Quantitative determination of parathyroid hypertensive factor by enzyme-linked immunosorbent assay
Bibliographic record
Abstract
A new competitive enzyme immunoassay for the detection parathyroid hypertensive factor (PHF) in human plasma using a PHF-horseradish peroxidase conjugate and IgM antibody adsorbed on the microtiter plate was established. The antibodies raised against rat PHF could recognize human PHF. Cross-reactivity of anti-PHF antibodies with other serum haptens and proteins was negligible. Conjugation of PHF with horseradish peroxidase did not neutralize the antigen activity. The limit of detection of PHF was 0.02 U/mL in reference units and PHF levels between 0.02 and 1 U/mL could be detected. Within-run coefficient of variation (CV) was less than 10%, and between-run CV was less than 15% for over the dynamic range of the assay. Preliminary clinical studies were performed with plasma samples from hypertensive patients with confirmed diagnosis. Parathyroid hypertensive factor levels, as detected with this immunoassay, were positively correlated with PHF levels detected with the semiquantitative blood pressure (BP) bioassay previously used. Parathyroid hypertensive factor levels detected with the enzyme-linked immunosorbent assay (ELISA) were also correlated with BP in patients. The PHF ELISA provides a selective, simple, and rapid method that can be used for routine determination of PHF in human plasma, and provides useful clinical information.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".