Haematological and biochemical parameters in Churra-da-Terra-Quente ewes from the northeast of Portugal

Hematological and biochemical parameters, including plasma electrolytes and thyroid hormones, were determined in 73 clinically healthy Churra-da-Terra-Quente ewes, a typical breed from the northeast of Portugal. The hemogram values were: erythrocytes 9.8±1.51012/L; haemoglobin 118.1±19.1g/L; haematocrit 40.8±5.9%; leukocytes 5.7±1.8109/L; and platelets 544.3±177.2109/L. The thrombin time was 17.3±1.7 seconds. The values of biochemical parameters were: total protein 76.4±6.1g/L; glucose 2.87±0.60mmol/L; total cholesterol 1.65±0.33mmol/L; aspartate aminotransferase 155.9±49.2U/L; alanine aminotransferase 23.2±9.6U/L; γ-glutamyl transferase 48.0±18.7U/L; total alkaline phosphatase 121.6±76.1U/L; glutamate dehydrogenase 6.4±3.7U/L; urea 7.32±2.22mmol/L; creatinine 123.0±54.1μmol/L; total calcium 2.53±0.25mmol/L; phosphorus 2.10±0.46mmol/L; magnesium 1.01±0.09mmol/L; sodium 152.04±3.65mmol/L; potassium 4.7±0.4mmol/L; ionized calcium 1.32±0.07mmol/L; total thyroxine 111.75±42.29nmol/L; total triiodothyronine 1.01±0.28nmol/L; free T4 11.93±1.78pmol/L; free T3 4.22±1.33pmol/L; and thyroid-stimulating hormone 0.18±0.19μIU/mL. Although differences among the Churra-da-Terra-Quente breed and other breeds may occur, the hematological and biochemical parameters, plasma electrolytes, and thyroid hormones, for this indigenous breed, were generally situated within the reference intervals previously reported for sheep

Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

BACKGROUND AND PURPOSE: Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. METHODS: The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). CONCLUSIONS: The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke