Nondestructive Extraction and Identification of Microplastics from Freshwater Sport Fish Stomachs

Microplastics were extracted from freshwater sport fish stomachs containing substantial biomass and identified using optical microscopy, scanning electron microscopy plus energy-dispersive X-ray spectroscopy (SEM/EDS), and Fourier transform infrared (FTIR) micro-spectroscopy with automated spectral mapping. An extraction method is presented that uses a negatively pressurized sieve stack and purified water to preserve plastic surface characteristics and any adsorbed persistent organic pollutants (POPs). This nondestructive extraction method for large predators' stomachs enables multiple trophic-level studies from one fish sampling event and provides other dietary and behavioral data. FTIR-identified microplastics 50-1500 μm, including polyethylene (two with plastic additive POPs), styrene acrylonitrile, polystyrene, and nylon and polyethylene terephthalate fibers 10-50 μm wide. SEM/EDS revealed characteristic surface weathering on the plastic surfaces. The nylon fibers appear to be from human fishing activities, suggesting options for management. Some particles visually identified as potential plastics were revealed by micro-spectroscopy to be mineralized, natural polyamide proteins, or nonplastic shell pieces. A low-cost, reflective sample preparation method with stable particle mounting was developed to enable automated mapping, improved FTIR throughput, and lower detection size limit. This study yielded 37 intact prey items set aside for future analyses.

Molecular Structural Changes in Alfalfa Detected by ATR-FTIR Spectroscopy in Response to Silencing of TT8 and HB12 Genes

This study investigated the spectral changes in alfalfa molecular structures induced by silencing of Transparent Testa 8 (TT8) and Homeobox 12 (HB12) genes with univariate and multivariate analyses. TT8-silenced (TT8i), HB12-silenced (HB12i) and wild type (WT) alfalfa were grown in a greenhouse under normal conditions and were harvested at early-to-mid vegetative stage. Samples were free-dried and grounded through 0.02 mm sieve for spectra collections with attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. Afterwards, both univariate and multivariate analyses were conducted on amide, carbohydrate and lipid regions. Univariate results showed that silencing of TT8 and HB12 genes affected peak heights of most total carbohydrate (TC) and structural carbohydrate (STC), and structural carbohydrate area (STCA) in carbohydrate regions; and β-sheet height, amide areas, and ratios of amide I/II and α-helix/β-sheet in amide region; and symmetric CH2 (SyCH2), asymmetric CH2 (AsCH2) and (a)symmetric CH2 and CH3 area (ASCCA) in the lipid region. Multivariate analysis showed that both hierarchy cluster analysis (HCA) and principal component analysis (PCA) clearly separated WT from transgenic plants in all carbohydrate regions and (a)symmetric CH2 and CH3 (ASCC) lipid region. In the amide region, PCA separated WT, TT8i and HB12i into different groups, while HCA clustered WT into a separate group. In conclusion, silencing of TT8 and HB12 affected intrinsic molecular structures of both amide and carbohydrate profiles in alfalfa, and multivariate analyses successfully distinguished gene-silenced alfalfa from its parental WT control.

Investigation of Dielectric Properties of Polymers and their Discrimination Using Terahertz Time-Domain Spectroscopy with Principal Component Analysis

Polymers are among the most commonly used materials in our everyday life. They are generally transparent to terahertz (THz) radiation, but are quite difficult to differentiate using optical techniques as few or no characteristic features exist in the spectral range of <2.0 THz for small and portable radiation systems. In this work, we report experimental measurement of refractive indices and absorption coefficients of styrene acrylonitrile (SAN) and Bakelite in the spectral range of 0.2-2.0 THz for the first time. Additionally, we demonstrate that by combining principle component analysis (PCA) with THz time-domain spectroscopy one can differentiate such polymers. In this analysis, the first three principle components PC1, PC2, and PC3 depict >94% variance with a distribution of 72.45%, 11.52%, and 9.38%, respectively.