High-fat Diet-induced Obesity Induces Peripheral Neuropathy During Impaired Cutaneous Wound Healing
Bibliographic record
Abstract
Type-II diabetes is a societal epidemic that is associated with obesity and metabolic disease often resulting from poor diet and reduced physical activity. Two major complications associated with type-II diabetes are peripheral neuropathy which leads to a loss of sensation and chronic pain as well as poor wound healing, which can progress to ulceration and ultimately amputation. Since clinical trials for the treatment of these chronic conditions have only fostered limited success we examined the possibility that the nervous system and wound repair are linked. The PURPOSE of this study was to investigate the potential that the peripheral nervous system is a necessary regulator for normal wound repair and that diabetes-induced neuropathy is in part, causative of impaired wound healing. METHODS: We administered a 6 mm skin punch biopsy wound to high-fat diet (HFD, 10 weeks of feeding with 60% of energy from fat content, n=9) and control (10% of energy via fat content, n=9) fed mice. RESULTS: A diabetic phenotype was confirmed in HFD mice as evidenced by elevated body weight (Control mean weight=32.4g, HFD mean weight=40.7g) and impaired glucose tolerance (p < 0.05) in response to an intraperitoneal glucose tolerance test. Following skin injury, HFD mice demonstrated an impaired wound healing rate as evidenced by a larger wound diameter and area (p < 0.05) at days 2-9 while hematoxylin, and eosin staining of tissue-cross sections revealed larger wound widths and a poorly formed dermis in HFD mice in comparison to controls at day 9. Immunohistochemical analysis demonstrated that poor wound healing was coincident with a reduction of S100ß+ cutaneous Schwann cells within and around the healing dermis. Ongoing analysis includes the examination of additional markers of cutaneous neuropathy using immunohistochemistry to quantify total nerve axons (UCHL-1+ cells), growing/regenerating axons (Gap43+ cells) and markers of activated/dedifferentiated Schwann cells (p75NTR+,Sox2+ cells) as well as testing the efficacy of Schwann cell transplantation to rescue HDF-induced neuropathy and wound healing deficits. CONCLUSION: Collectively, these experiments will give insight into the mechanisms underpinning two major complications associated with type-II diabetes that could be further explored to develop novel therapeutics.
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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) | 0.000 | 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 | 0.001 |
| 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".