Glucocortiosteroid subsensitivity and asthma severity
Bibliographic record
Abstract
PURPOSE OF REVIEW: Glucocorticosteroids (GCSs) remain the cornerstone of therapy for treating the inflammatory component of asthma. Clinical response to GCS is heterogeneous, varying both within asthma 'endotypes', as well as the same individual. Different factors and micro-environment can alter the canonical GCS-induced signalling pathways leading to reduced efficacy, collectively termed as GCS subsensitivity, which includes the entire spectrum of steroid insensitivity and steroid resistance. RECENT FINDINGS: In the past, steroid subsensitivity has been associated with dysregulated expression of glucocorticoid-receptor isoforms, neutrophilic inflammation and Th17 cytokines, oxidative stress-inducing factors and their downstream effect on histone deacetylase activities and gene expression. The review highlights recent observations, such as GCS-induced dysregulation of key transcription factors involved in host defence, role of airway infections altering expression of critical regulatory elements like the noncoding microRNAs, and the importance of interleukin (IL)-10 in reinstating steroid response in key immune cells. Further, emerging concepts of autoimmunity triggered because of delayed resolution of eosinophilic inflammation (due to GCS subsensitivity) and observed lymphopenia (plausibly a side-effect of continued GCS use) are discussed. SUMMARY: This review bridges concepts that have been known, and those under current investigation, providing both molecular and clinical insights to aid therapeutic strategies for optimal management of asthmatics with varying degree of steroid subsensitivity and disease severity, with particular emphasis on the PI3 kinase pathways.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".