Genetic Defects Associated with Familial and Sporadic Hyperparathyroidism
Bibliographic record
Abstract
Primary hyperparathyroidism (PHPT) occurs sporadically, but occasionally it may be a feature of a familial condition, such as multiple endocrine neoplasia type 1 (MEN1), MEN2A, or the HPT-jaw tumor syndrome (HPT-JT), and familial hypocalciuric hypercalcemia/neonatal severe hyperparathyroidism (FHH/NSHPT). PHPT may also occur as familial isolated hyperparathyroidism (FIHP), and has been observed as a consequence of mutations in the CDKN1B gene (MEN4). Tumorigenesis in these conditions may be the result of protooncogene activation (e.g. RET in MEN2) or two-hit losses of a tumor suppressor (e.g. MEN1, HPT-JT). In patients with MEN1, HPT-JT or FHH/NSHPT, the hyperparathyroidism manifests at a younger age and affects both sexes equally. In MEN1, mutations of the MEN1 gene also cause enteropancreatic and anterior pituitary tumors. In MEN2, activating mutations in the RET protooncogene also cause medullary thyroid carcinoma and pheochromocytoma. In HPT-JT, mutations of CDC73/HRPT2 are associated with parathyroid carcinoma, but tumors of the kidneys and uterus are additional features. In some FIHP families, a CASR mutation may be identified. In parathyroid carcinoma, even if sporadic, molecular diagnostics for CDC73/HRPT2 should be considered, as it should be for younger patients. Further exploration of these hereditary syndromes may shed light on the molecular mechanisms giving rise to nonhereditary PHPT.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".