Impact of SMOFLipid on Pulmonary Alveolar Development in Newborn Guinea Pigs
Bibliographic record
Abstract
BACKGROUND: Parenteral nutrition (PN) is associated with bronchopulmonary dysplasia in premature infants. In animals, PN leads to alveolar loss following stimulation of apoptosis by oxidative stress (oxidized redox potential). Peroxides and aldehydes generated in PN can induce hypo-alveolarization. The implication of peroxides, which is reduced by light protection, is demonstrated. The implication of aldehydes from omega-6 fatty acids oxidation is expected. The hypothesis is that composition and light exposure of PN influences bronchopulmonary dysplasia development. Since SMOFLipid (SMOF) contains a lower amount of omega-6 fatty acids than Intralipid (IL), the aim was to compare, the impacts of PN compounded with SMOF or IL, photo-protected or not, on alveolar development. MATERIALS AND METHODS: Three-day-old Guinea pigs received PN, photo-protected or not, made with SMOF or IL through a jugular vein catheter. After 4 days, lungs were sampled for determinations of redox potential of glutathione, apoptosis (caspase-3, caspase-8, and caspase-9) and alveolarization index (histology: number of intercepts/mm). RESULTS: Compared with IL, SMOF induces a greater oxidation of redox potential (-200 ± 1 versus [vs] -205 ± 1 mV), apoptosis (caspase-3: 0.27 ± 0.04 vs 0.16 ± 0.02; caspase-9: 0.47 ± 0.03 vs 0.30 ± 0.03), and a lower alveolarization index (27.2 ± 0.8 vs 30.0 ± 0.9). Photo-protection prevented activation of caspase-9 and was statistically without effect on redox potential, caspase-3, and alveolarization index. CONCLUSION: In our model, SMOF is pro-oxidant and induces hypo-alveolarization following exaggerated apoptosis. These results highlight the need for further studies before introducing SMOFLipid in standard neonatal care.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".