Bibliographic record
Abstract
Asthma is characterized by chronic inflammation of the airways in which there is an overabundance of eosinophils, mast cells, and activated T helper lymphocytes. These inflammatory cells release mediators that then trigger bronchoconstriction, mucus secretion, and remodeling. The inflammatory mediators that drive this process include cytokines, chemokines, growth factors, lipid mediators, immunoglobulins, and histamine. The inflammation in allergic asthma can be difficult to control. This is mainly due to the development of an adaptive immunity to an allergen, leading to immunological memory. This leads to recall reactions to the allergen, causing persistent inflammation and damage to the airways. Generally, in asthma inflammation is directed by Th2 cytokines, which can act by positive feedback mechanisms to promote the production of more inflammatory mediators including other cytokines and chemokines. This review discusses the role of cytokines and chemokines in the immunobiology of asthma and attempts to relate their expression to morphological and functional abnormalities in the lungs of asthmatic subjects. We also discuss new concepts in asthma immunology, in particular the role of cytokines in airway remodeling and the interaction between cytokines and infection.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".