Long‐term histological analysis of innervation and macrophage infiltration in a mouse model of intervertebral disc injury–induced low back pain
Bibliographic record
Abstract
Low back pain (LBP) is a leading cause of global disability. Multiple anatomical, cellular, and molecular factors are implicated in LBP, including the degeneration of lumbar intervertebral discs (IVDs). We previously described a mouse model that displays behavioral symptoms of chronic LBP. Here, we investigated the development of pathological innervation and macrophage infiltration into injured IVDs following a puncture injury in mice over 12 months. 2-month old CD1 female mice underwent a single puncture of the ventral L4/5 IVD using a 30G needle, and were sacrificed 4 days and 0.5-, 3-, 6- and 12-months post-injury. Severity of disc degeneration was assessed using colorimetric staining. IVD innervation was measured by PGP9.5-immunoreactivity (-ir) and calcitonin gene-related peptide-ir (CGRP-ir). Macrophage accumulation into IVDs was detected by F4/80-ir. Mechanical IVD injury resulted in severe degeneration and increased PGP9.5-ir nerve fiber density starting at 4 days that persisted for up to 12 months and dorsal herniations began to occur at 3 months. CGRP-ir was also upregulated in injured IVDs, with the largest increase at 12 months after injury. Infiltration of F4/80-ir macrophages was observed in injured IVDs by day 4 both dorsally and ventrally, with the latter diminishing in the later stage. Persistent LBP is a complex disease with multiple underlying pathologies. By highlighting pathological changes in IVD innervation and inflammation, our study suggests that strategies targeting these mechanisms might be useful therapeutically.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".