Methods of sputum processing for cell counts, immunocytochemistry and<i>in situ</i>hybridisation
Bibliographic record
Abstract
Since the first attempts to use standardised methods for sampling induced airways sputum, two methods for processing the expectorate have evolved. The first involves selecting all viscid or denser portions from the expectorated sample with the aid of an inverted microscope. This method has been extensively evaluated and reported in detail. The second approach involves processing the entire expectorate, comprising sputum plus variable amounts of saliva. Recent modifications to this method include collecting saliva and sputum separately in order to reduce salivary contamination. Both methods have advantages and disadvantages. The advantages of using selected sputum are: squamous cell contamination is v5%, making cell counting easier and quicker to perform, the total cell count (TCC) can be expressed per gram of lower airway secretions, and concentrations of chemicals in the fluid phase are unaffected by the confounding influence of saliva, and can be accurately corrected for dilution. The disadvantage is that selection takes a few minutes longer to perform and requires an inverted microscope. The advantage of using the entire expectorate is that the technique is quicker to perform, but there are some disadvantages that require consideration. The expectorate contains a variable mixture of sputum plus saliva which maydilute the sputum and confound its analysis. The reproducibility of cell counts has been reported to be lower if squamous cell contamination represents w20% of all recovered cells. There is conflicting data as to whether or not differential cell counts (DCCs) differ between the two methods. One study reported a higher percentage of eosinophils in sputum processed by the selection method compared to the entire expectorate but this has not been confirmed in other studies. Although, both the selected sputum and the entire expectorate methods have the same ability to distinguish asthmatics or bronchitics from healthy subjects, they are not interchangeable, and, once a technique has been adopted for a given study, it should always be applied.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.011 |
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".