Proteomic analysis of human cerebrospinal fluid from patients with painful and non-painful degenerative disc disease
Bibliographic record
Abstract
One of the primary causes of persistent lumbar back pain is degenerative disc disease (DDD). In most persons, DDD is a normal process occurring with natural age, while in others, DDD results in chronic pain. While imaging techniques can be used to detect degenerative changes, there is a low correlation between the extent of degenerative changes and the pain found upon physical evaluation, suggesting biochemical factors may be involved with the persistent pain state. The purpose of this study was to examine human cerebrospinal fluid (CSF) for changes in protein expression using high throughput proteomics technology, which would help to identify biochemical factors involved with DDD and low back pain. Differences at the protein level were observed in the CSF of persons with asymptomatic and painful degenerative disc disease. Markers of inflammation were altered in patients with degenerative disc disease. In the case of painful degenerative disc disease, our results suggest altered neuropeptide processing and nerve damage may be playing a role in the disease.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".