Peri‐Implantitis versus Periodontitis: Functional Differences Indicated by Transcriptome Profiling
Bibliographic record
Abstract
BACKGROUND: Periodontitis and Periimplantitis are oftentimes discussed as one entity, which is reflected by therapeutical as well as by scientific approaches. It is unclear, to which extent the similarity of the clinical characteristics is attributed to similarities in the underlying disease mechanisms. PURPOSE: The main objective of the study is to display if or how different periimplantitis and periodontitis are on the mRNA level, representing a high-resolution map of disease-associated events. MATERIALS AND METHODS: Aiming to describe the pathophysiological mechanisms in vivo, primary gingival tissue from 7 periimplantitis patients, 7 periodontitis patients and 8 healthy controls was employed in order to generate genome wide transcriptome profiles. RESULTS: On the basis of quantitative transcriptome analysis, we could show that periimplantitis and periodontitis exhibit significantly different mRNA signatures. Additionally we present a disease associated mRNA profile, which displays potential periimplantitis disease mechanisms. A gene ontology analysis revealed various pathways, supporting the hypothesis of periimplantitis being a complex inflammatory disorder with a unique pathophysiology. While in periimplantitis tissue the regulation of transcripts related to innate immune responses and defense responses were dominating, in periodontitis tissues bacterial response systems prevailed. CONCLUSIONS: Taken together, our results suggest considering periimplantitis and periodontitis as disease entities with shared as well as with distinct features, which should be reflected on the therapeutical as well as on the scientific level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".