Impaired surface marker expression in stimulated Epstein-Barr virus transformed lymphoblasts from Barth Syndrome patients
Bibliographic record
Abstract
Primary B lymphocytes rapidly respond to lipopolysaccharide (LPS) and cytosine linked to a guanine by a phosphate bond deoxyribonucleic acid (CpG DNA) stimulation to promote adaptive immune function through increased surface marker expression. Here we examined expression of surface markers in LPS and CpG DNA stimulated Epstein-Barr virus transformed B lymphoblasts from control and BTHS patients with different mutations. The percentage of cluster of differentiation (CD) positive cells including CD38 + , CD138 + , CD80 + surface expression and programmed cell death protein 1 (PD1 +) surface expression was similar between control and BTHS lymphoblasts incubated plus or minus LPS. The percentage of CD24 + , CD38 + and CD138 + cells was similar between control and BTHS lymphoblasts incubated plus or minus CpG DNA. CD27 + surface marker expression was reduced in both BTHS lymphoblasts and controls incubated with CpG DNA and PD1 + surface marker expression was higher in BTHS cells compared to controls but was unaltered by CpG DNA treatment. Thus, Epstein-Barr virus transformed control and BTHS lymphoblasts fail to increase selected surface markers upon stimulation with LPS and exhibit variable surface marker expression upon stimulation with CpG DNA. Since B lymphocyte surface marker expression upon activation is involved in B cell proliferation and differentiation, cell-cell interaction and the adaptive immune response, we suggest that caution should be exercised when interpreting immunological data obtained from Epstein-Barr virus transformed BTHS cells. Based upon our observations in control cells, our conclusions may be more broadly applicable to other diseases which utilize transformed B lymphocytes for the study of immune biology.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".