Progress and Challenges in the Understanding of Chronic Urticaria
Bibliographic record
Abstract
: Chronic urticaria is a skin disorder characterized by transient pruritic weals that recur from day to day for 6 weeks or more. It has a great impact on patients' quality of life. In spite of this prevalence and morbidity, we are only beginning to understand its physiopathology and we do not have a curative treatment. Moreover, a patient with chronic urticaria may undergo extensive laboratory evaluations seeking a cause only to be frustrated when none is found. In recent years there have been significant advances in our understanding of some of the molecular mechanisms responsible for hive formation. The presence and probable role of IgG autoantibodies directed against epitopes expressed on the alpha-chain of the IgE receptor and to lesser extent, to IgE in a subset of patients is generally acknowledged. These autoantibodies activate complement to release C5a, which augments histamine release, and IL4 and leukotriene C4 are released as well. A perivascular cellular infiltrate results without predominance of either Th1 or Th2 lymphocyte subpopulations. Basophils of all chronic urticaria patients (autoimmune or idiopathic) are hyperresponsive to serum, regardless of source, but poorly responsive to anti IgE. In this review we will summarize the recent contributions to this field and try to provide insights to possible future directions for research on 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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.008 | 0.023 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".