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Record W2020591340 · doi:10.1117/1.jbo.18.11.115003

Quantifying the backscattering of second harmonic generation in tissues with confocal multiphoton microscopy

2013· article· en· W2020591340 on OpenAlexafffund
Mengzhe Shen

Bibliographic record

VenueJournal of Biomedical Optics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia Graduate SchoolNatural Sciences and Engineering Research Council of Canada
KeywordsSecond-harmonic generationMaterials scienceOpticsPinhole (optics)Second-harmonic imaging microscopyConfocalConfocal microscopyMicroscopyLaserPhysics

Abstract

fetched live from OpenAlex

The backward second harmonic generation (SHG) in mouse tissues is studied with a confocal multiphoton microscopy system. The total backward collected SHG (B-SHG) consists of the backward generated SHG and the backward-scattered forward-generated SHG (BS-SHG), which can be modeled by a Gaussian and a uniform distribution, respectively, at the confocal pinhole plane. By varying the pinhole size with a series of collection fibers, the proportion of the BS-SHG to the B-SHG and the proportion of BS-SHG to the forward generated SHG can be obtained. The approach is first validated by Monte Carlo simulation. It is then applied to two types of mouse tissues: mouse tail tendon and Achilles tendon. It is found that the BS-SHG contributes less to the B-SHG for the tail tendon than Achilles tendon with thicknesses of ~300 μm. With the thickness of the Achilles tendon tissue increased to 1000 μm but the focal plane kept at the same depth, as high as ~10% of the total forward SHG is backscattered and collected. The results indicate that BS-SHG may not be the major source of B-SHG in the tail tendon, but it may be the major source in the Achilles tendon. These methods and results provide a noninvasive method and supporting information for investigating the generation mechanism of SHG and help with optimizing backward SHG microscopy and spectroscopy measurements.

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 score0.065
Threshold uncertainty score0.259

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 head0.018
GPT teacher head0.305
Teacher spread0.287 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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