MATHEMATICAL MODELING OF POSTHEMORRHAGE INFLAMMATION IN MICE
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
Hemorrhagic shock (HS) elicits a global acute inflammatory response, organ dysfunction, and death. We have used mathematical modeling of inflammation and tissue damage/dysfunction to gain insight into this complex response in mice. We sought to increase the fidelity of our mathematical model and to establish a platform for testing predictions of this model. Accordingly, we constructed a computerized, closed-loop system for mouse HS. The intensity, duration, and time to achieve target MAP could all be controlled using a software. Fifty-four male C57/black mice either were untreated or underwent surgical cannulation. The cannulated mice were divided into 8 groups: (a) 1, 2, 3, or 4 h of surgical cannulation alone and b) 1, 2, 3, or 4 h of cannulation + HS (25 mmHg). MAP was sustained by the computer-controlled reinfusion and withdrawal of shed blood within +/-2 mmHg. Plasma was assayed for the cytokines TNF, IL-6, and IL-10 as well as the NO reaction products NO2-/NO3-. The cytokine and NO2-/NO3- data were compared with predictions from a mathematical model of post-hemorrhage inflammation, which was calibrated on different data. To varying degrees, the levels of TNF, IL-6, IL-10, and NO2/NO3 predicted by the mathematical model matched these data closely. In conclusion, we have established a hardware/software platform that allows for highly accurate, reproducible, and mathematically predictable HS in mice.
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 | 0.000 | 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 it