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Two characteristics of the Mycobacterium tuberculosis complex (MTC) are particularly relevant for tuberculosis (TB) epidemiology and control, namely the ability of this group of pathogens to survive in the environment and thereby facilitate indirect transmission via water or feed, and the capacity to infect multiple host species including human beings, cattle, wildlife, and domestic animals other than cattle. As a consequence, rather than keeping the focus on certain animal species regarded as maintenance hosts, we postulate that it is time to think of complex and dynamic multi-host MTC maintenance communities where several wild and domestic species and the environment contribute to pathogen maintenance. Regarding the global situation of animal TB, many industrialized countries have reached the Officially Tuberculosis Free status. However, infection of cattle with M. bovis still occurs in most countries around the world. In low- and middle-income countries, human and animal TB infection is endemic and bovine TB control programs are often not implemented because standard TB control through testing and culling, movement control and slaughterhouse inspection is too expensive or ethically unacceptable. In facing increasingly complex epidemiological scenarios, modern integrated disease control should rely on three main pillars: (1) a close involvement of farmers including collaborative decision making, (2) expanding the surveillance and control targets to all three host categories, the environment, and their interactions, and (3) setting up new control schemes or upgrading established ones switching from single tool test and cull approaches to integrated ones including farm biosafety and vaccination.
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BACKGROUND: Inclusion of high throughput technologies in the field of biology has generated massive amounts of data in the recent years. Now, transforming these huge volumes of data into knowledge is the primary challenge in computational biology. The traditional methods of data analysis have failed to carry out the task. Hence, researchers are turning to machine learning based approaches for the analysis of high-dimensional big data. In machine learning, once a model is trained with a training dataset, it can be applied on a testing dataset which is independent. In current times, deep learning algorithms further promote the application of machine learning in several field of biology including plant virology. MAIN BODY: Plant viruses have emerged as one of the principal global threats to food security due to their devastating impact on crops and vegetables. The emergence of new viral strains and species help viruses to evade the concurrent preventive methods. According to a survey conducted in 2014, plant viruses are anticipated to cause a global yield loss of more than thirty billion USD per year. In order to design effective, durable and broad-spectrum management protocols, it is very important to understand the mechanistic details of viral pathogenesis. The application of machine learning enables precise diagnosis of plant viral diseases at an early stage. Furthermore, the development of several machine learning-guided bioinformatics platforms has primed plant virologists to understand the host-virus interplay better. In addition, machine learning has tremendous potential in deciphering the pattern of plant virus evolution and emergence as well as in developing viable control options. CONCLUSIONS: Considering a significant progress in the application of machine learning in understanding plant virology, this review highlights an introductory note on machine learning and comprehensively discusses the trends and prospects of machine learning in the diagnosis of viral diseases, understanding host-virus interplay and emergence of plant viruses.
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Vírus de Plantas , Viroses , Algoritmos , Biologia Computacional/métodos , Vírus de DNA , Aprendizado de Máquina , Vírus de Plantas/genética , Plantas , Viroses/diagnósticoRESUMO
BACKGROUND AND AIM: Highly pathogenic avian influenza (HPAI) is a deadly virus of zoonotic potential. The study mainly aims to determine the risk pathways (RPs) for the probable incursion of HPAI virus (HPAIV) in backyard poultry in Bangladesh. MATERIALS AND METHODS: The study involves expert elicitation technique. The concept map determines the possible RPs. The map consists of 16 concepts, each with nodes from which probabilities of an event originates. These probabilities are described by qualitative descriptors ranging from negligible to high. Risk assessment has been performed using the subjective risk assessment tool. RESULTS: The tool demonstrates positive correlation among groups of experts in the level of agreement by scoring RP; however, the level of agreement varies from 71% to 93% among group of experts. The median risk score of viral incursion through the "Exposure of backyard poultry with farm poultry in the trading market" was 11 and ranked as top, followed by "Contaminated live bird market environment" and "Sharing common scavenging space with migratory birds" (median risk score, 10.5; rank, 2), and "Scavenging of infected slaughtered poultry remnants by backyard poultry" (median risk score, 5.3; rank, 3) when no control options were applied along with the RPs. After applying or considering control option along with contaminated live bird market environment, the median risk score was reduced to 5.0. Applying a specific control option along with each RP reduced estimated median risk scores for HPAIV incursions. CONCLUSION: This study provides an insight into the incursion risks of HPAIV through various RPs in backyard poultry in Bangladesh.
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A multi-country outbreak of Listeria monocytogenes ST6 linked to blanched frozen vegetables (bfV) took place in the EU (2015-2018). Evidence of food-borne outbreaks shows that L. monocytogenes is the most relevant pathogen associated with bfV. The probability of illness per serving of uncooked bfV, for the elderly (65-74 years old) population, is up to 3,600 times greater than cooked bfV and very likely lower than any of the evaluated ready-to-eat food categories. The main factors affecting contamination and growth of L. monocytogenes in bfV during processing are the hygiene of the raw materials and process water; the hygienic conditions of the food processing environment (FPE); and the time/Temperature (t/T) combinations used for storage and processing (e.g. blanching, cooling). Relevant factors after processing are the intrinsic characteristics of the bfV, the t/T combinations used for thawing and storage and subsequent cooking conditions, unless eaten uncooked. Analysis of the possible control options suggests that application of a complete HACCP plan is either not possible or would not further enhance food safety. Instead, specific prerequisite programmes (PRP) and operational PRP activities should be applied such as cleaning and disinfection of the FPE, water control, t/T control and product information and consumer awareness. The occurrence of low levels of L. monocytogenes at the end of the production process (e.g. < 10 CFU/g) would be compatible with the limit of 100 CFU/g at the moment of consumption if any labelling recommendations are strictly followed (i.e. 24 h at 5°C). Under reasonably foreseeable conditions of use (i.e. 48 h at 12°C), L. monocytogenes levels need to be considerably lower (not detected in 25 g). Routine monitoring programmes for L. monocytogenes should be designed following a risk-based approach and regularly revised based on trend analysis, being FPE monitoring a key activity in the frozen vegetable industry.
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Managing and monitoring invasive alien species (IAS) is costly, and because resources are limited, prioritization decisions are required for planning and management. We present findings on plant pest prioritization for 63 established invader species of natural and grazing ecosystems of Queensland, Australia. We used an expert elicitation approach to assess risk (species occurrence, spread, and impact) and feasibility of control for each IAS. We elicit semi-quantitative responses from diverse expert stakeholders to score IAS on three management approaches (biocontrol, chemical and mechanical) in relation to cost, effectiveness and practicality, and incorporate uncertainty in expert inputs and model outputs. In the process, we look for promising management opportunities as well as seek general trends across species' ecological groups and management methods. Stakeholders were cautiously optimistic about the feasibility of managing IAS. Taking into consideration all factors, the overall feasibility of control was uncorrelated with the stakeholders' level of confidence. However, within individual management criterion, positive trend was observed for the same bivariate traits for chemical control, and negative trends for biocontrol and mechanical controls. Utility and confidence in IAS management options were in the order: chemicalâ¯>â¯biocontrolâ¯=â¯mechanical, with practicality and effectiveness being the main driver components. Management feasibility differed significantly between IAS life forms but not between habitats invaded. Lastly, we combined IAS risk assessment and management feasibility scores to create a risk matrix to guide policy goals (i.e. eradication, spread containment, protection of sensitive sites, targeted control, site management, monitoring, and limited action). The matrix identifies promising species to target for each of these policy outcomes. Overall, our general approach illustrates (i) the importance of understanding the feasibility of IAS control actions and the factors that drive it, and (ii) demonstrates how quantifying management feasibility can be used to enhance traditional risk assessment rankings to improve policy outcomes.
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Ecossistema , Espécies Introduzidas , Austrália , Estudos de Viabilidade , QueenslandRESUMO
EFSA and EMA have jointly reviewed measures taken in the EU to reduce the need for and use of antimicrobials in food-producing animals, and the resultant impacts on antimicrobial resistance (AMR). Reduction strategies have been implemented successfully in some Member States. Such strategies include national reduction targets, benchmarking of antimicrobial use, controls on prescribing and restrictions on use of specific critically important antimicrobials, together with improvements to animal husbandry and disease prevention and control measures. Due to the multiplicity of factors contributing to AMR, the impact of any single measure is difficult to quantify, although there is evidence of an association between reduction in antimicrobial use and reduced AMR. To minimise antimicrobial use, a multifaceted integrated approach should be implemented, adapted to local circumstances. Recommended options (non-prioritised) include: development of national strategies; harmonised systems for monitoring antimicrobial use and AMR development; establishing national targets for antimicrobial use reduction; use of on-farm health plans; increasing the responsibility of veterinarians for antimicrobial prescribing; training, education and raising public awareness; increasing the availability of rapid and reliable diagnostics; improving husbandry and management procedures for disease prevention and control; rethinking livestock production systems to reduce inherent disease risk. A limited number of studies provide robust evidence of alternatives to antimicrobials that positively influence health parameters. Possible alternatives include probiotics and prebiotics, competitive exclusion, bacteriophages, immunomodulators, organic acids and teat sealants. Development of a legislative framework that permits the use of specific products as alternatives should be considered. Further research to evaluate the potential of alternative farming systems on reducing AMR is also recommended. Animals suffering from bacterial infections should only be treated with antimicrobials based on veterinary diagnosis and prescription. Options should be reviewed to phase out most preventive use of antimicrobials and to reduce and refine metaphylaxis by applying recognised alternative measures.