Expression of Osteopontin in Patients with Thyroid Dysfunction
Bibliographic record
Abstract
Thyroid dysfunctions are common endocrine problems. They are often misdiagnosed, misunderstood, and frequently overlooked. These disorders affect almost every aspect of health. Most of them remain undetected because the clinical assessment alone lacks both sensitivity and specificity. As it is not sufficient enough we require the biochemical tests to confirm the diagnosis. As a consequence there is still great interest in new biomarkers that complement existing diagnostic tools. Osteopontin, a glycoprotein that can be detected in plasma, was found to be upregulated in several patients with hyperthyroidism and downregulated in hypothyroid patients so it may represent a new biomarker. 100 patients with thyroid dysfunctions (50 hyperthyroid, 50 hypothyroid) and 100 normal subjects were included in the study. Osteopontin and other clinical parameters for diagnosis of thyroid disorders were measured. Osteopontin is positively correlated with T3 and T4 (r = 0.62 and r = 0.75 respectively) while it is negatively correlated with thyroid stimulating hormone (r = -0.52) showing a significant correlation (p-value <0.001). Our findings suggest that osteopontin might be useful as a novel prognostic biomarker in patients with impaired thyroid function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".