The nature of innate and adaptive interleukin‐17A responses in sham or bacterial inoculation
Bibliographic record
Abstract
Streptococcus pyogenes is the causative agent of numerous diseases ranging from benign infections (pharyngitis and impetigo) to severe infections associated with high mortality (necrotizing fasciitis and bacterial sepsis). As with other bacterial infections, there is considerable interest in characterizing the contribution of interleukin-17A (IL-17A) responses to protective immunity. We here show significant il17a up-regulation by quantitative real-time PCR in secondary lymphoid organs, correlating with increased protein levels in the serum within a short time of S. pyogenes infection. However, our data offer an important caveat to studies of IL-17A responsiveness following antigen inoculation, because enhanced levels of IL-17A were also detected in the serum of sham-infected mice, indicating that inoculation trauma alone can stimulate the production of this cytokine. This highlights the potency and speed of innate IL-17A immune responses after inoculation and the importance of proper and appropriate controls in comparative analysis of immune responses observed during microbial infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".