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.
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http://dx.doi.org/10.3389/fpls.2021.793330 | DOI Listing |
Transl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
Nanotoxicology
January 2025
Institute of Physics Belgrade, University of Belgrade, Belgrade, Serbia.
In this study, we investigated the cytotoxic effect of highly soluble dextran-coated CeO nanoparticles on human fetal lung fibroblasts MRC-5. We examined individual nanoparticle-treated cells by Raman spectroscopy and analyzed Raman spectra using non-negative principal component analysis and k-means clustering. In this way, we determined dose-dependent differences between treated cells, which were reflected through the intensity change of lipid, phospholipid and RNA-related Raman modes.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Surface Physics and Department of Physics, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Fudan University, Shanghai 200433, China.
Numerous chemical reactions and most life processes occur in aqueous solutions, where the physical diffusion of small molecules plays a vital role, including solvent water molecules, solute biomolecules, and ions. Conventional methods of measuring diffusion coefficients are often limited by technical complexity, large sample consumption, or significant time cost. Here, we present an optical imaging method to study molecular diffusion by combining stimulated Raman scattering (SRS) microscopy with microfluidics: a "Y"-shaped microfluidic channel forming two laminar flows with a stable concentration gradient across the interface.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Internal Medicine and Liver Research Institute, Department of Medical Device Development, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and to evaluate the diagnostic power of Raman spectroscopy-based machine learning in gastric adenocarcinoma. Raman spectroscopy-based machine learning was applied in real-time during endoscopy in 19 patients (aged 51-85 years) with high-risk for gastric adenocarcinoma. Raman spectra were captured from suspicious lesions and adjacent normal mucosa, which were biopsied for matched histopathologic diagnosis.
View Article and Find Full Text PDFACS Photonics
January 2025
Institute of Biomedical Physics, Medical University of Innsbruck, Müllerstraße 44, 6020 Innsbruck, Austria.
Confocal Raman microscopy, a highly specific and label-free technique for the microscale study of thick samples, often presents difficulties due to weak Raman signals. Inhomogeneous samples introduce wavefront aberrations that further reduce these signals, requiring even longer acquisition times. In this study, we introduce Adaptive Optics to confocal Raman microscopy for the first time to counteract such aberrations, significantly increasing the Raman signal and image quality.
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