ABSTRACT
In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from farmed salmon. The lipids extracted from salmon muscles of different production methods and origins (26 wild from Canada, 25 farmed from Canada, 24 farmed from Chile and 25 farmed from Norway) were analyzed by gas chromatography with flame ionization detector (GC-FID). All the tested chemometric approaches, namely principal components analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and seven machine learning classifiers, namely k-nearest neighbors (kNN), decision tree, support vector machine (SVM), random forest, artificial neural networks (ANN), naïve Bayes and AdaBoost, allowed for differentiation between farmed and wild salmons using the 17 features obtained from chemical analysis. PCA did not allow clear distinguishing between salmon geographical origin since farmed samples from Canada and Chile overlapped. Nevertheless, using the 17 features in the models, six out of the seven tested machine learning classifiers allowed a classification accuracy of ≥99%, with ANN, naïve Bayes, random forest, SVM and kNN presenting 100% accuracy on the test dataset. The classification models were also assayed using only the best features selected by a reduction algorithm and the best input features mapped by t-SNE. The classifier kNN provided the best discrimination results because it correctly classified all samples according to production method and origin, ultimately using only the three most important features (16:0, 18:2n6c and 20:3n3 + 20:4n6). In general, the classifiers presented good generalization with the herein proposed approach being simple and presenting the advantage of requiring only common equipment existing in most labs.
ABSTRACT
N-benzyladriamycin-14-valerate (AD 198) is pharmacologically superior to Adriamycin (ADR) based upon comparable cytotoxicity, decreased cardiotoxicity and the ability of AD 198 to circumvent multidrug resistance conferred by either P-glycoprotein overexpression or reduced topoisomerase II activity. AD 198, however, suffers from systemic lability of the 14-O-valerate moiety to enzymatic and non-enzymatic cleavage to yield N-benzyladriamycin (AD 288), which is more similar to ADR in activity. The purpose of this study was to determine whether stability of the ester linkage could be achieved while preserving the favorable characteristics of AD 198 by using a series of N-benzylated ADR congeners containing 14-O-acyl substitutions of incrementally shorter carbon chain lengths. Results from this study indicate that the linear five-carbon valerate substitution is the minimum length necessary to circumvent P-glycoprotein and prevent inhibition of topoisomerase II activity. In addition, although AD 198 is not a pro-drug of AD 288, intracellular 14-O-acyl cleavage appears to contribute to the cytotoxicity of AD 198.
