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Record W4252279915 · doi:10.1360/zc2012-42-3-185

隐形微球表面吸附血浆蛋白的蛋白质组学分析

2012· article· zh· W4252279915 on OpenAlexafffund
丽 李, D.Scott Mark, Le Yevgeniya, 敦成 王

Bibliographic record

VenueScientia Sinica Vitae · 2012
Typearticle
Languagezh
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsCanadian Blood ServicesUniversity of British Columbia
FundersCanadian Institutes of Health ResearchHealth CanadaMichael Smith Health Research BCCanadian Blood Services
KeywordsComputer science

Abstract

fetched live from OpenAlex

细胞和生物材料表面的甲氧基聚乙二醇(mPEG)修饰是一项具有广阔应用前景的非药理性免疫调节技术, 但由于细胞的不稳定性, 目前对其表面与血浆间相互作用的认识还不够深入. 本实验采用相对稳定的乳胶微球作为模型, 来研究其表面对血浆蛋白的吸附. 结果显示, 血浆总蛋白的吸附水平随着mPEG修饰浓度和分子量的增加而降低, 未修饰的乳胶微球表面蛋白吸附量为(159.9±6.4) ng/cm<sup>2</sup>, mPEG 修饰后, 蛋白吸附量分别下降至(18.4±0.8) ng/cm<sup>2</sup>(1 mmol/L 2 kD SCmPEG)和(52.3±5.3) ng/cm<sup>2</sup>(1 mmol/L 20 kD SCmPEG). 聚炳烯酰胺凝胶电泳(SDS-PAGE)和同位素标记相对和绝对定量的质谱技术(iTRAQ-MS)分析表明, 在PEG 修饰微球表面的蛋白质吸附层中, 参与免疫系统活化的蛋白质丰度明显下降. 因此, 免疫修饰细胞和材料的生物学效应是通过降低抗原性及减弱表面与大分子间相互作用来实现的.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2012
Admission routes2
Has abstractyes

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