The role of glucosinolates and iodine on thyroid hormone concentrations in mares and foals
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».