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Record W2106592622 · doi:10.1364/ao.46.001852

Influence of semicrystalline order on the second-harmonic generation efficiency in the anisotropic bands of myocytes

2007· article· en· W2106592622 on OpenAlexaff
Catherine Greenhalgh, Nicole Prent, Chantal Green, Richard Cisek, Arkady Major, Bryan A. Stewart, Virginijus Barzda

Bibliographic record

VenueApplied Optics · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSarcomereCrystallinityMaterials scienceAnisotropyMyofibrilMyocyteMyosinSecond-harmonic generationBiophysicsOpticsMolecular physicsChemistryComposite materialBiologyPhysicsBiochemistry

Abstract

fetched live from OpenAlex

The influence of semicrystalline order on the second-harmonic generation (SHG) efficiency in the anisotropic bands of Drosophila melanogaster sarcomeres from larval and adult muscle has been investigated. Differences in the semicrystalline order were obtained by using wild-type and mutant strains containing different amounts of headless myosin. The reduction in semicrystalline order without altering the chemical composition of myofibrils was achieved by observing highly stretched sarcomeres and by inducing a loss of viability in myocytes. In all cases the reduction of semicrystalline order in anisotropic bands of myocytes resulted in a substantial decrease in SHG. Second-harmonic imaging during periodic contractions of myocytes revealed higher intensities when sarcomeres were in the relaxed state compared with the contracted state. This study demonstrates that an ordered semicrystalline arrangement of anisotropic bands plays a determining role in the efficiency of SHG in myocytes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.257
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations57
Published2007
Admission routes1
Has abstractyes

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