Right auricle aneurysm in dogs can be detected with multidetector-row CT and presents with varying morphology

Right auricle aneurysm (RAA) has been reported to be a rare congenital or acquired condition in dogs, however published CT characteristics are limited to a small number of cases. The aim of this 13-year, single-center, retrospective, cross-sectional study was to describe the prevalence and appearance of RAA in a larger group of dogs. Reports of 10,886 dogs that underwent thoracic CT examination for various reasons were reviewed. Computed tomographic data of dogs with presumed RAA (based on published imaging characteristics) were retrieved from the archive. Oblique multiplanar reformatted images were used to record RAA site, shape, and dimensions (neck, maximum height and width). Patients’ sex, age, and body weight were evaluated for any association with the presence of RAA. Presumed RAA was detected in 23/10,886 dogs having thoracic CT in the selected period of time (prevalence 0.21%). Three RAA phenotypes were described: diffuse saccular dilation in 19 of 23 dogs, focal saccular dilation in three of 23 dogs, and fusiform in one of 23 dogs. The bodyweights of dogs with presumed RAA were significantly lower than those of the remaining 10836 dogs without RAA (median 8 kg [IQR 5; range 37.6] and median 16 kg [IQR 23; range 116.9] respectively; P < 0.003. Female sex was also significantly associated with RAA (P = 0.03). Findings indicated that RAA has a low prevalence in dogs, can be detected with CT, can be present in asymptomatic dogs, and can have varying appearances. In this sample of dogs, female sex and low body weight were significantly associated with RAA.     

Comparison of the amounts of volatile compounds in French protected designation of origin virgin olive oils

Headspace solid-phase microextraction (HS-SPME) -gas chromatography using flame ionization detection and multivariate analysis were applied to the study of the specificity of protected designation of origin (PDO) virgin olive oils produced in a southern French region (Alpes-Maritimes) based on their volatile compounds. A total of 35 PDO olive oils from Nice, 6 commercial oils, and 12 other French PDO olive oils were analyzed. Recorded data were subjected to principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). The method developed here was able to perfectly distinguish different qualities of olive oils. Representative samples from each class obtained by chemometric treatment were analyzed by HS-SPME and GC-MS. PCA and SIMCA of chromatographic data were related to sensory analysis and led to a better understanding of the chemical features and observed sensory effects of olive oils.     

Use of differential scanning calorimetry (DSC) as a new technique for detection of adulteration in honeys. 1. Study of adulteration effect on honey thermal behavior.

Differential scanning calorimetry (DSC) was used to study the thermal behavior of authentic honeys (Lavandula, Robinia, and Fir honeys) and industrial sugar syrups. Thermal or thermochemical parameters such as the glass transition temperature (Tg), enthalpies of fusion (DeltaH(fus)), and heat capacity variation (DeltaC(p)) were measured. The syrups and honeys showed significant differences in thermal phenomena, as well as in their amplitude and position on the temperature scale. Results showed good reproducibility of the method for all samples studied. The effect of adulteration of honey with different amounts of syrup (5, 10, 20, 40, and 60%) was investigated. A linear relationship was found between the percentage of added syrup and the glass transition temperature. A similar relationship was obtained from the enthalpy of fusion results in the temperature range of 40-90 degrees C. Under applied conditions, the effects of adulteration of honeys by industrial syrups appeared to be detectable from a level as low as 5%.     

Honey characterization and adulteration detection by pattern recognition applied on HPAEC-PAD profiles. 1. Honey floral species characterization

An improved COFRAC (COmité FRan?ais d'ACréditation) method for the analysis and evaluation of the quality of honey by high-performance anion-exchange chromatography of sugar profiles is proposed. With this method, both minor and major sugars are simultaneously analyzed and the technique is integrated in a new chemometric approach, which uses the entire chromatographic sugars profile of each analyzed sample to characterize honey floral species. Sixty-eight authentic honey samples (6 varieties) were analyzed by high-performance anion-exchange chromatography-pulsed amperometric detection. A new algorithm was developed to create automatically the corresponding normalized data matrix, ready-to-use in various chemometric procedures. This algorithm transforms the analytical profiles to produce the corresponding calibrated table of the surfaces or intensities according to retention times of peaks. The possibility of taking into account unknown peaks (those for which no standards are available) allows the maximum chemical information provided by the chromatograms to be retained. The parallel application of principal component analysis (PCA)/linear discriminant analysis (LDA) and artificial neural networks (ANN) shows a high capability in the classification of the analyzed samples (LDA, 93%; ANN, 100%) and a very good discrimination of honey groups. This work is the starting point of the elaboration of a new system designed for the automatic pattern recognition of food samples (first application on honey samples) from chromatographic analyses for food characterization and adulteration detection.     

Dexmedetomidine chemical restraint of two raptor species undergoing inhalation anaesthesia

Veterinary Research Communications -