Noninvasive Localized Cold Therapy: A New Mode of Bone Repair Enhancement
Bibliographic record
Abstract
A new bone healing strategy that is based on localized cold is reported. A murine bone healing model was used, in which a unicortical defect was surgically created bilaterally within the femurs. After daily immersion in an ice bath for 28 days, a large increase in bone regeneration within a femoral cortical defect compared with the nontreated limb was observed. Bone regeneration mechanism within the defect upon cold was studied at 1 and 4 weeks using micro-computed tomography and immunohistochemical analysis and compared with the contralateral limb controls. The more advanced healing stage of the bone structure combined with the increased vascular channel density for the cold-treated group matched with an increased expression of vascular endothelial growth factor (VEGF), and a greater number of CD34+-stained cells in the early phase of repair in the cold group. This indicates an elevation in tissue angiogenesis secondary to VEGF expression in the cold group potentially through a temporary vasoconstriction of the local vasculature leading to a temporary state of relative hypoxia. Local cold therapy may be an unrecognized tool with which to accelerate bone regeneration. The absence of observed systemic or local side effects and enhanced bone healing indicates further study is warranted to develop potential clinical protocols. A variety of biological, mechanical, and physical therapeutic modalities of varying complexity, efficacy, cost, and safety profile have been developed to enhance bone healing. There have been sporadic reports of spontaneous bone formation after repeated cold exposure. In this study we report for the first time, the anabolic effect of cold exposure on bone healing in vivo resulting in a doubling of bone volume. Although the precise mechanism is not fully understood, cold is well known to stimulate osteoclastogenesis and modulate inflammation. The impact of this finding is considerable for tissue regeneration because cold application is noninvasive, safe, and easily implemented.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".