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Aflatoxin contamination can appear in various points of the food chain. If animals are fed with contaminated feed, AFB1 is transformed-among others-to aflatoxin M1 (AFM1) metabolite. AFM1 is less toxic than AFB1, but it is still genotoxic and carcinogenic and it is present in raw and processed milk and all kinds of milk products. In this article, the chronic exposure estimation and risk characterization of Hungarian consumers are presented, based on the AFM1 contamination of milk and dairy products, and calculated with a probabilistic method, the two-dimensional Monte-Carlo model. The calculations were performed using the R plugin (mc2d package) integrated into the KNIME (Konstanz Information Miner) software. The simulations were performed using data from the 2018-2020 food consumption survey. The AFM1 analytical data were derived from the Hungarian monitoring survey and 1,985 milk samples were analyzed within the framework of the joint project of the University of Debrecen and the National Food Chain Safety Office of Hungary (NÉBIH). Limited AFM1 concentrations were available for processed dairy products; therefore, a database of AFM1 processing factors for sour milk products and various cheeses was produced based on the latest literature data, and consumer exposure was calculated with the milk equivalent of the consumed quantities of these products. For risk characterization, the calculation of hazard index (HI), Margin of Exposure, and the hepatocellular carcinoma incidence were used. The results indicate that the group of toddlers that consume a large amount of milk and milk products are exposed to a certain level of health risk. The mean estimated daily intake of toddlers is in the range of 0.008-0.221 ng kg

The conversion of aflatoxin B1 in feed consumed by cows into aflatoxin M1 in their milk poses a challenge to food safety, with milk being a popular staple food and because of the harmful effects of these compounds. This study aimed at reviewing scientific information about the extent of carry-over of AFB1 from feed to milk. A range of studies reported about correlations of carry-over with different factors, particularly with milk yield and AFB1 intake. The extent of carry-over considerably varies, being 1–2% on average, which may be as high as 6% in the case of increased milk production. Specific factors influencing transfer rates, including milk yield, somatic cell counts, aflatoxin B1 intake, source of contamination, seasonal effects, particle size of feed, and the effects of certain interventions, namely vaccination and the use of adsorbents, are identified as the most important and are discussed in this review. The different mathematical formulas describing carry-over and instances of their application are reviewed as well. These carry-over equations may lead to largely different results, and no single carry-over equation can be suggested as the best one. While the exact quantification of carry-over is difficult as the process depends on many factors, including individual variabilities between animals, the intake of aflatoxin B1 and milk yield seem to be the most important factors influencing the excreted amount of aflatoxin M1 and the rate of carry-over.

Dendritic spines are the primary sites of excitatory transmission in the mammalian brain. Spines of cerebellar Purkinje Cells (PCs) are plastic, but they differ from forebrain spines in a number of important respects, and the mechanisms of spine plasticity differ between forebrain and cerebellum. Our previous studies indicate that in hippocampal spines cortactin—a protein that stabilizes actin branch points—resides in the spine core, avoiding the spine shell. To see whether the distribution of cortactin differs in PC spines, we examined its subcellular organization using quantitative preembedding immunoelectron microscopy. We found that cortactin was enriched in the spine shell, associated with the non-synaptic membrane, and was also situated within the postsynaptic density (PSD). This previously unrecognized distribution of cortactin within PC spines may underlie structural and functional differences in excitatory spine synapses between forebrain, and cerebellum.

Background Novel Coronavirus Disease (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), threatens humanity in terms of health and economy as it spreads extremely fast and causes massive epidemics all over the world. In the absence of a vaccine, social isolation and hygienic measures are the only way to curb the virus. Methods In our study, the Hungarian spread of COVID-19 is modelled by applying a modified SEIR (Susceptible, Exposed, Infected, Recovered) compartment model, which takes into account the route of disease transmission not only from infected, but from latent individuals (exposed compartment) as well. The differences between the modified model and the traditional SEIR model has been evaluated. The different scenarios of disease spreading simulate the effect of the different level of interventions (social distancing and hygienic measures) taken place in Hungary. The modelling also considers the population and mobility data which are also essential in case of infectious disease spreading. For controlling the disease in the long-term a network-based analysis is provided based on the concept of the epidemic threshold and the identification of super-spreader population groups. Results According to sensitivity analysis of the modified SEIR model, disease transmission of latent individuals has the greatest effect on the number of infections. Based on the results, the applied interventions have a great impact on the disease spreading and are effective in controlling the COVID-19 epidemic., a network-based analysis is provided based on the concept of the epidemic threshold and the identification of super-spreader population groups. According to the results of the network-based study, the proportion of people to be sampled for an effective disease control is the function of the identified people with high number of contacts in social networks who act as super-spreaders. Conclusion Applying network-based random, selective and targeted sampling, testing and isolation of affected individuals would yield significantly different sample sizes, highlighting the importance of super-spreaders. Network analysis (but also all computational science methods) need large amount of good quality data and the spread of these methods could be supported by easy-to-use tools. We wanted to raise awareness also on this issue.

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.