P19-derived neuronal cells express H1, H2, and H3 histamine receptors: a biopharmaceutical approach to evaluate antihistamine agents
Bibliographic record
Abstract
Abstract Histamine is a biogenic amine implicated in various biological and pathological processes. Convenient cellular models are needed to screen and develop new antihistamine agents. This report aimed to characterize the response of neurons differentiated from mouse P19 embryonal carcinoma cells to histamine treatment, and to investigate the modulation of this response by antihistamine drugs, vegetal diamine oxidase, and catalase. The exposure of P19 neurons to histamine reduced cell viability to 65% maximally. This effect involves specific histamine receptors, since it was prevented by treatment with desloratadine and cimetidine, respectively, H1 and H2 antagonists, but not by the H3 antagonist ciproxifan. RT-PCR analysis showed that P19 neurons express H1 and H2 receptors, and the H3 receptor, although it seemed not involved in the histamine effect on these cells. The H4 receptor was not expressed. H1 and H2 antagonists as well as vegetal diamine oxidase diminished the intracellular Ca2+ mobilization triggered by histamine. The treatment with vegetal diamine oxidase or catalase protected against mortality and a significant reduction of H2O2 level, generated from the cells under the histamine action, was found upon treatments with desloratadine, cimetidine, vegetal diamine oxidase, or catalase. Overall, the results indicate the expression of functional histamine receptors and open the possibility of using P19 neurons as model system to study the roles of histamine and related drugs in neuronal pathogenesis. This model is less expensive to operate and can be easily implemented by current laboratories of analysis and by Contract Research Organizations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".