The polymicrobial nature of airway infections in cystic fibrosis: Cangene Gold Medal LectureThis article is based on a presentation by Dr. Christopher Sibley at the 60th Annual Meeting of the Canadian Society of Microbiologists in Hamilton, Ontario, on 15 June 2010. Dr. Sibley was the recipient of the 2010 Cangene Gold Medal as the Canadian Graduate Student Microbiologist of the Year, an annual award sponsored by Cangene Corporation intended to recognize excellence in graduate research.
Bibliographic record
Abstract
Microbial communities characterize the airways of cystic fibrosis (CF) patients. Members of these diverse and dynamic communities can be thought of as pathogens, benign commensals, or synergens--organisms not considered pathogens in the traditional sense but with the capacity to alter the pathogenesis of the community through microbe-microbe or polymicrobe-host interactions. Very few bacterial pathogens have been implicated as clinically relevant in CF; however, the CF airway microbiome can be a reservoir of previously unrecognized but clinically relevant organisms. A combination of culture-dependent and culture-independent approaches provides a more comprehensive perspective of CF microbiology than either approach alone. Here we review these concepts, highlight the future challenges for CF microbiology, and discuss the implications for the management of CF airway infections. We suggest that the success of treatment interventions for chronic CF lung disease will rely on the context of the microbes within microbial communities. The microbiology of CF airways may serve as a model to investigate the emergent properties of other clinically relevant microbial communities in the human body.
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 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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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".