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Record W2511043879 · doi:10.1038/srep31685

Intravital assessment of myelin molecular order with polarimetric multiphoton microscopy

2016· article· en· W2511043879 on OpenAlexafffund
Raphaël Turcotte, Danette J. Rutledge, Erik Bélanger, Dorothy Dill, Wendy B. Macklin, Daniel Côté

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de Québec
FundersMultiple Sclerosis SocietyMultiple Sclerosis Society of Canada
KeywordsIntravital microscopyMultiphoton fluorescence microscopeMyelinMicroscopyMyelin sheathPolarimetryChemistryBiologyNeurosciencePathologyMedicinePhysicsOpticsFluorescence microscopeGeneticsCentral nervous system

Abstract

fetched live from OpenAlex

Myelin plays an essential role in the nervous system and its disruption in diseases such as multiple sclerosis may lead to neuronal death, thus causing irreversible functional impairments. Understanding myelin biology is therefore of fundamental and clinical importance, but no tools currently exist to describe the fine spatial organization of myelin sheaths in vivo. Here we demonstrate intravital quantification of the myelin molecular structure using a microscopy method based on polarization-resolved coherent Raman scattering. Developmental myelination was imaged noninvasively in live zebrafish. Longitudinal imaging of individual axons revealed changes in myelin organization beyond the diffraction limit. Applied to promyelination drug screening, the method uniquely enabled the identification of focal myelin regions with differential architectures. These observations indicate that the study of myelin biology and the identification of therapeutic compounds will largely benefit from a method to quantify the myelin molecular organization in vivo.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.285
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2016
Admission routes2
Has abstractyes

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