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Record W4306755851 · doi:10.1038/s41522-022-00347-3

Filamentous fungal biofilms: Conserved and unique aspects of extracellular matrix composition, mechanisms of drug resistance and regulatory networks in Aspergillus fumigatus

2022· review· en· W4306755851 on OpenAlexaff
Shuai Liu, François Le Mauff, Donald C. Sheppard, Shizhu Zhang

Bibliographic record

Venuenpj Biofilms and Microbiomes · 2022
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsMcGill UniversityInstitute of Infection and ImmunityMcGill University Health Centre
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsNational Natural Science Foundation of China
KeywordsBiofilmAspergillus fumigatusMicrobiologyExtracellular matrixBiologyDrug resistanceCell biologyBacteriaGenetics

Abstract

fetched live from OpenAlex

The filamentous fungus Aspergillus fumigatus is an ubiquitous mold that can cause invasive pulmonary infections in immunocompromised patients. Within the lung, A. fumigatus forms biofilms that can enhance resistance to antifungals and immune defenses, highlighting the importance of defining the mechanisms underlying biofilm development and associated emergent properties. A. fumigatus biofilms display a morphology and architecture that is distinct from bacterial and yeast biofilms. Moreover, A. fumigatus biofilms display unique characteristics in the composition of their extracellular matrix (ECM) and the regulatory networks governing biofilm formation. This review will discuss our current understanding of the form and function of A. fumigatus biofilms, including the unique components of ECM matrix, potential drug resistance mechanisms, the regulatory networks governing A. fumigatus biofilm formation, and potential therapeutics targeting these structures.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.016
GPT teacher head0.273
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations65
Published2022
Admission routes1
Has abstractyes

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