A complement-dependent balance between hepatic ischemia/reperfusion injury and liver regeneration in mice
Bibliographic record
Abstract
Massive liver resection and small-for-size liver transplantation pose a therapeutic challenge, due to increased susceptibility of the remnant/graft to ischemia reperfusion injury (IRI) and impaired regeneration. We investigated the dual role of complement in IRI versus regeneration in mice. Complement component 3 (C3) deficiency and complement inhibition with complement receptor 2-complement receptor 1-related protein y (CR2-Crry, an inhibitor of C3 activation) provided protection from hepatic IRI, and while C3 deficiency also impaired liver regeneration following partial hepatectomy (PHx), the effect of CR2-Crry in this context was dose dependent. In a combined model of IRI and PHx, either C3 deficiency or high-dose CR2-Crry resulted in steatosis, severe hepatic injury, and high mortality, whereas low-dose CR2-Crry was protective and actually increased hepatic proliferative responses relative to control mice. Reconstitution experiments revealed an important role for the C3a degradation product acylation-stimulating protein (ASP) in the balance between inflammation/injury versus regeneration. Furthermore, liver regeneration was dependent on the putative ASP receptor, C5L2. Several potential mechanisms of hepatoprotection and recovery were identified in mice treated with low-dose CR2-Crry, including enhanced IL-6 expression and STAT3 activation, reduced hepatic ATP depletion, and attenuated oxidative stress. These data indicate that a threshold of complement activation, involving ASP and C5L2, promotes liver regeneration and suggest a balance between complement-dependent injury and regeneration.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".