Amelioration of Acute Alcoholic Liver Injury via Attenuating Oxidative Damage and Modulating Inflammation by Means of Ursodeoxycholic Acid–Zein Nanoparticles
Bibliographic record
Abstract
Ursodeoxycholic acid (UDCA) has been broadly adopted for the clinical treatment of hepatic and biliary diseases; however, its poor water-solubility becomes an obstacle in wide applications. To overcome these challenges, herein, a two-tier UDCA-embedded system of zein nanoparticles (NPs) along with a polyelectrolyte complex was designed under facile conditions. Both the UDCA-zein NPs and their inclusion microcapsules showed a spherical shape with a uniform size. A typical wall plus capsule/core structure was formed in which UDCA-zein NPs distributed evenly in the interior. The UDCA inclusion microcapsules had an encapsulation rate of 67% and were released in a non-Fickian or anomalous transport manner. The bioavailability and efficacy of UDCA-zein NPs were assessed in vivo through the alcoholic liver disease (ALD) mouse model via intragastric administration. UDCA-zein NPs ameliorated the symptoms of ALD mice remarkably, which were mainly exerted through attenuation of antioxidant stress levels. Meanwhile, it notably upregulated the intestinal tight junction protein expression and improved and maintained the integrity of the mucosal barrier effectively. Collectively, with the improvement of bioavailability, the UDCA-zein NPs prominently alleviated the oxidative damage induced by alcohol, modulating the inflammation so as to restore ALD. It is anticipated that UDCA-zein NPs have great therapeutic potential as sustained-nanovesicles in ALD treatment.
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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) | 0.000 | 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".