Study of cytokine induced neuropathology by high resolution proton NMR spectroscopy of rat urine
Bibliographic record
Abstract
Multiple sclerosis is a major cause of non-traumatic neurological disability. The identification of markers that differentiate disease progression is critical to effective therapy. A combination of NMR spectroscopic metabolic profiling of urine and statistical pattern recognition was used to detect focal inflammatory central nervous system (CNS) lesions induced by microinjection of a replication-deficient recombinant adenovirus expressing TNF-alpha or IL1-beta cDNA into the brains of Wistar rats. These animals were compared with a group of naïve rats and a group of animals injected with an equivalent null adenovirus. Urine samples were collected 7 days after adenovirus injection, when the inflammatory lesion is maximally active. Principal components analysis and Partial Least Squares-Discriminate analysis of the urine (1)H NMR spectra revealed significant differences between each of the cytokine adenovirus groups and the control groups; for the TNF-alpha group the main differences lay in citrate and succinate, while for the IL-1beta group the predominant changes occurred in leucine, isoleucine, valine and myo-inositol. Thus, we can identify urinary metabolic vectors that not only separate rats with inflammatory lesions in the brain from control animals, but also distinguish between different types of CNS inflammatory lesions.
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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 | 0.000 | 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".