Neutrophil extracellular traps, B cells, and type I interferons contribute to immune dysregulation in hidradenitis suppurativa
Bibliographic record
Abstract
Hidradenitis suppurativa (HS), also known as acne inversa, is an incapacitating skin disorder of unknown etiology manifested as abscess-like nodules and boils resulting in fistulas and tissue scarring as it progresses. Given that neutrophils are the predominant leukocyte infiltrate in HS lesions, the role of neutrophil extracellular traps (NETs) in the induction of local and systemic immune dysregulation in this disease was examined. Immunofluorescence microscopy was performed in HS lesions and detected the prominent presence of NETs. NET complexes correlated with disease severity, as measured by Hurley staging. Neutrophils from the peripheral blood of patients with HS peripheral also displayed enhanced spontaneous NET formation when compared to healthy control neutrophils. Sera from patients recognized antigens present in NETs and harbored increased antibodies reactive to citrullinated peptides. B cell dysregulation, as evidenced by elevated plasma cells and IgG, was observed in the circulation and skin from patients with HS. Peptidylarginine deiminases (PADs) 1 to 4, enzymes involved in citrullination, were differentially expressed in HS skin, when compared to controls, in association with enhanced tissue citrullination. NETs in HS skin coexisted with plasmacytoid dendritic cells, in association with a type I interferon (IFN) gene signature. Enhanced NET formation and immune responses to neutrophil and NET-related antigens may promote immune dysregulation and contribute to inflammation. This, along with evidence of up-regulation of the type I IFN pathway in HS skin, suggests that the innate immune system may play important pathogenic roles in this disease.
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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 | 0.001 | 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".