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Record W1997007505 · doi:10.1117/1.jbo.19.9.090901

Multiphoton microscopy in defining liver function

2014· review· en· W1997007505 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Biomedical Optics · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of Manitoba
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsAutofluorescenceMicroscopyFluorescence microscopeMultiphoton fluorescence microscopeTwo-photon excitation microscopyFluorescence-lifetime imaging microscopyFluorescenceBiophysicsPathologyChemistryIn vivoMedicineBiologyOptics

Abstract

fetched live from OpenAlex

Multiphoton microscopy is the preferred method when in vivo deep-tissue imaging is required. This review presents the application of multiphoton microscopy in defining liver function. In particular, multiphoton microscopy is useful in imaging intracellular events, such as mitochondrial depolarization and cellular metabolism in terms of NAD(P)H changes with fluorescence lifetime imaging microscopy. The morphology of hepatocytes can be visualized without exogenously administered fluorescent dyes by utilizing their autofluorescence and second harmonic generation signal of collagen, which is useful in diagnosing liver disease. More specific imaging, such as studying drug transport in normal and diseased livers are achievable, but require exogenously administered fluorescent dyes. If these techniques can be translated into clinical use to assess liver function, it would greatly improve early diagnosis of organ viability, fibrosis, and cancer.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.343
Teacher spread0.328 · 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