Diffuse Axonal and Tissue Injury in Patients With Multiple Sclerosis With Low Cerebral Lesion Load and No Disability
Bibliographic record
Abstract
BACKGROUND: Although in situ pathological studies and in vivo magnetic resonance (MR) investigations have shown that axonal injury can be significant in the early stages of multiple sclerosis (MS), diffuse axonal injury is generally considered a secondary event. Cerebral axonal damage can be specifically assessed in vivo by measuring levels of brain N-acetylaspartate (NAA, a specific index of axonal integrity detected by MR spectroscopy). Other new MR measurements such as magnetization transfer ratio (MTr) or computed estimation of brain volume can provide less specific indexes of tissue damage. OBJECTIVE: To determine whether diffuse axonal and tissue injury is present in patients with definite MS who do not show clinically significant disability. METHODS: We measured brain NAA levels (normalized to creatine [Cr]), MTr values, and cerebral volumes in patients with definite MS who had low T2-weighted MR imaging lesion volumes and no clinical disability, and also in age-matched healthy control subjects. RESULTS: Values of central brain NAA/Cr and MTr in normal-appearing white matter were significantly lower in the MS patients than in controls (P<.001). In contrast, total brain volumes were not significantly different between these groups. Similar results were found for MS patients with early disease (duration, <3 years) and with a particularly low cerebral T2-weighted MR imaging lesion load (< or = 2 cm(3)). CONCLUSIONS: Cerebral NAA/Cr and MTr values are diffusely decreased in MS patients with early disease, low demyelinating lesion load, and no significant disability. This suggests that axonal and/or tissue injury begins very early in the course of MS and might be at least partially independent of cerebral demyelination.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".