Cervical Intervertebral Disc Displacement in Multiple Sclerosis Patients: A Possible Trigger for the Pathogenesis of Multiple Sclerosis?
Bibliographic record
Abstract
Background: Few articles in the world have already correlated these two themes. The reason we wrote this paper is to suggest a pathogenic hypothesis that correlates the two diseases. Methods: We reviewed the medical literature in the MEDLINE/PubMed and LILACS/SciELO databases. We used the terms “cervical intervertebral disc displacement”, “multiple sclerosis”, “neuroinflammation”, “pathogenesis” and its combinations. Results: Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS). Spinal cord myelopathy in MS presents with neck and radicular pain, segmental weakness, hypoesthesia and diminution of tendon reflexes. All of these symptoms may also appear in myelopathy due to cervical spine compression. It is observed in the context of cervical intervertebral disc displacement (CIDD). CIDD is the most common progressive disorder in the aging cervical spine. Clinical researches have described CIDD at different levels in MS patients. However, the majority of these clinical studies were only descriptive. The correlation between the two diseases and the study of the pathogenesis of them was little studied. We hypothesized an unprecedented theory for a possible pathogenic mechanism between CIDD and MS. Can the CIDD be a trigger for the onset of spinal demyelination in MS patients? Conclusions: We believe with blood-spinal cord barrier (BSCB) disruption the neutrophils invasion on CNS is facilitated. Thus local neuroinflammation on the spinal cord in patients with CIDD could be a facilitating factor for neutrophils infiltration to the CNS in MS. This cascade of neuroinflammation may be one of the triggers for the activation of demyelination in the spinal cord of MS patients. J Neurol Res. 2019;9(3):35-38 doi: https://doi.org/10.14740/jnr533
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".