Extraction Optimization, Structural Characterization, and Anticoagulant Activity of Acidic Polysaccharides from Auricularia auricula-judae
Bibliographic record
Abstract
polysaccharides (AAP) as natural anticoagulants for application in the functional food industry, ultrasound assisted extraction (UAE) was optimized for the extraction of AAP by using a response surface methodology (RSM). The maximum extraction yield of crude AAP (14.74 mg/g) was obtained at the optimized extraction parameters as follows: Extraction temperature (74 °C), extraction time (27 min), the ratio of liquid to raw material (103 mL/g), and ultrasound power (198 W). Furthermore, the acidic AAP (aAAP) was precipitated with cetyltrimethylammonium bromide (CTAB) from crude AAP (cAAP). aAAP was further purified using ion exchange chromatography with a DEAE Purose 6 Fast Flow column to obtain aAAP-1. Additionally, according to the HPLC analysis, the aAAP-1 was mainly composed of mannose, glucuronic acid, glucose, galactose, and xylose, with a molar ratio of 80.63:9.88:2.25:1:31.13. Moreover, the results of the activated partial thromboplastin time (APTT), prothrombin time (PT), and thrombin time (TT) indicated aAAP-1 had anticoagulant activity, which was a synergic anticoagulant activity by the endogenous and exogenous pathway.
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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 | 0.001 |
| 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".