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Record W4414438707 · doi:10.1016/j.jfscie.2025.100054

Proinflammatory and anti-inflammatory cytokines in modulating bone remodeling during orthodontic tooth movement

2025· article· en· W4414438707 on OpenAlexaboutno aff
Nisha Varughese, Karunya Krishnakumar, K Hema Shree, Aravind Kumar Subramanian, Ramya Ramadoss

Bibliographic record

VenueJADA Foundational Science · 2025
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
Fundersnot available
KeywordsProinflammatory cytokineBone remodelingSystematic reviewTumor necrosis factor alphaCytokineMultiplexDental alveolusObservational study

Abstract

fetched live from OpenAlex

Objectives: This systematic review and meta-analysis sought to assess the influence of proinflammatory (interleukin [IL]-1β, IL-6, tumor necrosis factor α) and anti-inflammatory (IL-10, IL-4, IL-1RA) cytokines on bone remodeling during orthodontic tooth movement. The aim was to clarify their dynamics over time and space and evaluate their potential as clinical biomarkers. Search Strategy: The review adhered to the Preferred Reporting Items for Systematic reviews and Meta-analyses 2020 guidelines. A structured population, intervention, comparator, outcome framework directed the search. Medical Subject Heading terms alongside free-text key words were used in combination with Boolean operators across various databases (PubMed, Embase, Scopus, Cochrane Library, Web of Science) from 2000 through 2024. The reference lists of the included studies were examined manually to ensure thoroughness. Citation Sources: Searching electronic databases and conducting manual reference checks resulted in an initial collection of 85 studies of which 14 met the criteria for inclusion. Study Selection Criteria: The studies eligible for inclusion measured cytokine levels (IL-1β, IL-10, IL-1RA, IL-4) in gingival crevicular fluid, saliva, or serum throughout orthodontic treatment. No age, sex, or appliance type restrictions were imposed on the participants. Both observational and interventional human studies were considered. Data Elements Included: Data extraction included details such as authorship, methodology, biological fluid examined, cytokines investigated, detection technique (enzymed-linked immunosorbant assay, multiplex assay, polymerase chain reaction), sample size, and key outcomes. Quality assessment was conducted using the Newcastle-Ottawa Scale. Overall Conclusions: Proinflammatory cytokines showed early peaks after the application of orthodontic force, triggering bone resorption at compression sites. In contrast, anti-inflammatory cytokines appeared later, facilitating repair and bone deposition at tension sites. IL-1β levels were positively correlated with the rate of tooth movement, while lower levels of IL-1RA were associated with quicker distal displacement. Although the pooled results from the meta-analysis did not show statistically significant differences, consistent trends supported the regulatory role of cytokines in orthodontic tooth movement. Future investigations should focus on larger, multicenter studies using standardized protocols to confirm the reliability of cytokines as biomarkers for precise orthodontic treatments.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.020
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.303
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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