Measurement and Analysis of the Dynamics of Erythrocyte Oxygen‐Dependent ATP Release
Bibliographic record
Abstract
Erythrocytes play a key role in the distribution of oxygen (O 2 ) supply in the microvasculature through the oxygen saturation (SO 2 )‐dependent release of adenosine triphosphate (ATP). Previous studies address the magnitude of ATP release, however, little attention is given to the dynamics, which are crucial to understanding this regulatory system. Our goal is to characterize the dynamics of SO 2 ‐dependent ATP release as it applies to O 2 mediated blood flow regulation. Previously, we developed a computational model of a device capable of measuring the dynamics of ATP release (Sove PLOS 2013). In the present study we have modified the model to match our current prototype that utilizes a new fabrication approach of embedding a polymethyl methacrylate (PMMA) O 2 impermeable barrier with a window for O 2 exchange, in a polydimethylsiloxane (PDMS) O 2 permeable layer. The model predicts how the PDMS exchange surface between the erythrocyte and gas channels affects the rate of O 2 saturation decrease; thus making it possible to optimize the design of the device and to define appropriate hematocrit and flow conditions for in vitro studies. The model predicts that the PDMS layer thickness causes a decrease in the rate of SO 2 decrease, and that low hematocrit results in larger SO 2 decrease in a quasi‐linear relationship (slope ‐0.12). Despite the predicted SO 2 decrease, ATP release is less due to the decreased number of erythrocytes. Our model shows that decreasing flow rate decreases the SO 2 , which results in a decrease in spatially derived resolution of ATP release time. The model of the microfluidic device aids in the design of future prototypes, facilitates the analysis of experimental results and provides a means to extract information from in vitro studies that cannot be measured directly.
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 | 0.000 | 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 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".