T cell unresponsiveness in a pediatric cystic fibrosis patient: a case report
Bibliographic record
Abstract
A girl was diagnosed with cystic fibrosis (CF) at birth, with repeatedly positive sweat tests and homozygous F508del mutations of her CF transmembrane conductance regulator (CFTR) gene. From an early age, her lung disease was more severe than her birth cohort peers despite aggressive treatment. At the age of 16 she was listed for lung transplantation, but prior to transplant was not on systemic corticosteroids or other immunosuppressive agents. In response to ex vivo stimulation, her pre-transplant peripheral blood T cells unexpectedly failed to produce detectable levels of IFN-γ, unlike cells from healthy controls or from another girl with CF and lung disease of comparable severity. Furthermore, naïve T cells freshly isolated from her peripheral blood showed a complete block of T cell differentiation into Th1, Th17 and Treg lineages, even in the presence of cytokines known to promote differentiation into the respective lineages. Her serology has been remarkably devoid of evidence of exposure to viruses that have been associated with T cell exhaustion. However, her freshly isolated naïve T cells showed sustained expression of markers of T cell exhaustion, which were further induced upon ex vivo stimulation, pointing to T cell exhaustion as the cause of the failure of naïve T cells to undergo differentiation in response to cytokine stimulation. Although excessive inflammation in CF lung can be both ineffective at clearing certain pathogens as well as destructive to the lung tissue itself, adequate inflammation is a component of an effective overall immune response to microbial pathogens. Our present findings suggest that intrinsic impairment of T cell differentiation may have contributed to the greater severity and more rapid progression of her CF lung disease than of the lung disease of most of her peers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".