Evaluation of purified natural killer cell functions in familial hemophagocytic lymphohistiocytosis
Bibliographic record
Abstract
Background: Familial hemophagocytic lymphohistiocytosis (FHL) is a rare, genetic, immune dysregulation disorder of aberrant hyperactivation of lymphocytes causing inflammation and hemophagocytosis. We report on a 3-month old male who was evaluated for the possibility of FHL because of a positive family history. The patient was asymptomatic; however, levels of the soluble interleukin 2 (IL-2) receptor were elevated and the quantity and function of the natural killer (NK) cells were severely decreased. Methods: Purification of NK cells and evaluation of the cytotoxicity and IFNγ/TNFα secretion of NK cells after IL-2 activation relative to the patient's family members. Results: The patient's NK specific lysis was enhanced compared with his mother, and it was slightly higher than his sister. The IFNγ and TNFα secretion by the patient's NK cells after challenge with target 721 cells or anti-natural cytotoxicity receptors (NKp30 and NKp44) antibodies showed levels that are close to the mother's and sister's NK secretion levels. Owing to a low yield of NK cells from the patient's father the results for his NK cells are incomplete. The patient did not undergo HSCT and continued to be followed. He is now 7 years old and thriving without signs of FHL. His last examination was in August 2012 for functionality of isolated NK cells. The results showed normal cytotoxicity, cytokine secretion, and CD107a up-regulation to the NK cell surface. Conclusion: We propose that NK function assessment in patients with presumed FHL should be performed on isolated NK cell populations. This practice may reduce the number of false-negative results in NK function assays. Statement of novelty: In this case report we show that functional assessment of unpurified NK cells could lead to a false-negative assessment in 1 of the parameters in FHL. Assessment of NK function without NK purification may lead to an erroneous diagnosis of poor NK function.
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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) | 0.001 | 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".