Project description:In recent years, vibrational spectroscopic techniques based on Fourier transform infrared (FTIR) or Raman microspectroscopy have been suggested to fulfill the unmet need for microplastic particle detection and identification. Inter-system comparison of spectra from reference polymers enables assessing the reproducibility between instruments and advantages of emerging quantum cascade laser-based optical photothermal infrared (O-PTIR) spectroscopy. In our work, IR and Raman spectra of nine plastics, namely polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, polycarbonate, polystyrene, silicone, polylactide acid and polymethylmethacrylate were simultaneously acquired using an O-PTIR microscope in non-contact, reflection mode. Comprehensive band assignments were presented. We determined the agreement of O-PTIR with standalone attenuated total reflection FTIR and Raman spectrometers based on the hit quality index (HQI) and introduced a two-dimensional identification (2D-HQI) approach using both Raman- and IR-HQIs. Finally, microplastic particles were prepared as test samples from known materials by wet grinding, O-PTIR data were collected and subjected to the 2D-HQI identification approach. We concluded that this framework offers improved material identification of microplastic particles in environmental, nutritious and biological matrices.
Project description:Caffeine is the most widely consumed stimulant and is the subject of significant ongoing research and discussions due to its impact on human health. The industry's need to comply with country-specific food and beverage regulations underscores the importance of monitoring caffeine levels in commercial products. In this study, we propose an alternative technique for caffeine analysis that relies on mid-infrared laser-based photothermal spectroscopy (PTS). PTS exploits the high-power output of the quantum cascade laser (QCL) sources to enhance the sensitivity of the mid-IR measurement. The laser-induced thermal gradient in the sample scales with the analytes' absorption coefficient and concentration, thus allowing for both qualitative and quantitative assessment. We evaluated the performance of our experimental PTS spectrometer, incorporating a tunable QCL and a Mach-Zehnder interferometer, for detecting caffeine in coffee, black tea, and an energy drink. We calibrated the setup with caffeine standards (0.1-2.5 mg mL-1) and we benchmarked the setup's capabilities against gas chromatography (GC) and Fourier-transform infrared (FTIR) spectroscopy. Quantitative results aligned with GC analysis, and limits of detection matched the research-grade FTIR spectrometer, indicating an excellent performance of our custom-made instrument. This method offers an alternative to established techniques, providing a platform for fast, sensitive, and non-destructive analysis without consumables as well as with high potential for miniaturization.
Project description:The aim of this study is to produce and characterize glass materials, which have an enhanced antibacterial property by the conventional melting method. Container glass compositions including different amounts of zinc oxide (ZnO) (5.0, 7.5, and 10.0%) were prepared and melted to be able to obtain the antibacterial glass. The Release and antibacterial tests, which were performed after the melting process, showed that the glass doped with 5% ZnO was the most appropriate composition according to test results (99.82% Escherichia coli inactivation) and its raw materials' costs. Physical, thermal, and mechanical properties such as thermal expansion coefficient (86.1 × 10-7/°C), density (2.523 g/cm3), refractive index (1.5191), hardness (596 kg/mm2), and elastic modulus (5.84 GPa) of the glass doped with 5% ZnO were determined, and the results showed that the obtained antibacterial glass sample is suitable to be used as a glass container. HighTemperature Melting Observation System studies were performed on the produced antibacterial glass composition, and it was found that the antibacterial glass can be produced in soda lime glass furnaces without changing any furnace design and production parameters. This antibacterial glass can be a remarkable product for the pharmaceutical and food industries.
Project description:Microplastics are particulate water contaminants that are raising concerns regarding their environmental and health impacts. Optical spectroscopy is the gold standard for their detection; however, it has severe limitations such as tens of hours of analysis time and spatial resolution of more than 10 μm, when targeting the production of a 2D map of the microparticle population. In this work, through a single spectrum acquisition, we aim at quickly getting information about the whole population of identical particles, their chemical nature, and their size in a range below 20 μm. To this end, we built a compact setup enabling both attenuated total reflection Fourier transform infrared (ATR-FTIR) and Raman spectroscopy measurement on the same sample for comparison purposes. We used monodisperse polystyrene and poly(methyl methacrylate) microplastic spheres of sizes ranging between 6 and 20 μm, also measured collectively using a bench-top FTIR spectrometer in ATR mode. The ATR-FTIR technique appears to be more sensitive for the smallest particles of 6 μm, while the opposite trend is observed using Raman spectroscopy. We use theoretical modeling to simulate and explain the ripples observed in the measured spectra at the shortest wavelength (higher wavenumber) region, which appears as an indicator of the microparticle dimension. The latter finding opens new perspectives for ATR-FTIR for the identification and classification of populations of nearly identical micro-scale bodies, such as bacteria and other micro-organisms, where the same measured spectrum embeds dual information about the chemical nature and the size.
Project description:Background and objectivesNot all fluids may be equally beneficial for reducing the risk of kidney stones. In particular, it is not clear whether sugar and artificially sweetened soda increase the risk.Design, setting, participants, & measurementsWe prospectively analyzed the association between intake of several types of beverages and incidence of kidney stones in three large ongoing cohort studies. Information on consumption of beverages and development of kidney stones was collected by validated questionnaires.ResultsThe analysis involved 194,095 participants; over a median follow-up of more than 8 years, 4462 incident cases occurred. There was a 23% higher risk of developing kidney stones in the highest category of consumption of sugar-sweetened cola compared with the lowest category (P for trend=0.02) and a 33% higher risk of developing kidney stones for sugar-sweetened noncola (P for trend=0.003); there was a marginally significant higher risk of developing kidney stones for artificially sweetened noncola (P for trend=0.05). Also, there was an 18% higher risk for punch (P for trend=0.04) and lower risks of 26% for caffeinated coffee (P for trend<0.001), 16% for decaffeinated coffee (P for trend=0.01), 11% for tea (P for trend=0.02), 31%-33% for wine (P for trend<0.005), 41% for beer (P for trend<0.001), and 12% for orange juice (P for trend=0.004).ConclusionsConsumption of sugar-sweetened soda and punch is associated with a higher risk of stone formation, whereas consumption of coffee, tea, beer, wine, and orange juice is associated with a lower risk.
Project description:The identification of microplastics becomes increasingly challenging with decreasing particle size and increasing sample heterogeneity. The analysis of microplastic samples by Fourier transform infrared (FTIR) spectroscopy is a versatile, bias-free tool to succeed at this task. In this study, we provide an adaptable reference database, which can be applied to single-particle identification as well as methods like chemical imaging based on FTIR microscopy. The large datasets generated by chemical imaging can be further investigated by automated analysis, which does, however, require a carefully designed database. The novel database design is based on the hierarchical cluster analysis of reference spectra in the spectral range from 3600 to 1250 cm-1. The hereby generated database entries were optimized for the automated analysis software with defined reference datasets. The design was further tested for its customizability with additional entries. The final reference database was extensively tested on reference datasets and environmental samples. Data quality by means of correct particle identification and depiction significantly increased compared to that of previous databases, proving the applicability of the concept and highlighting the importance of this work. Our novel database provides a reference point for data comparison with future and previous microplastic studies that are based on different databases. Graphical abstract ᅟ.
Project description:The presence of microplastics (MPs) in processed seafood is a growing concern. In this study, 33 different canned fish brands belonging to seven producers were purchased from the Turkish market and investigated. MPs composition, possible sources, and potential intake were assessed. Light microscopy was used to quantify potential MPs, and micro-Raman microscopy was used to identify the polymer types. The results showed that all the samples had at least one MPs particle, and fragments were the most abundant (57.3%) shape of MPs. Polyolefin (21.88%) was the most common polymer type. The results showed that packaging and the production processes are the main possible sources of MPs. Human intake estimation risk is relatively lower since canned fish consumption is relatively low. The findings suggest that the risk related to MPs in canned fish should be considered one of the components of food safety management systems.
Project description:BackgroundMicroplastics (MPs) are omnipresent in the environment, including the human food chain; a likely important contributor to human exposure is drinking water.ObjectiveTo undertake a systematic review of MP contamination of drinking water and estimate quantitative exposures.MethodsThe protocol for the systematic review employed has been published in PROSPERO (PROSPERO 2019, Registration number: CRD42019145290). MEDLINE, EMBASE and Web of Science were searched from launch to the 3rd of June 2020, selecting studies that used procedural blank samples and a validated method for particle composition analysis. Studies were reviewed within a narrative analysis. A bespoke risk of bias (RoB) assessment tool was used.Results12 studies were included in the review: six of tap water (TW) and six of bottled water (BW). Meta-analysis was not appropriate due to high statistical heterogeneity (I2>95%). Seven studies were rated low RoB and all confirmed MP contamination of drinking water. The most common polymers identified in samples were polyethylene terephthalate (PET) and polypropylene (PP), Methodological variability was observed throughout the experimental protocols. For example, the minimum size of particles extracted and analysed, which varied from 1 to 100 μm, was seen to be critical in the data reported. The maximum reported MP contamination was 628 MPs/L for TW and 4889 MPs/L for BW, detected in European samples. Based on typical consumption data, this may be extrapolated to a maximum yearly human adult uptake of 458,000 MPs for TW and 3,569,000 MPs for BW.ConclusionsThis is the first systematic review that appraises the quality of existing evidence on MP contamination of drinking water and estimates human exposures. The precautionary principle should be adopted to address concerns on possible human health effects from consumption of MPs. Future research should aim to standardise experimental protocols to aid comparison and elevate quality.
Project description:Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, 'BrainSignals'. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors.