Low‐dose lithium regimen enhances endochondral fracture healing in osteoporotic rodent bone
Bibliographic record
Abstract
Osteoporotic bone fractures are highly prevalent and involve lengthy recovery. Lithium, commonly used in psychiatric medicine, inhibits glycogen synthase kinase-3β in the Wnt/β-catenin pathway, leading to up-regulation of osteogenesis. Our recent preclinical work demonstrated that a 20 mg/kg lithium dose administered beginning 7 days post-fracture for 14 days optimally improved femoral fracture healing in healthy rats at 4 weeks post fracture (46% higher torsional strength). In this study, lithium treatment was evaluated for healing of osteoporotic bone fractures. Six-month-old ovariectomized rats were subjected to closed, load-drop induced femoral diaphyseal fracture. Two regimens involving treatment initiation on day 7 and day 10, respectively, 20 mg/kg/day oral dose and 14 days duration were evaluated. Femurs of lithium- vs. saline- treated rats were analyzed at 4 weeks (for day 7 onset regimen) or 6 weeks (for day 10 onset regimen) post-fracture by stereology and torsional mechanical testing. Initiation on day 10 led to a significant 50% higher maximum yield torque (primary outcome measure) at 6 weeks (309 vs. 206 N-mm, p = 0.005; n = 7, 7). Initiation on day 7 suggested a trend toward a more modest improvement in maximum yield torque (13%) evaluated at 4 weeks post-fracture (234 vs. 206 N-mm, p = 0.10; n = 10, 13). Qualitatively, lithium-treated femurs demonstrated better periosteal and mineralized callus bridging in the day 10 initiation group. Lithium is a widely-available, orally administered, low-cost drug, which represents a feasible pharmacological intervention for both healthy and osteoporotic fracture healing. This study provides important guidelines for future clinical evaluation of lithium in osteoporotic fracture patients. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1783-1789, 2018.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".