Single‐cell RNA analysis: Guiding the treatment of DiHS/DRESS
Bibliographic record
Abstract
Drug‐induced hypersensitivity syndrome (DiHS)—also termed as drug reaction with eosinophilia and systemic symptoms (DRESS)—is a potentially lethal inflammatory disease associated with human herpesvirus (HHV) reactivation. DiHS/DRESS is classified within a group of syndromes named severe cutaneous adverse reactions (SCARs), including acute generalized exanthematous pustulosis and Stevens‐Johnson syndrome/toxic epidermal necrolysis. SCARs are delayed type IV hypersensitivity reactions mainly characterized by T‐cell activation. The most commonly encountered dermatological manifestation of DRESS is an erythematous morbilliform rash, sometimes complicated by vesicles, bullae, atypical targetoid plaques, purpura, or sterile small pustules, or even progress to exfoliative dermatitis or erythroderma. The pathophysiology of DRESS is still poorly understood.1 The proposed mechanisms implicated in its pathogenesis include drug detoxification enzyme abnormalities, sequential reactivation of herpesviruses (cytomegalovirus, Epstein‐Barr virus, HHV‐6 and ‐7), and genetic predisposition related to certain human leukocyte antigen alleles. The limited knowledge of the mechanisms and pathways underlying the pathology of DRESS present an important treatment hurdle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".