Classifying Raman Spectra of Extracellular Vesicles based on Convolutional Neural Networks for Prostate Cancer Detection

Since early 2000s, machine learning algorithms have been widely used in many research and industrial fields, most prominently in computer vison. Lately, many fields of study have tried to use these automated methods, and there are several reports from the field of spectroscopy. In this study, we demonstrate a classification model based on machine learning to classify Raman spectra. We obtained Raman spectra from extracellular vesicles (EVs) to find tumor derived EVs. The convolutional neural network (CNN) was trained on preprocessed Raman data and raw Raman data. We compare the result from CNN with results from principal component analysis that is widely used among in spectroscopy. The new model classifies EVs with an accuracy of >90%. Moreover, the new model based on CNN is also suitable for classifying the raw Raman data directly without preprocessing with a minimum accuracy of 93%

Raman micro-spectroscopy for quantitative thickness measurement of nanometer thin polymer films

The sensitivity of far-field Raman micro-spectroscopy was investigated to determine quantitatively the actual thickness of organic thin films. It is shown that the thickness of organic films can be quantitatively determined down to 3 nm with an error margin of 20% and down to 1.5 nm with an error margin of 100%. Raman imaging of thin-film surfaces with a far-field optical microscope establishes the distribution of a polymer with a lateral resolution of ~400 nm and the homogeneity of the film. Raman images are presented for spin-coated thin films of polysulfone (PSU) with average thicknesses between 3 and 50 nm. In films with an average thickness of 43 nm, the variation in thickness was around 5% for PSU. In films with an average thickness of 3 nm for PSU, the detected thickness variation was 100%. Raman imaging was performed in minutes for a surface area of 900 µm2. The results illustrate the ability of far-field Raman microscopy as a sensitive method to quantitatively determine the thickness of thin films down to the nanometer range

Changes in human milk lipid composition and conformational state during a single breastfeed

Fat in human milk forms the main energy source for infants and is the most variable component in terms of concentration and composition. Knowledge on changes in human milk lipid composition and conformational state during a single breastfeed contributes to an in-depth understanding of lipid synthesis in the mammary gland. Therefore, the objective of this study was to evaluate the differences in fatty acid length, degree of unsaturation (lipid composition) and lipid phase (lipid conformational state) of milk released at different stages during a breastfeed (fore-, bulk- and hindmilk). A total of 30 samples from 10 lactating subjects were investigated using confocal Raman spectroscopy. No significant differences in lipid composition were observed between fore-, bulk- and hindmilk samples, which is consistent with literature. A new finding from this study is that the lipid conformational state in human fore-, bulk- and hindmilk was significantly different at room temperature. The lipid phase of foremilk was almost crystalline and the lipid phase of hindmilk was almost liquid. Based on this observation, we hypothesize that lipid synthesis in the mammary gland changes during a single breastfeed

Suspended sediment prolongs larval development in a coral reef fish

Increasing sediment input into coastal environments is having a profound influence on shallow marine habitats and associated species. Coral reef ecosystems appear to be particularly sensitive, with increased sediment deposition and re-suspension being associated with declines in the abundance and diversity of coral reef fishes. While recent research has demonstrated that suspended sediment can have negative impacts on post-settlement coral reef fishes, its effect on larval development has not been investigated. In this study, we tested the effects of different levels of suspended sediment on larval growth and development time in Amphiprion percula, a coral reef damselfish. Larvae were subjected to four experimental concentrations of suspended sediment spanning the range found around coastal coral reefs (0–45 mg l−1). Larval duration was significantly longer in all sediment treatments (12 days) compared with the average larval duration in the control treatment (11 days). Approximately 75% of the fish in the control had settled by day 11, compared with only 40–46% among the sediment treatments. In the highest sediment treatment, some individuals had a larval duration twice that of the median duration in the control treatment. Unexpectedly, in the low sediment treatment, fish at settlement were significantly longer and heavier compared with fish in the other treatments, suggesting delayed development was independent of individual condition. A sediment-induced extension of the pelagic larval stage could significantly reduce numbers of larvae competent to settle and, in turn, have major effects on adult population dynamics