Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response
Bibliographic record
Abstract
Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric asthma treatment response revealed by different omic approaches conducted in 2018-2019. A total of 13 studies were performed during this period to assess the role of genomics, epigenomics, transcriptomics, metabolomics, and the microbiome in the response to short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. These studies have identified novel associations of genetic markers, epigenetic modifications, metabolites, bacteria, and molecular mechanisms involved in asthma treatment response. This knowledge will allow us establishing molecular biomarkers that could be integrated with clinical information to improve the management of children with 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".