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Record W4282918996 · doi:10.1631/jzus.b2101091

Integrated metabolism and epigenetic modifications in the macrophages of mice in responses to cold stress

2022· article· en· W4282918996 on OpenAlexaff
Jingjing Lu, Shoupeng Fu, Jie Dai, Jianwen Hu, Shize Li, Hong Ji, Zhiquan Wang, Jiahong Yu, Jiming Bao, Bin Xu, Jingru Guo, Huanmin Yang

Bibliographic record

VenueJournal of Zhejiang University SCIENCE B · 2022
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Alberta
FundersHeilongjiang Bayi Agricultural UniversityNatural Science Foundation of Heilongjiang ProvinceNational Natural Science Foundation of China
KeywordsEpigeneticsReprogrammingCell biologyBiologyHistoneMacrophageMetabolismAcetylationCold stressMitochondrionBiochemistryGene

Abstract

fetched live from OpenAlex

The negative effects of low temperature can readily induce a variety of diseases. We sought to understand the reasons why cold stress induces disease by studying the mechanisms of fine-tuning in macrophages following cold exposure. We found that cold stress triggers increased macrophage activation accompanied by metabolic reprogramming of aerobic glycolysis. The discovery, by genome-wide RNA sequencing, of defective mitochondria in mice macrophages following cold exposure indicated that mitochondrial defects may contribute to this process. In addition, changes in metabolism drive the differentiation of macrophages by affecting histone modifications. Finally, we showed that histone acetylation and lactylation are modulators of macrophage differentiation following cold exposure. Collectively, metabolism-related epigenetic modifications are essential for the differentiation of macrophages in cold-stressed mice, and the regulation of metabolism may be crucial for alleviating the harm induced by cold stress.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.141

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.023
GPT teacher head0.271
Teacher spread0.249 · 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 designObservational
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

Citations22
Published2022
Admission routes1
Has abstractyes

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