The relationship between MMPs and pH in whole saliva of radiated head and neck cancer patients
Bibliographic record
Abstract
BACKGROUND: Radiation therapy for head and neck tumour patients may lead to decreased salivary flow, oral mucosal lesions and increased caries experience. Salivary matrix metalloproteinases (MMPs) may participate in the pathogenesis of mucosal lesions and dentinal caries. The aims of this study were: (i) to assay the presence, molecular forms and proteolytic activity of MMP-8 (collagenase-2) and MMP-9 (gelatinase B) in the whole saliva of head and neck cancer patients having radiation therapy; (ii) to see whether salivary pH affects the activity of MMP-8 and MMP-9; and (iii) to find out the possible connection between MMP-8 and MMP-9 with the eruption of oral mucosal lesions during radiation therapy. METHODS: The whole saliva samples of 39 head and neck cancer patients having radiation therapy were collected before, during and after radiation therapy, and saliva flow rate, pH, buffer capacity, Streptococcus mutans, Lactobacillus and Candida albicans were measured. Any oral mucosal lesions were examined during each visit. The levels of MMP-8 were measured by immunofluorometric assay (IFMA) and the presence of different MMP-8 forms was analysed using Western immunoblotting. The presence and molecular forms of MMP-9 were analyzed by gelatin zymography. MMP-9 capture activity assay was used to determine the APMA-activated MMP-9 activity (total) and the endogenously active MMP-9 (free activity). RESULTS: Salivary flow rate, buffer capacity and pH decreased, and the levels of Lactobacilli increased significantly, during the first half of the radiation therapy. The endogenously activated salivary MMP-9 correlated with low salivary pH (P = 0.013). No connection was found between the oral mucosal lesions and salivary MMP-8 or MMP-9. CONCLUSIONS: In this study, salivary MMP-8 or MMP-9 did not correlate with the presence of radiation induced oral mucosal lesions, but the activation of MMP-9 may be dependent on pH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".