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Record W2027880619 · doi:10.1111/php.12256

Measurement of Intracellular Oxygen Concentration During Photodynamic Therapy <i>in vitro</i>

2014· article· en· W2027880619 on OpenAlexaff
Mark A. Weston, Michael S. Patterson

Bibliographic record

VenuePhotochemistry and Photobiology · 2014
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsPhotodynamic therapyIntracellularPhotosensitizerOxygenPhosphorescenceMonolayerPhotobleachingChemistrySinglet oxygenBiophysicsPhotochemistryFluorescenceBiochemistryOrganic chemistryBiologyOptics

Abstract

fetched live from OpenAlex

A technique is introduced that monitors the depletion of intracellular ground state oxygen concentration ([(3)O(2)]) during photodynamic therapy of Mat-LyLu cell monolayers and cell suspensions. The photosensitizer Pd(II) meso-tetra(4-carboxyphenyl)porphine (PdT790) is used to manipulate and indicate intracellular [(3)O(2)] in both of the in vitro models. The Stern-Volmer relationship for PdT790 phosphorescence was characterized in suspensions by flowing nitrogen over the suspension while short pulses of 405 nm light were used to excite the sensitizer. The bleaching of sensitizer and the oxygen consumption rate were also measured during continuous exposure of the cell suspension to the 405 nm laser. Photodynamic therapy (PDT) was conducted in both cell suspensions and in cell monolayers under different treatment conditions while the phosphorescence signal was acquired. The intracellular [(3)O(2)] during PDT was calculated by using the measured Stern-Volmer relationship and correcting for sensitizer photobleaching. In addition, the amount of oxygen that was consumed during the treatments was calculated. It was found that even at large oxygen consumption rates, cells remain well oxygenated during PDT of cell suspensions. For monolayer treatments, it was found that intracellular [(3)O(2)] is rapidly depleted over the course of PDT.

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)0.000
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 score0.007
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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