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Record W4310602963 · doi:10.7150/thno.78851

Targeting psychological stress-steroid-MARCH1 signaling pathway promotes the efficacy of specific allergen immunotherapy

2022· article· en· W4310602963 on OpenAlexaff
X. He, Jie Liu, Xiaojun Xiao, Shuang Zhang, Xinxin Wang, Jiangqi Liu, Zhiqiang Liu, Junyi Wang, Xiaoyu Liu, Guoping Li, Ping–Chang Yang

Bibliographic record

VenueTheranostics · 2022
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsImmune systemMedicineDendritic cellImmunotherapyImmunologyCancer research

Abstract

fetched live from OpenAlex

The therapeutic efficacy of allergen specific immunotherapy (SIT) is recognized, but needs improved. Psychological stress influences the immune system's function. The objective of this study is to elucidate the effects of psychological stress on compromising the effectiveness of SIT. Methods: A murine model with the airway allergic disorder (AAD) was established. Mice were treated with SIT with or without restraint stress (Rs). Results: Rs was found to significantly hamper the efficacy of SIT in mice with AAD. Induction of IL-10 + dendritic cells and type 1 regulatory T cells were reduced by Rs in the airway tissues. Rs-induced cortisol release subverted immune tolerance generation. Expression of MARCH1 was elevated in dendritic cells of the allergic lesion sites. The Rs-induced MARCH1 mediated the immune impairment in AAD mice. Genetic ablation of MARCH1 in dendritic cells efficiently blocked the Rs-compromised the therapeutic efficacy of SIT. Conclusion: Rs can increase the expression of MARCH1 in DCs of the allergic lesion sites. MARCH1 interferes with the immune regulatory properties in DCs, and impairs the immune regulatory capacity. Blocking MARCH1 can counteract the Rs-affected SIT efficacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.050
GPT teacher head0.295
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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