Diagnosis of subclinical mastitis is of increasing importance and appropriate detection methods are needed. Both haptoglobin (Hp), an acute phase protein in cattle, as well as lactate dehydrogenase (LDH), an ubiquitous enzyme, can be successfully used to detect clinical mastitis. The present paper describes quantification of Hp and LDH in milk samples from healthy and subclinically diseased udder quarters. Hp was analysed in the laboratory using an ELISA. The activity of LDH was measured in raw milk directly in the milking parlor. Both parameters were suitable to distinguish between sterile samples and bacteriologically positive samples. The ability to differentiate between minor and major pathogens was better for Hp in skim milk than for LDH in raw milk. Hp and somatic cell count (SCC) as well as LDH and SCC were positively correlated (r = 0.8 and r = 0.76, respectively). Subclinical mastitis was defined as follows: SCC > 100 × 10 3 cells/ml and bacteriological positive findings in two out of three weekly samples. Sensitivity and specificity were above 85% for Hp and above 81% for LDH. Using a less rigid classification to define mastitis, i.e. SCC > 200 × 10 3 cells/ml and two out of three weekly samples bacteriologically positive, sensitivity for Hp improved (89%) and remained unchanged for LDH. Both parameters are useful parameters for the diagnosis of subclinical mastitis. LDH activity in raw milk was less sensitive and specific than Hp but the method described herein offers the opportunity to measure LDH activity directly in the milking parlor and might therefore be suitable for on-line system developments.
Whether changes in animal behavior allow for short‐term earthquake predictions has been debated for a long time. Before, during and after the 2016/2017 earthquake sequence in Italy, we deployed bio‐logging tags to continuously observe the activity of farm animals (cows, dogs, and sheep) close to the epicenter of the devastating magnitude M6.6 Norcia earthquake (Oct–Nov 2016) and over a subsequent longer observation period (Jan–Apr 2017). Relating 5,304 (in 2016) and 12,948 (in 2017) earthquakes with a wide magnitude range (0.4 ≤ M ≤ 6.6) to continuously measured animal activity, we detected how the animals collectively reacted to earthquakes. We also found consistent anticipatory activity prior to earthquakes during times when the animals were in a building (stable), but not during their time on a pasture. We detected these anticipatory patterns not only in periods with high, but also in periods of low seismic activity. Earthquake anticipation times (1–20 hr) are negatively correlated with the distance between the farm and earthquake hypocenters. Our study suggests that continuous bio‐logging of animal collectives has the potential to provide statistically reliable patterns of pre‐seismic activity that could yield valuable insights for short‐term earthquake forecasting. Based on a priori model parameters, we provide empirical threshold values for pre‐seismic animal activities to be used in real‐time observation stations.
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