Estimation of periostin as a biomarker for early pregnancy diagnosis in goats: a preliminary study.

BACKGROUND: Periostin (POSTN) is an extracellular matrix (ECM) protein that plays an important role in the metastatic process and cancer cell migration. As implantation is a similar mechanism to metastasis, it has been hypothesized that POSTN may also play a role in the implantation process. AIMS: The aim of the present study was to compare POSTN and progesterone levels during the early pregnancy stage in Damascus goats. METHODS: Forty goats were synchronized using progesterone based sponges and were mated upon estrus signs display. While ten goats were kept as control (CON) and were not allowed to mate. Blood samples were taken through jugular venepuncture from CON and synchronized goats on day 13, 15, 17, 19, and 21 of breeding. Progesterone and POSTN levels were determined by enzyme-linked immunosorbent assay (ELISA). Later the pregnancy diagnosis was confirmed by transabdominal ultrasonography on day 50 after mating. RESULTS: Progesterone level was influenced by status of pregnancy and day of observation with an interaction between the status of pregnancy and day of observation in goats. Whereas POSTN level was only affected by the day of observation. CONCLUSION: POSTN level did not vary with progesterone level during phase of embryonic implantation in goats; however, standardization and application of different procedures for POSTN assay in a large group of animals might be useful as an early pregnancy biomarker in goats.

Variations in serum metabolites in response to season, cyclicity, and pregnancy in estrus-synchronized Damascus goats.

The current study was carried out to determine the changes in serum electrolytes, liver enzymes, and hormones during breeding and non-breeding seasons in estrus-synchronized goats. Forty goats (n = 40) were synchronized by inserting the sponges intravaginally for 12 days; PMSG and PGF2α were injected on day of sponge removal. Blood samples were collected from the goats at the time of sponges insertion (day -12), estrus day (day 0), and at 15 day after sponge withdrawal (day 15). The blood samples were analyzed for glucose, cholesterol (CHO), aspartate aminotransferase (AST), alanine aminotransferase (ALT), thyroid stimulating hormone (TSH), triiodothyronine (T3), thyroxine (T4) and progesterone (P4), calcium (Ca), phosphate (PO4), magnesium (Mg), sodium (Na), potassium (K), and chlorine (Cl) levels. Repeated measurements ANOVA of general linear model were used as statistical model. The results showed that seasons have an effect (p < 0.05) on glucose, Ca, Na, K, Cl, CHO, T3, and T4 levels. There was an effect (p < 0.05) of cyclicity only on P4 level. Whereas, nonpregnant, or goats carrying singlet and twin fetuses have shown variation (p < 0.05) in glucose, Ca, and P4 levels. Although, the correlations existed between different serum metabolites but strong correlations (p < 0.05) were observed either between Ca and Na or T3 and T4. In conclusion, the serum electrolytes and liver enzymes are correlated with hormones during the different seasons, pregnancy status, and fecundity. In recommendation, the results of the study could be as managemental tool to monitor the reproductive activity across seasons and to maintain pregnancy carrying twining in goat breeds.

Glucose-6-phosphate dehydrogenase, glutathione peroxidase, total glutatione and reduced nicotinamide adenine dinucleotide phosphate in milk cells of subclinical mastitic cows.

This study aimed to determine the levels of milk cell total protein (TP), reduced nicotinamide adenine dinucleotide phosphate (NADPH), total glutathione (tGSH), activities of glucose-6-phosphate dehydrogenase (G6PD) and glutathione peroxidase (GPx) in subclinical mastitic cows. Milk from each udder was collected and grouped by the California Mastitis Test. Then, a somatic cell count (SCC) was performed, and the groups were re-scored as control (5-87 × 103 cells), 1st group (154-381 × 103 cells), 2nd group (418-851 × 103 cells), 3rd group (914-1958 × 103 cells), and 4th group (2275-8528 × 103 cells). Milk cell TP, NADPH, tGSH levels, G6PD, and GPx activities were assessed. Microbiological diagnosis and aerobic mesophyle general organism (AMG, cfu/g) were also conducted. In mastitic milk, TP, NADPH, and tGSH levels, and G6PD and GPx activities were significantly reduced per cell (in samples of 106 cells). In addition, milk SCC was positively correlated with AMG (r=0.561, p⟨0.001), NADPH (r=0.380, p⟨0.01), TP (r=0.347, p⟨0.01) and G6PD (r=0.540, p⟨0.001). There was also positive correlation between NADPH (r=0.428, p⟨0.01), TP (r=0.638, p⟨0.001) and AMG. NADPH was positively correlated with TP (r=0.239, p⟨0.05), GPx (r=0.265, p⟨0.05) and G6PD (r=0.248, p=0.056). Total protein was positively correlated with tGSH (r=0.354, p⟨0.01) and G6PD (r=0.643, p⟨0.001). There was a negative correlation between tGSH and GPx activity (r=-0.306, p⟨0.05). The microbiological analysis showed the following ratio of pathogens: Coagulase-Negative Staphylococci 66.6%, Streptococcus spp 9.5%, Bacillus spp 9.5%, yeast 4.8%, and mixed infections 9.5%. As a conclusion, when evaluating the enzyme and oxidative stress parameters in milk, it is more suitable to assign values based on cell count rather than ml of milk. The linear correlation between the SCC and AMG, milk cell NADPH, TP and G6PD suggests that these parameters could be used as markers of mastitis.

Integrated chemical exposure assessment of coastal green turtle foraging grounds on the Great Barrier Reef.

The Great Barrier Reef receives run-off from 424,000 km2 catchment area across coastal Queensland, incorporating diffuse agricultural run-off, and run-off point sources of land-based chemical pollutants from urban and industrial development. Marine biota, such as green turtles (Chelonia mydas), are exposed to these diverse chemical mixtures in their natural environments, and the long term effects on turtle and ecosystem health remain unknown. This study was part of a larger multi-disciplinary project characterising anthropogenic chemical exposures from the marine environment and turtle health. The aim of this study was to screen for a wide range of anthropogenic chemical pollutants present in the external and internal environment of green turtles, using a combination of traditional targeted chemical analyses, non-target suspect screening, and effect-based bioassay methods, while employing a case-control study design. A combination of passive (water) and grab (water, sediment) samples were investigated. Three known green turtle foraging sites were selected for sampling: two coastal 'case' sites influenced primarily by urban/industrial and agricultural activities, respectively; and a remote, offshore 'control' site. Water and sediment samples from each of the three sampling locations showed differences in chemical pollutant profiles that reflected the dominant land uses in the adjacent catchment. Targeted mass spectrometric analysis for a range of pesticides, industrial chemicals, pharmaceuticals and personal care products found the greatest detection frequency and highest concentrations in coastal samples, compared to the control. Non-target screening analysis of water showed clear differentiation in chemical profile of the urban/industrial site. In-vitro assays of sediment samples from the control site had lowest induction, compared to coastal locations, as expected. Here we present evidence that turtles foraging in coastal areas are exposed to a range of anthropogenic pollutants derived from the adjacent coastal catchment areas.