An Efficient and Simple Method to Establish NK and T Cell Lines from Patients with Chronic Active Epstein-Barr Virus Infection
Bibliographic record
Abstract
A number of methods have been described to establish NK/T cell lines from patients with lymphoma or lymphoproliferative syndrome. These methods employed feeder cells, purified NK or T cells with as much as 10 mL of blood, or a high-dose of IL-2. This study presents a new method with a powerful and simple strategy to establish NK and T cell lines by culturing the peripheral blood mononuclear cells (PBMC) with the addition of recombinant human IL-2 (rhIL-2), and uses as little as 2 mL of whole blood. The cells can proliferate quickly in two weeks and be maintained for more than 3 months. With this method, 7 NK or T cell lines have been established with a high success rate. This method is simple, reliable, and applicable to establishing cell lines from more cases of CAEBV or NK/T cell lymphoma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".