Immune system transcriptome in gingival tissues of young nonhuman primates
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Young/adolescent humans harbor many microorganisms associated with periodontal disease in adults and show substantial gingival inflammatory responses. However, younger individuals do not demonstrate the soft- and hard-tissue destruction that hallmark periodontitis. MATERIAL AND METHODS: This study evaluated responses to the oral microbial ecology in gingival tissues from clinically healthy young Macaca mulatta (< 3 years of age) compared with older animals (5-23 years of age). RNA was isolated from the tissues and analyzed for the transcriptome using the Rhesus Macaque GeneChip (Affymetrix). RESULTS: Global transcriptional profiling of four age groups revealed a subset of 159 genes that were differentially expressed across at least one of the age comparisons. Correlation metrics generated a relevance network abstraction of these genes. Partitioning of the relevance network revealed seven distinct communities comprising functionally related genes associated with host inflammatory and immune responses. A group of genes was identified that were selectively increased/decreased or positively/negatively correlated with gingival profiles in the animals. A principal components analysis created metagenes of expression profiles for classifying the 23 animals. CONCLUSION: The results provide novel system-level insights into gene-expression differences in gingival tissues from healthy young animals, weighted toward host responses associated with anti-inflammatory biomolecules or those linked with T-cell regulation of responses. The combination of the regulated microenvironment may help to explain the apparent 'resistance' of younger individuals to developing periodontal disease.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".