Role of acitretin in regulating glucose and lipid homeostasis in an imiquimod-induced psoriasis model mouse.
Bibliographic record
Abstract
OBJECTIVES: Psoriasis is a chronic inflammatory skin disease often accompanied by comorbidities such as hyperglycemia, insulin resistance, and obesity. Acitretin, as a second-generation retinoid, is used in the treatment of psoriasis. This study aims to explore the role of acitretin on glucose and lipid metabolism in psoriasis. METHODS: HepG2 cells were treated with acitretin under high- or low-glucose conditions. mRNA and protein expression levels of glucose transport-related genes were evaluated using real-time reverse transcription PCR (real-time RT-PCR) and Western blotting. Glucose uptake was analyzed by flow cytometry, and intracellular lipid droplet formation was assessed via Oil Red O staining. Healthy adult female BALB/C mice were randomly divided into 3 groups: a control group, an imiquimod (IMQ)-induced psoriasis model group (IMQ group), and an acitretin treatment group. Skin lesions and inflammatory markers were examined, along with changes in body weight, plasma glucose/lipid levels, and transcription of metabolic genes. Islets were isolated from normal and psoriasis-induced mice, and the effect of acitretin on insulin secretion was evaluated in vitro. RESULTS: <0.05). These findings suggest that acitretin plays a critical role in improving islet function and restoring islet homeostasis. CONCLUSIONS: Acitretin helps maintain the balance between hepatic glycogenesis and gluconeogenesis, enhances insulin sensitivity, and improves pancreatic islet function, thereby promoting systemic and cellular glucose homeostasis.
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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 | 0.001 | 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 | 0.001 |
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".