Ultrastructural and SINS analysis of the cell wall integrity response of<i>Aspergillus nidulans</i>to the absence of galactofuranose
Bibliographic record
Abstract
With lethal opportunistic fungal infections on the rise, it is imperative to explore new methods to examine virulence mechanisms. The fungal cell wall is crucial for both the virulence and viability of Aspergillus nidulans. One wall component, Galf, has been shown to contribute to important fungal processes, integrity of the cell wall and pathogenesis. Here, we explore gene deletion strains lacking the penultimate enzyme in Galf biosynthesis (ugmAΔ) and the protein that transports Galf for incorporation into the cell wall (ugtAΔ). In applying gene deletion technology to the problem of cell wall integrity, we have employed multiple micro- and nano-scale imaging tools, including confocal fluorescence microscopy, electron microscopy, X-Ray fluorescence and atomic force microscopy. Atomic force microscopy allows quantification of ultrastructural cell wall architecture while near-field infrared spectroscopy provides spatially resolved chemical signatures, both at the nanoscale. Here, for the first time, we demonstrate correlative data collection with these two emerging modalities for the multiplexed in situ study of the nanoscale architecture and chemical composition of fungal cell walls.
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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) | 0.000 | 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 | 0.000 |
| 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".