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Simplified quantitation of myeloid dendritic cells in peripheral blood using flow cytometry

2000· article· en· W1997681881 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCytometry · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsMcMaster University
FundersNational Health and Medical Research CouncilMedical Research CouncilMcMaster University
KeywordsMyeloidCD33Peripheral blood mononuclear cellDendritic cellFlow cytometryCD14ImmunologyBiologyLeukapheresisMolecular biologyAndrologyMedicineImmune systemCell biologyCD34Stem cellIn vitro

Abstract

fetched live from OpenAlex

BACKGROUND: Recognition of the importance of dendritic cells (DC) in the initiation of T-cell-dependent immune responses has led to increasing interest in methods for the identification of DC within the circulation. We sought to develop a flow cytometric method that would allow the reliable enumeration of absolute myeloid DC counts in minimally manipulated blood samples. METHODS: Myeloid DC were identified by three-color staining of whole blood leukocytes as a discrete population of mononuclear cells expressing high levels of HLA-DR and CD33, yet having little or no expression of CD14 and CD16. This method was analyzed for reproducibility and variation in blood DC number during typical clinical day hours and after exercise. The new method was compared to an established commercial kit method. RESULTS: FACS sorting of the CD33(+) DC showed that they morphologically resembled immature DC, and developed cytoplasmic projections typical of mature DC following overnight culture in granulocyte macrophage-colony stimulating factor (GM-CSF). Within peripheral blood, these DC were found at a mean concentration of 17. 4 +/- 5.4 x 10(6) per liter, corresponding to 0.93 +/- 0.27% of mononuclear cells. Comparison of duplicate samples stained and analyzed in parallel showed that the intrasample variability was very low, with an intraclass correlation coefficient of 0.95. The frequency of CD33(+) myeloid DC and their light scatter characteristics were similar to that of CD11c(+) myeloid cells. Four-color FACS analysis revealed complete identity of CD11c(hi), HLA-DR(+) DC with CD33(+), HLA-DR(+) DC. Only rare CD33(+) DC coexpressed CD123 and HLA-DR. Numbers of blood myeloid DC, identified by CD33 staining, showed no significant variation during standard laboratory hours. However, their numbers rose significantly during vigorous exercise, in parallel to other blood cells. CONCLUSIONS: The method described herein is rapid, reproducible, requires only small volumes of blood, can be readily used by a clinical immunology laboratory, and requires fewer antibodies than a currently available commercial method.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.017
GPT teacher head0.267
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it