Impact of orthodontic retainers on periodontal health status assessed by biomarkers in gingival crevicular fluid
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
OBJECTIVE: To evaluate whether biomarkers of inflammation and periodontal remodeling are differentially expressed in the gingival crevicular fluid (GCF) of patients wearing different types of orthodontic retainers. MATERIALS AND METHODS: Thirty-one adult subjects (17 men and 14 women with an age range of 20 to 35 years) were allocated to three different groups. Group 1 consisted of 10 patients wearing fixed retainers, group 2 included 11 patients using lower removable retainers, and group 3 comprised 10 patients without retainers (control). Periodontal health assessment and GCF collection were carried out at two sites per subject: the lingual side of a central lower incisor and the lingual side of a lower second premolar. Aliquots from diluted GCF were screened for the presence of biomarkers using a microarray technique. RESULTS: Group 1 patients exhibited a higher percentage of sites with visible plaque in the incisor region than the other groups (P = .03); no differences were noted in gingival bleeding and probing depths. The median concentrations (pg/mL) of interferon-gamma and interleukin-10 were significantly higher in the premolar sites of patients in group 2 (P = .01 and P = .04, respectively), whereas the concentration of matrix metalloproteinase-9 was significantly higher at the incisors of patients wearing fixed retainers (P = .02). A significant difference between the two sites was seen only in group 2. CONCLUSIONS: The presence of different orthodontic retainers may promote specific alterations in the GCF composition. With retention periods potentially becoming longer, this finding may be of clinical significance.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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