Calcium-sensing receptor mutations and denaturing high performance liquid chromatography
Bibliographic record
Abstract
The calcium-sensing receptor (CASR), a plasma membrane G-protein-coupled receptor, is expressed in parathyroid gland and kidney, and controls systemic calcium homeostasis. Inactivating CASR mutations are associated with familial hypocalciuric hypercalcemia (FHH) and neonatal severe hyperparathyroidism, and activating mutations cause autosomal dominant hypocalcemia (ADH). CASR mutation identification plays an important role in the clinical management of mineral metabolism disorders. We describe here a high-throughput method using screening with denaturing high performance liquid chromatography (DHPLC) to initially interrogate 12 amplicons covering translated exons and exon/intron boundaries, followed by sequencing of any amplicon with a modified melting curve relative to wild type, and direct sequencing of a 13th amplicon encoding the COOH-terminal tail to distinguish causative mutations from three common missense single nucleotide polymorphisms. A blinded analysis of 32 positive controls representing mutations throughout the CASR sequence, as well as 22 negative controls, yielded a concordance rate of 100%. We report eight novel and five recurrent FHH mutations, along with six novel and two recurrent ADH mutations. Thus, DHPLC provides a rapid and effective means to screen for CASR mutations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".