A central question that has long plagued
  • Significantly, a new CJD variation has been etiologically linked to exposure to BSE and scrapie agents through the b catenin inhibitor (Bruce et al., 1997; Ironside, 1998). Epidemiological studies have failed to identify specific risk factors for the disease other than the consumption of ABPs. However, experiments have demonstrated the transmission of BSE and scrapie via blood transfusions (Hunter et al., 2002; Houston et al., 2008). Cassard et al. (2014) demonstrated that scrapie prions have a zoonotic potential, raising new questions image about the possible link between animal and human prions in mouse models.
    The addition of ABPs to ruminant feed is prohibited in most countries due to the risk of PD transmission. Thus, monitoring PDs in ruminants is crucial and depends on accurate diagnoses. This unique challenge requires the development of novel assays to explore prion protein complexes (Sobrova et al., 2012). Currently diagnostic tests for PDs can only be performed when animals show symptoms or postmortem (Leal et al., 2015; Cosier and Daraban, 2016).
    Stable isotope ratio masimages spectrometry (IRMS) has recently been proposed as a tool for authenticating animal products (Bahar et al., 2008; Chesson et al., 2008; Heaton et al., 2008), certifying the geographic origin and types of sheep feed (Piasentier et al., 2003) and evaluating conventional and organic production systems for beef (Schmidt et al., 2005). The analysis of biological samples using this technique may reflect the animal proteins in diets (Denadai et al., 2008; Cruz et al., 2012). However, there is a gap between the approach used to trace proteins and assessments of their tissue turnover rates (Bahar et al., 2009). Ascertaining the assimilation of stable isotopes in different tissues or biological fluids can define turnover rates, which depend on feeding times (Fossato da Silva et al., 2012; Martinez et al., 2014).
    Using naturally occurring stable isotopes as dietary indicators can provide information about diets over both short- and long-term periods, depending on the type of tissue evaluated. However, to obtain such information, studies on the isotopic assimilation of organic matter in different animal tissues need to be carried out (Martins et al., 2012). There are few descriptions of turnover in biological samples and/or tissues from sheep, and they are focused on turnover involving C3 and C4 plant diets (Zazzo et al., 2008; Harrison et al., 2011; Martins et al., 2012) and lipid metabolism studies (Hattori et al., 2010; Richter et al., 2012).
    A theoretical model to express the relative isotopic enrichment (δx) using carbon-13 (δ13C) was proposed by Tieszen et al. (1983). The hypothesis is based on the metabolism of certain animal tissues, which depends on the input rate of dietary carbon compounds and the substitution rate of the preexisting compounds. This model provides parameters such as the half-life (T) and turnover rate (k), allowing the substitution time for the incorporation of a diet to be ascertained.
    Therefore, the aim of this study was to detect previous ABP intake by determining the stable isotope ratios for carbon (13C/12C) and nitrogen (15N/14N) in sheep serum.

    Materials and methods

    To determine whether the 12C/13C and 14N/15N ratios in sheep changed following dietary changes, these ratios were analyzed in three groups: one that was fed a base diet consisting of vegetable protein only (VP) for the 89 days of the experiment (days 0–89); one that was fed a diet with 30% bovine meat and bone meal added between days 16 and 89 (AVP); and one that was fed 30% bovine meat and bone meal between days 16 and 49 (AVPR).
    There was no variation in 13C isotope levels across all sample collection dates or among the experimental groups (Fig. 1); thus, turnover rates could not be estimated. In contrast, 15N incorporation increased following the inclusion of MBM in the diet and to decrease again following the removal of MBM from the diet, as shown by the results from the AVPR group (Fig. 2). For this group, a first-order polynomial fit identified a maximum 1

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