Accurate Quantitative Results Research Articles

Three efficient chemometrics assisted fluorimetric detection methods for interference-free, rapid, and simultaneous determination of ibrutinib and pralatrexate in various complicated biological fluids

In this study, a series of green, interference-free fluorimetric detection methods of the excitation-emission matrix coupled with the second-order calibration methods were proposed for the determination of ibrutinib and pralatrexate in various complicated biological fluids. The second-order advantage of the proposed method can overcome the problem of poor selectivity caused by the wide spectra of the fluorescence method. Even in the presence of uncalibrated interferences and severe peak overlap, the signal of pure substance and accurate quantitative results were still obtained. The average recoveries of the three methods were 94.5–104.9% for Alternating Trilinear Decomposition (ATLD) algorithm, 95.5–105.8% for Alternating Normalization Weighted Error (ANWE) algorithm and 94.4–105.7% for Parallel Factor Analysis (PARAFAC) algorithm, respectively. For ATLD, ANWE and PARAFAC, the relative standard deviations (RSD) were lower than 9.2%, 6.8% and 9.2%, and the RMSEPs were less than 8.1, 8.4 and 8.6 ng mL−1, respectively. In addition, the elliptic joint confidence region (EJCR) was adopted to further prove the accuracy of the three methods. The results showed that the three methods can accurately be quantified without significant difference. Good figures of merit parameters were also obtained. Among them, the limit of detection (LOD) and limit of quantification (LOQ) of ibrutinib and pralatrexate were in the range of 0.11–0.76 ng mL−1 and 0.21–1.12 ng mL−1, respectively, which were lower than the corresponding blood concentrations. These results indicate that the proposed method provides a promising, alternative and universal analysis strategy for clinical drug monitoring.

Challenges and emerging perspectives of an international SARS-CoV-2 epidemiological surveillance in wastewater.

SARS-CoV-2 is a new type of coronavirus capable to infect humans and cause the severe acute respiratory syndrome COVID-19, a disease that has been causing huge impacts across the Earth. COVID-19 patients, including mild, pre-symptomatic and asymptomatic cases, were often seen to contain infectious fragments of SARS-CoV-2 in feces and urine samples. Therefore, studies to detect the new coronavirus in wastewater, which collect and concentrate human excreta, have been extremely useful as a viral tracking tool in communities. This type of monitoring, in addition to serve as a non-invasive early warning of COVID-19 outbreaks, would provide better predictions about the SARS-CoV-2 spread and strongly contribute to maintenance the global health. Although current methods to detect viruses in wastewater, based on molecular RT-PCR and RT-qPCR techniques, were considered as reliable and provided accurate qualitative and quantitative results, they have been facing considerable challenges concerning the SARS-CoV-2 surveillance. In this review, the methods used to detect the SARS-CoV-2 in wastewater and the challenges to implement an international viral monitoring network were described. The article also addressed the emerging perspectives associated with the SARS-CoV-2 epidemiological surveillance in this environment and the importance of a worldwide collaboration to generate and disseminate the detection results.

DETERMINATION OF UNIT PARAMETERS WITH SELECTIVE MEMBRANES

The energy complex of Russia is largely based on oil and gas potential. One of the ways to maintain the rate of hydrocarbon production is the use of gas methods. In this regard, inexpensive methods of obtaining pure gases are relevant. One of such approaches is the use of installations with selective membranes, the use of which is ineffective without preliminary modeling. There are currently no models that provide accurate quantitative results. Therefore, the main goal of this article is to develop a detailed mathematical model of the gas separation process in an installation with selective membranes and to determine the technological parameters with its help. The paper deals with the division of air in a membrane unit into pure gases: nitrogen and oxygen. The membrane consists of fibers, their sizes are comparable to the sizes of gas molecules, due to which the gas separation process takes place, since the transmission rate of the components is different. Filtering rate is a function of spatial coordinate and time. The basic system of the mechanics equations of multiphase systems is used for modeling. The developed mathematical model is based for the first time on the most detailed approach, in which the process is considered both inside and outside the membrane. To describe the processes outside the membrane, a system of equations for component fluxes is used, and inside the membrane, the conservation laws of mass and momentum are used. The model is reduced to a dimensionless form in order to get away from dimensional physical quantities and to carry out a criterion analysis to assess the contribution of parameters affecting the gas separation process. The data used for the evaluation correspond to a real membrane plant. By numerically solving the model equations, the distribution of nitrogen concentration inside and outside the membrane tubes is obtained. Analysis of the model in a dimensionless form shows that all factors make a comparable order of magnitude contribution to the final distribution of gas concentration.

Acrophobia Quantified by EEG Based on CNN Incorporating Granger Causality.

The aim of this study is to quantify acrophobia and provide safety advices for high-altitude workers. Considering that acrophobia is a fuzzy quantity that cannot be accurately evaluated by conventional detection methods, we propose a comprehensive solution to quantify acrophobia. Specifically, this study simulates a virtual reality environment called High-altitude Plank Walking Challenge, which provides a safe and controlled experimental environment for subjects. Besides, a method named Granger Causality Convolutional Neural Network (GCCNN) combining convolutional neural network and Granger causality functional brain network is proposed to analyze the subjects' noninvasive scalp EEG signals. Here, the GCCNN method is used to distinguish the subjects with severe acrophobia, moderate acrophobia, and no acrophobia in a three-class classification task or no acrophobia and acrophobia in a two-class classification task. Compared with the mainstream methods, the GCCNN method achieves better classification performance, with an accuracy of 98.74% for the two-class classification task (no acrophobia versus acrophobia) and of 98.47% for the three-class classification task (no acrophobia versus moderate acrophobia versus severe acrophobia). Consequently, our proposed GCCNN method can provide more accurate quantitative results than the comparative methods, making it to be more competitive in further practical applications.

Review on Common Observed HPLC Troubleshooting Problems

HPLC provide much higher resolution, more accurate quantitative results, as well as shorter analysis times in comparison to the earlier techniques, HPLC has evolved into an indispensable tool in many analytical laboratories. Troubleshooting is a form of problem solving, often applied to repair failed products or processes. Actually, HPLC refers to a number of separation techniques that use a liquid mobile phase, or eluent. Troubleshooting HPLC instrumentation and separations require a fundamental understanding of how the instrument functions and how the separation works. Common HPLC problems are caused by component malfunctions (pump, degasser, injector, detector, data system, column), and faulty preparation of the mobile phase or sample preparation. Always use well cleaned glassware for preparation for better results. Main key to resolve HPLC problem is Cleaning of HPLC with appropriate solvent. If any problem occurs, it is advisable to perform a quick visual check of the instrument and column. If Monograph or any protocol is provided then try to follow same process. Troubleshooting is a form of problem solving, often applied to repair failed products or processes. Otherwise, we suggest that you read the entire article so as to pick up some ideas that will help you avoid problems in the future. We hope that this article useful to diagnose problems and to gain understanding of underlying causes so that you can prevent or minimize future occurrence. Colum and HPLC care is most important part of troubleshooting. In This article, we tried to cover all major troubleshooting problems.

Analysing Academic Texts with Computational Linguistics Tools

Writing academic texts in English introduces certain difficulties associated with translating Russian sentences with pronounced stylistic peculiarities, especially for young researchers who are just starting their publication activity. It seems impossible to study any genre without analysing examples of the discourse, which highlights the use of computational linguistics as it allows automating a lot of language and text processing mechanisms and generates relatively accurate quantitative results. The present study considers the application of AntConc and Coh-Metrix toolkits for analyzing master students’ abstracts to research papers written for international English-language journals or conference proceedings (Learner Corpus) in comparison with international researchers’ abstracts published in high-impact journals (Reference Corpus). The analysis conducted in the above-mentioned software tools revealed the drawbacks and strengths of master students’ texts, allowed characterizing them on the words, sentence and discourse levels, as well as outlined the potentials of their use in teaching academic writing skills.

Reliability Assessment Based on GO Method of Metro Traction System

In order to improve the reliability of the metro traction system (MTS), the whole life cycle of metro vehicles can be operated safely and reliably. A reliability assessment method based on the GO method of the MTS is proposed. In this paper, the reliability assessment is completed without operation service failure of the metro vehicle. The maintainability and shutdown correlation of many electrical components in the MTS are considered. An accurate algorithm with shared signals is used. Then the quantitative and qualitative reliability assessment of the system is achieved with the goal of traction system providing traction for the vehicle. The evaluation identifies the weak links of the system. Comparing the completely independent quantitative calculation result of each component with the accurate quantitative calculation results, it is found that the complex correlation in the repairable system has an important effect on the reliability of the system. A comparative analysis is performed on the calculating results of the GO method and fault tree analysis (FTA) method. The results demonstrate that the reliability analysis of the MTS by the GO method is feasible and reasonable. The principle of the method is simple and the logic is clear. It can not only objectively reflect the working process of the MTS, but also fully characterize the complex correlation with shut down fault in the MTS. The qualitative assessment results of the system show that the cut set probability of the pantograph is the highest, which should be the focus of the MTS.

Generalization of the Franck-Condon model for phonon excitations by resonant inelastic x-ray scattering

Resonant inelastic x-ray scattering (RIXS) is increasingly used to quantify vibronic interactions in materials. In the case of periodic systems, this is most often done through fitting experimental results to a parameterized but exact analytical solution of a simple Holstein Hamiltonian that consists of a single electronic level coupled linearly to a single Einstein vibrational mode. Working within this standard framework, we consider the impact of minor generalizations of this model, namely, introducing a second Einstein oscillator and allowing the curvature of the excited-state potential energy surface to differ from that of the ground-state potential energy surface. We find that dynamics occurring in the RIXS intermediate (electronically excited) state considerably alter the quantitative interpretation of the phonon features observed in the RIXS final state. This complicates the use of the single mode model when multiple phonon modes are active. Our generalized model may in principle be substituted in this case, though we find that accurate quantitative results rely on knowledge of the excited-state potential energy surface, which typically is not known.

Characterization of the Chemical Composition of Uranium Microparticles with Irregular Shapes Using Standardless Electron Probe Microanalysis and Micro-Raman Spectrometry

We describe an approach enabling the identification of the elemental composition of uranium microparticles with undefined geometry using standardless quantitative Electron Probe MicroAnalysis (EPMA) and Micro-Raman Spectrometry (MRS). The standardless procedure is based on a ZAF peak-to-background quantitative method in combination with Monte Carlo simulations. The experimental X-ray spectra were measured with an energy dispersive spectrometer attached to a scanning electron microscope. In order to account for the X-ray intensity loss due to the transmission of electrons in microparticles with irregular shapes, a method was developed enabling the determination of an apparent thickness of the particle by means of the mean distance that electrons travel inside the particle before being transmitted. Size effects were further taken into account by using peak-to-background ratios and performing simulations on a particle with a thickness equal to the apparent thickness. In order, to assess the validity of the standardless procedure in EPMA, weight fractions were determined for NIST homogeneous spherical microparticles of K411 glass and compared to certified ones. The correction of size effects was achieved and lead to accurate quantitative results with absolute relative deviations less than 9%. The model used for the determination of the apparent thickness was validated on the set of spherical K411 particles and enabled to conduct quanti-fications on irregularly shaped uranium microparticles. The chemical composition of uranium particles was further investi-gated using MRS which enabled to verify the reliability of the results obtained by the standardless approach.

Classification of Breast Cancer Cells Using the Integration of High-Frequency Single-Beam Acoustic Tweezers and Convolutional Neural Networks.

Single-beam acoustic tweezers (SBAT) is a widely used trapping technique to manipulate microscopic particles or cells. Recently, the characterization of a single cancer cell using high-frequency (>30 MHz) SBAT has been reported to determine its invasiveness and metastatic potential. Investigation of cell elasticity and invasiveness is based on the deformability of cells under SBAT’s radiation forces, and in general, more physically deformed cells exhibit higher levels of invasiveness and therefore higher metastatic potential. However, previous imaging analysis to determine substantial differences in cell deformation, where the SBAT is turned ON or OFF, relies on the subjective observation that may vary and requires follow-up evaluations from experts. In this study, we propose an automatic and reliable cancer cell classification method based on SBAT and a convolutional neural network (CNN), which provides objective and accurate quantitative measurement results. We used a custom-designed 50 MHz SBAT transducer to obtain a series of images of deformed human breast cancer cells. CNN-based classification methods with data augmentation applied to collected images determined and validated the metastatic potential of cancer cells. As a result, with the selected optimizers, precision, and recall of the model were found to be greater than 0.95, which highly validates the classification performance of our integrated method. CNN-guided cancer cell deformation analysis using SBAT may be a promising alternative to current histological image analysis, and this pretrained model will significantly reduce the evaluation time for a larger population of cells.

Simulation and validation of residual deformations in additive manufacturing of metal parts

Selective laser melting (SLM) is gaining increasing relevance in industry. Residual deformations and internal stresses caused by the repeated layerwise melting of the metal powder and transient cooling of the solidified layers still presents a significant challenge to the profitability and quality of the process. Excessive distortions or cracking may lead to expensive rejects. In practice, critical additively manufactured parts are either iteratively pre-compensated or redesigned based on production experience. To satisfy the need for improved understanding of this complex manufacturing process, CAE software providers have recently developed solutions to simulate the SLM process. This study focuses on the evaluation of two solutions by ANSYS, i.e. ANSYS Additive Print and ANSYS Additive Suite.ANSYS Additive Print (AAP), a user-oriented software, and ANSYS Additive Suite (AAS), a software requiring advanced experience with Finite Element Methods (FEM), are investigated and validated with regard to residual deformations. For the evaluation of the two programs, calibration and validation geometries were printed by SLM in Ti–6Al–4V and residual deformations have been measured by 3D scanning. The results have been used for the calibration of isotropic and anisotropic strain scaling factors in AAP, and for sensitivity analyses on the effect of basic model parameters in AAS. The actual validation of the programs is performed on the basis of different sample geometries with varying wall thickness and deformation characteristic.While both simulation approaches, AAP and AAS, are capable of predicting the qualitative characteristics of the residual deformations sufficiently well, accurate quantitative results are difficult to obtain. AAP is more accessible and yields accurate results within the calibrated regime. Extrapolation to other geometries introduces uncertainties, however. AAS, on the other hand, features a sounder physical basis and therefore allows for a more robust extrapolation. Numerical efforts and modelling uncertainties as well as requirements for an extensive set of material parameters reduce its practicality, however. More appropriate calibration geometries, continuing extension of a more reliable material database, improved user guidelines and increased numerical efficiency are key in the future establishment of the process simulation approaches in the industrial practice.

Simultaneous Analysis of Fenthion and Its Five Metabolites in Produce Using Ultra-High Performance Liquid Chromatography-Tandem Mass Spectrometry.

A simultaneous analytical method for the organophosphorus insecticide fenthion and its five metabolites (fenthion oxon, fenthion oxon sulfoxide, fenthion oxon sulfone, fenthion sulfoxide, and fenthion sulfone) was developed based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Five matrices (brown rice, chili pepper, orange, potato, and soybean) were selected to validate the method. The target compounds were analyzed using positive electrospray ionization in the multiple reaction monitoring mode. For the best sensitivity in regard to the detector response, water and methanol containing formic acid (0.1%) were selected as the mobile phase. The optimum extraction efficiency was obtained through a citrate-buffered QuEChERS (quick, easy, cheap, effective, rugged, and safe) method. Recovery tests were carried out at three spiking levels (n = 3). At all fortification levels, the accuracy and precision results were between 70% and 120% with a relative standard deviation of ≤15%. The limit of quantitation was 0.01 mg/kg, and the correlation coefficients (r2) of the matrix-matched calibration curves were >0.99. Significant signal suppression in the detector responses were observed for all matrices, suggesting that a compensation method, such as matrix-matched calibration, is required to provide accurate quantitative results. The applicability of the presented method was confirmed for the simultaneous analysis of fenthion and its metabolites in various crops.

A preliminary comparison of time-of-flight laser ionization and secondary ion mass spectrometry in solids analysis

In this work, a preliminary comparison was made between buffer-gas-assisted laser ionization time-of-flight mass spectrometry (LI-TOFMS) and time-of-flight secondary ionization mass spectrometry (TOF-SIMS). A reference steel sample and a soil sample were used as representative metal and oxide solid samples in the experiment. The comparison was focused on their spectral characteristics and standard-less quantitative capability in determine elements in solid samples. Since the oxygen has low ion yield, a new standard-less quantitative method was proposed for oxides analysis, which derives the oxygen intensity from other detected elements using their common oxidation states in calculation of oxygen concentration. The results indicate that both techniques meet the needs of standard-less semi-quantitative analysis. However, LI-TOFMS offers spectra with less interference, and leads to more determined elements and accurate quantitative results.

High resolution X-ray computed tomography: A versatile non-destructive tool to characterize CFRP-based aircraft composite elements

The aim of the current study is to propose a versatile, non-destructive inspection strategy to evaluate the structure of two different aircraft carbon fibre reinforced polymer (CFRP) -based composite configurations, which are widely used for structural elements, respectively layered composite and sandwich structure. X-ray computed tomography (CT) has been used as a flexible method for assessment of porosity levels in CFRP components in both types of configuration, permitting to investigate the volume distribution of the individuated pores/voids, giving an interactive 3D exploration and quantitative analysis of porosity by the complete 3D volume rendering of the analysed composites. Moreover, specific data analysis could supply detailed information on size, shape and position of pores or defect or misalignment which could be a valuable indication for damage tolerant design methodology or local stress analysis. This presented non-destructive approach based on CT can be a good alternative to standard destructive methods based on the acid digestion or 2D microscopy for porosity evaluation in composite, especially for severe stressed element in aerospace structure. Of course, the high resolution X-ray CT cannot substitute the ultrasounds test for analysing full scale components, but it can be complementary to it to provide accurate quantitative results on small samples used as references.

Application of a Pseudotargeted MS Method for the Quantification of Glycated Hemoglobin for the Improved Diagnosis of Diabetes Mellitus.

Proteins in a human body continuously undergo glycation reactions with reducing sugars, forming early as well as advanced glycation end-products (AGEs) which are highly disease-relevant. Specifically, N-1-(deoxyfructosyl) valine of β-hemoglobin (HbA1c) has been considered as a marker of diabetes, but the exact map of glycated Hb peptides corelated with diabetes in different stages is poorly studied. Here, the pseudotargeted parallel reaction monitoring (PRM) method combined with relative retention time (iRT) endogenous peptides was proposed for exploring the roles of deoxyfructosyl (DF-), carboxymethyl (CM-), and carboxyethyl (CE-) based Hb modifications in clinical prognosis and diagnosis of type 2 diabetes mellitus (T2DM) and its complication. For building the pseudotargeted list, data-dependent acquisition (DDA) combined with multiple enzyme digestion was employed for the comprehensive identification of the three types of modification in vitro Hb and in vivo Hb. The introduction of the endogenous iRT peptides during PRM analysis facilitates being able to obtain accurate quantitative results. When applying this new strategy to quantify the three kinds of glycated Hb peptides in clinical samples, patients with T2DM in different pathophysiological conditions were fully distinguished from the controls, indicating the necessity of adopting multiple glycation types for the improved diagnosis of T2DM. Taken together, the newly developed pseudotargeted PRM method not only expands the horizons of glycated Hb by reliably assessing the actual status of T2DM but also reveals that endogenous iRT might be a viable option for label-free quantitative analysis.

High accuracy determination of copper in copper concentrate with double genetic algorithm and partial least square in laser-induced breakdown spectroscopy.

There are many challenges in the determination of elements in complex matrix such as soil, coal and minerals by laser induced breakdown spectroscopy (LIBS) method. Due to the influence of matrix effect, instability of laser plasma and fluctuation of laser parameters, the repeatability and accuracy of quantitative results are always not satisfactory. In order to improve the accuracy, high-energy laser (30mJ-100mJ) with precise control was utilized in many laboratories. In this paper, quantitative analysis of copper in copper concentrate by low-energy (10µJ) LIBS is studied. In order to reduce the influence of matrix effect and other factors, a partial least square regression method based on double genetic algorithm (DGA-PLS) is proposed. The detail operations are as follow: the reference spectral lines are automatically selected by GA as the optimal internal standard for spectral normalization. Then the GA is used to select variables from the normalized spectra for PLS. The results showed that, for univariate model, the coefficient of determination (R2) was improved from 0.6 to 0.97 by the optimal internal standard normalization. Compared with tradition PLS, the root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) of PLS trained by the normalized spectral data decreased from 1.4% and 0.42% to 0.9% and 0.29% respectively. Compared with the normalized PLS, the RMSECV and RMSEP of the DGA-PLS trained by the normalized and feature selected spectral data decreased from 0.9% and 0.29% to 0.26% and 0.21% respectively. The results show that DGA-PLS can significantly reduce matrix effect, improve prediction accuracy and reduce the risk of overfitting in determination of copper in copper concentrate.

N-way partial least squares combined with new self-construction strategy—A promising approach of using near infrared spectral data for quantitative determination of multiple compounds

Because of the complexity of near infrared spectral data, effective strategies are necessary proposed for accurate quantitative analysis purpose. This work explores a new self-construction strategy for the arrangement of conventional near infrared two-dimensional spectra into new self-constructed three-dimensional spectra, and investigate the feasibility of N-way partial least squares combined with the new self-constructed three-dimensional near infrared spectra for obtaining accurate quantitative determination results. A proof-of-concept model system, the quantitative analysis of four components (moisture, oil, protein, and starch) in corn samples, was applied to evaluate the performance of the proposed strategy. The ability of the newly proposed approach to predict the target compounds was checked with test samples. The established models have good predictive power for the target compounds with acceptable values of Rp (range from 0.82 to 0.997) and RMSEP (range from 0.03 to 0.47). Compared with partial least squares method on pretreated near infrared spectra and N-way partial least squares method on the basis of near infrared self-constructed three-dimensional spectra, the proposed method is competitive.

Identifying Challenges and Risks Associated with the Analysis of Major Mycotoxins in Feed and Botanicals

Abstract Changing weather conditions have heightened the risk of growth of mycotoxigenic molds on crops and various agricultural commodities. Mycotoxins, which are linked to carcinogenic and nephrotoxic effects in animals and humans, have been traditionally analyzed by immunoassays, gas, and LC techniques with spectrophotometric detectors. This review discusses the current techniques and challenges in commercial settings associated with the analysis of mycotoxins in unique matrices such as animal feeds, herbal products, and dietary supplements containing botanicals. Because of the advantages and growing acceptance of LC-tandem MS (MS/MS) over traditional approaches, discussion is mainly based on LC-MS/MS-based approaches. Considering the impact of sample preparation on accuracy of quantitative results, discussion about pros and cons of recently introduced sample preparation techniques is integrated with analytical methods. A section of the review explains the importance and availability of reference materials for mycotoxins. The present discussion provides good insight into the current challenges and developments during mycotoxin analysis of feed and botanicals and addresses the need for researchers in terms of an official MS-based method.

Matrix Effect Corrections in X-ray Fluorescence Spectrometry

X-ray fluorescence is subject to significant matrix effects, which must be corrected in order to obtain accurate quantitative results. These are due to both absorption and enhancement effects, whic...

CHARMed PyMca, Part II: An evaluation of interlaboratory reproducibility for ED‐XRF analysis of copper alloys

CHARMed PyMca is a protocol for researchers using energy‐dispersive X‐ray fluorescence spectroscopy (ED‐XRF) who wish to maximize interlaboratory reproducibility of quantitative results from copper alloys found in heritage materials. This paper reports the results of a study evaluating the interlaboratory reproducibility expected when following this protocol. Five institutions participated in this study, using nine tube‐based instruments of seven types. A set of 12 reference materials not used for calibration was analysed according to the protocol. The results show an improvement in reproducibility of between 65% and 83%, depending on the element, in comparison with a similar study carried out in 2010. The protocol allowed the consistent reporting of concentrations for 15 elements, in contrast to only eight elements that were reported in the 2010 study. Finally, the protocol was shown to generate accurate quantitative results with a well‐characterized precision. It is hoped the information presented here can help researchers studying heritage copper alloys to collaborate more effectively and with greater confidence in the reproducibility of their results. It should also aid researchers to make realistic and informed decisions about whether or not the degree of reproducibility that they may expect from ED‐XRF makes the protocol suitable for their specific purposes.