Thyroid hormones and lipid profile in Labrador Retriever male dogs
Bibliographic record
Abstract
A study was conducted to assess the thyroid hormones and lipid profile in Labrador Retriever male dogs presented to the Veterinary College Hospital, Bengaluru for routine health check up and vaccination. Based on their age, they were randomly divided into Group I, Group II and Group III that consisted of one to three years age (young age), more than three years to six years age (middle age) and more than six to nine years age (old age), respectively. In all the dogs the body weight was recorded. The profile of thyroid hormones such as thyroid stimulating hormone (TSH), triiodothyronine (T3) and Thyroxine (T4) were estimated by using ELISA kits. The lipid profile parameters such as triglycerides, cholesterol and HDL cholesterol were estimated by using biochemical reagent kits. The values of LDL and VLDL cholesterol were calculated by using Friedewald formula. Further, the blood glucose level was estimated using the Glucochek® glucometer and serum total protein level by using reagent kit. Results revealed that the increased body weight was observed as age advanced. The T3 levels did not vary significantly among different age groups. Whereas, in the advanced age groups there was reduction in T4 levels and increase in TSH levels which was suggestive of hypothyroidism. Triglycerides, cholesterol, LDL and VLDL levels were significantly higher in older dogs followed by middle age group compared to young age group. However, the alterations in blood glucose and serum total protein levels were non significant between different age groups. It was concluded that the Labrador Retriever male dogs could be more prone to hypothyroidism and hyperlipidemia and therefore master health check-up could be taken up at least once in a year as a precautionary measure to avoid complications of hypothyroidism and hyperlipidemia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".