Protective effects of purslane seed (Portulaca Oleracea L.) on plasma levels of Cystatin C, Cathepsin S, and Creatinine in women with type 2 Diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Diabetes is a chronic metabolic disease which is associated with the inflammation of cardiovascular system and kidney. Studies have shown that medicinal plants could be effective in reducing inflammation; however, the effectiveness of purslane (Portulaca oleracea) on inflammation is not well defined. Thus, this study attempted to investigate the effect of Portulaca oleracea seed consumption on plasma levels of cystatin C, cathepsin S, and creatinine in women with type 2 diabetes. Methods: In this quasi-experimental study, 14 women with type 2 diabetes were randomly divided into two equal groups of intervention and control (n=7). The subjects received Portulaca oleracea seed 2.5 g at lunch and 5 g at dinner (totally 7.5 g) per day for 8 weeks. Blood was collected before and 48 hours after the last intervention. Data were analyzed with paired and independent t-tests, and P<0.05 was considered significant. Results: Levels of cystatin C, cathepsin S, creatinine, and lipid profile decreased significantly in the intervention group after 8 weeks (P<0.05). There was also a significant difference between the intervention and control groups in levels of cystatin C and cathepsin S. Conclusion: Changes in biochemical markers showed that Portulaca oleracea seed could improve the levels of cardiovascular and kidney damage biomarkers and lipid profile in diabetic patients. However, further research is needed for more accurate conclusions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it