<i>Treponema denticola</i> may stimulate both epithelial proliferation and apoptosis through MAP kinase signal pathways
Bibliographic record
Abstract
Mitogen-activated protein kinases (MAP kinases) play a key role in the regulation of cell survival and death. Effects of Treponema denticola ATCC 35405 on ERK, p38 and JNK MAP kinases, and cell behavior was studied using non-keratinizing periodontal ligament epithelial cells (PLE) in vitro. Compared to Chinese hamster ovary cells, human cervix adenocarcinoma cells, human osteosacroma cells and human gingival fibroblasts, PLE cells were much more resistant to T. denticola-induced reduction in cell viability, assayed by tetrazolium and crystal violet assays. A low dose of 5 x 10(7) T. denticola cells/ml increased DNA synthesis ([3H]thymidine uptake) in PLE cells but at higher concentrations DNA synthesis was decreased. TUNEL staining analysis showed that about 50% of epithelial cells in onolayers died through apoptosis when exposed to a high dose of 10(11) T. denticola/ml for 24 h. Morphological light and electron microscopic analysis supported the idea that both apoptotic and necrotic cell death took place. Rounding, membrane damage, fragmentation and detachment were observed in selective cells of both mono- and multilayered PLE cultures challenged with T. denticola. Western blot analysis using MAP kinase phosphospecific antibodies showed that T. denticola strongly but transiently activated ERK1 and ERK2, signals mediating cell proliferation, and JNK and p38, kinases mediating apoptosis. While a specific inhibitor of the ERK MAP kinase pathway prevented the T. denticola stimulation of cell proliferation, inhibitor of p38 increased the cell numbers in T. denticola-treated cultures. The results suggest that T. denticola activates epithelial cell MAP kinase signal pathways controlling cell proliferation and cell survival. In addition, T. denticola exerts cytotoxic effects that appear to predominate at higher bacterial concentrations.
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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 | 0.000 |
| 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 | 0.000 | 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".