Chicken bone marrow mesenchymal stem cells improve lung and distal organ injury
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) are associated with pulmonary protection and longevity. We separated chicken bone marrow-derived mesenchymal stem cells (BM-MSCs); investigated whether BM-MSCs can improve lipopolysaccharide (LPS)-induced lung and distal organ injury; and explored the underlying mechanisms. Ninety-six male ICR (6 weeks old) mice were randomly divided into three groups: Sham, LPS, and LPS + MSC groups. The mice were intratracheally injected with 5 mg/kg LPS to induce acute lung injury (ALI). The histopathological severity of injury to the lung, liver, kidney, heart, and aortic tissues was detected. Wet/dry ratio, protein concentrations in bronchoalveolar lavage fluid (BALF), BALF cell counts, inflammatory cytokine levels in serum, inflammatory cytokine gene expression, and oxidative stress-related indicators were detected. In addition, a survival analysis was performed in sixty male ICR mice (6 weeks old, 18-20 g). This study used chicken BM-MSCs, which are easier to obtain and more convenient than other animal or human MSCs, and have MSC-associated properties, such as a colony forming ability, multilineage differentiation potential, and certain phenotypes. BM-MSCs administration significantly improved the survival rate, systemic inflammation, and the histopathological severity of lung, liver, kidney, and aortic injury during ALI. BM-MSCs administration reduced the levels of inflammatory factors in BALF, the infiltration of neutrophils, and oxidative stress injury in lung tissue. In addition, BM-MSCs administration reduced TRL4 and Mdy88 mRNA expression during ALI. Chicken BM-MSCs serve as a potential alternative resource for stem cell therapy and exert a prominent effect on LPS-induced ALI and extrapulmonary injury, in part through TRL4/Mdy88 signaling and inhibition of neutrophil inflammation and oxidative stress injury.
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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) | 0.001 | 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".