Polarization-dependent responses of fluorescent indicators partitioned into myelinated axons
Bibliographic record
Abstract
Myelination, i.e. the wrapping of axons in multiple layers of lipid-rich membrane, is a unique phenomenon in the nervous systems of both vertebrates and invertebrates, that greatly increases the speed and efficiency of signal transmission. In turn, disruption of axo-myelinic integrity underlies disability in numerous clinical disorders. The dependence of myelin physiology on nanometric organization of its lamellae makes it difficult to accurately study this structure in the living state. We expected that fluorescent probes might become highly oriented when partitioned into the myelin sheath, and in turn, this anisotropy could be interrogated by controlling the polarization state of the exciting laser field used for 2-photon excited fluorescence (TPEF). Live ex vivo myelinated rodent axons were labeled with a series of lipohilic and hydrophilic fluorescenct probes, and TPEF images acquired while laser polarization was varied at the sample over a broad range of ellipticities and orientations of the major angle [see Brideau, Micu & Stys, abstract this meeting]. We found that most probes exhibited strong dependence on both the major angle of polarization, and perhaps more surprisingly, on ellipticity as well. Lipophilic vs. hydrophilic probes exhibited distinctly different behavior. We propose that polarization-dependent TPEF microscopy represents a powerful tool for probing the nanostructural architecture of both myelin and axonal cytoskeleton in a domain far below the resolution limit of visible light microscopy. By selecting probes with different sizes and physicochemical properties, distinct aspects of cellular nanoarchitecture can be accurately interrogated in real-time in living tissue.
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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 | 0.001 |
| 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 | 0.001 |
| 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".