Intercellular communication via gap junctions affected by mechanical load in the bovine annulus fibrosus
Bibliographic record
Abstract
Cells in the intervertebral disc, as in other connective tissues including tendon, ligament and bone, form interconnected cellular networks that are linked via functional gap junctions. These cellular networks may be necessary to affect a coordinated response to mechanical and environmental stimuli. Using confocal microscopy with fluorescence recovery after photobleaching methods, we explored the in situ strain environment of the outer annulus of an intact bovine disc and the effect of high-level flexion on gap junction signalling. The in situ strain environment in the extracellular matrix of the outer annulus under high flexion load was observed to be non-uniform with the extensive cellular processes remaining crimped sometimes at flexion angles greater than 25°. A significant transient disruption of intercellular communication via functional gap junctions was measured after 10 and 20 min under high flexion load. This study illustrates that in healthy annulus fibrosus tissue, high mechanical loads can impede the functioning of the gap junctions. Future studies will explore more complex loading conditions to determine whether losses in intercellular communication can be permanent and whether gap junctions in aged and degenerated tissues become more susceptible to load. The current research suggests that cellular structures such as gap junctions and intercellular networks, as well as other cell-cell and cell-matrix interconnections, need to be considered in computational models in order to fully understand how macroscale mechanical signals are transmitted across scales to the microscale and ultimately into a cellular biosynthetic response in collagenous tissues.
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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 | 0.000 |
| 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 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".