MICROVASCULAR ENDOTHELIAL ACTIVATION/DYSFUNCTION AND DYSREGULATION OF THE ANGIOPOIETIN-TIE2 SYSTEM IN THE PATHOGENESIS OF LIFE-THREATENING INFECTIONS.
Bibliographic record
Abstract
Microvascular endothelial activation/dysfunction has emerged as an important mechanistic pathophysiological process in the development of morbidity and mortality in life-threatening infections. The angiopoietin-Tie2 system plays an integral role in the regulation of microvascular endothelial integrity. Angiopoietin-1 (Ang-1), produced by platelets and pericytes, is the cognate agonistic ligand for Tie2, promoting endothelial quiescence and inhibiting microvascular leak. Angiopoietin-2 (Ang-2), released from activated endothelial cells in Weibel-Palade bodies, competes with Ang-1 for binding to Tie-2, thereby promoting endothelial activation/dysfunction and microvascular leak. In healthy homeostasis, levels of Ang-1 far exceed Ang-2 in circulating serum/plasma. In diseases associated with systemic inflammation, Ang-1 falls and Ang-2 rises (i.e., Ang-1/2 dysregulation). Our research has shown that Ang-1/2 dysregulation is a prominent feature in a number of life-threatening infections and critical illnesses, including sepsis, cerebral malaria, COVID-19, streptococcal toxic shock syndrome (STSS), hemolytic-uremic syndrome (HUS), dengue, and CAR T-cell-associated neurotoxicity. Further work has implicated Ang-1/2 dysregulation in the development of end-organ injury, including acute lung injury/ARDS, acute kidney injury (AKI), and blood-brain-barrier (BBB) breakdown. Current studies are focused in three areas: (a) translation of Ang-1 and -2 as clinically informative prognostic and "theranostic" biomarkers in critically ill individuals; (b) incorporation of Ang-1/2 assays in a point of care device for clinical triage decision making; and (c) development of an engineered Ang-1 super agonist nanoparticle as a novel pathogen-agnostic therapeutic to prevent and/or mitigate end-organ dysfunction in individuals with life-threatening infections and critical illnesses associated with systemic inflammation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".