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Record W1997901015 · doi:10.1117/1.jbo.17.8.086010

Optical assessment of tissue anisotropy in <italic>ex vivo</italic> distended rat bladders

2012· article· en· W1997901015 on OpenAlexaff
Karen Aitken

Bibliographic record

VenueJournal of Biomedical Optics · 2012
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersDeutsche Forschungsgemeinschaft
KeywordsDistensionAnisotropyBirefringenceOptical coherence tomographyMaterials scienceEx vivoOpticsIsotropyAnatomyIn vivoPhysicsMedicineBiology

Abstract

fetched live from OpenAlex

Microstructural remodelling in epithelial layers of various hollow organs, including changes in tissue anisotropy, are known to occur under mechanical distension and during disease processes. In this paper, we analyze how bladder distension alters wall anisotropy using polarized light imaging (followed by Mueller matrix decomposition). Optical retardance values of different regions of normal rat bladders under different distension pressures are derived. Then optical coherence tomography is used to measure local bladder wall thicknesses, enabling the calculation of the tissue birefringence maps as a measure of the tissue anisotropy. Selected two-photon microscopy is also performed to better understand the compositional origins of the obtained anisotropy results. The dome region of the bladder shows maximum birefringence when the bladder is distended to high pressures, whereas the ventral remains roughly isotropic during distension. In addition, the average anisotropy direction is longitudinal, along the urethra to dome. The derived wall anisotropy trends are based on birefringence as an intrinsic property of the tissue organization independent of its thickness, to aid in understanding the structure-functions relation in healthy bladders. These new insights into the wall microstructure of ex vivo distending bladders may help improve the functionality of the artificially engineered bladder tissues.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.311
Teacher spread0.295 · 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

Citations18
Published2012
Admission routes1
Has abstractyes

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