Delayed but not Early Treatment with DNase Reduces Organ Damage and Improves Outcome in a Murine Model of Sepsis
Bibliographic record
Abstract
Sepsis is characterized by systemic activation of coagulation and inflammation in response to microbial infection. Although cell-free DNA (cfDNA) released from activated neutrophils has antimicrobial properties, it may also exert harmful effects by activating coagulation and inflammation. The authors aimed to determine whether deoxyribonuclease (DNase) administration reduces cfDNA levels, attenuates coagulation and inflammation, suppresses organ damage, and improves outcome in a cecal ligation and puncture (CLP) model of polymicrobial sepsis. Healthy C57Bl/6 mice were subjected to CLP, a surgical procedure involving two punctures of the ligated cecum, or sham surgery (no ligation/puncture). Mice were given DNase or saline by intraperitoneal injection 2, 4, or 6 h after surgery. Two hours after treatment, organs were harvested and plasma levels of cfDNA, interleukin-6 (IL-6), IL-10, thrombin-antithrombin complexes, lung myeloperoxidase, creatinine, alanine transaminase, and bacterial load were quantified. Survival studies were also performed. The CLP-operated mice had rapid time-dependent elevations in cfDNA that correlated with elevations in IL-6, IL-10, and thrombin-antithrombin complexes and had organ damage in the lungs and kidneys. Administration of DNase at 2 h after CLP resulted in increased IL-6 and IL-10 levels and organ damage in the lungs and kidneys. In contrast, DNase administration at 4 or 6 h after CLP resulted in reduced cfDNA and IL-6 levels, increased IL-10, and suppressed organ damage and bacterial dissemination. Deoxyribonuclease administration every 6 h after CLP also rescued mice from death. Our studies are the first to demonstrate that delayed but not early administration of DNase may be protective in experimental 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".