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Record W3008165957 · doi:10.1097/ccm.0000000000004247

Epigenetics of Sepsis

2020· article· en· W3008165957 on OpenAlexafffund
Alexandra Binnie, Jennifer Tsang, Pingzhao Hu, Gabriela Carrasqueiro, Pedro Castelo‐Branco, Claúdia C. dos Santos

Bibliographic record

VenueCritical Care Medicine · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of TorontoUniversity of ManitobaMcMaster UniversityWilliam Osler Health SystemNiagara Health SystemSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsEpigeneticsSepsisDNA methylationMedicineHistoneImmunologyOrgan dysfunctionBioinformaticsBiologyGene expressionGeneticsGene

Abstract

fetched live from OpenAlex

OBJECTIVES: Recent evidence from the fields of microbiology and immunology, as well as a small number of human sepsis studies, suggest that epigenetic regulation may play a central role in the pathogenesis of sepsis. The term "epigenetics" refers to regulatory mechanisms that control gene expression but are not related to changes in DNA sequence. These include DNA methylation, histone modifications, and regulation of transcription via non-coding RNAs. Epigenetic modifications, occurring in response to external stressors, lead to changes in gene expression, and thus lie at the intersection between genetics and the environment. In this review, we examine data from in vitro studies, animal studies, and the existing human sepsis studies in epigenetics to demonstrate that epigenetic mechanisms are likely central to the pathogenesis of sepsis and that epigenetic therapies may have potential in the treatment of sepsis and its associated organ failures. DATA SOURCES: Online search of published scientific literature via Pubmed using the term "epigenetics" in combination with the terms "sepsis", "infection", "bacterial infection", "viral infection", "critical illness", "acute respiratory distress syndrome", and "acute lung injury". STUDY SELECTION: Articles were chosen for inclusion based on their relevance to sepsis, acute inflammation, sepsis-related immune suppression, and sepsis-related organ failure. Reference lists were reviewed to identify additional relevant articles. DATA EXTRACTION: Relevant data was extracted and synthesized for narrative review. DATA SYNTHESIS: Epigenetic regulation is a key determinant of gene expression in sepsis. At the onset of infection, host-pathogen interactions often result in epigenetic alterations to host cells that favor pathogen survival. In parallel, the host inflammatory response is characterized by epigenetic modifications in key regulatory genes, including tumor necrosis factor and interleukin-1β. In human sepsis patients, multiple epigenetic modifying enzymes show differential expression in early sepsis, suggesting a role for epigenetics in coordinating the response to infection. In the later stages of sepsis, epigenetic modifications accompany endotoxin tolerance and the immune-suppressed state. In animal models, treatment with epigenetic modifiers can mitigate the effects of sepsis and improve survival as well as reverse sepsis-associated organ injury. CONCLUSIONS: Epigenetic modifications are associated with key phases of sepsis, from the host-pathogen interaction, to acute inflammation, to immune suppression. Epigenetic markers show promise in the diagnosis and prognosis of sepsis and epigenetic modifying agents show promise as therapeutic tools in animal models of sepsis. Human studies in the area of epigenetics are sorely lacking and should be a priority for sepsis researchers.

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)0.001
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 score0.111
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.028
GPT teacher head0.326
Teacher spread0.298 · 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

Citations79
Published2020
Admission routes2
Has abstractyes

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