Infrared spectrometry (IR) became a workhorse to characterize microplastics (MPs) worldwide. However, reports on the experimental conditions to measure them decreased alarmingly. As complete, ...relevant information on the instrumental setup determining IR spectra is crucial for scientific reproducibility, ca. 50% of the papers that reported FTIR to measure MPs were evaluated and it was found that most studies cannot be replicated due to missing experimental details. To ameliorate this, the most critical parameters influencing IR spectra are depicted, their impact when matching a spectrum against databases exemplified, and, following efforts from other scientific fields, a minimum information for publication of IR-related data on MPs characterization (MIPIR-MP) is proposed, along with a brief, simple paragraph to resume the most critical information to be reported. This can be used to improve the worrying figures that point out to a reproducibility crisis in the field, as disclosed by the survey.
•Studies on microplastics lack information on IR measurement setup parameters•Around 25% of published papers do not offer useful instrumental information•A lack of understanding of basic IR parameters might affect polymer identifications•The quality of reported data on microplastics is compromised•A paragraph is proposed to minimize the lack of IR instrumental information
Currently, gas chromatography is the most common analytical technique for natural gas (NG) analysis as it offers very precise results, with very low limits of detection and quantification. However, ...it has several drawbacks, such as low turnaround times and high cost per analysis, as well as difficulties for on-line implementation. With NG applications rising, mostly thanks to its reduced gaseous emissions in comparison with other fossil fuels, the necessity for more versatile, fast, and economic analytical methods has augmented. This work summarizes the latest advances to determine the composition and physico-chemical properties of regasified liquid natural gas, focusing on infrared spectroscopy-based techniques, as well as on data processing (chemometric techniques), necessary to obtain adequate predictions of NG properties.
Pollution caused by plastics and, in particular, microplastics has become a source of environmental concern for Society. Their ubiquity, with millions of tons of plastic debris spilled in both land ...and sea, requires efficient technological improvements in the ways residues are collected, handled, characterized and recycled. For reliable decision-making, dependable chemical information is essential to assess both the nature of the plastics found in the environment and their fate. In this work an efficient method to identify the polymeric composition of microplastic fragments is proposed. It combines infrared reflectance spectra and chemometric methods. A breakthrough result is that the models include polymers weathered under both dry (shoreline) and submerged (in sea water) conditions and, hence, they are very promising as a starting point for eventual practical applications. In addition, no spectral processing is required after the initial measurement.
This approach to identify microplastics in aquatic environments combines infrared measurements and multivariate data analysis to fight against (micro)plastic pollution.
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•ATR spectra yield better models than their micro reflectance counterparts.•Genetic algorithms allowed a significant reduction in the number of variables.•KNN (3 neighbours) extracted the most satisfactory predictive models.•LDA arose as the worst classification methodology.•The models included microplastics weathered under beach and sea conditions.
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•Nylon microplastics identification may be defective if weathering is neglected.•Usual databases do not contain spectra of environmentally relevant polymers.•Polyamide weathering was ...monitored and interpreted chemically.•A collection of IR indexes reflect overall weathering routes.
The EU goal to reduce marine plastic litter by ca. 30% by 2020 stressed the need to deploy analytical methods to ascertain the polymeric nature of a residue. Furthermore, as plastics age under natural conditions and usual databases do not include their weathered spectra, (micro)plastics in environmental samples may be unidentified. In this paper, polyamide (nylon) microplastics weathering was monitored because of its ubiquity in household commodities, clothes, fishery items and industry, whose residues end up frequently in the environment. Infrared spectra (ATR and microreflectance) and Scanning Electron Microscopy (SEM) images were collected periodically while exposing nylon to controlled weathering. It was seen that ATR was more sensitive than microreflectance to monitor the structural evolution of polyamide and that the spectra and the surface of weathered microplastics showed remarkable differences with the pristine material, which stresses the need for considering its evolution when identifying microplastics in environmental studies. The evolution of six band ratios related to the chemical evolution of this polymer are presented. SEM images revealed the formation of secondary microplastics at the most advanced weathering stages of polyamide.
The number of studies dealing with airborne microplastics (MPs) is increasing but sampling and sample treatment are not standardized, yet. Here, a fast and reliable method to characterize MPs is ...presented. It involves the study of two passive sampling devices to collect atmospheric bulk deposition (wet and dry deposition) and three digestion methods (two alkaline-oxidative and an oxidative) to treat the samples. The alkaline-oxidative method based on KOH and NaClO was selected for a mild organic matrix digestion. In addition, some operational parameters of a high-throughput quantum cascade laser-based infrared device (LDIR) were optimized: an effective automatic tiered approach to differentiate fibres from particles (>90 % success in validation) and a criterion to establish positive matches when comparing an unknown spectrum against the spectral database (proposed match index > 0.85). The procedural analytical recoveries were very good for particles (82–90 %) and slightly lower for fibres (62–73 %). Finally, the amount and type of MPs deposited at a sub-urban area NW Spain were evaluated. Most common polymers were Polyethylene (PE), Polypropylene (PP) and Polyethylene terephthalate (PET). The deposition rates ranged 98–1220 MP/m2/day, ca. 1.7 % of the total collected particles. More than 50 % of the total MPs deposited were in the 20–50 μm size range, whereas fibres were mostly in the 50–500 μm size range.
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•Passive sampling devices to collect atmospheric bulk deposition•An alkaline-oxidative method allows excellent recoveries for particles (82–90 %).•An automatic LDIR approach to differentiate fibres from particles (>90 % success)•An LDIR identification criterion to positive matches is proposed.•Deposition rates 98–1220 MP/m2/day (1.7 % of total collected particles)
The presence and effects of microplastics in the environment is being continuously studied, so the need for a reliable approach to ascertain the polymer/s constituting them has increased. To ...characterize them, infrared (IR) spectrometry is commonly applied, either reflectance or attenuated total reflectance (ATR). A common problem when considering field samples is their weathering and biofouling, which modify their spectra. Hence, relying on spectral matching between the unknown spectrum and spectral databases is largely defective. In this paper, the use of IR spectra combined with pattern recognition techniques (principal components analysis, classification and regression trees and support vector classification) is explored first time to identify a collection of typical polymers regardless of their ageing. Results show that it is possible to identify them using a reduced suite of spectral wavenumbers with coherent chemical meaning. The models were validated using two datasets containing artificially weathered polymers and field samples.
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•Weathered polymers can be identified using a reduced suite of IR wavenumbers.•In most cases 10 variables were selected out of 3400 spectral wavenumbers.•Models were validated using a weathering series and field samples.•The best model used SVM and ATR wavenumbers from the most relevant loadings.
•A quality procedure to determine the composition of natural gas was developed.•Production samples instead of synthetic mixtures yielded accurate predictions.•Selectivity ratio and iPLS were selected ...among five variable selection procedures.•The prediction errors and limits of detection halved those previously published.
Quality control of natural gas frequently relies on off-line slow standardized chromatographic techniques. Previous implementations of new measurement approaches focused of synthetic mixtures without extensive industrial validation. Here, a fast alternative based on infrared spectra is presented to predict the gas constituents and a physical parameter, the Wobbe index. Commercial samples instead of synthetic mixtures were used to develop predictive models. Method performance parameters were calculated and ca. 100 % of the sample-specific confidence intervals for the predictions overlapped with those of the reference values and the approach was unbiased and precise. The limits of detection and quantification (classical and considering errors of type I and II) outperformed other approaches. Validation included commercial samples and primary mixtures. Furthermore, prediction models considering reduced sets of variables were sought for using Markov-chain Monte Carlo guided searches (uninformative variable elimination and random frog) and common (iPLS, UVE and SR) approaches. The prediction errors and limits of detection of these ‘reduced’ models outperformed those from other approaches. The methodology takes only minutes to analyse a sample, requires few sample and no reagents (only some argon), making this approach cost-effective and environmentally-friendly.
European trends to get greener cities and protect the environment imply substituting traditional diesel/gasoline engines for gas (gas-hybrid) powered engines. To accomplish this, straightforward ...quality control of liquefied and/or compressed natural gas is needed. This communication shows that the broadening effect of an auxiliary inert gas (Ar) enhances their infrared (IR) gaseous spectra and improves usual analytical performance parameters by 50%, which paves the way to use IR routinely to assess the composition of natural gas samples.
To assess the knocking properties of natural gas (NG) when it is used as fuel for vehicles is vital to optimize the design and functioning of their motors. Analytical efforts in this field are needed ...as the engines used to define it empirically are not available anymore, and existent mathematical algorithms yield different accuracy. The hybridization of gas-phase infrared spectrometry and partial least squares multivariate regression is presented first time to address the determination of the methane number (MN) of NG samples. It circumvents the need for the previous knowledge of the NG composition required to apply dedicated equations. The use of true NG samples to develop the models is also quite new in the field. Proof-of-concept studies were made with synthetic spectra and, then, a collection of liquefied NG samples for which MN values were computed by the National Physics Laboratory algorithm (NPL) from their sample composition were used to develop operative models. Additional validation was made with a collection of synthetic standard mixtures prepared for two European projects (EMRP LNG II and EMPIR LNG III) whose service methane numbers (SMN) were measured with an engine. The FTIR-PLS approach yielded statistically unbiased predictions with average standard errors around 0.4% MN when compared to the NPL-MN and SMN values, and standard deviations of the means ca. 1% MN. The approach is fast, cost effective as it involves standard instrumentation, and can be considered compliant with the green chemistry principles.
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•PLS regression and IR spectrometry successfully predict methane number of LNG.•Average errors are lower than 0.5% and standard deviation lower than 1%.•Predictions were statistically unbiased.•Exploratory studies using synthetic spectra and real spectra strongly agreed.
Ramipril in High-Risk Patients With COVID-19 Amat-Santos, Ignacio J.; Santos-Martinez, Sandra; López-Otero, Diego ...
Journal of the American College of Cardiology,
07/2020, Letnik:
76, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Coronavirus disease-2019 (COVID-19) is caused by severe acute respiratory-syndrome coronavirus-2 that interfaces with the renin-angiotensin-aldosterone system (RAAS) through angiotensin-converting ...enzyme 2. This interaction has been proposed as a potential risk factor in patients treated with RAAS inhibitors.
This study analyzed whether RAAS inhibitors modify the risk for COVID-19.
The RASTAVI (Renin-Angiotensin System Blockade Benefits in Clinical Evolution and Ventricular Remodeling After Transcatheter Aortic Valve Implantation) trial is an ongoing randomized clinical trial randomly allocating subjects to ramipril or control groups after successful transcatheter aortic valve replacement at 14 centers in Spain. A non-pre-specified interim analysis was performed to evaluate ramipril’s impact on COVID-19 risk in this vulnerable population.
As of April 1, 2020, 102 patients (50 in the ramipril group and 52 in the control group) were included in the trial. Mean age was 82.3 ± 6.1 years, 56.9% of the participants were male. Median time of ramipril treatment was 6 months (interquartile range: 2.9 to 11.4 months). Eleven patients (10.8%) have been diagnosed with COVID-19 (6 in control group and 5 receiving ramipril; hazard ratio: 1.150; 95% confidence interval: 0.351 to 3.768). The risk of COVID-19 was increased in older patients (p = 0.019) and those with atrial fibrillation (p = 0.066), lower hematocrit (p = 0.084), and more comorbidities according to Society of Thoracic Surgeons score (p = 0.065). Admission and oxygen supply was required in 4.9% of patients (2 in the ramipril group and 3 in the control group), and 4 of them died (2 in each randomized group). A higher body mass index was the only factor increasing the mortality rate (p = 0.039).
In a high-risk population of older patients with cardiovascular disease, randomization to ramipril had no impact on the incidence or severity of COVID-19. This analysis supports the maintenance of RAAS inhibitor treatment during the COVID-19 crisis. (Renin-Angiotensin System Blockade Benefits in Clinical Evolution and Ventricular Remodeling After Transcatheter Aortic Valve Implantation RASTAVI; NCT03201185)
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