Gene Expression Profiling Identifies Interferon Signalling Molecules and IGFBP3 in Human Degenerative Annulus Fibrosus
Bibliographic record
Abstract
Low back pain is a major cause of disability especially for people between 20 and 50 years of age. As a costly healthcare problem, it imposes a serious socio-economic burden. Current surgical therapies fail to replace the normal disc in facilitating spinal movements and absorbing load. The focus of regenerative medicine is on identifying biomarkers and signalling pathways to improve our understanding about cascades of disc degeneration and allow for the design of specific therapies. We hypothesized that comparing microarray profiles from degenerative and non-degenerative discs will lead to the identification of dysregulated signalling and pathophysiological targets. Microarray data sets were generated from human annulus fibrosus cells and analysed using IPA ingenuity pathway analysis. Gene expression values were validated by qRT-PCR, and respective proteins were identified by immunohistochemistry. Microarray analysis revealed 238 differentially expressed genes in the degenerative annulus fibrosus. Seventeen of the dysregulated molecular markers showed log2-fold changes greater than ±1.5. Various dysregulated cellular functions, including cell proliferation and inflammatory response, were identified. The most significant canonical pathway induced in degenerative annulus fibrosus was found to be the interferon pathway. This study indicates interferon-alpha signalling pathway activation with IFIT3 and IGFBP3 up-regulation, which may affect cellular function in human degenerative disc.
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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 | 0.001 | 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".