Synthesis, characterization, and anticoagulant activity of carboxymethyl starch sulfates
Bibliographic record
Abstract
Abstract To develop a renewable and compatible anticoagulant as potential heparin alternative, carboxymethyl starch sulfate (CMSS) was prepared by the reaction of carboxymethyl starch (CMS) and sulfating reagent [N(SO3Na)3]. The chemical structures of CMS and CMSS were characterized by Fourier transform infrared spectroscopy and 13C nuclear magnetic resonance. The influences of reaction parameters, including the pH of sulfating reagent, the molar ratio of sulfating reagent to CMS, reaction time, and temperature on the degree of substitution of sulfate groups (DS) of CMSS were studied. Meantime, the DS of each CMSS was determined by barium sulfate–glutin nephelometery method. Moreover, the anticoagulant activity of CMSS was investigated by the coagulation assays of activated partial thromboplastin time, thrombin time, and prothrombin time. The results revealed that the anticoagulant activity of CMSS was closely related to the DS value and concentration. The anticoagulant activity was promoted with the increasing of the DS and concentration. The molecular weight (Mw) in measured range had little impact on anticoagulant activity in contract to the DS and concentration. In this article, the CMSS with the DS of 1.91, concentration of 75 μg/mL and the Mw of 2.61 × 104 had the best blood anticoagulant activities. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
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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) | 0.000 | 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 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".