Virus-inhibitory activity of the antigen complex of opportunistic pathogenic bacteria against SARS-CoV-2

Introduction. The antigen complex of opportunistic pathogenic bacteria (ACOPB) has a protective effect against avian influenza viruses, herpes virus type 2, and other viruses that cause acute respiratory viral infections. In the context of the COVID-19 pandemic, an important task is to find out whether ACOPB has a protective effect against SARS-CoV-2. The purpose of the study was to evaluate in vitro the ACOPB virus-inhibitory activity against the Dubrovka laboratory strain of SARS-CoV-2. Materials and methods. The study was performed using Vero cell line CCL-81, human peripheral blood mononuclear cells (PBMCs), mouse monoclonal anti-idiotypic antibodies structurally mimicking biological effects of human interferons (IFNs), the Dubrovka laboratory strain of SARS-CoV-2. The infectivity of the virus was assessed by two methods: by virus titration using cell cultures and the limiting dilution method when the results are assessed by a cytopathic effect; the second method was a plaque assay. The in vitro virus inhibition test was performed using the cell culture susceptible to SARS-CoV-2; the mixture containing a specific dose of the virus and a two-fold dilution of ACOPB was transferred to the cell culture after the ACOPB medication had interacted with the virus at 4C for 2 hours. The ACOPB virus-inhibitory activity against SARS-CoV-2 was assessed by the functional activity of / and IFN receptors (RIFN) in human PBMCs induced in vitro by ACOPB and the ACOPB mixture with the specific dose of SARS-CoV-2. The RIFN expression level was measured by the indirect membrane immunofluorescence test. Results. Hemagglutination assay using chicken, mouse, guinea pig, and human red blood cells was performed for detection of the SARS-CoV-2 inhibitory protein. The lysate of Vero CCL-81 cells infected with SARS-CoV-2 Dubrovka demonstrated the highest hemagglutination activity with guinea pig red blood cells and low titers of hemagglutination in the virus-containing fluid. The virus inhibition test in the Vero CCL-81 cell culture demonstrated that ACOPB inhibited 10 doses of SARS-CoV-2 Dubrovka with the titer 1 : 32, providing 100% protection of the cell culture for 8 days (the monitoring period). ACOPB induced / and RIFN expression on membranes of human PBMCs in in vitro cultures and decreased RIFN / and expression after its interaction with SARS-CoV-2 Dubrovka. Conclusion. The experimental studies including the virus inhibition test in the cell culture susceptible to SARS-CoV-2 Dubrovka and the indirect membrane immunofluorescence assay using monoclonal anti-idiotypic antibodies mimicking IFN-like properties demonstrated that ACOPB had both an immunomodulatory and a virus-inhibitory effect

Ecological features of the persistence of Vibrio cholerae: retrospective analysis and actual state of the problem

The review presents retrospective data on six cholera pandemics and current views on the causative agent of the seventh pandemic V. cholerae El Tor, which caused a pandemic infection with the formation of true persistent and temporary intermediate endemic foci that provide the longest pathogen circulation in the history of the disease. One of the possible explanations for such a long course of the cholera pandemic is associated with an extremely high variability of the genome and the development of a number of adaptive reactions that allow cholera vibrios to adapt and remain in the environment. Due to the development of molecular genetic research methods, the ability of cholera vibrios to form biofilms which increases stress resistance, the ability to spread by attachment to abiotic (plastic) and biotic substrates (zooplankton and phytoplankton) has been discovered. Biofilm formation is also directly related to overcoming the antagonistic action of members of aquatic ecosystems. Another strategy for the survival of cholera vibrios is the transition to an uncultured state that proves a low level of death in the population. Published data on the possible effects of temperature increasing due to the climate change on cholera outbreaks in Africa (Democratic Republic of the Congo, Nigeria, Angola, Zimbabwe, Sierra Leone), Southeast Asia (Thailand, Malaysia), Central Asia (Pakistan, Afghanistan, Kazakhstan) and South Asia (Nepal) are overviewed. Based on the publications of recent years, an analysis is made of the current state of the studied problem in the Russian Federation and, in particular, in the Rostov region

Prevalence of anti-tuberculosis drug resistance in foreign-born tuberculosis cases in the U.S. and in their countries of origin.

BACKGROUND: Foreign-born individuals comprise >50% of tuberculosis (TB) cases in the U.S. Since anti-TB drug resistance is more common in most other countries, when evaluating a foreign-born individual for TB, one must consider the risk of drug resistance. Naturally, clinicians query The Global Project on Anti-tuberculosis Drug Resistance Surveillance (Global DRS) which provides population-based data on the prevalence of anti-TB drug resistance in 127 countries starting in 1994. However, foreign-born persons in the U.S. are a biased sample of the population of their countries of origin, and Global DRS data may not accurately predict their risk of drug resistance. Since implementing drug resistance surveillance in 1993, the U.S. National TB Surveillance System (NTSS) has accumulated systematic data on over 130,000 foreign-born TB cases from more than 200 countries and territories. Our objective was to determine whether the prevalence of drug resistance among foreign-born TB cases correlates better with data from the Global DRS or with data on foreign-born TB cases in the NTSS. METHODS AND FINDINGS: We compared the prevalence of resistance to isoniazid and rifampin among foreign-born TB cases in the U.S., 2007-2009, with US NTSS data from 1993 to 2006 and with Global DRS data from 1994-2007 visually with scatterplots and statistically with correlation and linear regression analyses. Among foreign-born TB cases in the U.S., 2007-2009, the prevalence of isoniazid resistance and multidrug resistance (MDR, i.e. resistance to isoniazid and rifampin), correlated much better with 1993-2006 US surveillance data (isoniazid: r = 0.95, P<.001, MDR: r = 0.75, P<.001) than with Global DRS data, 1994-2007 (isoniazid: r = 0.55, P = .001; MDR: r = 0.50, P<.001). CONCLUSION: Since 1993, the US NTSS has accumulated sufficient data on foreign-born TB cases to estimate the risk of drug resistance among such individuals better than data from the Global DRS

Isoniazid Resistant and Multidrug-Resistant Tuberculosis Among Foreign-born^*,† Cases in Recent U.S. NTSS (2007–2009), Previous U.S. NTSS (1993–2006) and Global DRS (1994–2007) Data.

<p><b>Note.</b> Countries and regions are sorted in descending order by prevalence of MDR TB in recent U.S. NTSS data (2007–2009).</p><p>N = total number of patients from specific country or region with reported DST results.</p><p>n = total number of patients from specific country or region with reported pattern of resistance (INH resistant or MDR, respectively).</p><p>NTSS = National Tuberculosis Surveillance System.</p><p>Global DRS =  Global Project on Anti-Tuberculosis Drug Resistance Surveillance.</p>*<p>Foreign-born include persons born outside the United States, American Samoa, the Federated States of Micronesia, Guam, the Republic of the Marshall Islands, Midway Island, the Commonwealth of the Northern Mariana Islands, Puerto Rico, the Republic of Palau, the U.S. Virgin Islands, and U.S. minor and outlying Pacific islands.</p>†<p>TB cases from 14 countries for which prevalence of drug-resistant TB was reported separately were not included in respective WHO regions counts.</p>‡<p>Rank of country was assigned based on 5-year average number of TB cases from that country in the U.S. in 2005–2009. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049355#pone.0049355-CDC1" target="_blank">[1]</a>.</p>§<p>WHO nine epidemiological regions <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049355#pone.0049355-World3" target="_blank">[8]</a> include following countries:</p><p><b>Africa – high HIV:</b> Botswana, Burkina Faso, Burundi, Cameroon, Central African Rep, Chad, Congo, Côte d’Ivoire, DR Congo, Ethiopia, Equatorial Guinea, Gabon, Kenya, Lesotho, Malawi, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Swaziland, Uganda, UR Tanzania, Zambia, Zimbabwe. Ethiopia was excluded from the region estimates and reported separately.</p><p><b>Africa – low HIV:</b> Algeria, Angola, Benin, Cape Verde, Comoros, Eritrea, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Madagascar, Mali, Mauritania, Mauritius, Niger, Sao Tome & Principe, Senegal, Seychelles, Sierra Leone, Togo.</p><p><b>Central Europe:</b> Albania, Bosnia & Herzegovina, Croatia, Cyprus, Hungary, Poland, Serbia & Montenegro, Slovakia, Slovenia, TFYR Macedonia, Turkey.</p><p><b>Eastern Europe:</b> Armenia, Azerbaijan, Belarus, Bulgaria, Estonia, Georgia, Kazakhstan, Kyrgystan, Latvia, Lithuania, Rep Moldova, Romania, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan.</p><p><b>Eastern Mediterranean:</b> Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libyan Arab Jamahiriya, Morocco, Oman, Pakistan, Qatar, Saudi Arabia, Somalia, Sudan, Syrian Arab Rep, Tunisia, United Arab Emirates, West Bank & Gaza Strip, Yemen.</p><p><b>Established Market Economies</b>: Andorra, Australia, Austria, Belgium, Canada, Czech Rep, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Japan, Luxembourg, Malta, Monaco, Netherlands, New Zealand, Norway, Portugal, San Marino, Singapore, Spain, Sweden, Switzerland, Vatican City, United Kingdom.</p><p><b>Latin America:</b> Anguilla, Antigua & Barbuda, Argentina, Bahamas, Barbados, Belize, Bermuda, Bolivia, Brazil, British Virgin Is, Cayman Is, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Montserrat, Netherlands Antilles, Nicargua, Panama, Paraguay, Peru, St Kitts & Nevis, St Lucia, St Vincent & the Grenadines, Suriname, Trinidad & Tobago, Turks & Caicos Is, Uruguay, Venezuela. Dominican Republic, Ecuador, Guatemala, El Salvador, Honduras, Mexico and Peru were excluded from the region estimates and reported separately.</p><p><b>South-East Asia:</b> Bangladesh, Bhutan, DPR Korea, India, Indonesia, Maldives, Myanmar, Nepal, Sri Lanka, Thailand, Timor-Leste. India was excluded from the region estimates and reported separately.</p><p><b>Western Pacific:</b> Brunei Darussalam, Cambodia, China, China Hong Kong SAR, China Macao SAR, Cook Is, Fiji, French Polynesia, Kiribati, Lao PDR, Malaysia, Mongolia, Nauru, New Caledonia, Niue, Papua New Guinea, Philippines, Rep Korea, Solomon Is, Taiwan, Tokelau, Tonga, Tuvalu, Vanuatu, Viet Nam, Wallis & Futuna Is, Western Samoa. Cambodia, China, Philippines, Republic of Korea and Viet Nam were excluded from the region estimates and reported separately.</p

Scatterplots of (A) prevalence of isoniazid resistance among recent foreign-born NTSS cases (2007–2009) versus prevalence of isoniazid resistance among (a) previous foreign-born NTSS cases (1993–2006), and (b) Global DRS TB cases (1994–2007), and (B) prevalence of MDR TB among foreign-born NTSS cases (2007–2009) versus prevalence of MDR TB among (c) previous foreign-born NTSS cases (1993–2006), and (d) Global DRS TB cases (1994–2007).

<p>Each dot represents a country or a region as specified in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049355#pone-0049355-t001" target="_blank">Table 1</a>.</p

Correlation and Simple Linear Regression Analyses of Prevalence of Drug-resistant TB in Recent and Previous U.S. NTSS Data and Global DRS Data.

<p>Note. *P value is reported for F test of overall significance of simple linear regression model. Dashes were put for comparisons where no linear association was observed. NTSS = National Tuberculosis Surveillance System. Global DRS =  Global Project on Anti-Tuberculosis Drug Resistance Surveillance.</p

Association between Mycobacterium tuberculosis complex phylogenetic lineage and acquired drug resistance.

BackgroundDevelopment of resistance to antituberculosis drugs during treatment (i.e., acquired resistance) can lead to emergence of resistant strains and consequent poor clinical outcomes. However, it is unknown whether Mycobacterium tuberculosis complex species and lineage affects the likelihood of acquired resistance.MethodsWe analyzed data from the U.S. National Tuberculosis Surveillance System and National Tuberculosis Genotyping Service for tuberculosis cases during 2004-2011 with assigned species and lineage and both initial and final drug susceptibility test results. We determined univariate associations between species and lineage of Mycobacterium tuberculosis complex bacteria and acquired resistance to isoniazid, rifamycins, fluoroquinolones, and second-line injectables. We used Poisson regression with backward elimination to generate multivariable models for acquired resistance to isoniazid and rifamycins.ResultsM. bovis was independently associated with acquired resistance to isoniazid (adjusted prevalence ratio = 8.46, 95% CI 2.96-24.14) adjusting for HIV status, and with acquired resistance to rifamycins (adjusted prevalence ratio = 4.53, 95% CI 1.29-15.90) adjusting for homelessness, HIV status, initial resistance to isoniazid, site of disease, and administration of therapy. East Asian lineage was associated with acquired resistance to fluoroquinolones (prevalence ratio = 6.10, 95% CI 1.56-23.83).ConclusionsWe found an association between mycobacterial species and lineage and acquired drug resistance using U.S. surveillance data. Prospective clinical studies are needed to determine the clinical significance of these findings, including whether rapid genotyping of isolates at the outset of treatment may benefit patient management

Genotoxicity of Natural Water during the Mass Development of Cyanobacteria Evaluated by the Allium Test Method: A Model Experiment with Microcosms

Cyanobacteria, which develop abundantly in aquatic ecosystems, can be harmful to humans and animals not only by releasing toxins that cause poisoning but also by provoking cytogenetic effects. The influence of the mass development of cyanobacteria on the genotoxic properties of natural water has been studied in model ecosystems (microcosms) with different compositions of biotic components (zooplankton, amphipods and fish). The validated plant test system “Allium test” was used in this study. Genotoxic effects were detected at microcystin concentrations below those established by the World Health Organization (WHO) for drinking water. In all experimental treatments, cells with disorders such as polyploidy and mitotic abnormalities associated with damage to the mitotic spindle, including c-mitosis, as well as lagging chromosomes were found. Genotoxic effects were associated with the abundance of cyanobacteria, which, in turn, depended on the composition of aquatic organisms in the experimental ecosystem. Fish, to a greater extent than other aquatic animals, maintain an abundance of cyanobacteria. After one month, in microcosms with fish, mitotic abnormalities and polyploidy continued to be detected, whereas in other treatments, there were no statistically significant genotoxic effects. In microcosms with amphipods, the number and biomass of cyanobacteria decreased to the greatest extent, and only one parameter of genotoxic activity (frequency of polyploidy) significantly differed from the control

Adaptive Digital Hologram Binarization Method Based on Local Thresholding, Block Division and Error Diffusion

High-speed optical reconstruction of 3D-scenes can be achieved using digital holography with binary digital micromirror devices (DMD) or a ferroelectric spatial light modulator (fSLM). There are many algorithms for binarizing digital holograms. The most common are methods based on global and local thresholding and error diffusion techniques. In addition, hologram binarization is used in optical encryption, data compression, beam shaping, 3D-displays, nanofabrication, materials characterization, etc. This paper proposes an adaptive binarization method based on a combination of local threshold processing, hologram division into blocks, and error diffusion procedure (the LDE method). The method is applied for binarization of optically recorded and computer-generated digital holograms of flat objects and three-dimensional scenes. The quality of reconstructed images was compared with different methods of error diffusion and thresholding. Image reconstruction quality was up to 22% higher by various metrics than that one for standard binarization methods. The optical hologram reconstruction using DMD confirms the results of the numerical simulations