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Quantitative Flow Cytometric Assessment of CD36 (Platelet Glycoprotein IV) Expression on Monocytes and Platelets: Assay Development, Role in Plasmodium falciparum Risk Assessment, and Relationship to Sickle Hemoglobin.

2007· article· en· W2523233730 on OpenAlexaff
Christine Cserti‐Gazdewich, Songyi Xu, Robert Sutherland, R. Nayar, Marciano D. Reis, Michelle E. Dorn, Robert O. Quagliaroli, John D. Sullivan, Frederic I. Preffer, Sunny Dzik

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsPrincess Margaret Cancer CentreToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCD36Plasmodium falciparumImmunologyPlateletFlow cytometryBiologyMalariaCD14MedicineAndrologyReceptorBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background: CD36 (platelet glycoprotein IV) is a known binding site for red cells infected with Plasmodium falciparum (iRBC). The pathologic adhesion of iRBC to CD36 accounts for much of the endothelial sequestration and platelet rosetting observed. Deficient expression of CD36 is hypothesized to be another adaptation to P. falciparum malaria, because a 10-fold higher prevalence of deficiency (3–12%) exists in malaria-endemic areas. Purpose: A technique to quantitatively assess CD36 expression was developed for a future study on factors affecting P. falciparum malaria severity. In this pilot, CD36 levels were assessed in African-Americans (AA), non-African-Americans (non-AA), and a cohort of patients screened for sickle hemoglobin (HbS), in order to determine the prevalence and types of CD36 deficiency, and deficiency co-inheritance with HbS, a known malaria-adaptive mutation. Method: EDTA-anticoagulated blood was retrieved from clinical specimens. Antibody-conjugated fluorochromes (CD36-PE, CD14-FITC/− APC, CD61-PerCP, and CD54-FITC) were used. Effects of different assay conditions were investigated on samples from AA (N=57), non-AA (N=36), and those screened for HbS (N=27). FacsLyse lysis was used in the AA and non-AA subjects, but NH4Cl was selected in HbSS samples because of its unique ability to lyse otherwise lysisresistant sickle cells. After washing, samples were analysed by flow cytometry (FACSCalibur). Monocytes and platelets were identified by light-scatter and CD14- and CD61-expression respectively, and analyzed for CD36 at different storage times. Viability was assessed in 2 non-AA controls with 7-AAD. The median fluorescence intensity (MFI) of CD36 expression was log transformed. Results: Monocyte CD36 MFI follows a log-normal distribution: number tested mean SD *5% of AA were type I CD36-deficient (logMFI <1.5; MFI<32.) AA* 57 2.42 .45 non-AA 36 2.58 .22 HbS-pos 15 2.51 .35 HbS-neg 12 2.73 .28 Monocyte CD36 MFI at day 4 of room temperature storage was not significantly different from day 1 [N=28; mean MFI 96% of fresh, mean Δ = 65±241, p=NS, paired t-test], despite reduced monocyte viability and CD14 expression after 3 days. Results of platelet CD36 paralleled monocyte CD36. Platelet-monocyte aggregates gave spuriously high CD36, occurring commonly in citrated, heparinized, and ACD anticoagulants, but were rare in EDTA. Sample size was insufficient to detect an association between reduced CD36 and HbS+ (p=0.23, Fisher’s exact test). Conclusions: Flow cytometry using EDTA blood can quantify CD36 expression on monocytes and platelets. NH4Cl lysis is preferred for Hb SS specimens. Monocyte CD36 follows a log-normal distribution with 5% of AA deficient in CD36. Monocyte CD36 appears stable during room temperature storage for 4 days. This assay should be useful in studies of malaria and CD36-expression. Further work is required to assess if the reduced expression of CD36 is associated with adaptations to malaria.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.019
GPT teacher head0.309
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2007
Admission routes1
Has abstractyes

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