Therapeutic Consistency of ADSC Secretomes for Wound Healing, Scar Modulation, and Autoimmune Disease
Bibliographic record
Abstract
INTRODUCTION: Adipose-derived stem cell (ADSC) secretomes have been demonstrated to have potential therapeutic applications in various conditions, including wound healing, tissue repair, and autoimmune diseases. The ADSC secretome includes a variety of proteins, growth factors, and a wide range of signaling molecules, which should be further analyzed to pave the way for the development of novel ADSC-based therapies. Prior secretome analyses have been limited to select individual donors, so it is not clear whether there is variability amongst donors. Because ADSC-based therapies would entail autologous grafting, the aim of our investigation was therefore to determine whether the secretome therapeutic benefits are consistent from donor to donor. METHODS: Lipoaspirate was obtained from 9 healthy donors undergoing elective liposuction at the Department of Plastic Surgery, University of California, Irvine. The lipoaspirate underwent a cellular isolation protocol and was passaged to obtain a pure population of ADSC’s. After culturing to confluency, secretome samples were collected and sent to Eve Technologies, Inc (AB, Canada) for interrogation. The secretome report was subsequently decoded followed by classification of proteins into 3 categories: low, mid, and high secretion. This partitioned data was then imported into REACTOME and STRING for visualization and interpretation of implicated pathways and protein-protein interactions, respectively. An algorithm was then utilized to identify significant pathways and interactions present across combinations of all 3 secretion categories. RESULTS: 23 genes and associated proteins with a low coefficient of variation were identified across all donors. A REACTOME and STRING analysis of all combined data demonstrated 152 implicated cellular pathways. After analyzing the partitioned data and evaluating for overlap between all secretion levels, 37 significant pathways were identified. The pathways were then classified according to their contributions to general biological processes. Pathways involving signaling and regulation of IL-4, IL-13, and IL-17 were associated with immunomodulation. The secretomes also contained proteins contributing to the regulation of blood vessel endothelial cell proliferation involved in sprouting angiogenesis. Lastly, Insulin-Like Growth Factor Binding Proteins (IGFB) involved in the regulation of IGF were identified. CONCLUSION: Our investigation demonstrates that ADSC secretomes contain key factors that are consistently present across donors. The identified factors have been implicated in various immunomodulatory and angiogenic processes, in addition to the regulation of IGF transport and uptake through IGF binding proteins. These findings suggest that autologous grafting in patients may reliably provide consistent therapeutic advantages for wound healing, scar modulation, and autoimmune processes.
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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 | 0.000 | 0.001 |
| 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".