Effect of Sulgidduk containing pine needle juice on lipid metabolism in high fat-cholesterol diet induced dyslipidemic rats
Bibliographic record
Abstract
Purpose: Dyslipidemia is a major risk factor for cardiovascular disease. Pine needles (Pinus densiflora seib et Zucc) are a traditional medicine used to treat dyslipidemia in clinical settings. This study examined the potential effects of sulgidduk, a Korean traditional rice cake containing pine needle juice to protect against dyslipidemia induced by a high-fat/sugidduk diet in a rat model. Methods: Twenty one male Sprague-Dawley rats were divided randomly into three groups: normal control (NC), Sulgidduk diet (SD), Sulgidduk diet containing pine needle juice (PSD). The blood lipid levels, production of lipid peroxide in the plasma and liver, total cholesterol and triglyceride in the liver and feces, antioxidant enzyme activities in plasma and erythrocytes were measured to assess the effects of PSD on dyslipidemia. Results: A high-fat/Sulgidduk diet induced dyslipidemia, which was characterized by significantly altered lipid profiles in the plasma and liver. The food intake was similar in the three groups, but weight gain and food efficiency ratio (FER) were reduced significantly in the PSD group compared to those in the SD group. The level of total cholesterol, LDL-cholesterol and TBARS in the plasma showed tendencies to decrease in the PSD group compared to those in the SD group. The levels of high-fat/Sulgidduk diet-induced sterol regulatory element-binding protein 2 (SREBP2) gene expression were reduced significantly in the PSD group. The supplementation of PSD reduced the hepatic triglyceride and total cholesterol levels significantly, and enhanced the fecal excretion of triglyceride and hepatic antioxidant enzyme activities compared to the SD group. Conclusion: These results suggest that the addition of 0.4% pine needle juice to Sulgidduk may be an alternative snack to control dyslipidemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".