A Comparison of Collagen Crosslink Content in Bone Specimens from Elective Total Hip Arthroplasty Patients with and without Type 2 Diabetes
Bibliographic record
Abstract
Objective: To compare the amount of non-enzymatic and enzymatic collagen crosslinks in bone specimens from total hip replacement patients with and without type 2 diabetes (controls). Methods: This ex vivo cross-sectional study included 34 bone specimens (13 from patients with type 2 diabetes, 21 from controls) from men and women ≥ 65 years. All participants were undergoing an elective total hip replacement due to osteoarthritis. Cancellers cores were extracted from the interior of the femoral neck/head and bone cores were reduced to approximately 50 mg of powder. High performance liquid chromatography (HPLC) was used to quantify pentosidine, pyridinoline (PYD) and deoxypyridoline (DPD), which were normalized to collagen content. The mean (SD) was calculated for continuous variables and an independent Student’s t-test was used to compare crosslink content between groups. Results: 13 specimens were collected from participants with type 2 diabetes (mean [SD] age 73.8 [6.2] years) and 21 specimens were collected from controls (mean [SD] age 76.7 [6.8] years, p=0.222). There was no between-group difference in the amount of bone pentosidine (type 2 diabetes: 2.07 [0.94] mmol/mol collagen vs. control: 1.99 [0.60] mmol/mol collagen, p=0.753), PYD (type 2 diabetes: 219.2 [25.3] mmol/mol collagen vs. control: 208.1 [25.8] mmol/mol collagen, p=0.227) or DPD (type 2 diabetes: 132.3 [25.9] mmol/mol collagen vs. control: 130.0 [22.8] mmol/mol collagen, p=0.787). Conclusion: Elective total hip replacement patients with and without type 2 diabetes have similar collagen crosslink profiles. Future studies should consider potential confounding factors, such as bone turnover rate, which may influence collagen crosslink content.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".