FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4324100041> ?p ?o ?g. }

• W4324100041 abstract "Abstract OBJECTIVE To innovatively developed a macrophage-target nanoparticle based contrast-enhanced high-resolution magnetic resonance vessel wall imaging (HR-VWI) strategy to characterize the plaques’ vulnerable features on rabbits. BACKGROUND Lacking of sensitive and specific image-marker of HR-VWI leads this technique depending upon the plaque morphological characteristics. Nanoparticle-based contrast agents modified with targeting ligands allow amplifying MR signals of the interested components. The key to successful translation is the requirement that conducting studies in larger animals to provide reasonable diagnostic readouts. METHODS The HR-VWI enhanced with macrophage-targeted PP1-Au@GSH@Gd (GdMG) nanoclusters (NCs) and the conventional Gadovist were utilized for the plaque vulnerability evaluation by a systematic histogram analysis in atherosclerosis (AS) rabbit model. RESULTS Due to the compelling targeting capacity of GdMG NCs to foamy macrophages, the contrast-to-noise ratio (CNR) from pre-injection baseline dramatically raised from 6.50 to 36.91 ( p < 0.001), with an increment of 1.39-fold higher than that of the Gadovist approach. Spearman’ s correlation test confirmed that the coefficient of variation (CV) derived from the histogram analysis based on GdMG NCs HR-VWI was indeed positively linearly correlated with pathology vulnerability index (VI P ) significantly ( p < 0.05) with adjusted R 2 = 0.775. Finally, mathematic formulas with histogram-derived parameters as variables were fitted to quantitatively calculate the histogram vulnerability index (VI H ) with the strength of the adjusted R 2 = 0.952 ( p < 0.001), and Area under the curve (AUC) of 0.875 ( p < 0.001) to realize the in vivo and quantitative calculation of the plaque vulnerability. CONCLUSION Profiting from the splendid inflammation targeted capacity and excellent MRI performance of GdMG NCs, as well as the highly quantitative characteristics of histogram analysis, we disclosed that our established imaging protocol was able to identify the plaques’ vulnerability index that were comparable to pathological examinations in both retrospective and prospective experiments." @default.
• W4324100041 created "2023-03-14" @default.
• W4324100041 creator A5005098292 @default.
• W4324100041 creator A5008149388 @default.
• W4324100041 creator A5017956469 @default.
• W4324100041 creator A5021768967 @default.
• W4324100041 creator A5029625530 @default.
• W4324100041 creator A5031804038 @default.
• W4324100041 creator A5033684035 @default.
• W4324100041 creator A5034558590 @default.
• W4324100041 creator A5042913977 @default.
• W4324100041 creator A5070286881 @default.
• W4324100041 creator A5076807070 @default.
• W4324100041 date "2023-03-13" @default.
• W4324100041 modified "2023-09-28" @default.
• W4324100041 title "Sophisticated Prediction of Carotid-Plaque Vulnerability by Nanocluster Sensitized High-resolution Vessel-Wall-Imaging Profile in Rabbit Atherosclerotic Model" @default.
• W4324100041 cites W1986805734 @default.
• W4324100041 cites W2019632342 @default.
• W4324100041 cites W2161739492 @default.
• W4324100041 cites W2498943185 @default.
• W4324100041 cites W2548106059 @default.
• W4324100041 cites W2610518082 @default.
• W4324100041 cites W2612214598 @default.
• W4324100041 cites W2748877250 @default.
• W4324100041 cites W2776534022 @default.
• W4324100041 cites W2790654167 @default.
• W4324100041 cites W2805846806 @default.
• W4324100041 cites W2896830913 @default.
• W4324100041 cites W2922099742 @default.
• W4324100041 cites W2927941727 @default.
• W4324100041 cites W2940867807 @default.
• W4324100041 cites W2954437881 @default.
• W4324100041 cites W2965080641 @default.
• W4324100041 cites W3001771035 @default.
• W4324100041 cites W3008482685 @default.
• W4324100041 cites W3036445380 @default.
• W4324100041 cites W3047616033 @default.
• W4324100041 cites W3093446383 @default.
• W4324100041 cites W3094971534 @default.
• W4324100041 cites W3102573615 @default.
• W4324100041 cites W3108231579 @default.
• W4324100041 cites W3131249572 @default.
• W4324100041 cites W4304842861 @default.
• W4324100041 doi "https://doi.org/10.1101/2023.03.09.23287077" @default.
• W4324100041 hasPublicationYear "2023" @default.
• W4324100041 type Work @default.
• W4324100041 citedByCount "0" @default.
• W4324100041 crossrefType "posted-content" @default.
• W4324100041 hasAuthorship W4324100041A5005098292 @default.
• W4324100041 hasAuthorship W4324100041A5008149388 @default.
• W4324100041 hasAuthorship W4324100041A5017956469 @default.
• W4324100041 hasAuthorship W4324100041A5021768967 @default.
• W4324100041 hasAuthorship W4324100041A5029625530 @default.
• W4324100041 hasAuthorship W4324100041A5031804038 @default.
• W4324100041 hasAuthorship W4324100041A5033684035 @default.
• W4324100041 hasAuthorship W4324100041A5034558590 @default.
• W4324100041 hasAuthorship W4324100041A5042913977 @default.
• W4324100041 hasAuthorship W4324100041A5070286881 @default.
• W4324100041 hasAuthorship W4324100041A5076807070 @default.
• W4324100041 hasBestOaLocation W43241000411 @default.
• W4324100041 hasConcept C115961682 @default.
• W4324100041 hasConcept C126838900 @default.
• W4324100041 hasConcept C138010386 @default.
• W4324100041 hasConcept C142724271 @default.
• W4324100041 hasConcept C143409427 @default.
• W4324100041 hasConcept C143753070 @default.
• W4324100041 hasConcept C154945302 @default.
• W4324100041 hasConcept C171250308 @default.
• W4324100041 hasConcept C185592680 @default.
• W4324100041 hasConcept C192562407 @default.
• W4324100041 hasConcept C202751555 @default.
• W4324100041 hasConcept C2778402822 @default.
• W4324100041 hasConcept C2778710248 @default.
• W4324100041 hasConcept C2779244956 @default.
• W4324100041 hasConcept C2989005 @default.
• W4324100041 hasConcept C41008148 @default.
• W4324100041 hasConcept C53533937 @default.
• W4324100041 hasConcept C55493867 @default.
• W4324100041 hasConcept C64012434 @default.
• W4324100041 hasConcept C71924100 @default.
• W4324100041 hasConceptScore W4324100041C115961682 @default.
• W4324100041 hasConceptScore W4324100041C126838900 @default.
• W4324100041 hasConceptScore W4324100041C138010386 @default.
• W4324100041 hasConceptScore W4324100041C142724271 @default.
• W4324100041 hasConceptScore W4324100041C143409427 @default.
• W4324100041 hasConceptScore W4324100041C143753070 @default.
• W4324100041 hasConceptScore W4324100041C154945302 @default.
• W4324100041 hasConceptScore W4324100041C171250308 @default.
• W4324100041 hasConceptScore W4324100041C185592680 @default.
• W4324100041 hasConceptScore W4324100041C192562407 @default.
• W4324100041 hasConceptScore W4324100041C202751555 @default.
• W4324100041 hasConceptScore W4324100041C2778402822 @default.
• W4324100041 hasConceptScore W4324100041C2778710248 @default.
• W4324100041 hasConceptScore W4324100041C2779244956 @default.
• W4324100041 hasConceptScore W4324100041C2989005 @default.
• W4324100041 hasConceptScore W4324100041C41008148 @default.
• W4324100041 hasConceptScore W4324100041C53533937 @default.
• W4324100041 hasConceptScore W4324100041C55493867 @default.
• W4324100041 hasConceptScore W4324100041C64012434 @default.
• W4324100041 hasConceptScore W4324100041C71924100 @default.

• next