TSLPR deficiency attenuates AHR independently of eosinophilia and mucus secretion in a chronic HDM mouse model of allergic asthma
Bibliographic record
Abstract
BACKGROUND: Asthma is marked by chronic airway inflammation, immune dysregulation, and airway remodeling. While TSLP is known to influence allergic diseases like asthma, the role of TSLPR in airway remodeling is not well-defined. METHODS: Using TSLPR-deficient (TSLPR-/-) mice in a chronic HDM asthma model, we assessed lung function, inflammatory cell infiltration, cytokine levels, and antibody production in serum and lung tissues. Airway remodeling was evaluated by examining mucus production, goblet cell metaplasia, and collagen deposition. RESULTS: TSLPR-/- mice showed lower airway resistance, tissue resistance, and tissue elastance compared to wild-type mice after chronic HDM exposure. TSLPR-/- mice also had reduced HDM-specific IgE levels and decreased IL-4, IL-13, and IFN-γ in BALF. However, airway and lung inflammation, including inflammatory cell counts and eosinophil infiltration, were similar between TSLPR-/- and WT mice. Collagen deposition, mucus production, and goblet cell changes were also comparable. CONCLUSION: TSLPR deficiency reduced airway hyperresponsiveness but did not significantly impact lung eosinophil and neutrophil counts or mucus and collagen production in a chronic HDM asthma model, highlighting the complex role of TSLP and TSLPR in severe 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".