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In order to intensify and guarantee the agricultural productivity and thereby to be able to feed the world's rapidly growing population, irrigation has become very important. In parallel, the limited water resources lead to an increase in usage of poorly characterized sources of water, which is directly linked to a higher prevalence of foodborne diseases. Therefore, analyzing the microorganisms or even the complete microbiome of irrigation water used for food production can prevent the growing numbers of such cases. In this study, we compared the efficacy of MALDI-TOF Mass spectrometry (MALDI TOF MS) identification to 16S rRNA gene Sanger sequencing of waterborne microorganisms. Furthermore, we analyzed the whole microbial community of irrigation water using high-throughput 16S rRNA gene amplicon sequencing. The identification results of MALDI-TOF MS and 16S rRNA gene Sanger sequencing were almost identical at species level (66.7%; 64.3%). Based on the applied cultivation techniques, Acinetobacter spp., Enterobacter spp., Pseudomonas spp., and Brevundimonas spp. were the most abundant cultivable genera. In addition, the uncultivable part of the microbiome was dominated by Proteobacteria followed by Actinobacteria, Bacteroidota, Patescibacteria, and Verrucomicrobiota. Our findings indicate that MALDI-TOF MS offers a fast, reliable identification method and can act as an alternative to 16S rRNA gene Sanger sequencing of isolates. Moreover, the results suggest that MALDI-TOF MS paired with 16S rRNA gene amplicon sequencing have the potential to support the routine monitoring of the microbiological quality of irrigation water.

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The working programme 'Emerging risk identification by applying data analytical tools' was delivered by the Digital Food Chain Education, Research, Development, and Innovation Institute (Digital Food Institute, DFI) on the field of emerging risks at the University of Veterinary Medicine Budapest, Hungary. The Institute is the University's research and education unit that provides data analysis and research along the whole food chain and takes networking in this area to a new level. The Fellow joined the hub of experts and researchers in the field of food chain safety data analysis, responsible for protecting public health concerning food in Hungary. The programme consisted of several different activities to provide an overview of the different tools that can be employed in the emerging risk identification process and prepare various stakeholders for new food chain safety issues. The programme was split into four modules to run over the one-year fellowship covering different areas of data analysis and emerging risk identification. The aim was to be fully integrated with the organisation's work experience, increase knowledge of scientific aspects relevant in the field of data analysis and visualisation tools in the emerging risk identification area, and implement the results into various EU stakeholders' environments assessments.

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The study presents a systematic review of published scientific articles investigating the effects of interventions aiming at aflatoxin reduction at the feed production and animal feeding phases of the milk value chain in order to identify the recent scientific trends and summarize the main findings available in the literature. The review strategy was designed based on the guidance of the systematic review and knowledge synthesis methodology that is applicable in the field of food safety. The Web of Science and EBSCOhost online databases were searched with predefined algorithms. After title and abstract relevance screening and relevance confirmation with full-text screening, 67 studies remained for data extraction, which were included in the review. The most important identified groups of interventions based on their mode of action and place in the technological process are as follows: low-moisture production using preservatives, acidity regulators, adsorbents and various microbiological additives. The results of the listed publications are summarized and compared for all the identified intervention groups. The paper aimed to help feed producers, farmers and relevant stakeholders to get an overview of the most suitable aflatoxin mitigation options, which is extremely important in the near future as climate change will likely be accompanied by elevated mycotoxin levels.

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The Spatiotemporal Epidemiologic Modeler (STEM) is an open source software project supported by the Eclipse Foundation and used by a global community of researchers and public health officials working to track and, when possible, control outbreaks of infectious disease in human and animal populations. STEM is not a model or a tool designed for a specific disease; it is a flexible, modular framework supporting exchange and integration of community models, reusable plug-in components, and denominator data, available to researchers worldwide at www.eclipse.org/stem. A review of multiple projects illustrates its capabilities. STEM has been used to study variations in transmission of seasonal influenza in Israel by strains; evaluate social distancing measures taken to curb the H1N1 epidemic in Mexico City; study measles outbreaks in part of London and inform local policy on immunization; and gain insights into H7N9 avian influenza transmission in China. A multistrain dengue fever model explored the roles of the mosquito vector, cross-strain immunity, and antibody response in the frequency of dengue outbreaks. STEM has also been used to study the impact of variations in climate on malaria incidence. During the Ebola epidemic, a weekly conference call supported the global modeling community; subsequent work modeled the impact of behavioral change and tested disease reintroduction via animal reservoirs. Work in Germany tracked salmonella in pork from farm to fork; and a recent doctoral dissertation used the air travel feature to compare the potential threats posed by weaponizing infectious diseases. Current projects include work in Great Britain to evaluate control strategies for parasitic disease in sheep, and in Germany and Hungary, to validate the model and inform policy decisions for African swine fever. STEM Version 4.0.0, released in early 2019, includes tools used in these projects and updates technical aspects of the framework to ease its use and re-use.

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Advanced oxidation processes are promising technologies for removal of antibiotic residues from wastewater in terms of their high efficacy. However, recent studies have reported the remaining antibacterial activity of the products at early-stages of treatment. The present study investigates the effect of such products of model ß-lactams (amoxicillin, ampicillin, cloxacillin) on bacteria introducing structure-based, and biological approaches involving Gram-positive and Gram-negative bacterial strains. Chemical analysis revealed the destruction of the ß-lactam pharmacophore in competition with the reaction at the aromatic ring. Multisite attack occurs on the penicillin skeleton producing OH-substituted products. The enhanced hydrophilicity confers higher diffusion rate through the porin channels of Gram-negative bacteria and through the hydrophilic cell wall of Gram-positive species. Accordingly, an increase in acute toxicity of treated samples was observed at the beginning of the treatment. The same tendency was observed for target-specific antimicrobial activity investigated with antibiotic susceptibility testing (agar-diffusion, bacterial growth). Prolonged treatments yielded products, e.g. polyhydroxylated phenolic compounds, being also deleterious for bacteria. Therefore, the advanced oxidation process should be judiciously optimized.

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Bacteriocin producing lactic acid bacteria (LAB) cultures can be used as biopreservatives in fermented food products; thus the food industry is interested in stable cultures that produce bacteriocins consistently. Inhibtion of Listeria spp. by bacteriocinogenic Pediococcus acidilactici and Lactobacillus plantarum (both isolated from fermented meats) was investigated under conditions of stress induced by low pH and high salt concentrations. Listeria monocytogenes serogroup IIb (from cheese), L. monocytogenes serogroup IVb (from cheese), L. monocytogenes serogroup IIb (from ground beef) and Listeria innocua NCTC 11288 were used as target strains. P. acidilactici and Lb. plantarum demonstrated antilisterial activity under the stress conditions investigated (pH 3.5; pH 8.5; 7.5% NaCl). However, activity was dependent on the stress conditions applied and on the target organism. L. monocytogenes serogroup IIb (from ground beef) and L. innocua C 11288 were, respectively the most sensitive and the most resistant to the cell-free supernatants produced by the LAB investigated.

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