OBJECTIVE To determine the correlation between glucose concentrations in serum, plasma, and blood measured by a point-of-care glucometer (POCG) and serum glucose concentration measured by an automated biochemical analyzer (ABA; gold standard). SAMPLE 152 canine and 111 feline blood samples. PROCEDURES For each sample, the glucose concentration in serum, plasma, and blood was measured by a POCG and compared with the ABA-measured glucose concentration by means of the Lin concordance correlation coefficient. Results were summarized by species for all samples and subsets of samples with hyperglycemia (ABA-measured glucose concentration > 112 mg/dL for dogs and > 168 mg/dL for cats) and pronounced hyperglycemia (ABA-measured glucose concentration > 250 mg/dL for both species). The effect of PCV on correlations between POCG and ABA measurements was also assessed. RESULTS Hyperglycemia and pronounced hyperglycemia were identified in 69 and 36 canine samples and 44 and 29 feline samples, respectively. The POCG-measured glucose concentrations in serum, plasma, and blood were strongly and positively correlated with the gold standard concentration. The PCV was positively associated with the correlation between the POCG-measured blood glucose concentration and the gold standard concentration but was not associated with the correlations between the POCG-measured glucose concentrations in serum and plasma and the gold standard concentration. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that POCG-measured glucose concentrations in serum, plasma, and blood were strongly correlated with the ABA-measured serum glucose concentration, even in hyperglycemic samples. Given the time and labor required to harvest serum or plasma from blood samples, we concluded that blood was the preferred sample type for use with this POCG.

High-intensity exercise can be associated with the occurrence of muscle injury, as well as the induction of an acute-phase response (APR). The present study aims to investigate the synthesis and profile of serum proteins in horses before and after participating in 2 different exercise protocols and to relate this profile to the presence or absence of muscular injury caused by exercise. Ten purebred Arabian (n = 5) and Criollo (n = 5) horses were subjected to 2 different tests on a treadmill, one consisting of short-duration and rapid-acceleration training (TRA) that was mostly anerobic and the other of long-duration and slow-acceleration training (TLD) that was predominantly aerobic. Blood samples were obtained before the beginning of exercise (T0) and at 6 post-exercise time points: immediately after (T1) and 30 min (T2), 3 h (T3), 12 h (T4), 24 h (T5), and 48 h (T6) after exercise. Hematocrit was determined by the microhematocrit method. Plasma and serum samples were prepared by centrifugation (1500 × g for 5 min) for plasma concentrations of fibrinogen, total serum proteins (TP), sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), and creatine-kinase (CK) serum activity. Total protein concentration and CK serum activity were determined in an automated biochemistry analyzer. Fibrinogen was determined by the heat precipitation method in microhematocrit capillary tubes. Estimated concentrations of haptoglobin (Hp) significantly decreased after TRA and estimated concentrations of alpha-1 acid glycoprotein (AGP) significantly increased after both protocols at T2. Albumin increased after the TLD exercise protocol. Changes in hematocrit, haptoglobin, and albumin concentrations in horses subjected to different treadmill exercise protocols are related to a physiological response to hemoconcentration and hemolysis. Increases of AGP in the TLD protocol suggest the release of catecholamines as a response to avoid oxidative damage to tissue.

In this study, three different methods were compared for the identification of some Gram-positive and Gramnegative reference bacteria. Material and Methods: For this purpose, the identification accuracy rates of Enterococcus faecalis, Enterococcus faecium, Streptococcus agalactiae, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhimurium, Serratia marcescens were analysed by conventional bacteriological methods, commercial bacterial identification test kit (Microgen™ ID) and automated bacteria identification system (BD Phoenix 100™).