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Comparison of Procoagulant and Proinflammatory Effects of Nuclear, Mitochondrial, and Bacterial DNA

2014· article· en· W2586194045 on OpenAlexaff
Vinai Bhagirath, Dhruva J. Dwivedi, Patricia C. Liaw

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsNeutrophil extracellular trapsPropidium iodideMitochondrial DNANuclear DNAProinflammatory cytokineBiologyMolecular biologyDNAImmunologyInflammationApoptosisBiochemistryProgrammed cell deathGene

Abstract

fetched live from OpenAlex

Abstract Background: Sepsis is a syndrome in which infection triggers a systemic inflammatory and pro-coagulant response, with a prevalence of up to 1 case per 1000 and a mortality rate of up to 40%. Cell-free DNA (cfDNA) is elevated in sepsis, and correlates with mortality. This DNA may come from nuclear, mitochondrial, or bacterial sources. Nuclear and mitochondrial DNA may come from activated neutrophils which release neutrophil extracellular traps (NETs). CpG motifs on bacterial and mitochondrial DNA can stimulate inflammatory responses via TLR9, which is present on neutrophils, monocytes, and recently shown to be expressed on platelets. cfDNA can activate coagulation via the intrinsic pathway. cfDNA may thus play an important pathogenic role in sepsis. This study elucidates the relative effects of nuclear, mitochondrial, and bacterial DNA on inflammatory and pro-coagulant pathways. Methods: Mitochondrial DNA concentrations were measured by PCR using plasma samples from septic patients. Nuclear and mitochondrial DNA were purified from human embryonic kidney 293 cells, and bacterial DNA was from E. coli. Neutrophils from healthy donors were cultured with purified bacterial, mitochondrial, or nuclear DNA at 15µg/mL for 20h. IL-6 levels in the supernatants were measured by ELISA, and neutrophil viability was measured by flow cytometry for annexin-V binding and propidium iodide exclusion. The three types of DNA were added to either citrated normal human platelet-poor plasma or platelet-rich plasma, and continuous thrombin generation was measured (Technothrombin, Vienna, Austria). Light transmission aggregometry was performed in citrated platelet-rich plasma with co-treatment of a sub-threshold concentration of ADP and varying concentrations of DNA. Markers of platelet activation were measured by flow cytometry for P-selectin and activated integrin αIIbβ3. All reagents contained less than 0.06EU/mL of LPS by limulus amoebocyte lysate assay. Results: Cell-free mitochondrial DNA was elevated in plasma from septic patients compared to healthy controls. Bacterial, but not mitochondrial or nuclear, DNA increased neutrophil IL-6 secretion. Both mitochondrial and bacterial DNA increased neutrophil viability at 20h. At concentrations found in the plasma of critically-ill patients, mitochondrial, nuclear, and bacterial DNA increased thrombin generation in both platelet-poor plasma and platelet-rich plasma to a similar degree, and this effect was abolished by corn-trypsin inhibitor and reduced in FXII-depleted plasma, indicating dependence on the intrinsic pathway of coagulation. Independently of coagulation, nuclear DNA at high concentrations, such as may be seen in the NET micro-environment, was capable of causing aggregation of ADP pre-stimulated platelets in citrated plasma, which was accompanied by activation of integrin αIIbβ3and surface expression of P-selectin. This effect also occurred with synthetic phosphodiester oligonucleotides, and was abolished by DNase pre-digestion. Conclusions: cfDNA of bacterial origin can stimulate neutrophil IL-6 release, while both mitochondrial and bacterial DNA prolonged neutrophil viability. All types of DNA can activate coagulation via the contact pathway. DNA at high concentrations may be able to directly stimulate platelets. Total plasma cfDNA and cell-free mitochondrial DNA specifically are elevated in sepsis. Thus, nuclear, mitochondrial, and bacterial DNA may play distinct roles in the pathogenesis of sepsis. Disclosures Bhagirath: Pfizer: Research Funding.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2014
Admission routes1
Has abstractyes

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