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Record W2081784640 · doi:10.1159/000237295

Immunophenotypic Analysis of HL-60 Cells during Basophilic Differentiation

2009· article· en· W2081784640 on OpenAlexaff
Dennis A. Wong, Peter Valent, Peter Bettelheim, Jan Switzer, Judah A. Denburg

Bibliographic record

VenueInternational Archives of Allergy and Immunology · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCD15BiologyBasophilicImmunophenotypingPopulationIntegrin alpha MCluster of differentiationFlow cytometryCellular differentiationCD14ImmunologyMyeloidCell biologyPathologyCellCD34MedicineGeneticsStem cell

Abstract

fetched live from OpenAlex

Differentiation along specific myeloid lineages may be accompanied by characteristic cell surface marker changes. We have examined leukemic HL-60 cell changes under conditions which induce basophilic differentiation. An increased surface expression of CD35, CD11b, and decreased expression of CD15 was found by flow cytometry during the 5-day induction period. Further investigation revealed two cell populations after 5 days in vitro: (i) a CD35-positive population (61% of cells present) containing a significant number of CD15-negative cells, and (ii) a CD15-positive/CD35-negative population. The CD35-positive subset appears to account for the majority of the basophilic cells induced under these conditions, as measured by histamine content and metachromatic staining. In addition, this subset contains a small number of early monocytic cells (CD14 and CD23 positive). The expression of CD11b is variably found on the CD15-positive/ CD35-negative subset of induced cells. These results suggest that CD35 and CD15 surface immunophenotyping can be used to map steps involved in myeloid development. A role for CD35 and CD15 in early basophil differentiation is proposed.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2009
Admission routes1
Has abstractyes

Explore more

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