Strategies for overcoming the lung surfactant barrier and achieving success in antimicrobial photodynamic therapy
Bibliographic record
Abstract
• Overcoming the pulmonary surfactant barrier using Gantrez™ AN-139 copolymers as a carrier for indocyanine green. • High biocompatibility of Gantrez AN-139 in human lung cell lines. • Potential for minimally invasive treatment of pneumonia with photodynamic action using external infrared thoracic illumination. The impressive increase in antimicrobial resistance has required the development of alternative treatments that act on multiple non-specific molecular targets and are effective against a broad range of microorganisms. Antimicrobial Photodynamic Therapy (aPDT) is based on microbial inactivation from oxidative stress and represents an important tool for inactivating microorganisms with low risk of resistance selection. Therefore, our research group has been devoted to demonstrating its effectiveness against pathogens that cause pneumonia, one of the most lethal infections worldwide. Previous studies reported the efficiency and safety of an in vitro photoinactivation protocol for Streptococcus pneumoniae and the delivery of infrared light (external illumination) and photosensitizer (PS) in an animal model. However, the in vivo inactivation of microorganisms still poses challenges due to the presence of lung surfactant (LS), which traps PSs, preventing them from reaching the microbial target. This study investigated different approaches such as use of emulsifiers, perfluorocarbon, oxygen nanobubbles, and copolymer towards overcoming LS and optimizing aPDT response. The most promising strategy consisted in combining indocyanine green (ICG) with Gantrez TM AN-139 - a Polyvinyl Methyl Ether/Maleic Anhydride copolymer (PVM/MA) – showing high microbial inactivation and safety for human lung epithelial (A549) and fibroblast (MRC-9) cell lines. The in vitro experiments provided an alternative to overcome the limited PS distribution through LS and will serve as the basis for in vivo studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".