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Record W3011699337 · doi:10.1093/cvr/cvaa067

Sectm1a deficiency aggravates inflammation-triggered cardiac dysfunction through disruption of LXRα signalling in macrophages

2020· article· en· W3011699337 on OpenAlexaff
Yutian Li, Shan Deng, Xiaohong Wang, Wei Huang, Jing Chen, Nathan Robbins, Xingjiang Mu, Kobina Essandoh, Tianqing Peng, Anil G. Jegga, Jack Rubinstein, David E. Adams, Yigang Wang, Jiangtong Peng, Guo‐Chang Fan

Bibliographic record

VenueCardiovascular Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsLawson Health Research Institute
FundersNational Institute of General Medical SciencesNational Institutes of HealthAmerican Heart Association
KeywordsInflammationProinflammatory cytokineLipopolysaccharideLiver X receptorEndocrinologyInternal medicineMacrophageMedicineCardiac function curveImmunologyBiologyHeart failureTranscription factorNuclear receptorIn vitroGene

Abstract

fetched live from OpenAlex

AIMS: Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) has previously been implicated to regulate inflammatory responses, yet its role in inflammation-associated cardiac dysfunction is virtually unknown. METHODS AND RESULTS: Using the CRISPR/Cas9 system, we generated a global Sectm1a-knockout (KO) mouse model and observed significantly increased mortality and cardiac injury after lipopolysaccharide (LPS) injection, when compared with wild-type (WT) control. Further analysis revealed significantly increased accumulation of inflammatory macrophages in hearts of LPS-treated KO mice. Accordingly, ablation of Sectm1a remarkably increased inflammatory cytokines levels both in vitro [from bone marrow-derived macrophages (BMDMs)] and in vivo (in serum and myocardium) after LPS challenge. RNA-sequencing results and bioinformatics analyses showed that the most significantly down-regulated genes in KO-BMDMs were modulated by LXRα, a nuclear receptor with robust anti-inflammatory activity in macrophages. Indeed, we identified that the nuclear translocation of LXRα was disrupted in KO-BMDMs when treated with GW3965 (LXR agonist), resulting in higher levels of inflammatory cytokines, compared to GW3965-treated WT-cells. Furthermore, using chronic inflammation model of high-fat diet (HFD) feeding, we observed that infiltration of inflammatory monocytes/macrophages into KO-hearts were greatly increased and accordingly, worsened cardiac function, compared to WT-HFD controls. CONCLUSION: This study defines Sectm1a as a new regulator of inflammatory-induced cardiac dysfunction through modulation of LXRα signalling in macrophages. Our data suggest that augmenting Sectm1a activity may be a potential therapeutic approach to resolve inflammation and associated cardiac dysfunction.

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)0.001
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 score0.025
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.299
Teacher spread0.257 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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