McKay agar enables routine quantification of the ‘Streptococcus milleri’ group in cystic fibrosis patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 'Streptococcus milleri' group (SMG) has recently been recognized as a contributor to bronchopulmonary disease in cystic fibrosis (CF). Routine detection and quantification is limited by current CF microbiology protocols. McKay agar was developed previously for the semi-selective isolation of this group. Here, McKay agar was validated against a panel of clinical SMG isolates, which revealed improved SMG recovery compared with Columbia blood agar. The effectiveness of this medium was evaluated by appending it to the standard CF sputum microbiology protocols in a clinical laboratory for a 6-month period. All unique colony types were isolated and identified by 16S rRNA gene sequencing. Whilst a wide variety of organisms were isolated, members of the SMG were the most prevalent bacteria cultured, and McKay agar allowed routine quantification of the SMG from 10(3) to >10(8) c.f.u. ml(-1) directly from sputum. All members of the SMG were detected [Streptococcus anginosus (40.7 %), Streptococcus intermedius (34.3 %) and Streptococcus constellatus (25 %)] with an overall prevalence rate of 40.6 % in our adult CF population. Without exception, samples where SMG isolates were cultured at 10(7) c.f.u. ml(-1) or greater were associated with pulmonary exacerbations. This study demonstrates that McKay agar can be used routinely to quantify the SMG from complex clinical samples.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it