Secretion of SDF‐1α by bone marrow‐derived stromal cells enhances skin wound healing of C57BL/6 mice exposed to ionizing radiation
Bibliographic record
Abstract
Patients treated for cancer therapy using ionizing radiation (IR) have delayed tissue repair and regeneration. The mechanisms mediating these defects remain largely unknown at present, thus limiting the development of therapeutic approaches. Using a wound healing model, we here investigate the mechanisms by which IR exposure limits skin regeneration. Our data show that induction of the stromal cell-derived growth factor 1alpha (SDF-1alpha) is severely impaired in the wounded skin of irradiated, compared to non-irradiated, mice. Hence, we evaluated the potential of bone marrow-derived multipotent stromal cells (MSCs), which secrete high levels of SDF-1alpha, to improve skin regeneration in irradiated mice. Injection of MSCs into the wound margin led to remarkable enhancement of skin healing in mice exposed to IR. Injection of irradiated MSCs into the wound periphery of non-irradiated mice delayed wound closure, also suggesting an important role for the stromal microenvironment in skin repair. The beneficial actions of MSCs were mainly paracrine, as the cells did not differentiate into keratinocytes. Specific knockdown of SDF-1alpha expression led to drastically reduced efficiency of MSCs in improving wound closure, indicating that SDF-1alpha secretion by MSCs is largely responsible for their beneficial action. We also found that one mechanism by which SDF-1alpha enhances wound closure likely involves increased skin vascularization. Our findings collectively indicate that SDF-1alpha is an important deregulated cytokine in irradiated wounded skin, and that the decline in tissue regeneration potential following IR can be reversed, given adequate microenvironmental support.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".