Targeting Intracellular Mycobacteria Using Nanosized Niosomes Loaded with Antibacterial Agents
Bibliographic record
Abstract
Background: Pathogenic intracellular mycobacteria are challenging to treat because of the waxy and complex cell wall characterizing the genus. Niosomes are vesicles with biomimetic cell membrane composition, which allow them to efficiently bind to the eukaryotic cells and deliver their cargo into the cytoplasm. The objective of this study was to develop a new platform based on niosomes loaded with antimicrobial agents to target intracellular mycobacteria. Nanoniosomes were fabricated and loaded with antibiotics and lignin–silver nanoparticles. The efficacy of these nanoniosomes was tested against the intracellular pathogen Mycobacterium abscessus used as a model of infection of human-derived macrophages (THP-1). The cytotoxicity and the immunological response of the agents were tested on THP-1 cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the secretion of pro- and anti-inflammatory cytokines, respectively. Results: M. abscessus was susceptible to the nanoniosomes in infected THP-1 macrophages, suggesting that the nanoniosomes were internalized due to their fusion to the macrophage cellular membrane. Moreover, nanoniosomes showed no upregulation of pro-inflammatory cytokines when exposed to THP-1 macrophages. Conclusions: Nanoniosomes improved drug efficacy while decreasing toxicity and should be considered for further testing in the treatment of intracellular pathogenic mycobacteria or as a new platform for precise intracellular delivery of drugs.
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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) | 0.001 | 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) | 0.012 | 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".