The microcirculation as a functional system.
Bibliographic record
Abstract
This review examines experimental evidence that the microvascular dysfunction that occurs early in sepsis is the critical first stage in tissue hypoxia and organ failure. A functional microvasculature maintains tissue oxygenation despite limitations on oxygen delivery from blood to tissue imposed by diffusion; the density of perfused (functional) capillaries is high enough to ensure appropriate diffusion distances, and arterioles regulate the distribution of oxygen within the organ precisely to where it is needed. Key components of this regulatory system are the endothelium, which communicates and integrates signals along the microvascular network, and the erythrocytes, which directly monitor and regulate oxygen delivery. During hypovolemic shock, a functional microvasculature responds to diminish the impact of a decrease in oxygen supply on tissue perfusion. However, within hours of the onset of sepsis, a dysfunctional microcirculation is, due to a loss of functional capillary density and impaired regulation of oxygen delivery, unable to maintain capillary oxygen saturation levels and prevent the rapid onset of tissue hypoxia despite adequate oxygen supply to the organ. The mechanism(s) responsible for this dysfunctional microvasculature must be understood in order to develop appropriate management strategies for 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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".