Mitochondrial DNA: A Biomarker of Disease Severity in Necrotizing Enterocolitis
Bibliographic record
Abstract
Abstract Introduction There is a need to develop sensitive markers to diagnose or monitor the severity of intestinal damage in necrotizing enterocolitis (NEC). Mitochondrial deoxyribonucleic acid (mtDNA) is increased in the intestine and blood of adults in response to intestinal ischemia and can trigger secondary organ damage. We hypothesize that mtDNA is increased during experimental NEC and that mtDNA levels are correlated to the degree of intestinal injury. Materials and Methods NEC was induced in C57BL/6 mice (n = 18) (approval: 44032) by gavage feeding with hyperosmolar formula, hypoxia, and lipopolysaccharide administration from postnatal day (P) 5 to 9. Breastfed pups served as control (n = 15). Blood was collected by cardiac puncture and terminal ileum was harvested on P9. Reverse transcription quatitative polymerase chain reaction was used to measure mtDNA (markers COX3, CYTB, ND1) and inflammatory cytokines (interleukin 6 [IL-6] and tumor necrosis factor-α[TNF-α]) in blood and ileum. Intestinal injury was scored blindly by four investigators and classified as no/minor injury (score 0 or 1) or NEC (score ≥2). Results mtDNA is significantly increased in gut and blood of NEC mice (p < 0.05). Furthermore, mtDNA increases in intestine and blood proportionally to the degree of intestinal injury as indicated by a positive correlation with histological scoring and inflammation (r = 0.6; p < 0.05) (expression of IL-6 and TNF-α). Conclusion Following NEC intestinal injury, mtDNA is released from the intestine into circulation. The blood level of mtDNA is related to the degree of intestinal injury. mtDNA can be a novel marker of intestinal injury and can be useful for monitoring the progression of NEC.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".