Global <scp>TLR</scp>2 and 4 deficiency in mice impacts bone resorption, inflammatory markers and atherosclerosis to polymicrobial infection
Bibliographic record
Abstract
Summary Toll‐like‐receptors ( TLR s) play a significant role in the generation of a specific innate immune response against invading pathogens. TLR 2 and TLR 4 signaling contributes to infection‐induced inflammation in periodontal disease ( PD ) and atherosclerosis. Observational studies point towards a relationship between PD and atherosclerosis, but the role of TLR 2 and TLR 4 in the recognition of multiple oral pathogens and their modulation of host response leading to atherosclerosis are not clear. We evaluated the role of TLR 2 and TLR 4 signaling in the induction of both PD and atherosclerosis in TLR 2 −/− and TLR 4 −/− mice to polymicrobial infection with periodontal pathogens Porphyromonas gingivalis , Treponema denticola , Tannerella forsythia , and Fusobacterium nucleatum . Polybacterial infections have established gingival colonization in TLR 2 −/− and TLR 4 −/− mice and induction of a pathogen‐specific immunoglobulin G immune response. But TLR deficiency dampened accelerated alveolar bone resorption and intrabony defects, indicating a central role in infection‐induced PD . Periodontal bacteria disseminated from gingival tissue to the heart and aorta through intravascular dissemination; however, there was no increase in atherosclerosis progression in the aortic arch. Polybacterial infection does not alter levels of serum risk factors such as oxidized low‐density lipoprotein, nitric oxide, and lipid fractions in both mice. Polymicrobial‐infected TLR 2 −/− mice demonstrated significant levels ( P < 0.05 to P < 0.01) of T helper type 2 [transforming growth factor‐β 1 , macrophage inflammatory protein‐3α, interleukin‐13 ( IL ‐13)] and T helper type 17 ( IL ‐17, IL ‐21, IL ‐22, IL ‐23) splenic T‐cell cytokine responses. Increased heat‐shock protein expression, hspa1a for Hsp 70, was observed for both TLR 2 −/− and TLR 4 −/− mice. This study supports a role for TLR 2 and TLR 4 in PD and atherosclerosis, corroborating an intricate association between two inflammatory diseases.
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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".