Genetic Analysis in the Diagnosis of Familial Paragangliomas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: In the management of two related patients with multicentric glomus jugulare tumors, given the incidence of 1:30,000 with approximately 20% familial cases, our objective was to review the genetic characteristics and inheritance patterns of these tumors and to determine what molecular genetic screening possibilities exist for the phenotypically normal family members. In addition, our aim was to review the incidence of various multicentric paraganglioma (PGL) tumor location combinations. METHODS: Molecular genetic linkage analysis testing was performed on the 2 patients and 14 other unaffected family members. We report the results of this screening and review the literature on the incidence and genetics of paragangliomas. RESULTS: The inheritance pattern in the literature demonstrates autosomal dominant transmission with maternal imprinting (inactivation). The proclivity for multicentric origin increases to 26% in familial cases, as reflected in our patients. In addition to the two patients, four unaffected family members demonstrated the presence of the disease haplotype at chromosome band 11q23, which indicates a very high likelihood of developing a paraganglioma, given the highly penetrant nature of the disease. CONCLUSIONS: It is clear that the familial PGL gene locus is situated at chromosome 11q23. The gene itself and its exact degree of penetrance, however, still await identification. Since early detection of paragangliomas reduces the incidence of morbidity and mortality, genotypic analysis as a screening tool in families of affected patients should play a front-line diagnostic role, leading to more timely and cost-effective patient management.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.002 | 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 it