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Record W4407029913 · doi:10.3390/antiox14020176

Analysis of Singlet Oxygen Luminescence Generated By Protoporphyrin IX

2025· article· en· W4407029913 on OpenAlexaff
Vikas Vikas, Weibing Yang, Brian C. Wilson, Timothy C. Zhu, Robert H. Hadfield

Bibliographic record

VenueAntioxidants · 2025
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of Health
KeywordsSinglet oxygenProtoporphyrin IXLuminescencePhotochemistryChemistryOxygenMaterials scienceOptoelectronicsPhotodynamic therapyOrganic chemistry

Abstract

fetched live from OpenAlex

The effectiveness of photodynamic therapy (PDT) for cancer treatment relies on the generation of cytotoxic singlet oxygen (1O2) in type II PDT. Hence, monitoring of 1O2 generation during PDT enables optimal treatment delivery to the tumor target with reduced off-target effects. Direct 1O2 observation by measuring its luminescence at 1270 nm remains challenging due to the very weak signal. This study presents 1O2 luminescence measurements using a time-resolved singlet oxygen luminescence detection system (TSOLD) applied to protoporphyrin IX (PpIX) in different solvents (ethanol and acetone) and biological media (bovine serum albumin and agarose-based solid phantom). The compact experimental setup includes a nanosecond diode laser with a function generator, a cuvette with photosensitizer solution, optical filtering and mirrors, an InGaAs single-photon avalanche diode detector, and time-tagger electronics. Increasing the concentration of PpIX in these media from 1 to 10 µg/g resulted in a 3–5 × increase in the 1O2 luminescence signal. Furthermore, increasing light scattering in the sample using Intralipid from 0.1 to 1% led to a decrease in the 1O2 luminescence signal and lifetime. These results confirm the marked effect of the microenvironment on the 1O2 signal and, hence, on the photodynamic efficacy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.014
GPT teacher head0.322
Teacher spread0.308 · 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
Published2025
Admission routes1
Has abstractyes

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