53 Regulation of Glycolysis and the Warburg Effect in Keloids
Bibliographic record
Abstract
Abstract Introduction Hypertrophic and keloid scarring are considered as major determinants for long-term outcomes and quality of life for burn survivors. Keloid development is predicated on prolonged local inflammation and altered glucose metabolism. Owing to its tumor-like dependence on glucose, we hypothesized that keloids would display the bioenergetics of cancer cells; namely, increased glucose uptake via Glut1 and upregulation of key glycolytic enzymes. Furthermore, burn patients who develop keloids potentially demonstrate early evidence of the aforementioned features compared to non-keloid patients. Therefore, elevated Glut1 expression could serve as a marker for keloid development in burn patients. Methods We enrolled 27 control burn patients with 39% ± 4% total body surface area (TBSA) burns. The keloid burn group included 9 burn patients with 47% ± 9% TBSA burns. Skin was obtained for histology, gene and protein expression at 0–17 days post-burn. Results Keloids have higher Glut1 expression compared to normal and burn skin (7.72 vs. 0.15, p< 0.001; 7.72 vs. 2.35, p< 0.05). Keloids also exhibit enhanced expression of critical glycolytic enzymes compared to burn skin at 7–10 days post-burn (HK2: 4.14 vs. 2.36, p< 0.001; PFK1: 6.51 vs. 3.83, p< 0.001; PFK2: 5.35 vs. 1.27, p< 0.001; PDK1: 5.50 vs. 4.31, p< 0.05; PKM2: 7.58 vs. 2.98, p< 0.001). A Glut1 time-course analysis in burn skin from non-keloid patients indicated a significant elevation at 7–10 days post-burn compared to normal skin (3.22 vs. 0.20, p< 0.01). Skin from keloid burn patients prior to development of keloids demonstrate higher Glut1 expression compared to skin from non-keloid controls when matched by days post-burn (40.5 vs. 0.58 at 0–2 days, p< 0.05). Conclusions Patients who develop post-burn keloids exhibit early risk factors prior to the development of keloids (e.g. elevated skin Glut1). Keloids have an augmented reliance on glycolysis compared to burn skin. Therefore, early identification and targeting glycolysis in susceptible patients is key. Applicability of Research to Practice Upregulation of glycolytic enzymes and transporters such as Glut1 may serve as keloid predictive markers. Identification of at-risk patients allows for a tailored treatment regimen that targets dysregulated glycolysis in these patients. Pharmaceutical agents like shikonin suppress multiple glycolytic steps, serving as an effective means to interfere with the proliferative capacity of keloids. Potentially, local shikonin administration could serve as a therapy in select patients exhibiting keloid risk factors.
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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".