resistance Genes ◽  
Distribution Analysis

scholarly journals Antibacterial Compounds from Mushrooms: A Lead to Fight ESKAPEE Pathogenic Bacteria?

Planta Medica ◽  
2020 ◽  
Author(s):  
Violette Hamers ◽  
Clément Huguet ◽  
Mélanie Bourjot ◽  
Aurélie Urbain
Keyword(s):  
Antibiotic Resistance ◽  
Global Health ◽  
Pathogenic Bacteria ◽  
Resistance Mechanisms ◽  
Pathogenic Microorganisms ◽  
Bacterial Strains ◽  
Antibacterial Compounds ◽  
New Antibiotics ◽  
Hospital Stays ◽  
Antibacterial Potential

AbstractInfectious diseases are among the greatest threats to global health in the 21st century, and one critical concern is due to antibiotic resistance developed by an increasing number of bacterial strains. New resistance mechanisms are emerging with many infections becoming more and more difficult if not impossible to treat. This growing phenomenon not only is associated with increased mortality but also with longer hospital stays and higher medical costs. For these reasons, there is an urgent need to find new antibiotics targeting pathogenic microorganisms such as ESKAPEE bacteria. Most of currently approved antibiotics are derived from microorganisms, but higher fungi could constitute an alternative and remarkable reservoir of anti-infectious compounds. For instance, pleuromutilins constitute the first class of antibiotics derived from mushrooms. However, macromycetes still represent a largely unexplored source. Publications reporting the antibacterial potential of mushroom extracts are emerging, but few purified compounds have been evaluated for their bioactivity on pathogenic bacterial strains. Therefore, the aim of this review is to compile up-to-date data about natural products isolated from fruiting body fungi, which significantly inhibit the growth of ESKAPEE pathogenic bacteria. When available, data regarding modes of action and cytotoxicity, mandatory when considering a possible drug development, have been discussed in order to highlight the most promising compounds.

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

scholarly journals Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Niloufar Nouri ◽  
Naresh Devineni ◽  
Valerie Were ◽  
Reza Khanbilvardi
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Southern Oscillation ◽  
The United States ◽  
Anthropogenic Factors ◽  
Climate Variables ◽  
Term Trend ◽  
Cyclical Variability ◽  
Long Term Trend

AbstractThe annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

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