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Record W4249168186 · doi:10.1002/9780470027318.a0101m

Fluorescence Imaging

2000· other· en· W4249168186 on OpenAlexaff
Bram Ramjiawan, Michael Jackson, Henry H. Mantsch

Bibliographic record

VenueEncyclopedia of Analytical Chemistry · 2000
Typeother
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsNational Research Council Institute for Biodiagnostics
Fundersnot available
KeywordsIndocyanine greenFluorescenceAutofluorescenceFluorescence-lifetime imaging microscopyChromophoreChemistryBiomedical engineeringBiophysicsMaterials sciencePathologyMedicinePhotochemistryOpticsBiology

Abstract

fetched live from OpenAlex

Abstract A number of fluorescence imaging techniques show diagnostic promise. Imaging endogenous fluorescence has been proposed as a method for cancer diagnosis. Unfortunately, tissue autofluorescence is relatively weak and poor contrast between malignant and normal tissue is seen. Contrast may be enhanced with the addition of fluorescent materials that are selectively accumulated by malignant cells, such as fluoroscein or porphyrin derivatives. The limited penetration of light at the emission maxima of these materials restricts the use of fluorescence techniques utilizing these chromophores to superficial phenomena. However, many potential applications still exist. For example, monitoring fluorescence during surgery may allow resection margins to be clearly delineated. Other exogenous chromophores that may have may have diagnostic utility include indocyanine green (ICG). Techniques based upon visualization of the distribution of ICG fluorescence (i.e. choroidal angiography) are already prominent in ophthalmology. ICG fluorescence imaging may also find a useful niche in monitoring of burns and transplant tissue. In addition, monitoring of vascular parameters during cardiac surgery presents exciting opportunities. For example, low oxygen levels (e.g. during bypass surgery) in the heart can result in alterations in microvascular permeability. As ICG is largely bound to serum albumin, it should not be seen in extravascular spaces in normal hearts. However, increased permeability will allow albumin to diffuse into the extravascular spaces, and diffuse fluorescence across the surface of the heart will be seen. In principle, the infusion of polymers (e.g. dextrans) of various molecular weights labeled with dyes that fluoresce at various wavelengths will allow the assessment of the porosity of capillary beds in such systems. Immunofluorescence techniques have the potential to provide unmatched sensitivity and specificity. The unique nature of antibody–antigen interactions ensures specific delivery of the fluorophore to the site of interest. The specific interaction of labeled antibodies with antigens means that the fluorophore persists in the body for a prolonged period of time (days). Following a single injection of labeled antibody, repeated measurements on the same site over the course of hours or days allow kinetic information to be readily obtained. In principle, this means that the effect of therapeutic intervention, i.e. radiation therapy, chemotherapy, etc., can be monitored.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.078
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0780.066

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 head0.008
GPT teacher head0.288
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2000
Admission routes1
Has abstractyes

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