Quantitation of the physicochemical properties of myelin using Nile Red fluorescence spectroscopy
Bibliographic record
Abstract
Myelin is a vital structure that is key to rapid saltatory conduction in the central and peripheral nervous systems. Much work has been done over the decades examining the biochemical composition and morphology of myelin at the light and electron microscopic levels. Here we report a method to study myelin based on the fluorescent probe Nile Red. This lipophilic dye readily partitions into live and chemicallyfixed myelin producing bright, well-resolved images of the sheath. Using spectral confocal microscopy, a complete emission spectrum of Nile Red fluorescence can be acquired for each pixel in an image. The solvatochromic properties of Nile Red cause its emission spectrum to change depending on the polarity of its local environment. Therefore, measuring spectral shifts can report subtle changes in the physicochemical properties of myelin. We show differences in myelin polarity in central versus peripheral nervous system and in different regions of central nervous system white matter of the mouse brain, together with developmental and sex variations. This technique is also well suited for measuring subtle changes in myelin properties in live ex vivo white matter specimens. We also demonstrate how light deprivation induces a myelin polarity change in adult mouse optic nerve underscoring a continuing myelin plasticity in response to axonal activity well into adulthood. The Nile Red spectroscopic method allows measurement of subtle physicochemical changes in myelin that can importantly influence its electrical properties and by extension, conduction velocities in axons.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".