Ten‐color 15‐antibody flow cytometry panel for immunophenotyping of lymphocyte population
Bibliographic record
Abstract
Summary We have developed a lymphoproliferative disorder screening tube (LPD‐ST) with the aim to provide comprehensive immunophenotyping of lymphocyte subsets with minimal need for additional testing. The LPD‐ST consists of CD4/kappa FITC, CD8/lambda PE, CD3/CD14ECD, CD38PC5.5, CD20/CD56PC7, CD10APC, CD19APC‐A700, CD5APC‐A750, CD57/CD23PB and CD45KO. The LPD‐ST was validated against previously used lymphocyte subset panels in Canada (n=60) and in Sweden (n=43) and against the OneFlow™ LST (n=60). The LPD‐ST panel was then implemented in clinical practice using dried monoclonal antibody reagents (Duraclone®) on 649 patient samples in Sweden. In 204 of 649 samples (31%), a monotypic B‐cell population was found. Of these cases, a final diagnosis could be rendered in 106 cases (52%), and in the remainder, additional B‐cell immunophenotyping was performed. In 20 (3%) samples, an aberrant T‐cell population was confirmed by additional testing. Of 425 samples diagnosed as normal/reactive lymphoid tissue, 50 (12%) required additional immunophenotyping, mostly due to an abnormal CD4/CD8 ratio. The LPD‐ST tube significantly minimizes the need for additional testing, improves the turn‐around time, and reduces the cost of LPD immunophenotyping. It is also suitable for investigating paucicellular samples such as cerebrospinal fluid or fine needle aspirates.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".