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Record W2093190068 · doi:10.1021/la7008573

Fluorescence of Amphotericin B-Deoxycholate (Fungizone) Monomers and Aggregates and the Effect of Heat-Treatment

2007· article· en· W2093190068 on OpenAlexaff
Robin Stoodley, Kishor M. Wasan, Dan Bizzotto

Bibliographic record

VenueLangmuir · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistrySodium dodecyl sulfateFluorescenceDimerMonomerPulmonary surfactantPhotochemistryEmission spectrumAnalytical Chemistry (journal)Spectral lineChromatographyOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Fluorescence excitation and emission spectra are reported for the polyene macrolide antifungal agent Amphotericin B formulated as micellar dispersion Fungizone (FZ) and its modified counterpart heat-treated Fungizone. The addition of sodium dodecyl sulfate or sodium deoxycholate surfactant to modulate the aggregation state of Amphotericin B confirms that the monomer and dimer states have different fluorescence spectra. Energy transfer from excited dimer to monomer is observed. Both FZ and heat-treated FZ (HTFZ) show expected S1 --> S0 fluorescence emission as well as anti-Kasha fluorescence emission from the S2 state. The excitation and S1 --> S0 emission spectra of HTFZ are similar to those of FZ, while the S2 --> S0 fluorescence differs in intensity between them. The variation in the rate constant for internal conversion from S2 to S1 as the surfactant concentration is increased differs for FZ and HTFZ; we propose that this may form a new basis for examining the super-aggregated character of AmB preparations. FZ and HTFZ have a similar stability to disaggregation by added sodium dodecyl sulfate surfactant. These findings provide the groundwork for future fluorescence characterization of FZ or HTFZ interactions with cell membranes.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.199
Teacher spread0.194 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

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