Genetics of Allergic Asthma and Current Perspectives on Therapeutic Management
Bibliographic record
Abstract
Globally, more than 300 million people are asthmatics and this number has been estimated to become 400 million by 2025. Asthma is a chronic inflammatory condition, which, although has no cure, is treatable in most patients. The most common structural alterations in asthmatic airways include thickening of the epithelial and sub epithelial layers, increased airway smooth muscle mass, and angiogenesis. Several genetically controlled factors greatly influence the predisposition and severity of allergic asthma. Twin studies have attributed as much as 75% of asthma susceptibility to heredity. Particularly, genome-wide association studies (GWASs) have discovered several asthma and/or atopy susceptibility genes. Current treatment protocols for managing asthma involve the use of corticosteroids and β-agonists. Over the last 40 years, there has been a marked development-targeted therapy for asthma, such as anti-leukotrienes, anti-immunoglobulin (Ig)E, anti-tumor necrosis factor (TNF)-α, and anti-interleukins (ILs) (Th2 cytokines). To identify novel targets and to develop newer drug generations, better understanding of asthma molecular pathophysiology is required. Furthermore, the pharmacogenetic studies, focusing on better understanding of beneficial or/and adverse effects to anti-asthma drugs, will also facilitate the development of more effective and targeted treatments in specific subpopulations of patients suffering from asthma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".