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Record W2163870542 · doi:10.1002/app.38088

Synthesis, characterization, and anticoagulant activity of carboxymethyl starch sulfates

2012· article· en· W2163870542 on OpenAlexaff
Lihong Fan, Yugui Gong, Mi Cao, Song Gao, Yi Sun, Lingyun Chen, Hua Zheng, Weiguo Xie

Bibliographic record

VenueJournal of Applied Polymer Science · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsReagentPartial thromboplastin timeChemistryThromboplastinThrombin timeAnticoagulantProthrombin timeNuclear chemistryHeparinCoagulationInorganic chemistryBiochemistryOrganic chemistrySurgeryInternal medicine

Abstract

fetched live from OpenAlex

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(SO 3 Na) 3 ]. The chemical structures of CMS and CMSS were characterized by Fourier transform infrared spectroscopy and 13 C 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 ( M w ) 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 M w of 2.61 × 10 4 had the best blood anticoagulant activities. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.269
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2012
Admission routes1
Has abstractyes

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