Quantitative biochemical investigation of various neuropathologies using high-resolution spectral CARS microscopy
Bibliographic record
Abstract
The pathology of multiple sclerosis involves the gray and white matter regions of the brain and spinal cord often characterized by various combinations of demyelination, inflammatory infiltration, axonal degeneration, and later gliosis in chronic lesions. While acute and chronic white matter lesions are well characterized and easily identified, evidence indicates that the CNS of MS patients may be globally altered, with subtle abnormalities found in grossly normal appearing white matter (NAWM) with histochemical stains and magnetic resonance imaging only indicating a general alteration in tissue composition at best. Thus, the prototypical acute inflammatory lesion may merely represent the most obvious manifestation of a chronic widespread involvement of the CNS, which is difficult to examine reliably. The current study deals with the microstructure and biochemistry of demyelination, remyelination and axonal loss in various regions in post-mortem human MS brain, especially NAWM areas around more typical acute and chronic lesions. The myelin sheath, neuroglia and perivascular spaces were investigated through changes in the intrinsic molecular vibrational signatures of lipid biochemistry using a novel, label-free Coherent anti-Stokes Raman Scattering (CARS) microscope. The biochemistry of myelin lipids can be probed by detecting subtle changes to phospholipids and the intra-molecular disorder of their fatty acid acyl chains, various oxidation products and general protein contributions. NAWM regions surrounding pathological MS lesions were shown to reveal abnormalities despite morphological classifications indicating otherwise. CARS data were correlated with immunohistochemical stains and lipophilic dyes. Spectral data were analyzed using a unique non-linear algorithm, which allows quantification and classification through gated parameters and displayed through bivariate histograms. Our CARS microscopy system provides high-resolution, detailed morphological and unique biochemical information regarding CNS pathology in human MS examples and may be applicable to a broad range of other white matter centric neurological disorders.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".