Development of a simple model for studying the effects of antifungal agents on multicellular communities of Aspergillus fumigatus
Bibliographic record
Abstract
Aspergillus fumigatus is an increasingly prevalent opportunistic fungal pathogen of various immunocompromised individuals. It has the ability to form filaments within the lungs, producing dense intertwined mycelial balls, which are difficult to treat. The aim of this study was to develop a suitable model of A. fumigatus to examine the effects of antifungal challenge on these intertwined filamentous communities. A. fumigatus NCPF 7367 growth conditions were optimized on both Thermanox coverslips and on flat-bottomed microtitre plates to establish optimal conidial seeding densities. Isolates were treated with itraconazole, voriconazole, amphotericin B and caspofungin and their overall killing efficiency was measured using an XTT formazan metabolic dye assay. This was compared with the CLSI (formerly NCCLS) methodology of broth microdilution of moulds (standard M38-A). It was shown that 1x10(5) conidia ml(-1) in RPMI 1640 was the optimum concentration of spores for biofilm formation. Filamentous growth characteristics were not observed until 10 h incubation, followed by an exponential increase in the biofilm biomass (hyphae and extracellular material) and cellular activity (metabolism). When susceptibility testing of biofilms was compared with that of planktonic cells by CLSI broth microdilution testing, all antifungal drugs were at least 1000 times less effective at reducing the overall metabolic activity of 90 % of the cells. Overall, this study showed that A. fumigatus has the ability to form coherent multicellular biofilm structures that are resistant to the effects of antifungal drugs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".