<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">J.F. Picron</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Food contamination with pyrrolizidine alkaloids: the expected… and the unexpected</style></title><secondary-title><style face="normal" font="default" size="100%">Giftige planten en hun toxines - wetgeving, controle en beheersing van giftige planten in voedselketen</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><pub-location><style face="normal" font="default" size="100%">Botanic Garden, Meise</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Pyrrolizidine alkaloids (PAs) and their N-oxides (PANOs) are natural toxins, exclusively biosynthesized by a wide variety of plant species (&amp;gt;6000). They are secondary plant metabolites against herbivores and are believed to be one of the most widely spread natural toxins. PAs and PANOs can become a significant public human health problem from the intake of contaminated food of botanical or animal origin. Human poisoning cases have been documented, are mainly characterized by acute and chronic liver damage, and can lead to death. Therefore, the development of efficient analytical methods was required to detect and quantify PAs/PANOs in a large range of food items in order to evaluate if they can pose a health problem, filling a data gap at Belgium’s level.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;The presentation will provide an introduction to those emerging natural toxins, will describe some analytical strategies deployed at Sciensano for different and highly diversified food matrices, including some original approaches, and will highlight some analytical results and the unexpected ones in particular.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">KVCV</style></issue></record></records></xml>