Decreased salivary sulphotransferase activity correlated with inflammation and autoimmunity parameters in Sjogren's syndrome patients
Bibliographic record
Abstract
OBJECTIVES: To determine the expression and enzymatic activities of sulphotransferases involved in mucin hyposulphation in labial salivary glands (LSGs) from SS patients and to correlate sulphotransferase activity with clinical parameters such as secretion, inflammation and serology. METHODS: LSG from 31 SS patients and 31 control subjects were studied. Relative mRNA and protein levels of Gal3-O-sulphotransferases (Gal3STs) and β1,3-galactosyltransferase-5 (β3GalT5) were determined by quantitative RT-PCR and western blotting, respectively. Enzymatic activities were quantified using radioactively labelled donor substrates and specific acceptor substrates. Products were purified by chromatography. Spearman's correlation analysis was used to compare data. RESULTS: The levels of Gal3ST activity were significantly decreased in SS patients, without changes in mRNA and protein levels, while the enzymatic activities of glycosyltransferases involved in mucin glycosylation were similar in both groups. An inverse correlation was observed between Gal3ST activity and glandular function measured by scintigraphy, but not with unstimulated salivary flow. Gal3ST activity was inversely correlated with focus score, TNF-α levels and presence of the autoantibodies Ro/SS-A and La/SS-B. CONCLUSION: The decrease in sulphotransferase activity provides an explanation for mucin hyposulphation observed in the LSGs from SS patients. The decrease in Gal3STs activity was not a consequence of reduced gene expression, but probably due to alterations in the enzyme activity regulation. Interestingly, the levels of sulphotransferase activity detected correlated well with secretory function, inflammation and serology. Finally, we postulate that pro-inflammatory cytokines induced by autoantibodies, such as Ro/SS-A and La/SS-B in SS patients, may modulate Gal3ST activity, thereby altering mucin quality and leading to mouth dryness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".