The role of specific immunoglobulins in antibody-dependent cell-mediated cytotoxicity assays during Babesia bovis infection

A stabilate prepared from Babesia bovis-infected Boophilus microplus ticks was used to infect intact adult cattle. Whole sera and immunoglobulin fractions from representative sera were tested by complement fixation (CF), indirect fluorescent antibody (IFA), and antibody-dependent cell-mediated cytotoxicity (ADCC) assays. The last test utilized 51Cr-labeled chicken erythrocytes coated with Babesia bovis antigen as targets. Mononuclear cell preparations, obtained from peripheral blood of normal donors and consisting of lymphocytes with 2--6% large monocytes, were used as the source of effector cells. Antibody activity was detected by all tests between 14 and 16 days following infection. Specific IgM and IgG1 were reactive in both CF and IFA tests, although the development of high titers was attributable to IgG, alone. The ADCC activity was restricted to IgG1 fractions and was greater in those sera or fractions with greater CF activity. No activity was demonstrated in IgG2 fractions by any test used.     

Opioid inhibition stimulates luteinizing hormone and prolactin secretion in the gilt

Ten gilts on day 6·11 of the estrous cycle (onset of estrus = day 0) were given 115 mg of naloxone (NAL), an opioid antagonist, in saline i.v. (n = 5) or saline Lv. (n = 5). Jugular blood was collected at 15 min intervals for 2 hr before and 4 hr after treatment. Serum LH concentrations were 0.4 ± 0.1 ng/ml before NAL treatment, increased (P<.01) to 4.3 ± 0.7 ng/ml at 15 min following NAL treatment and returned to control concentrations by 75 minutes. Serum PRL concentrations were 5.0 ± 0.1 ng/ml before NAL treatment, increased (P<.05) to 14.8 ± 2.9 ng/ml at 30 min following NAL treatment and returned to control concentrations by 120 minutes. Serum LH and PRL concentrations were 0.5 ± 0.1 ng/ml and 5.2 ± 0.4 ng/ml, respectively, at 15 min following saline treatment and remained unchanged throughout the blood sampling period. Four of the 5 NAL treated gilts responded with an increase in both serum LH and PRL concentrations. The mean of serum progesterone concentrations, quantitated in samples taken every 2 hr, were similar for controls (22.7 ± 1.8 ng/ml) and NAL (26.5 ± 1.4 ng/ml) treated gilts. The gilt which failed to respond to NAL had nondetectable concentrations of serum progesterone and was excluded from analysis. These data indicate that the opioids modulate LH and PRL secretion during the luteal phase of the estrous cycle.     

Cattle Grazing Distribution in Shortgrass Steppe: Influences of Topography and Saline Soils

The distribution of livestock across heterogeneous landscapes is often uneven, which has important implications for vegetation dynamics and how rangeland managers achieve desired outcomes from these landscapes. Here, we use data from widely available digital elevation models to classify a landscape in the shortgrass steppe with subtle topographic variation using two different approaches: topographic wetness index (TWI) and topographic position classes (TPCs) derived from topographic position indices. We used global positioning system collars to track the grazing locations of cattle within replicate pastures and fit generalized linear mixed models to their locations to quantify the influence of topography on grazing distribution. In addition, we examine the influence of the presence of saline vegetation communities on cattle use of lowlands. The resulting models indicate that TPC more effectively predicts grazing distribution than TWI and that the patterns are strongest in the second half of the growing season (August ? October). Model performance was improved with the inclusion of saline vegetation communities, although the magnitude of cattle grazing time in these communities was not consistent across multiple pastures. These models, in combination with local knowledge, can be used by managers to predict and manage livestock distribution even in landscapes with relatively subtle topographic variability.