Histamine receptor 2 blockade selectively impacts B and T cells in healthy subjects
Bibliographic record
Abstract
Histamine receptor 2 (H2R) blockade is commonly used in patients with gastric, duodenal ulcers or gastroesophageal reflux disease. Beyond the gastrointestinal tract, H2R is expressed by multiple immune cells, yet little is known about the immunomodulatory effects of such treatment. Clinical reports have associated H2R blockade with leukopenia, neutropenia, and myelosuppression, and has been shown to provide clinical benefit in certain cancer settings. To systematically assess effects of H2R blockade on key immune parameters, a single-center, single-arm clinical study was conducted in 29 healthy subjects. Subjects received daily high dose ranitidine for 6 weeks. Peripheral blood immunophenotyping and mediator analysis were performed at baseline, 3 and 6 weeks into treatment, and 12 weeks after treatment cessation. Ranitidine was well-tolerated, and no drug related adverse events were observed. Ranitidine had no effect on number of neutrophils, basophils or eosinophils. However, ranitidine decreased numbers of B cells and IL-2Rα (CD25) expressing T cells that remained lower even after treatment cessation. Reduced serum levels of IL-2 were also observed and remained low after treatment. These observations highlight a previously unrecognised immunomodulatory sustained impact of H2R blockade. Therefore, the immune impacts of H2R blockade may require greater consideration in the context of vaccination and immunotherapy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".