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Record W1656784771

Angiopoietin-1 and -2 in Infectious Diseases associated with Endothelial Cell Dysfunction

2012· dissertation· en· W1656784771 on OpenAlexfundno aff
Andrea Page, W. Conrad Liles

Bibliographic record

VenueTSpace (University of Toronto) · 2012
Typedissertation
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsnot available
FundersAdvanced Research Projects AgencyUniversity of TorontoCanadian Institutes of Health ResearchGenome CanadaOntario GenomicsOntario Genomics Institute
KeywordsAngiopoietin 2SepsisAngiopoietinEndothelial dysfunctionSeptic shockMedicineEndothelial activationEndotheliumImmunologyBiomarkerEndothelial stem cellPhenotypeInflammationInternal medicineBiologyVascular endothelial growth factorIn vitro
DOInot available

Abstract

fetched live from OpenAlex

Normal endothelial cell function is controlled in part by a tightly regulated balance between angiopoietin-1 and -2 (Ang-1 and Ang-2). Angiopoietin dysregulation (decreased Ang-1 and increased Ang-2) leads to an activated endothelium that is contractile, adhesive, and prothrombotic. Since an activated endothelial phenotype is seen in invasive group A streptococcal infection, E. coli O157:H7-induced hemolytic-uremic syndrome (HUS), and sepsis, we hypothesized that angiopoietin dysregulation might also be present in these syndromes, and to that end, measured angiopoietin levels in several well-characterized patient cohorts. Decreased Ang-1 and/or increased Ang-2 were found in all three syndromes, and were predictive of clinical outcome in HUS and sepsis. The prognostic utility of Ang-2 in sepsis was further enhanced by combination with biomarkers of inflammation. Angiopoietin dysregulation may therefore represent a shared final common pathway to endothelial activation as well as a clinically useful prognostic biomarker in streptococcal toxic shock, HUS, and sepsis.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.001

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueTSpace (University of Toronto)Same topicLipid metabolism and disordersFrench-language works237,207