The Efficacy of Additives for the Mitigation of Aflatoxins in Animal Feed: A Systematic Review and Network Meta-Analysis

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Abstract

The contamination of animal feed with aflatoxins is an ongoing and growing serious issue, particularly for livestock farmers in tropical and subtropical regions. Exposure of animals to an aflatoxin-contaminated diet impairs feed efficiency and increases susceptibility to diseases, resulting in mortality, feed waste, and increased production costs. They can also be excreted in milk and thus pose a significant human health risk. This systematic review and network meta-analysis aim to compare and identify the most effective intervention to alleviate the negative impact of aflatoxins on the important livestock sector, poultry production. Eligible studies on the efficacy of feed additives to mitigate the toxic effect of aflatoxins in poultry were retrieved from different databases. Additives were classified into three categories based on their mode of action and composition: organic binder, inorganic binder, and antioxidant. Moreover, alanine transaminase (ALT), a liver enzyme, was the primary indicator. Supplementing aflatoxin-contaminated feeds with different categories of additives significantly reduces serum ALT levels (p < 0.001) compared with birds fed only a contaminated diet. Inorganic binder (P-score 0.8615) was ranked to be the most efficient in terms of counteracting the toxic effect of aflatoxins, followed by antioxidant (P-score 0.6159) and organic binder (P-score 0.5018). These findings will have significant importance for farmers, veterinarians, and animal nutrition companies when deciding which type of additives to use for mitigating exposure to aflatoxins, thus improving food security and the livelihoods of smallholder farmers in developing countries.

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Ranking treatments in frequentist network meta-analysis works without resampling methods

Gerta Rücker, Guido Schwarzer (2015)

Background Network meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments. The treatments can then be ranked by the surface under the cumulative ranking curve (SUCRA). For comparing treatments in a network meta-analysis, we propose a frequentist analogue to SUCRA which we call P-score that works without resampling. Methods P-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments. Results Using case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical. Conclusions Ranking treatments in frequentist network meta-analysis works without resampling. Like the SUCRA values, P-scores induce a ranking of all treatments that mostly follows that of the point estimates, but takes precision into account. However, neither SUCRA nor P-score offer a major advantage compared to looking at credible or confidence intervals. Electronic supplementary material The online version of this article (doi:10.1186/s12874-015-0060-8) contains supplementary material, which is available to authorized users.

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Global Mycotoxin Occurrence in Feed: A Ten-Year Survey

Christiane Gruber-Dorninger, Timothy Jenkins, Gerd Schatzmayr (2019)

Mycotoxins contaminating animal feed can exert toxic effects in animals and be transferred into animal products. Therefore, mycotoxin occurrence in feed should be monitored. To this end, we performed a large-scale global survey of mycotoxin contamination in feed and assessed regional differences and year-to-year variation of mycotoxin occurrence. Concentrations of aflatoxin B1, zearalenone, fumonisins, ochratoxin A, deoxynivalenol, and T-2 toxin were analyzed in 74,821 samples of feed and feed raw materials (e.g., maize, wheat, soybean) collected from 100 countries from 2008 to 2017. In total, 88% of the samples were contaminated with at least one mycotoxin. Mycotoxin occurrence showed distinct regional trends and climate was a key determinant governing these trends. In most regions, the majority of samples complied with maximum levels and guidance values for mycotoxins in animal feed that are in effect in the European Union. However, 41.1%, 38.5%, and 20.9% of samples from South Asia, Sub-Saharan Africa, and Southeast Asia, respectively, exceeded the maximum level for aflatoxin B1 (20 µg/kg). In several regions, mycotoxin concentrations in maize showed a pronounced year-to-year variation that could be explained by rainfall or temperature during sensitive periods of grain development. A large fraction of samples (64%) was co-contaminated with ≥ 2 mycotoxins. Most frequently observed mycotoxin mixtures were combinations of deoxynivalenol, zearalenone, and fumonisins, as well as fumonisins and aflatoxin B1. Deoxynivalenol and zearalenone concentrations were correlated in maize and wheat. In conclusion, according to an extensive global survey, mycotoxin (co-)contamination of animal feed is common, shows regional trends, and is governed in part by climate and weather.