Relevance and implication of genetic determinants to asthma pathophysiology
Bibliographic record
Abstract
PURPOSE OF REVIEW: The number of single nucleotide polymorphisms (SNPs) found to be associated with asthma and related phenotypes outnumbers those with functional impacts. In this review we briefly described some of the approaches used to investigate functionality of SNPs, and summarized recent findings related to the characterization of functional SNPs in asthma. RECENT FINDINGS: For disease-associated SNPs residing in the promoter or 3' untranslated regions, differential protein binding affinity between the major and minor alleles is often the first logical area of investigation. In this review, we described SNPs associated with asthma or related phenotypes in five genes which in the past 12 months have new data implicating potential mechanisms in asthma development. SUMMARY: Variability in treatment responses poses a great challenge in asthma management. It is established that the genetic makeup of individuals plays a role in asthma development, yet the mechanisms remain unclear. Investigations on the functional impacts of disease-associated SNPs will help us gain insights into potential disease mechanisms, and ultimately lead to effective therapies for those who suffer from 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".