Screening for α-glucosidase inhibitors in natural medicines by immobilized enzyme
Bibliographic record
Abstract
Objective:To establish a screening model of immobilized enzymes for α-glucosidase inhibitors in vitro in natural medicines.Methods:Following after the immobilization of α-glucosidase in a mimic physical microenvironment as small intestinal membrane,a screening model for α-glucosidase inhibitors was established.The model was validated by means of a standard α-glucosidase inhibitor acarbose.Subsequently, the model was used to screen the α-glucosidase inhibitors from two natural medicines-aqueous extracts of Polygonum cuspidatum and methanol extracts of Guangxi Dragon's blood.Results:Inhibition of acarbose to immobilized α-glucosidase was 3.3 times more potent than to free α-glucosidase(IC_(50) 0.413 versus 0.126 mg·mL~(-1)),which was coincident with the inhibition of acarbose in vivo.The IC_(50) of Polygonum cuspidatum and Guangxi Dragon's blood against immobilized α-glucosidase was 0.224 mg·mL~(-1) and 5.5 μg·mL~(-1),respectively.Conclusion:The model showed a potent capacity to screen α-glucosidase inhibitors in vitro in natural medicines,which was consistent with literatures'outcomes.
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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 | 0.000 | 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 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".