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Record W2115339089 · doi:10.1126/scitranslmed.3002011

Broken Barriers: A New Take on Sepsis Pathogenesis

2011· article· en· W2115339089 on OpenAlexafffund
Neil M. Goldenberg, Benjamin E. Steinberg, Arthur S. Slutsky, Warren L. Lee

Bibliographic record

VenueScience Translational Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsPathogenesisSepsisMedicineImmunologyKey (lock)Intensive care medicineBiology

Abstract

fetched live from OpenAlex

Despite intense research into the pathogenesis of sepsis, the current therapy for this devastating syndrome is primarily supportive and mortality remains high. The paucity of specific therapies is not for lack of effort; countless clinical trials in sepsis patients have failed despite promising preclinical data obtained from in vitro and animal models. Human sepsis is characterized by diffuse microvascular leak and tissue edema-features that have been largely ignored in animal models. Moreover, there have been no clinical trials of agents designed to prevent or treat leaky vasculature. Recent compelling evidence suggests that the breakdown in endothelial barrier function plays a crucial role in the pathogenesis of sepsis. In particular, these data suggest that preventing vascular leak can reduce mortality from sepsis. In this Perspective, we highlight the endothelial barrier as a new target for sepsis therapeutics, examining three potential strategies: enhancement of endothelial junctions; reinforcement of the endothelial cytoskeleton; and modulation of endothelial activation.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0020.012
Scholarly communication0.0070.019
Open science0.0010.004
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.186
GPT teacher head0.360
Teacher spread0.175 · 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 designTheoretical or conceptual
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

Citations324
Published2011
Admission routes2
Has abstractyes

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