Protective effects of <i>Lactococcus lactis</i> expressing alcohol dehydrogenase and acetaldehyde dehydrogenase on acute alcoholic liver injury in mice
Bibliographic record
Abstract
Abstract BACKGROUND Alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) play important roles in alcohol metabolism. Therefore, a possible effective way to attenuate alcoholic liver damage is the exogenous supply of these two enzymes to the stomach as they might accelerate the oxidation of ethanol into nontoxic acetate. RESULTS ADH and ALDH were coexpressed in Lactococcus lactis NZ3900 and used as treatments for acute alcoholic liver injury in mice. Intragastric ethanol administration was carried out at 5.6 g kg‐1 body weight per day in mice for 15 consecutive days and different doses of recombinant ADH‐ALDH L. lactis treatment were administrated together with ethanol. A high dose of L. lactis recombinant ADH‐ALDH treatment (ADH activity of 2000 U kg‐1 BW and ALDH activity of 1000 U kg‐1 BW) reduced the serum alanine aminotransferase, aspartate aminotransferase and alkaline phosphatase levels by 38.1%, 54.8% and 23.2%, respectively, in ethanol‐treated mice. Moreover, it also helped maintaining serum lipid levels and liver oxidative stress parameters against ethanol. Histopathological examination of mice livers revealed that L. lactis recombinant ADH‐ALDH at a high dose (ADH activity of 2000 U kg‐1 BW and ALDH activity of 1000 U kg‐1 BW) protected liver tissue from the damage induced by ethanol. CONCLUSION Results demonstrate that L. lactis with ADH and ALDH activity exhibit a dose‐dependent protective effect on alcohol‐induced liver damage in mice. © 2017 Society of Chemical Industry
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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) | 0.001 | 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) | 0.001 | 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".