Vascular endothelial growth factor is an important determinant of sepsis morbidity and mortality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sepsis, the systemic inflammatory response to infection, is a leading cause of morbidity and mortality. The mechanisms of sepsis pathophysiology remain obscure but are likely to involve a complex interplay between mediators of the inflammatory and coagulation pathways. An improved understanding of these mechanisms should provide an important foundation for developing novel therapies. In this study, we show that sepsis is associated with a time-dependent increase in circulating levels of vascular endothelial growth factor (VEGF) and placental growth factor (PlGF) in animal and human models of sepsis. Adenovirus-mediated overexpression of soluble Flt-1 (sFlt-1) in a mouse model of endotoxemia attenuated the rise in VEGF and PlGF levels and blocked the effect of endotoxemia on cardiac function, vascular permeability, and mortality. Similarly, in a cecal ligation puncture (CLP) model, adenovirus-sFlt-1 protected against cardiac dysfunction and mortality. When administered in a therapeutic regimen beginning 1 h after the onset of endotoxemia or CLP, sFlt peptide resulted in marked improvement in cardiac physiology and survival. Systemic administration of antibodies against the transmembrane receptor Flk-1 but not Flt-1 protected against sepsis mortality. Adenovirus-mediated overexpression of VEGF but not PlGF exacerbated the lipopolysaccharide-mediated toxic effects. Together, these data support a pathophysiological role for VEGF in mediating the sepsis phenotype.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it