An automated approach to high-plex cytometric immunophenotyping with CyTOF XT
Bibliographic record
Abstract
Abstract CyTOF® mass cytometry is a single-cell analysis platform that uses isotope-tagged antibodies to resolve 50-plus markers in a single tube without signal compensation, making CyTOF ideal for routine immunophenotyping. CyTOF XT™, the latest CyTOF system, features automated sample acquisition. Stained samples were acquired in parallel using the automated CyTOF XT system and manually, using the Helios™ system, to assess performance of the automated system. Multiple suspension mass cytometry staining workflows were evaluated. Population frequencies and resolution indices for markers were assessed by manual gating. There was no significant difference between population frequencies analyzed between the two CyTOF systems. On average, samples acquired on CyTOF XT resulted in greater resolution between positive and negative populations compared to Helios. The Maxpar® Direct™ Immune Profiling System, which comprises the Maxpar® Direct™ Immune Profiling Assay™ and Maxpar Pathsetter™ software, was also compared on the CyTOF XT and Helios systems. The Maxpar Direct Immune Profiling Assay includes a 30-marker panel in a dry, single-tube format for staining human whole blood or PBMC. Maxpar Pathsetter automates reporting of population statistics and stain assessments for the panel. Maxpar Pathsetter showed comparable population frequencies between the two CyTOF systems and improved staining assessment on CyTOF XT. Overall, these studies find that the CyTOF XT system generates better signal resolution than the Helios system. Automated acquisition by CyTOF XT enables researchers to accurately and reproducibly streamline human immunophenotyping. For Research Use Only. Not for use in diagnostic procedures.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".