Evidence that a neutrophil–keratinocyte crosstalk is an early target of <scp>IL</scp>‐17A inhibition in psoriasis
Bibliographic record
Abstract
The response of psoriasis to antibodies targeting the interleukin (IL)-23/IL-17A pathway suggests a prominent role of T-helper type-17 (Th17) cells in this disease. We examined the clinical and immunological response patterns of 100 subjects with moderate-to-severe psoriasis receiving 3 different intravenous dosing regimens of the anti-IL-17A antibody secukinumab (1 × 3 mg/kg or 1 × 10 mg/kg on Day 1, or 3 × 10 mg/kg on Days 1, 15 and 29) or placebo in a phase 2 trial. Baseline biopsies revealed typical features of active psoriasis, including epidermal accumulation of neutrophils and formation of microabscesses in >60% of cases. Neutrophils were the numerically largest fraction of infiltrating cells containing IL-17 and may store the cytokine preformed, as IL-17A mRNA was not detectable in neutrophils isolated from active plaques. Significant clinical responses to secukinumab were observed 2 weeks after a single infusion, associated with extensive clearance of cutaneous neutrophils parallel to the normalization of keratinocyte abnormalities and reduction of IL-17-inducible neutrophil chemoattractants (e.g. CXCL1, CXCL8); effects on numbers of T cells and CD11c-positive dendritic cells were more delayed. Histological and immunological improvements were generally dose dependent and not observed in the placebo group. In the lowest-dose group, a recurrence of neutrophils was seen in some subjects at Week 12; these subjects relapsed faster than those without microabscesses. Our findings are indicative of a neutrophil-keratinocyte axis in psoriasis that may involve neutrophil-derived IL-17 and is an early target of IL-17A-directed therapies such as secukinumab.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".