Pneumonia treatment by photodynamic therapy with extracorporeal illumination ‐ an experimental model
Bibliographic record
Abstract
Abstract Infectious pneumonia is a major cause of morbidity/mortality, mainly because of the increasing rate of microorganisms resistant to antibiotics. Photodynamic Therapy (PDT) is emerging as a promising approach, as effects are based on oxidative stress, preventing microorganism resistance. In two previous studies, the in vitro inactivation of Streptococcus pneumoniae using indocyanine green (ICG) and infrared light source was a success killing 5 log 10 colony‐forming units (CFU/mL) with only 10 μ mol/L ICG. In this work, a proof‐of‐principle protocol was designed to treat lung infections by PDT using extracorporeal illumination with a 780 nm laser device and also ICG as photosensitizer. Hairless mice were infected with S. pneumoniae and PDT was performed two days after infection. For control groups, CFU recovery ranged between 10 3 –10 4 /mouse. For PDT group, however, no bacteria were recovered in 80% of the animals. Based on this result, animal survival was evaluated separately over 50 days. No deaths occurred in PDT group, whereas 60% of the control group died. Our results indicate that extracorporeal PDT has the potential for pneumonia treatment, and pulmonary decontamination with PDT may be used as a single therapy or as an antibiotics adjuvant.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".