Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities

Effects of eugenol (AQUI‐S^®20E, 10% active eugenol) sedation on cool water, yellow perch Perca flavescens (Mitchill), and warm water, Nile tilapia Oreochromis niloticus L. fish metabolic rates were assessed. Both species were exposed to 0, 10, 20 and 30 mg L^?1 eugenol using static respirometry. In 17°C water and loading densities of 60, 120 and 240 g L^?1, yellow perch controls (0 mg L^?1 eugenol) had metabolic rates of 329.6–400.0 mg O₂ kg^?1 h^?1, while yellow perch exposed to 20 and 30 mg L^?1 eugenol had significantly reduced metabolic rates of 258.4–325.6 and 189.1–271.0 mg O₂ kg^?1 h^?1 respectively. Nile tilapia exposed to 30 mg L^?1 eugenol had a significantly reduced metabolic rate (424.5 ± 42.3 mg O₂ kg^?1 h^?1) relative to the 0 mg L^?1 eugenol control (546.6 ± 53.5 mg O₂ kg^?1 h^?1) at a loading density of 120 g L^?1 in 22°C water. No significant differences in metabolic rates for Nile tilapia were found at 240 or 360 g L^?1 loading densities when exposed to eugenol. Results suggest that eugenol sedation may benefit yellow perch welfare at high densities (e.g. live transport) due to a reduction in metabolic rates, while further research is needed to assess the benefits of eugenol sedation on Nile tilapia at high loading densities.     

Effects of Serum Deprivation and Cycloheximide on Cell Cycle of Low and High Passage Porcine Fetal Fibroblasts

Arrest of cells in G0/G1 cell cycle phase is desired for nuclear transfer procedures. Serum starvation and cell cycle inhibitors are different ways to induce synchronization of the cell cycle. This study investigated the effects of serum starvation and cycloheximide (CHX) on the cell cycle of low (5th) and high (15th) passages fetal porcine fibroblasts. Cell cycle phases were determined using fluorescent activated cell sorting. Fifth passage fibroblast cultures had higher (p < 0.05) proportion of cells in G0/G1 only after 72 h of serum starvation (77.60 ± 0.65) when compared with non‐starved cells (71.44 ± 1.88). Serum starvation for all periods tested induced an increase (p < 0.05) on proportion of cells in G0/G1 on the 15th passage. No significant differences were observed on the 5th passage cultures exposed to CHX, although, on the 15th passage an increase on proportion of cells was observed after all periods of exposure (p < 0.05). These data indicates that high passage cells in vitro are more susceptible to serum starvation and CHX G0/G1 synchronization.     

OC9Effect of Melatonin Implants in Guirra Ewes

In extensive systems, beef cows should be continuously with their calves to optimise pasture use but this practice can lengthen post-partum interval (PPI). A study was conducted to determine the influence of suckling frequency on Parda de Montaña cow-calf performance when cows are fed 70% energy requirements during lactation (outdoor winter conditions simulation). Thirty-six autumn-calving cows with similar body condition at calving (2.57) were assigned to three suckling systems [ ad libitum (AL), twice (2D) or once daily (1D) for 30 min]. Blood samples were collected twice a week to analyse progesterone concentrations by RIA. Cows lost similar weight until start of mating period (day 52 post-partum; −0.583, –0.513, –0.520 kg/day in AL, 2D and 1D). Standard milk yield was higher in AL than the rest (8.9, 6.2, 7.0 kg; p < 0.05), which was reflected on greater calf gain (0.895, 0.752, 0.676 kg/day; p < 0.05) and larger cow weight loss within 90 days post-partum in this treatment (–0.345, –0.188, –0.083 kg/day; p < 0.05). Suckling system did not affect either PPI (69.6, 89.1, 65.5 days) or cows cycling within 90 days post-partum (55, 46, 58%), which may compromise the target calving interval. In Parda de Montaña breed fed moderately pre-calving and undernourished during lactation, restricted suckling did not favour ovarian activity resumption, but post-partum subnutrition delayed about 40 days PPI observed in similar body condition at calving and calf management (Sanz et al., 2003; Anim Reprod Sci 79: 57–69)     

Validation of two dilution models to predict chloramine-T concentrations in aquaculture facility effluent

Accurate estimates of drug concentrations in hatchery effluent are critical to assess the environmental risk of hatchery drug discharge resulting from disease treatment. This study validated two simple dilution models to estimate chloramine-T environmental introduction concentrations by comparing measured and predicted chloramine-T concentrations using the US Geological Survey’s Upper Midwest Environmental Sciences Center aquaculture facility effluent as an example. The hydraulic characteristics of our treated raceway and effluent and the accuracy of our water flow rate measurements were confirmed with the marker dye rhodamine WT. We also used the rhodamine WT data to develop dilution models that would (1) estimate the chloramine-T concentration at a given time and location in the effluent system and (2) estimate the average chloramine-T concentration at a given location over the entire discharge period. To test our models, we predicted the chloramine-T concentration at two sample points based on effluent flow and the maintenance of chloramine-T at 20 mg/l for 60 min in the same raceway used with rhodamine WT. The effluent sample points selected (sample points A and B) represented 47 and 100% of the total effluent flow, respectively. Sample point B is analogous to the discharge of a hatchery that does not have a detention lagoon, i.e. the sample site was downstream of the last dilution water addition following treatment. We then applied four chloramine-T flow-through treatments at 20 mg/l for 60 min and measured the chloramine-T concentration in water samples collected every 15 min for about 180 min from the treated raceway and sample points A and B during and after application. The predicted chloramine-T concentration at each sampling interval was similar to the measured chloramine-T concentration at sample points A and B and was generally bounded by the measured 90% confidence intervals. The predicted average chloramine-T concentrations at sample points A or B (2.8 and 1.3 mg/l, respectively) were not significantly different (P>0.05) from the average measured chloramine-T concentrations (2.7 and 1.3 mg/l, respectively). The close agreement between our predicted and measured chloramine-T concentrations indicate either of the dilution models could be used to adequately predict the chloramine-T environmental introduction concentration in Upper Midwest Environmental Sciences Center effluent.