raman imaging
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2022 ◽  
Vol 811 ◽  
pp. 152409
Author(s):  
Yunlong Luo ◽  
Christopher T. Gibson ◽  
Youhong Tang ◽  
Ravi Naidu ◽  
Cheng Fang
Keyword(s):  

2022 ◽  
Author(s):  
Jan Rix ◽  
Michael Rüsing ◽  
Roberta Galli ◽  
Jonas Golde ◽  
Sven Reitzig ◽  
...  

Nanoscale ◽  
2022 ◽  
Author(s):  
Da Li ◽  
Philippe Nizard ◽  
Delphine Onidas ◽  
Aazdine Lamouri ◽  
Jean Pinson ◽  
...  

The surface functionalization of silver nanoparticles (NPs) by Raman reporters has stimulated a wide interest in recent years for the design of Surface-Enhanced Raman Spectroscopy (SERS) labels. However, silver NPs...


2022 ◽  
pp. 118857
Author(s):  
Yunlong Luo ◽  
Md Al Amin ◽  
Christopher T. Gibson ◽  
Clarence Chuah ◽  
Youhong Tang ◽  
...  
Keyword(s):  

Author(s):  
Prakash Muthudoss ◽  
Satheesh Kumar ◽  
Eddy Yii Chung Ann ◽  
Kwok Jia Young ◽  
Rayce Lim Rui Chi ◽  
...  
Keyword(s):  

2021 ◽  
Vol 12 ◽  
Author(s):  
Peter Bock ◽  
Martin Felhofer ◽  
Konrad Mayer ◽  
Notburga Gierlinger

The cuticle covers almost all plant organs as the outermost layer and serves as a transpiration barrier, sunscreen, and first line of defense against pathogens. Waxes, fatty acids, and aromatic components build chemically and structurally diverse layers with different functionality. So far, electron microscopy has elucidated structure, while isolation, extraction, and analysis procedures have revealed chemistry. With this method paper, we close the missing link by demonstrating how Raman microscopy gives detailed information about chemistry and structure of the native cuticle on the microscale. We introduce an optimized experimental workflow, covering the whole process of sample preparation, Raman imaging experiment, data analysis, and interpretation and show the versatility of the approach on cuticles of a spruce needle, a tomato peel, and an Arabidopsis stem. We include laser polarization experiments to deduce the orientation of molecules and multivariate data analysis to separate cuticle layers and verify their molecular composition. Based on the three investigated cuticles, we discuss the chemical and structural diversity and validate our findings by comparing models based on our spectroscopic data with the current view of the cuticle. We amend the model by adding the distribution of cinnamic acids and flavonoids within the cuticle layers and their transition to the epidermal layer. Raman imaging proves as a non-destructive and fast approach to assess the chemical and structural variability in space and time. It might become a valuable tool to tackle knowledge gaps in plant cuticle research.


Author(s):  
Nicolas Neidert ◽  
Jakob Straehle ◽  
Daniel Erny ◽  
Vlad Sacalean ◽  
Amir El Rahal ◽  
...  

AbstractHistopathological diagnosis is the current standard for the classification of brain and spine tumors. Raman spectroscopy has been reported to allow fast and easy intraoperative tissue analysis. Here, we report data on the intraoperative implementation of a stimulated Raman histology (SRH) as an innovative strategy offering intraoperative near real-time histopathological analysis. A total of 429 SRH images from 108 patients were generated and analyzed by using a Raman imaging system (Invenio Imaging Inc.). We aimed at establishing a dedicated workflow for SRH serving as an intraoperative diagnostic, research, and quality control tool in the neurosurgical operating room (OR). First experiences with this novel imaging modality were reported and analyzed suggesting process optimization regarding tissue collection, preparation, and imaging. The Raman imaging system was rapidly integrated into the surgical workflow of a large neurosurgical center. Within a few minutes of connecting the device, the first high-quality images could be acquired in a “plug-and-play” manner. We did not encounter relevant obstacles and the learning curve was steep. However, certain prerequisites regarding quality and acquisition of tissue samples, data processing and interpretation, and high throughput adaptions must be considered. Intraoperative SRH can easily be integrated into the workflow of neurosurgical tumor resection. Considering few process optimizations that can be implemented rapidly, high-quality images can be obtained near real time. Hence, we propose SRH as a complementary tool for the diagnosis of tumor entity, analysis of tumor infiltration zones, online quality and safety control and as a research tool in the neurosurgical OR.


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