Activation of Wnt signaling in human fracture callus and nonunion tissues
Bibliographic record
Abstract
The Wnt signaling pathway is a key molecular process during fracture repair. Although much of what we now know about the role of this pathway in bone is derived from in vitro and animal studies, the same cannot be said about humans. As such, we hypothesized that Wnt signaling will also be a key process in humans during physiological fracture healing as well as in the development of a nonunion (hypertrophic and oligotrophic). We further hypothesized that the expression of Wnt-signaling pathway genes/proteins would exhibit a differential expression pattern between physiological fracture callus and the pathological nonunion tissues. We tested these two hypotheses by examining the mRNA levels of key Wnt-signaling related genes: ligands (WNT4, WNT10a), receptors (FZD4, LRP5, LRP6), inhibitors (DKK1, SOST) and modulators (CTNNB1 and PORCN). RNA sequencing from calluses as well as from the two nonunion tissue types, revealed that all of these genes were expressed at about the same level in these three tissue types. Further, spatial expression experiments identified the cells responsible of producing these proteins. Robust expression was detected in osteoblasts for the majority of these genes except SOST which displayed low expression, but in contrast, was mostly detected in osteocytes. Many of these genes were also expressed by callus chondrocytes as well. Taken together, these results confirm that Wnt signaling is indeed active during both human physiological fracture healing as well as in pathological nonunions.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".