Profiling of differentially expressed genes in wound margin biopsies of horses using suppression subtractive hybridization
Bibliographic record
Abstract
Disturbed gene expression may disrupt the normal process of repair and lead to pathological situations resulting in excessive scarring. To prevent and treat impaired healing, it is necessary to first define baseline gene expression during normal repair. The objective of this study was to compare gene expression in normal intact skin (IS) and wound margin (WM) biopsies using suppression subtractive hybridization (SSH) to identify genes differentially expressed during wound repair in horses. Tissue samples included both normal IS and biopsies from 7-day-old wounds. IS cDNAs were subtracted from WM cDNAs to establish a subtracted (WM-IS) cDNA library; 226 nonredundant cDNAs were identified. Detection of genes previously shown to be expressed 7 days after trauma, including the pro-alpha(2)-chain of type 1 pro-collagen (COL1A2), annexin A(2), the pro-alpha(3)-chain of type 6 pro-collagen, beta-actin, fibroblast growth factor 7, laminin receptor 1, matrix metalloproteinase 1 (MMP1), secreted protein acidic cystein rich, and tissue inhibitor of metalloproteinase 2, supported the validity of the experimental design. A RT-PCR assay confirmed an increase or induction of the cDNAs of specific genes (COL1A2, MMP1, dermatan sulfate proteoglycan 2, cluster differentiation 68, cluster differentiation 163, and disintegrin and metalloproteinase domain 9) within wound biopsies. Among these, COL1A2 and MMP1 had previously been documented in horses; 68.8% of the cDNAs had not previously been attributed a role during wound repair, of which spermidine/spermine-N-acetyltransferase, serin proteinase inhibitor B10, and sorting nexin 9 were highly expressed and whose known functions in other processes made them potential candidates in regulating the proliferative response to wounding. In conclusion, we identified novel genes that are differentially expressed in equine wound biopsies and that may modulate repair. Future experiments must correlate changes in mRNA levels for precise molecules with spatiotemporal protein expression within tissues.
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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 | 0.000 |
| 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 | 0.000 |
| 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".