Functional human T-cell immunity and osteoprotegerin ligand control alveolar bone destruction in periodontal infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Periodontitis, a prime cause of tooth loss in humans, is implicated in the increased risk of systemic diseases such as heart failure, stroke, and bacterial pneumonia. The mechanisms by which periodontitis and antibacterial immunity lead to alveolar bone and tooth loss are poorly understood. To study the human immune response to specific periodontal infections, we transplanted human peripheral blood lymphocytes (HuPBLs) from periodontitis patients into NOD/SCID mice. Oral challenge of HuPBL-NOD/SCID mice with Actinobacillus actinomycetemcomitans, a well-known Gram-negative anaerobic microorganism that causes human periodontitis, activates human CD4(+) T cells in the periodontium and triggers local alveolar bone destruction. Human CD4(+) T cells, but not CD8(+) T cells or B cells, are identified as essential mediators of alveolar bone destruction. Stimulation of CD4(+) T cells by A. actinomycetemcomitans induces production of osteoprotegerin ligand (OPG-L), a key modulator of osteoclastogenesis and osteoclast activation. In vivo inhibition of OPG-L function with the decoy receptor OPG diminishes alveolar bone destruction and reduces the number of periodontal osteoclasts after microbial challenge. These data imply that the molecular explanation for alveolar bone destruction observed in periodontal infections is mediated by microorganism-triggered induction of OPG-L expression on CD4(+) T cells and the consequent activation of osteoclasts. Inhibition of OPG-L may thus have therapeutic value to prevent alveolar bone and/or tooth loss in human periodontitis.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it