The presence of integron and other resistance determinants was investigated in 90 Aeromonas isolates derived from nine freshwater trout farms in Victoria (Australia).
Polymerase chain reaction was carried out for the detection of integrase genes Int1, Int2 and Int3, gene cassette array, integron-associated GS-7977 aadA, sul1 and qac1 genes, streptomycin resistance genes strA-strB, beta-lactamase resistance genes (bla)TEM and (bla)SHV, and tetracycline resistance genes tetA-E and tetM. Clonal analysis was performed by pulsed-field gel electrophoresis (PFGE). Class 1 integrons were detected in 28/90 (31%) and class 2 and class 3 in none of the strains, aadA gene in 19/27 (70%) streptomycin-resistant strains, sul1 in 13/15 (86.7%) sulphonamide-resistant strains and qac1 gene in 8/28 (28.6%) integron-bearing strains. Five strains from two different farms carried gene cassettes of 1000 bp each containing the aadA2 gene and PFGE analysis revealed genetic relatedness. tetC was detected in all and tetA in
9/18 (50%) tetra-cycline-resistant strains. The strA-strB, blaTEM or blaSHV genes were not detected in any of the strains. Aeromonas spp. carrying integrons and other resistance genes are present in farm-raised fish and sediments even though no antibiotics were licensed for use in Australian aquaculture at the time of the study.”
“Automated systems for monitoring behaviour of cows within dairy production are increasing and developments in technology provide new opportunities JNK-IN-8 in this area. This study aimed to validate the use of a 3D activity logger (HOBO (R) Pendant G Data Logger), that registers the cow’s head positions during grazing, to distinguish grazing behaviour from non-grazing behaviour.\n\n20 lactating dairy cows of the breed Swedish Red were included in the trial. All cows were observed for 30 min each day either in the morning or afternoon. The behavioural observations were conducted by two trained observers during 5 h a day for
ten days, 2.5 h in the morning (9:30-12:00 am) and 2.5 h in the evening (06:00-08:30 pm). Each cow had a logger attached to the right bottom side of the halter and the logging interval was set to 5s, which means that the head inclination was measured every fifth second. DZNeP research buy Furthermore an IceTag3D (TM) logger was attached to the right hind leg of each cow in order to evaluate if this information together with the information from the 3D activity sensor could increase the precision of the prediction. The DISCRIM procedure in SAS 9.12 was used to find the optimal value of a linear discrimination between grazing and non-grazing registrations and the 3D activity sensor was validated with 5 s, 5 min and 10 min logging intervals between observations points against the visual observation of grazing behaviour. The 5 and 10 min logging point was taken from the 5s logging point occurring with 5 and 10 min interval.