cAMP and cGMP in nasal mucus related to severity of smell loss in patients with smell dysfunction
Bibliographic record
Abstract
PURPOSE: To evaluate nasal mucus levels of cAMP and cGMP in patients with taste and smell dysfunction with respect to severity of their smell loss. METHODS: cAMP and cGMP were measured in nasal mucus using a sensitive spectrophotometric 96 plate ELISA technique. Smell loss was measured in patients with taste and smell dysfunction by standardized psychophysical measurements of olfactory function and classified by severity of loss into four types from most severe to least severe such that anosmia > Type I hyposmia > Type II hyposmia > Type III hyposmia. Measurements of nasal mucus cyclic nucleotides and smell loss were made independently. RESULTS: As smell loss severity increased stepwise cAMP and cGMP levels decreased stepwise [cAMP, cGMP (in pmol/ml); anosmia - 0.004, 0.008: Type I hyposmia - 0.12+/-0.03, 0.10+/-0.03: Type II hyposmia - 0.15+/-0.02, 0.16+/-0.01: Type III hyposmia - 0.23+/-0.05, 0.20+/-0.15]. CONCLUSIONS: These results confirm the association of biochemical changes in cyclic nucleotides with systematic losses of smell acuity. These results confirm the usefulness of the psychophysical methods we defined to determine the systematic classification of smell loss severity. These changes can form the basis for the biochemical definition of smell loss among some patients with smell loss as well as for their therapy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".