为了开发适合吞咽困难患者食用的植物蛋白3D打印食品,本文将亚麻籽胶和魔芋胶按照质量比2:3进行复配形成复合多糖,并与豌豆分离蛋白(Pea protein isolate,PPI)进行剪切处理,探究了不同浓度的复合多糖(0.5%、0.7%、0.9%、1.1%和1.3%)对...为了开发适合吞咽困难患者食用的植物蛋白3D打印食品,本文将亚麻籽胶和魔芋胶按照质量比2:3进行复配形成复合多糖,并与豌豆分离蛋白(Pea protein isolate,PPI)进行剪切处理,探究了不同浓度的复合多糖(0.5%、0.7%、0.9%、1.1%和1.3%)对乳液凝胶粒径、流变学特性和3D打印性能的影响。并通过国际吞咽障碍标准化倡议(IDDSI)对乳液凝胶进行评估。结果表明:不同浓度的复合多糖改善乳液凝胶的效果不同。粒径测试表明随着复合多糖浓度的增加,PPI乳液凝胶的粒径呈现减小的趋势。流变学特性表明多糖的加入使PPI乳液凝胶具有粘弹性,且所有的乳液凝胶样品均显示出G'>G''。当复合多糖浓度为1.1%时,乳液凝胶的粒径最小,G'和G''值最高,粘弹性最好,打印的产品具有最清晰的纹理、最稳定的结构和较好的印刷适应性。IDDSI测试表明添加1.1%和1.3%浓度复合多糖的乳液凝胶可归类为Ⅳ级过渡性食品。综上所述,1.1%浓度的复合多糖对豌豆分离蛋白乳液凝胶3D打印性能的改善最显著,这为开发植物基3D打印油墨提供理论依据。展开更多
Cancer deaths and new cases worldwide are projected to rise by 47%by 2040,with transitioning countries experiencing an even higher increase of up to 95%.Tumor severity is profoundly influenced by the timing,accuracy,a...Cancer deaths and new cases worldwide are projected to rise by 47%by 2040,with transitioning countries experiencing an even higher increase of up to 95%.Tumor severity is profoundly influenced by the timing,accuracy,and stage of diagnosis,which directly impacts clinical decision-making.Various biological entities,including genes,proteins,mRNAs,miRNAs,and metabolites,contribute to cancer development.The emergence of multi-omics technologies has transformed cancer research by revealing molecular alterations across multiple biological layers.This integrative approach supports the notion that cancer is fundamentally driven by such alterations,enabling the discovery ofmolecular signatures for precision oncology.This reviewexplores the role of AI-drivenmulti-omics analyses in cancer medicine,emphasizing their potential to identify novel biomarkers and therapeutic targets,enhance understanding of Tumor biology,and address integration challenges in clinical workflows.Network biology analyzes identified ERBB2,KRAS,and TP53 as top hub genes in lung cancer based on Maximal Clique Centrality(MCC)scores.In contrast,TP53,ERBB2,ESR1,MYC,and BRCA1 emerged as central regulators in breast cancer,linked to cell proliferation,hormonal signaling,and genomic stability.The review also discusses how specific Artificial Intelligence(AI)algorithms can streamline the integration of heterogeneous datasets,facilitate the interpretation of the tumor microenvironment,and support data-driven clinical strategies.展开更多
文摘为了开发适合吞咽困难患者食用的植物蛋白3D打印食品,本文将亚麻籽胶和魔芋胶按照质量比2:3进行复配形成复合多糖,并与豌豆分离蛋白(Pea protein isolate,PPI)进行剪切处理,探究了不同浓度的复合多糖(0.5%、0.7%、0.9%、1.1%和1.3%)对乳液凝胶粒径、流变学特性和3D打印性能的影响。并通过国际吞咽障碍标准化倡议(IDDSI)对乳液凝胶进行评估。结果表明:不同浓度的复合多糖改善乳液凝胶的效果不同。粒径测试表明随着复合多糖浓度的增加,PPI乳液凝胶的粒径呈现减小的趋势。流变学特性表明多糖的加入使PPI乳液凝胶具有粘弹性,且所有的乳液凝胶样品均显示出G'>G''。当复合多糖浓度为1.1%时,乳液凝胶的粒径最小,G'和G''值最高,粘弹性最好,打印的产品具有最清晰的纹理、最稳定的结构和较好的印刷适应性。IDDSI测试表明添加1.1%和1.3%浓度复合多糖的乳液凝胶可归类为Ⅳ级过渡性食品。综上所述,1.1%浓度的复合多糖对豌豆分离蛋白乳液凝胶3D打印性能的改善最显著,这为开发植物基3D打印油墨提供理论依据。
基金funded by KAU Endowment(WAQF)at King Abdulaziz University,Jeddah,Saudi Arabia.
文摘Cancer deaths and new cases worldwide are projected to rise by 47%by 2040,with transitioning countries experiencing an even higher increase of up to 95%.Tumor severity is profoundly influenced by the timing,accuracy,and stage of diagnosis,which directly impacts clinical decision-making.Various biological entities,including genes,proteins,mRNAs,miRNAs,and metabolites,contribute to cancer development.The emergence of multi-omics technologies has transformed cancer research by revealing molecular alterations across multiple biological layers.This integrative approach supports the notion that cancer is fundamentally driven by such alterations,enabling the discovery ofmolecular signatures for precision oncology.This reviewexplores the role of AI-drivenmulti-omics analyses in cancer medicine,emphasizing their potential to identify novel biomarkers and therapeutic targets,enhance understanding of Tumor biology,and address integration challenges in clinical workflows.Network biology analyzes identified ERBB2,KRAS,and TP53 as top hub genes in lung cancer based on Maximal Clique Centrality(MCC)scores.In contrast,TP53,ERBB2,ESR1,MYC,and BRCA1 emerged as central regulators in breast cancer,linked to cell proliferation,hormonal signaling,and genomic stability.The review also discusses how specific Artificial Intelligence(AI)algorithms can streamline the integration of heterogeneous datasets,facilitate the interpretation of the tumor microenvironment,and support data-driven clinical strategies.
