Microbial Factor, Its Role in the Development and Course of Chronic Periodontitis, Current Research Direction (Literature Review)

The purpose of the study was to analyze the available data about the role of the microbial factor in the development and course of chronic periodontitis at the present stage on the basis of available domestic and foreign specialized literature, to identify unsolved problems and outline directions for further research. Materials and methods. The special literature is analyzed: periodicals for the last 10 years, basic manuals and monographs. We used descriptive method. Results and discussion. A large number of works are devoted to the analysis of the composition and properties of bacterial biofilm of the oral cavity using microscopic, bacteriological and molecular research methods used to assess microbial risk factors for periodontal diseases. At the same time, satisfactory results of conservative treatment of this pathology vary from 61.1% to 93.9%. The situation is aggravated by the fact that apical periodontitis, cystogranulomas and radicular cysts in 65.0% are the cause of severe complications that threaten death. Even outside of exacerbation, the presence of foci of focal infection is accompanied by sensitization of the patient's body and contribute to its generalization. The accumulated experience of research on the etiology and pathogenesis of periodontal diseases over the past decades indicates that the leading role in the formation and development of the inflammatory process of this localization belongs to obligate-anaerobic and microaerophilic facultative-anaerobic microflora. Despite a significant number of studies devoted to this issue, the problem of the effectiveness of endodontic treatment nowadays is far from its final solution, which convinces of the relevance of the research undertaken and its expediency. Conclusion. The results of the analysis of special literature allow us to conclude that the development of new rational complex methods of treatment based on an in-depth analysis of morphological, microbiological, immunological, biochemical, clinical and somatic components is based not only on the need to create effective methods of treatment of chronic periodontitis and the justification of their differentiated use, but also on the need for preventive measures aimed at preventing the development of severe complications of acute odontogenic infection and its generalization. The development of new effective and rational methods for the treatment of chronic periodontitis based on their differentiated use will reduce the number of cases of acute odontogenic infection and its severe complications, which will positively affect the quality of life of patients, increase the rates of specialized medical care and will have a certain socio-economic significance

Microbial-Maximum Likelihood Estimation Tool for Microbial Quantification in Food From Left-Censored Data Using Maximum Likelihood Estimation for Microbial Risk Assessment

In food microbial measurements, when most or very often bacterial counts are below to the limit of quantification (LOQ) or the limit of detection (LOD) in collected food samples, they are either ignored or a specified value is substituted. The consequence of this approach is that it may lead to the over or underestimation of quantitative results. A maximum likelihood estimation (MLE) or Bayesian models can be applied to deal with this kind of censored data. Recently, in food microbiology, an MLE that deals with censored results by fitting a parametric distribution has been introduced. However, the MLE approach has limited practical application in food microbiology as practical tools for implementing MLE statistical methods are limited. We therefore developed a user-friendly MLE tool (called “Microbial-MLE Tool”), which can be easily used without requiring complex mathematical knowledge of MLE but the tool is designated to adjust log-normal distributions to observed counts, and illustrated how this method may be implemented for food microbial censored data using an Excel spreadsheet. In addition, we used two case studies based on food microbial laboratory measurements to illustrate the use of the tool. We believe that the Microbial-MLE tool provides an accessible and comprehensible means for performing MLE in food microbiology and it will also be of help to improve the outcome of quantitative microbial risk assessment (MRA).

Absence of virological and epidemiological evidence that SARS-CoV-2 poses COVID-19 risks from environmental fecal waste, wastewater and water exposures

This review considers evidence for infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presence and COVID-19 infection and illness resulting from exposure to environmental fecal wastes and waters. There is no documented evidence that (1) infectious, replication-capable SARS-CoV-2 is present in environmental fecal wastes, wastewater or water, and (2) well-documented epidemiological evidence of COVID-19 infection, illness or death has never been reported for these exposure media. COVID-19 is transmitted mainly by direct personal contact and respiratory secretions as airborne droplets and aerosols, and less so by respiratory-secreted fomites via contact (touch) exposures. While SARS-CoV-2 often infects the gastrointestinal tract of infected people, its presence as infectious, replication-capable virus in environmental fecal wastes and waters has never been documented. There is only rare and unquantified evidence of infectious, replication-capable SARS-CoV-2 in recently shed feces of COVID-19 hospital patients. The human infectivity dose–response relationship of SARS-CoV-2 is unknown, thereby making it impossible to estimate evidence-based quantitative health effects assessments by quantitative microbial risk assessment methods requiring both known exposure assessment and health effects assessment data. The World Health Organization, Water Environment Federation, US Centers for Disease Control and Prevention and others do not consider environmental fecal wastes and waters as sources of exposure to infectious SARS-CoV-2 causing COVID-19 infection and illness.

Untangling the Governance of Public Health Aspects of Manure in The Netherlands

The Netherlands is one of the most densely populated countries in terms of people and livestock and is the second largest exporter of agricultural products worldwide. As a result, the Netherlands has a manure surplus. Excess application of manure can lead to environmental problems; therefore, manure needs to be treated and discharged. Manure can contain zoonotic pathogens, but whether exposure to manure and manure treatment also poses a risk to public health is still unknown. This study analysed the regulations, relevant actors, and responsibilities in the complex system of manure and public health in the Netherlands. Interviews and system mapping have demonstrated interlinkages between environmental, economic, and health aspects. Constraints and opportunities for public health protection have been identified. This study reveals the complexity of the Dutch manure policy, its scattered responsibilities, the challenge to deal with uncertainties, and, most importantly, the need for a microbial risk assessment in order to adequately communicate and manage possible risks to protect the health of animals, the environment, and people.

Improved quantitative microbiome profiling for environmental antibiotic resistance surveillance

Background Understanding environmental microbiomes and antibiotic resistance (AR) is hindered by over reliance on relative abundance data from next-generation sequencing. Relative data limits our ability to quantify changes in microbiomes and resistomes over space and time because sequencing depth is not considered and makes data less suitable for Quantitative Microbial Risk Assessments (QMRA), critical in quantifying environmental AR exposure and transmission risks. Results Here we combine quantitative microbiome profiling (QMP; parallelization of amplicon sequencing and 16S rRNA qPCR to estimate cell counts) and absolute resistome profiling (based on high-throughput qPCR) to quantify AR along an anthropogenically impacted river. We show QMP overcomes biases caused by relative taxa abundance data and show the benefits of using unified Hill number diversities to describe environmental microbial communities. Our approach overcomes weaknesses in previous methods and shows Hill numbers are better for QMP in diversity characterisation. Conclusions Methods here can be adapted for any microbiome and resistome research question, but especially providing more quantitative data for QMRA and other environmental applications.