Psychological significance in the COVID19 pandemic worldwide Review of your unique matter

The annual amount of food waste or loss is about one-third of the total edible food globally produced for human consumption. Continuous and real-time monitoring by spoilage detectors can significantly reduce food waste. A novel paper-based pH-sensitive meat spoilage detector was developed. A mixture of soybean hulls (SBHs) (hydrothermally-treated in an acidic environment), bentonite, and bromocresol purple (BCP) was coated on paper to produce the detector. The resultant meat spoilage detector was evaluated as a real-time freshness and spoilage indicator of catfish fillets (Ictalurus punctatus). Freshness and spoilage of fish meat with varying weights and headspace were determined by tailoring the detector's pH. Elemental, structural, and functional analysis verified the formation of a packed SBH-bentonite matrix with enhanced gas adsorption capacity and effective BCP-immobilization. Binder nanofibrillation increased the overall visual color vibrancy and decreased the binder demand in the coating formulation. Headspace volume in the studied range (40 and 160 cm3) did not affect the activation time of the detectors. However, increasing fish weight decreased the detectors' optimum activation time and pH. The findings of this study show that the developed detectors can be tailored for a wide range of sample and packaging sizes by simply adjusting the pH of the detector.Plasticizers are chemical compounds used in the production of flexible plastics for a large variety of applications. They are present in most of the environments and, hence, we are highly exposed to them via several routes (ingestion, inhalation, etc). Due to the endocrine disruption potential of some of these chemicals and the unknown toxicological effects of their alternatives, assessing human exposure to these contaminants is an issue of emerging concern. Herein we propose an analytical methodology for the determination of several plasticizer metabolites in wastewater as a non-invasive, cheap, and fast exposure monitoring tool complementary to the analysis of urine. A solid-phase extraction procedure followed by an ultra(high)-performance liquid chromatography-tandem mass spectrometry method was optimized and validated for 21 analytes among phthalate, terephthalate, and di-iso-nonyl cyclohexane-1,2-dicarboxylate metabolites. Method quantification limits ranged from 0.079 to 4.4 ng L-1. The method was applied to the analysis of seven daily composite wastewater samples collected in the NW of Spain. Metabolites of low molecular weight phthalates and of di-2-ethylhexyl phthalate were quantified in all samples, despite the existing regulations limiting the use of phthalates. Metabolites of terephthalates, introduced at the end of the 20th century as phthalate substituents, were also quantified in all samples, being the first time that they were detected in this matrix. Exposure back-calculation highlighted di-2-ethylhexyl terephthalate as the second most common plastic additive after diethyl phthalate in the population considered, reflecting the increasing substitution of di-2-ethylhexyl phthalate by its analogous terephthalate.A new procedure is described for the determination of Hg2+ ions in water samples. A Rhodamine based fluorescent sensor was synthesized and the experimental conditions were specifically optimized for application to environmental samples, which requires low detection limits and high selectivity in competitive experiments with realistic concentrations of other metal ions. Incorporation of a Rhodamine-6G fluorophore to a previously described sensor and optimization of the buffer system (detection with acetic acid at pH 5.25) enabled significant enhancement of the sensitivity (detection limit = 0.27 μg L-1) and selectivity. The optimized procedure using high-throughput microplates has been applied to tap and river waters with good results.This study utilizes advanced wavenumber selection techniques to improve the prediction of amylose content in grounded rice samples with near-infrared spectroscopy. Four different wavenumber selection techniques, i.e. covariate selection (CovSel), variable combination population analysis (VCPA), bootstrapping soft shrinkage (BOSS) and variable combination population analysis-iteratively retains informative variables (VCPA-IRIV), were used for model optimization and key wavenumbers selection. The results of the several wavenumber selection techniques were compared with the predictions reported previously on the same data set. All the four wavenumber selection techniques improved the predictive performance of amylose in rice samples. The best performance was obtained with VCPA, where, with only 11 wavenumbers-based model, the prediction error was reduced by 19% compared to what reported previously on the same data set. The selected wavenumbers can help in development of low-cost multi-spectral sensors for amylose prediction in rice samples.Quantification of volatile organoselenium species released by Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), after their growth in the presence of 1 and 2 mg Se·L-1 as both selenite and chitosan-modified selenium nanoparticles (Ch-SeNPs), was achieved by the application of a method based on headspace solid-phase microextraction (HS-SPME) and in-fiber internal standardization, combined with gas chromatography coupled to mass spectrometry (GC-MS). learn more This method consisted of an initial extraction of the released volatile organoselenium compounds on the SPME fiber, followed by the extraction of internal standard (IS), deuterated dimethyl sulfide (d6-DMS), on the same fiber before its desorption at the injection port of GC-MS. The results showed that the biotransformation of selenite and Ch-SeNPs into volatile organoselenium compounds was dependent on both the type of bacterial species and the chemical form of selenium (Se) administered. In this sense, E. coli was able to biotransform both selenite and Ch-SeNPs into dimethylselenium (DMSe) and dimethyldiselenium (DMDSe) while S. aureus, biotransformed selenite into DMSe and DMDSe and, Ch-SeNPs only into DMDSe. Additionally, the formation of a volatile mixed sulfur/selenium compound, dimethyl selenenyl sulfide (DMSeS), from Se in nanoparticulated form has been detected for the first time.