The role of glucosinolates and iodine on thyroid hormone concentrations in mares and foals
Bibliographic record
Abstract
Adequate levels of thyroid hormones and iodine are essential for health and normal fetal development. Disruptions in maternal iodine metabolism during pregnancy or transfer of iodine to the fetus may cause fetal thyroid dysfunction, which may lead to severe negative effects on development and organ maturation. A syndrome characterized by prolonged gestational length, moderate to severe musculoskeletal deformities such as contracted tendons, failure of tarsal and/or carpal ossification, prognathia, signs of dysmaturity and goiter called congenital hypothyroidism dysmaturity syndrome in foals (CHDS) has been described. The risk factors for CHDS include a lack of trace mineral supplementation and consumption of Brassicaceae family plants containing glucosinolates (GSL) during pregnancy. Glucosinolates have negative effects on thyroid function and animal health in other species. There are no previous reports on the effects of GSL on thyroid function and iodine levels in horses at any age and physiologic state. There is also a lack of robust information on iodine levels in mares and foals in different body fluids and secretions despite the prevalence of CHDS in foals in Western Canada, where Brassica family GSL plants are widely cultivated, mustard family GSL containing weeds are abundant and soil iodine concentrations are inadequate. We hypothesized that the combination of a low iodine and a glucosinolate (GSL) (sinigrin) containing diet fed for 3 months to non-pregnant mares would affect thyroid hormones and serum iodine concentrations in non-pregnant mares and that colostrum, milk and serum iodine levels and thyroid hormone concentrations would decrease over time in healthy post-partum mares and foals. Nineteen mares aged 2 to 14 years were divided into Control with iodine supplementation and, Low (20 mmol/day) and High GSL (35 mmol/day) diet groups without iodine supplementation. Thyrotropin releasing hormone (TRH) stimulation tests and serum iodine measurements were performed at 0 and 12 weeks. Total triiodothyronine (TT3), total thyroxine (TT4) and thyroid stimulating hormone (TSH) concentrations at baseline and in post-TRH samples were measured. The post-TRH fold changes (FC) were calculated for TSH, TT3 and TT4. There was a group and group by week interaction (P <0.001) in TT4 FC values, with week 12 Control concentrations higher (P < 0.006) than all groups. Iodine concentrations decreased (P < 0.002) in GSL mares. Additionally, colostrum, milk and blood samples from ten draft mares and foals, with an estimated intake of 39 mg iodine per day per mare during pregnancy were obtained at foaling date and 10 days later. Measurements included: mare basal concentrations of serum: TT3, TT4, iodine; iodine in colostrum at day 0 and milk iodine (day 10); foal basal TT3, TT4 and serum iodine (day 0 and 10). Median ± SE foal serum iodine (268.5 ± 7.6 µg/L), TT4 (1225 ± 47.8 nmol/L) and TT3 (14.2 ± 1.1 nmol/L) at foaling date were higher than at 10 days (70 ± 3.6 µg/L; 69.6. ± 20.4 nmol/L; 5.4 ± 0.3 nmol/L, respectively). Colostrum iodine levels (165 ± 15.1 µg/L) were higher than milk (48 ± 5.6 µg/L) levels. In conclusion, the effect of sinigrin along with a low iodine supplemented diet did not have a negative impact on body weight and overall health in non-pregnant mares, but T4 responsiveness and iodine levels decrease after 12 weeks. Similar controlled studies on the effects of GSL should be performed in pregnant mares in which thyroid function and adequate levels of iodine are more critical for the developing fetus. Furthermore, nutritional studies with known and confirmed iodine intakes should be performed to determine robust reference ranges for iodine levels in serum, colostrum and milk from mare and foal pairs at different ages.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".