Serum fetuin-A levels following recombinant human thyroidstimulating hormone stimulation
Bibliographic record
Abstract
PURPOSE: Fetuin-A is a hepatokine that is linked to lipid metabolism, obesity, insulin resistance, type 2 diabetes and cardiovascular disease. Elevated thyroid-stimulating hormone (TSH) levels are associated with metabolic and cardiovascular disturbances. Our aim was to determine if TSH can regulate fetuin-A levels. METHODS: Fetuin-A serum levels were examined in 26 subjects (19 women; previous thyroidectomy and radioactive iodine ablation) undergoing recombinant human TSH (rhTSH) stimulation to screen for thyroid cancer recurrence. Their age was 49±10 years, and body mass index (BMI) was 28±6 (both expressed as mean±SD). The patients received two doses of rhTSH (0.9 mg), administered 24 hours apart on days 1 and 2, without discontinuation of ongoing L-thyroxine therapy. Morning blood samples were obtained on days 1 (prior to the first dose of rhTSH), 3 and 5. RESULTS: The baseline value of fetuin-A (mean±SD) for all participants was 527±186 mg/L. Values of fetuin-A did not change in response to rhTSH administration. The lack of response was not dependent on gender, age, baseline free thyroxine level or BMI. CONCLUSION: Fetuin-A has been implicated in metabolic and inflammatory conditions, but there have been no reports on whether fetuin-A is influenced by TSH. Within the context of rhTSH administration for surveillance of thyroid cancer recurrence, there was no effect on serum levels of fetuin-A.
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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 | 0.000 | 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 | 0.001 |
| 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".