Effect of liposomal confinement on photochemical properties of photosensitizers with varying hydrophilicity
Bibliographic record
Abstract
Preferential tumor localization and the aggregation state of photosensitizers (PSs) can depend on the hydrophilic/hydrophobic nature of the molecule and affect their phototoxicity. In this study, three PSs of different hydrophilicity are introduced in liposomes to understand the structure-photochemistry relationship of PSs in this cellular model system. Absorbance and fluorescence spectra of amphiphilic aluminum (III) phthalocyanine disulfonate chloride adjacent isomer (Al-2), hydrophilic aluminum (III) phthalocyanine chloride tetrasulfonic acid (Al-4), and lipophilic 2-(1-hexyloxyethyl)-2-devinyl pyropheophorbide (HPPH) are compared in a liposomal confined state with free PS in bulk solution. For fluorescence measurements, a broad range of concentrations of both bulk and liposomal confined PSs are examined to track the transition from monomers to dimers or higher order aggregates. Epifluorescence microscopy, absorbance, and fluorescence measurements all confirm different localization of the PSs in liposomes, depending on their hydrophilicity. In turn, the localization affects the aggregation of molecules inside the liposome cell model. Data obtained with such cellular models could be useful in optimizing the photochemical properties of photosensitizing drugs based on their structure-dependent interactions with cellular media and subcellular organelles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".