Cytokine Therapeutics for Asthma: An Appraisal of Current Evidence and Future Prospects
Bibliographic record
Abstract
Although current pharmacopoeia is effective in alleviating asthma symptomatology, it is equally unable to modify the fundamental immunological basis of the allergic diathesis. The explosion in knowledge of the immunobiology of cytokines that has occurred in the last decade has remarkably clarified our understanding of the pathogenesis of allergic asthma, and has unleashed a plethora of compelling opportunities. In the first part of this review, we will summarize current knowledge on the pathogenesis of allergic asthma, with particular emphasis on relevant cytokine networks. This will position us to appraise critically initiatives in the search to modulate cytokine targets that are key to the expression of the allergic asthma phenotype. We will review the use of recombinant cytokines, soluble cytokine receptors, cytokine receptor antagonists and cytokine inhibitors, in pre-clinical and clinical development. Finally, we will assess the applicability of transgene-based modalities, including anti-sense oligonucleotide technology and gene therapy, as novel therapeutic strategies in the treatment of allergic asthma.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".