Manuka Honey: Histological Effect on Respiratory Mucosa
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) is an inflammatory disease in which bacteria are commonly implicated often in the form of a biofilm. Manuka honey has been shown in vitro to be an effective treatment against two common CRS pathogens both in the planktonic and in the biofilm forms. The purpose of this study was to determine if the application of manuka honey to respiratory epithelium would result in histological evidence of epithelial injury. METHODS: Using a rabbit animal model, a nonrandomized controlled trial of four treatment regimes was performed with two rabbits in each group. The left nasal cavity was irrigated with a 1.5-mL manuka honey solution once daily and the right nasal cavity was not treated. Groups 1-3 were treated for 3, 7, and 14 consecutive days, respectively, and killed the morning after the last treatment. Group 4 was treated for 14 consecutive days followed by a 14-day washout period and then killed the following morning. The nasal respiratory mucosa was immediately harvested after death. The mucosa was examined by light microscopy for histological change in comparison with the control side. RESULTS: Cilia were not measured quantitatively but were equally present on the treated and untreated mucosa. There was no histological evidence of inflammation, epithelial injury, or significant morphological changes. CONCLUSION: The application of a manuka honey solution to rabbit nasal respiratory mucosa over different treatment intervals did not show evidence of histological epithelial injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".