MétaCan
Menu
Back to cohort

Critical Role for Oxidative Stress, Platelets, and Coagulation in Capillary Blood Flow Impairment in Sepsis

2010· review· en· W1896508015 on OpenAlexaff
Karel Tyml

Bibliographic record

VenueMicrocirculation · 2010
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsPlateletOxidative stressCoagulationSepsisMedicineBlood flowCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Sepsis is a complex multifaceted response to a local infectious insult. One important facet is the circulatory system dysfunction, which includes capillary bed plugging. This review addresses the mechanisms of capillary plugging and highlights our recent discoveries on the roles of NO, ROS, and activated coagulation in platelet adhesion and blood flow stoppage in septic mouse capillaries. We show that sepsis increases platelet adhesion, fibrin deposition and flow stoppage in capillaries, and that NADPH oxidase-derived ROS, rather than NO, play a detrimental role in this adhesion/stoppage. P-selectin and activated coagulation are required for adhesion/stoppage. Further, platelet adhesion in capillaries (i) strongly predicts capillary flow stoppage, and (ii) may explain why severe sepsis is associated with a drop in platelet count in systemic blood. Significantly, we also show that a single bolus of the antioxidant ascorbate (injected intravenously at clinically relevant dose of 10 mg/kg) inhibits adhesion/stoppage. Our data suggest that eNOS-derived NO at the platelet-endothelial interface is anti-adhesive and required for the inhibitory effect of ascorbate. Because of the critical role of ROS in capillary plugging, ascorbate bolus administration may be beneficial to septic patients whose survival depends on restoring microvascular perfusion.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.056
GPT teacher head0.370
Teacher spread0.314 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations91
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueMicrocirculationSame topicSepsis Diagnosis and TreatmentFrench-language works237,207