Inflammation Caused by Nanosized Delivery Systems: Is There a Benefit?
Bibliographic record
Abstract
Secondary macrophage cytotoxicity induced by nanoparticles was described before. The study aim was to investigate the role of secondary cytotoxic effect in a macrophage-lung cancer coculture model after nanoparticle treatment in the presence and absence of anti-inflammatory drugs. An in vitro coculture model composed of confluent alveolar macrophage MH-S and A-549 lung cancer cells separated by a 0.4 μm porous membrane was used in the study. Macrophages were treated with two sizes of gelatin nanoparticles and two sizes of poly(isobutyl cyanoacrylate) (PIBCA) nanoparticles, with and without doxorubicin as a chemotherapeutic drug. The treatment effect with and without the presence of anti-inflammatory drug was studied using an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. The model drugs were ibuprofen, celecoxib, prednisolone, dexamethasone, and methotrexate. Different nanoparticles in different sizes were synthesized with a range of physicochemical characteristics. Doxorubicin loaded nanoparticles were prepared with an entrapment efficiency of 82-83% for PIBCA and 39-42% for gelatin. Nanoparticle treatment of macrophages showed a secondary cytotoxic effect on A-549 cancer cells at 24 and 36 h, with a drop in cell viability of 40-62%. However, this effect was significantly reduced to 10-48% if the macrophages were exposed to anti-inflammatory drugs. When ibuprofen and celecoxib were used the cell viability rebounded between 24 and 36 h. For prednisolone, dexamethasone, and methotrexate the cell viability dropped further between 24 and 36 h. Macrophages exposed to nanoparticles show secondary cytotoxicity, which has a significant antitumor effect in the microclimate of the coculture model. The beneficial nanoparticle treatment effect was significantly reduced if nonsteroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, or methotrexate was given at the same time. The data suggest that anti-inflammatory treatments can decrease the carrier-induced macrophage cytotoxicity and its antitumor effectiveness with chemotherapy.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".