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Record W2040235050 · doi:10.4161/viru.25740

Emerging therapeutic strategies to prevent infection-related microvascular endothelial activation and dysfunction

2013· review· en· W2040235050 on OpenAlexafffund
Ilyse Darwish, W. Conrad Liles

Bibliographic record

VenueVirulence · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of TorontoCentre for Global Health ResearchToronto General HospitalUniversity Health Network
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsBiologyEndothelial dysfunctionImmunologyIntensive care medicineMicrobiologyMedicine

Abstract

fetched live from OpenAlex

Recent evidence suggests that loss of endothelial barrier function and resulting microvascular leak play important mechanistic roles in the pathogenesis of infection-related end-organ dysfunction and failure. Several distinct therapeutic strategies, designed to prevent or limit infection-related microvascular endothelial activation and permeability, thereby mitigating end-organ injury/dysfunction, have recently been investigated in pre-clinical models. In this review, these potential therapeutic strategies, namely, VEGFR2/Src antagonists, sphingosine-1-phosphate agonists, fibrinopeptide Bβ 15-42, slit2N, secinH3, angiopoietin-1/tie-2 agonists, angiopoietin-2 antagonists, statins, atrial natriuretic peptide, and mesenchymal stromal (stem) cells, are discussed in terms of their translational potential for the management of clinical infectious diseases.

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 score0.004
Threshold uncertainty score0.012

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 science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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

Citations64
Published2013
Admission routes2
Has abstractyes

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