Quality Control Approach Research Articles

Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study.

BackgroundInstrumented assessment of motor symptoms has emerged as a promising extension to the clinical assessment of several movement disorders. The use of mobile and inexpensive technologies such as some markerless motion capture technologies is especially promising for large-scale application but has not transitioned into clinical routine to date. A crucial step on this path is to implement standardized, clinically applicable tools that identify and control for quality concerns.ObjectiveThe main goal of this study comprises the development of a systematic quality control (QC) procedure for data collected with markerless motion capture technology and its experimental implementation to identify specific quality concerns and thereby rate the usability of recordings.MethodsWe developed a post hoc QC pipeline that was evaluated using a large set of short motor task recordings of healthy controls (2010 recordings from 162 subjects) and people with multiple sclerosis (2682 recordings from 187 subjects). For each of these recordings, 2 raters independently applied the pipeline. They provided overall usability decisions and identified technical and performance-related quality concerns, which yielded respective proportions of their occurrence as a main result.ResultsThe approach developed here has proven user-friendly and applicable on a large scale. Raters’ decisions on recording usability were concordant in 71.5%-92.3% of cases, depending on the motor task. Furthermore, 39.6%-85.1% of recordings were concordantly rated as being of satisfactory quality whereas in 5.0%-26.3%, both raters agreed to discard the recording.ConclusionsWe present a QC pipeline that seems feasible and useful for instant quality screening in the clinical setting. Results confirm the need of QC despite using standard test setups, testing protocols, and operator training for the employed system and by extension, for other task-based motor assessment technologies. Results of the QC process can be used to clean existing data sets, optimize quality assurance measures, as well as foster the development of automated QC approaches and therefore improve the overall reliability of kinematic data sets.

Process Analytical Technology (PAT) in Quality Assurance: A Detailed Review

Process Analytical Technology (PAT) is a proactive initiative published by the Food and Drug Administration so as to overcome the conventional way of batch testing. As per the documented guideline it can be stated as a system for designing, analyzing, and controlling pharmaceutical manufacturing through the timely measurement of critical quality and performance parameters. PAT is a quality driven approach with innovative, strategic and rapid systems, so as to clearly understand, predict, manipulate, control and refine manufacturing processes. Owing to its multidimensional applications, process analysis can be carried out even in the most critical processes, like crystallization, by the on-line technique.PAT is one of the prime objectives stressed in the Initiative for Pharmaceutical CGMPs for the 21st Century published by the Food and Drug Administration. The chief motive of this dynamic approach is to carry out measurements on raw materials and in the in process materials or process parameters with tight controls, with a prime goal to enhance final product quality and reduce the chances of error or default/defect. The prime inventiveness of the PAT initiative is to focus on building quality inside the product and the entire manufacturing processes, in addition to continuous process improvement. The adoption of PAT approach can provide a plethora of benefits to the pharmaceutical industry by enhancing product quality while providing supercilious asset utilization and niche financial value. PAT bestows better insight of raw materials, by characterizing it physically and chemically, detailed understanding of manufacturing parameters, all of which collectively decide the fate of the quality and appeal of the final product. Unlikely to the traditional approach of testing the product at its terminal stage, PAT is a dynamic approach to keeping an eye on the manufacturing and other related processes on a continuous basis compared to a discrete one, and keeps a strict check at all stages of production. Hence this detailed review will stress on the importance of PAT and its overall conceptualization, which shall be indeed propitious for furnishing an integrated systems approach for quality design, process analyses, understanding and control, continuous improvement, knowledge and risk-based management within the FDA 21st century framework of Good manufacturing initiative and will be a useful guide to the industry and academia personnel for better understanding of this approach. Additionally it also highlights the unique synergy of Quality by Design with PAT for establishing an in depth understanding of the manufacturing process.

A New Perspective to Tribocharging: Could Tribocharging Lead to the Development of a Non-Destructive Approach for Process Monitoring and Quality Control of Powders?

This study explores a new perspective on triboelectrification that could potentially lead to the development of a non-destructive approach for the rapid characterization of powders. Sieved yellow pea powders at various particle sizes and protein contents were used as a model system for the experimental charge measurements of the triboelectrified powders. A tribocharging model based on the prominent condenser model was combined with a Eulerian–Lagrangian computational fluid dynamics (CFD) model to simulate particle tribocharging in particle-laden flows. Further, an artificial neural network model was developed to predict particle–wall collision numbers based on a database obtained through CFD simulations. The tribocharging and CFD models were coupled with the experimental tribocharging data to estimate the contact potential difference of powders, which is a function of contact surfaces’ work functions and depends on the chemical composition of powders. The experimentally measured charge-to-mass ratios were linearly related to the calculated contact potential differences for samples with different protein contents, indicating a potential approach for the chemical characterization of powders.

Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping

BackgroundGenetic variants within the APOE locus may modulate Alzheimer’s disease (AD) risk independently or in conjunction with APOE*2/3/4 genotypes. Identifying such variants and mechanisms would importantly advance our understanding of APOE pathophysiology and provide critical guidance for AD therapies aimed at APOE. The APOE locus however remains relatively poorly understood in AD, owing to multiple challenges that include its complex linkage structure and uncertainty in APOE*2/3/4 genotype quality. Here, we present a novel APOE*2/3/4 filtering approach and showcase its relevance on AD risk association analyses for the rs439401 variant, which is located 1801 base pairs downstream of APOE and has been associated with a potential regulatory effect on APOE.MethodsWe used thirty-two AD-related cohorts, with genetic data from various high-density single-nucleotide polymorphism microarrays, whole-genome sequencing, and whole-exome sequencing. Study participants were filtered to be ages 60 and older, non-Hispanic, of European ancestry, and diagnosed as cognitively normal or AD (n = 65,701). Primary analyses investigated AD risk in APOE*4/4 carriers. Additional supporting analyses were performed in APOE*3/4 and 3/3 strata. Outcomes were compared under two different APOE*2/3/4 filtering approaches.ResultsUsing more conventional APOE*2/3/4 filtering criteria (approach 1), we showed that, when in-phase with APOE*4, rs439401 was variably associated with protective effects on AD case-control status. However, when applying a novel filter that increases the certainty of the APOE*2/3/4 genotypes by applying more stringent criteria for concordance between the provided APOE genotype and imputed APOE genotype (approach 2), we observed that all significant effects were lost.ConclusionsWe showed that careful consideration of APOE genotype and appropriate sample filtering were crucial to robustly interrogate the role of the APOE locus on AD risk. Our study presents a novel APOE filtering approach and provides important guidelines for research into the APOE locus, as well as for elucidating genetic interaction effects with APOE*2/3/4.

Quality Control of Nuclear Magnetic Resonance Measurements Using Pseudo-T2 Distributions

Summary Nuclear magnetic resonance (NMR) measurements are extremely valuable in the assessment of fluid-flow properties of rocks. However, inverted NMR transverse-relaxation time (T2) distributions are often biased by positivity constraints and the implementation of regularization (stabilization) methods. In some cases, it is difficult to determine whether the estimated pore-size distributions are reliable or byproducts of the inversion. On-site quality control of NMR inversion results is thus essential to avoid erroneous analyses based on nonphysical interpretations across conventional or unconventional rocks. It is also important to adjust the measurement acquisition process in real time in response to variable signal/noise conditions in the borehole environment. We introduce and compare three quality-control approaches; two of them are based on two different signal processing practices, namely the semilogarithmic derivative and the Hilbert transform, while the third is based on a nonlinear optimization technique. Validation of the inverted T2 distribution is performed by applying either method to the echo train decay of proton magnetization to estimate a pseudo-T2 distribution that is not affected by inversion artifacts. These three methods are data-driven processes for on-site, continuous quality control of borehole NMR measurements. In the first method, a pseudo-T2 distribution is constructed by taking the derivative of the echo train decay with respect to the natural logarithm of the relaxation time. For the second method, the Hilbert transform is applied to the raw proton magnetization decay to approximate the T2 distribution. The latter method consists of an approximation of the derivative of the time decay of magnetization using least-squares minimization. NMR laboratory measurements were performed on a wide variety of rocks, the associated T2 distributions were estimated using linear inversion, and the three quality-control methods were applied for comparison. The reliability of our quality-control procedures was verified by benchmarking them against the inverted T2 distributions. Furthermore, these quality-control methods, when applied continuously to borehole NMR measurements, enable the optimization of the measurements in real time to mitigate the effects of biasing noise. By verifying the location of the dominant mode of the T2 distribution during NMR measurement acquisition, the operator can determine whether (a) more stacking of proton magnetization decays is needed, or (b) longer- or shorter-time sampling is needed to attain a high-quality estimation of the pore-size distribution before performing the T2 inversion. Our work provides the basis of effective quality-control methods for NMR measurements for the petrophysical interpretation of rocks with complex pore-size distributions, especially in unconventional rocks, where noise present in the measurements (notably at early acquisition times), can mask the useful signal originating from pore-size distributions and fluids. The fast and reliable quality control of estimated T2 distributions is not affected by inversion artifacts, relying only on unfiltered, raw data.

Contribution to the Molybdenum Blue Reaction and its Application in Soil Analysi

This paper presents a study on the molybdenum blue reaction (MB) as a finishing detection step in soil analysis for quantification of plant available phosphorus. An ammonium acetate/calcium lactate reagent (pH = 4.2) was used for soil phosphorus extraction. The molybdenum blue color reaction using premixed Murphy-Riley reagent and ascorbic acid as a reductant was reinvestigated. UV-Vis characteristics of MB, optimal wavelength, reaction time and concentration of reductant were studied. The effect of ascorbic acid concentration and the reaction time on linearity, bias and uncertainty was discussed. The molybdenum blue reaction was found to obey Beer’s law in the targeted concentration range of 0.04 – 1.0 mg L-1 PO43- - P. The linearity was proved by “lack-of-fit” test. The uncertainty budget was made and the uncertainty was estimated by modelling approach, as well as single laboratory and quality control approach. The recovery and the expanded uncertainty were found to be, respectively, (95.7 ± 8.7) % (P = 95 %, n = 3) and 9.2 mg PO43- - P/kg dry soil (k = 2). The results showed that the soil sample inhomogeneity and the repeatability of extraction process were the main factors which contribute to the uncertainty of measurement in soil analysis.

Quality Control: Chain Pairing Precision and Monitoring of Cross-Sample Contamination: A Method by the AIRR Community.

New approaches in high-throughput analysis of immune receptor repertoires are enabling major advances in immunology and for the discovery of precision immunotherapeutics. Commensurate with growth of the field, there has been an increased need for the establishment of techniques for quality control of immune receptor data. Our laboratory has standardized the use of multiple quality control techniques in immunoglobulin (IG) and T-cell receptor (TR) sequencing experiments to ensure quality control throughout diverse experimental conditions. These quality control methods can also validate the development of new technological approaches and accelerate the training of laboratory personnel. This chapter describes multiple quality control techniques, including split-replicate cell preparations that enable repeat analyses and bioinformatic methods to quantify and ensure high sample quality. We hope that these quality control approaches can accelerate the technical adoption and validated use of unpaired and natively paired immune receptor data.

基于生态系统服务的浙江省水生态环境分区分类管控

水环境综合管理被普遍认为是促进流域可持续发展的基本手段。生态系统服务是生态系统对人类福祉和生存的直接和间接贡献, 是维持与影响流域水生态环境的重要因素。随着流域空间管控日益受到重视, 基于生态特征的"分区分类"管控已成为流域精细化管理的重要内容。论文基于生态系统服务功能与水质关联性, 采用典型对应分析(CCA)选取了土壤类型、土地利用、归一化植被指数和人口密度等4种生态特征作为水生态功能分区指标。结合流域生态特征、汇水区域和行政管理单元的空间分布, 通过聚类分析及空间叠置法, 将浙江省划分了10个水生态功能区和510个水环境控制单元。采用当量因子法对各控制单元的生态系统服务价值进行系统评估。结果表明2015年浙江省生态系统服务总价值为5123.7亿元, 其中控制单元的生态系统服务价值范围为59.8-136.5亿元。利用K-means聚类方法得到了4类生态服务簇, 并探讨了各类生态服务簇的服务类型、空间分布特征以及与各单元水质的关系。研究结果表明, Ⅰ类簇主要分布在西部及西南部的山地丘陵区, 其面积占了全省面积的52.68%;Ⅱ类簇的占地面积最小但水域面积相对较高, 主要覆盖千岛湖和钱塘江河口; Ⅲ类簇分布相对分散, 主要分布在丘陵平原地区; 而Ⅳ类簇主要分布在城镇较集中的平原地区。不同生态服务簇的主要生态服务类型存在明显差异, 如Ⅰ类簇以原料生产、水土保持、生物多样性保护、气体调节和气候调节为主; Ⅱ类簇的主要生态服务类型为调节功能, 包括气体调节、水文调节和废物处理; Ⅲ类簇和Ⅳ类簇以食物生产为主要的生态服务类型。水质特征与生态服务功能密切相关, 生态服务价值越高, 水体水质越好。因此根据各个生态服务簇的水质特征, 将各类生态服务簇划分为保护、维持、改善、整治4种类型, 并提出了不同生态服务簇内水环境控制单元的差异化管控措施, 以推进浙江省水生态环境的差异化管理。;Integrated water environmental management has been world widely treated as a fundamental means to support sustainable watershed development. Ecosystem Services (ESs), which refer to the direct and indirect contributions of ecosystems to human well-being and subsistence, are important factors for water quality maintenance and improvement. With increasing attention paid to the spatial management and control, zoning classification based on the ecosystem characteristics has become an important content of integrated watershed management. Based on the relationships between ecosystem characteristics and water quality, four ecological features including soil type, land usage, normalized vegetation index and population density were selected for aquatic ecoregion zoning using canonical correspondence analysis (CCA). Combining the spatial distribution of ecological features, catchments and administrative management units, Zhejiang Province was divided into ten aquatic ecoregions and 510 water environmental control units through cluster analysis and spatial overlap. The ES value of each unit was evaluated with the method of equivalent factor. The results showed that in 2015, the total ES value in Zhejiang Province reached 512.37 billion RMB, and those of individual units ranged from 5.98 to 13.65 billion RMB. Four ES bundles were obtained by K-means clustering method, and the service types and spatial distribution characteristics of the bundles were analyzed. Subsequently, the relationships between water quality and ecosystem services were analyzed for each unit. The results showed that Bundle I covered most of the mountain and hilly areas mainly located in the west and southwest, accounting for 52.68% of the province's total area, while Bundle Ⅱ had the smallest area but a relatively high water occupation ratio, mainly covering the Qiandao Lake and the estuary of the Qiantang River. Bundle Ⅲ was distributed relatively scattered, mostly in hilly and plain areas, while Bundle Ⅳ was primarily distributed in plain areas where cities and towns were located. The dominant ESs varied significantly in different ES bundles. For example, ESs such as raw material production, soil conservation, biodiversity protection, gas regulation, and climate regulation dominated in the Bundle I, while the regulatory services were the dominant ESs in Bundle Ⅱ, including gas regulation, water regulation and waste treatment. Food production contributed significantly to both Bundles Ⅲ and Ⅳ. The results also indicated that the characteristics of water quality are closely related to the ecological service, i.e., the higher the ES value, the better the water quality. As a result, the units were classified into four types, including protection, maintenance, improvement and remediation according to the characteristics of the water quality of each ES bundle. The differentiated water quality control and improvement approaches were proposed for the units in the four types of ES bundle, to support the water eco-environment management of Zhejiang Province.

Whole Slide Image Quality in Digital Pathology: Review and Perspectives

With the advent of whole slide image (WSI) scanners, pathology is undergoing a digital revolution. Simultaneously, with the development of image analysis algorithms based on artificial intelligence tools, the application of computerized WSI analysis can now be expected. However, transferring such tools into clinical practice is very challenging as they must deal with many artifacts that can occur during sample preparation and digitization. Therefore, the quality of WSIs is of prime importance, and we propose a review of the state-of-the-art of computational approaches for quality control. In particular, we focus on WSI quality issues related to the presence of sample preparation artifacts, compression artifacts, color variations, and out-of-focus areas. An analysis of the monthly WSI clinical routine in a cytological laboratory confirms the importance of implementing quality control measures. Given this observation, we draw perspectives on how a computational quality process can be included in a computational pathology diagnosis pipeline.

A Machine Learning Perspective on fNIRS Signal Quality Control Approaches.

Despite a rise in the use of functional Near Infra-Red Spectroscopy (fNIRS) to study neural systems, fNIRS signal processing is not standardized and is highly affected by empirical and manual procedures. At the beginning of any signal processing procedure, Signal Quality Control (SQC) is critical to prevent errors and unreliable results. In fNIRS analysis, SQC currently relies on applying empirical thresholds to handcrafted Signal Quality Indicators (SQIs). In this study, we use a dataset of fNIRS signals (N = 1,340) recorded from 67 subjects, and manually label the signal quality of a subset of segments (N = 548) to investigate the pitfalls of current practices while exploring the opportunities provided by Deep Learning approaches. We show that SQIs statistically discriminate signals with bad quality, but the identification by means of empirical thresholds lacks sensitivity. Alternatively to manual thresholding, conventional machine learning models based on the SQIs have been proven more accurate, with end-to-end approaches, based on Convolutional Neural Networks, capable of further improving the performance. The proposed approach, based on machine learning, represents a more objective SQC for fNIRS and moves towards the use of fully automated and standardized procedures.

Chemical, Manufacturing, and Standardization Controls of Grape Polyphenol Dietary Supplements in Support of a Clinical Study: Mass Uniformity, Polyphenol Dosage, and Profiles.

Bioactive dietary polyphenols in grape (Vitis vinifera) have been used in Dietary Supplements (DSs) with the aim to prevent numerous diseases, including cardiovascular and neurodegenerative diseases, and to reduce depression and anxiety. Given prior recognition that DSs can be quality challenged from the purity, authentication, adulteration, and actual concentration of targeted bioactives, to ensure consumer health protection as well as the quality and safety of grape polyphenol-based DSs, the present investigation was aimed at establishing a comprehensive quality control (QC) approach for grape polyphenol-based DSs in support of a human clinical study. In this study, the manufactured grape seed polyphenol extract (GSPE) and trans-resveratrol (RSV) capsules and Concord Grape Juice (CGJ) along with the corresponding original drug materials were analyzed using the developed different liquid chromatography/UV-visible spectroscopy/mass spectrometry (LC/UV-Vis/MS) methods. The weight variation of GSPE and RSV capsules was also evaluated according to the US Pharmacopeia (USP) tests. The results indicate that the total identified polyphenol content in each grape seed extract (GSE) capsule/CGJ is very similar and all GSE/RSV capsules pass the content/weight uniformity test. Given the complexity of these and many botanical products from the issues of purity, quality, adulteration, consistency, and their coupling to the complex chemistry in each grape-derived botanical, quality assurance and the steps needed to ensure grape-derived DSs being well homogeneous and stable and containing the known and expected bioactives at specific concentration ranges are fundamental to any research study and in particular to a clinical trial. Each of these issues is essential to provide a solid foundation upon which clinical trials with botanicals can be conducted with the goal of realizing measurable mental health outcomes such as reducing depression and anxiety as well as understanding of their underlying biological mechanisms.

Automatic Quality Control of Crowdsourced Rainfall Data With Multiple Noises: A Machine Learning Approach

AbstractIn geophysics, crowdsourcing is an emerging nontraditional environmental monitoring approach that supports data acquisition from individual citizens. However, because of the involvement of undertrained citizens and imprecise low‐cost sensors, crowdsourced data applications suffer from different types of noises that can deteriorate the overall monitoring accuracy. In this study, we propose a machine learning approach for automatic crowdsourced data quality control (CSQC) that detects and removes noisy data inputs in spatially and temporally discrete crowdsourced observations coming from both fixed‐point sensors (e.g., surveillance cameras) and moving sensors (e.g., moving cars/pedestrians). We design a set of features from original and interpolated rainfall data and use them to train and test the CSQC models using both supervised and unsupervised machine learning algorithms. The performances of the CSQC models under various scenarios assuming no retraining are also tested (hereafter referred to as transferability). The results based on synthetic but realistic data show that the CSQC models can significantly reduce the overall rainfall estimate errors. Under the stationary assumption, the CSQC models based on both supervised and unsupervised algorithms perform well in noisy data identification and overall rainfall estimation error reduction; however, if the model is transferred to other cities with different rainfall patterns or noise compositions (without retraining), supervised multilayer perceptrons (MLPs) show the best performance.

Quality intervention, supplier performance and buyer–supplier relationships: evidence from the garment industry

PurposeThis study investigates the impact of a buyer-assisted quality intervention on suppliers' quality performance and buyer–supplier relational dynamics in the garment industry.Design/methodology/approachThis study employed a multiple-embedded case study following a qualitative research approach. The study used data from buyer-assisted quality interventions in sewing lines of four garment supplier factories. Qualitative data were collected through semi-structured interviews of buyer's representatives at their office and senior managers, line inspectors, supervisors and workers in supplier factories. In addition, data related to product quality was obtained from quality check sheets and observations on the shop floor. Data were analysed using qualitative data analysis techniques.FindingsThis study demonstrates that a buyer-assisted quality intervention improves product quality performance by reducing quality defects in targeted garment products resulting in improved buyer–supplier relationships. Moreover, this study identifies the lack of a systematic approach in quality control as a key reason for poor product quality.Research limitations/implicationsThe study adds knowledge to the literature on quality improvement and buyer–supplier relationships by analysing buyer-assisted quality interventions in the garment industry in Bangladesh. The study demonstrates that buyer's assistance and adopting a systematic approach in quality control can significantly improve product quality in the garment industry.Practical implicationsThis research can help the quality assurance managers in buyer and supplier firms understand the significance of quality interventions and systematic quality control approach to decrease product quality defects and ensure smooth buyer–supplier relationships.Originality/valueThe study adds new knowledge on the link between buyer-assisted quality interventions, systematic quality control and product quality in garments factories in Bangladesh.

Quality Control Approach for the Detection of Internal Lower Density Areas in Composite Disks in Industrial Conditions Based on a Combination of NDT Techniques.

Voids in polymer matrix composites are one of the most common manufacturing defects, which may influence the mechanical properties and structural behavior of the final parts made of composites by various manufacturing methods. Therefore, numerous non-destructive testing (NDT) techniques were developed and applied for quality control and in-service testing of such structures. In this paper, the authors analyzed various alternatives to the reference technique, X-ray computed tomography (XCT) NDT, which is used for industrial testing of composite disks having defects in the form of the lower density areas. Different candidates, namely: vibration-based testing, infrared thermography, vibro-thermography, as well as ultrasonic testing were analyzed in terms of their sensitivity and technical feasibility. The quality of the results, the complexity of the testing procedure, time and labor consumption, and the cost of the equipment were analyzed and compared with the reference technique. Based on the conducted research the authors finally proposed a hybrid approach to quality control, using a combination of two NDT techniques–infrared thermography (for initial scanning and detection of near-surface defects) and ultrasonic testing (for a more detailed analysis of products that pass the first testing procedure). It allowed for replacing the costly XCT diagnostics with a much cheaper, but almost equally effective, alternative.

FNIRS-QC: Crowd-Sourced Creation of a Dataset and Machine Learning Model for fNIRS Quality Control

Despite technological advancements in functional Near Infra-Red Spectroscopy (fNIRS) and a rise in the application of the fNIRS in neuroscience experimental designs, the processing of fNIRS data remains characterized by a high number of heterogeneous approaches, implicating the scientific reproducibility and interpretability of the results. For example, a manual inspection is still necessary to assess the quality and subsequent retention of collected fNIRS signals for analysis. Machine Learning (ML) approaches are well-positioned to provide a unique contribution to fNIRS data processing by automating and standardizing methodological approaches for quality control, where ML models can produce objective and reproducible results. However, any successful ML application is grounded in a high-quality dataset of labeled training data, and unfortunately, no such dataset is currently available for fNIRS signals. In this work, we introduce fNIRS-QC, a platform designed for the crowd-sourced creation of a quality control fNIRS dataset. In particular, we (a) composed a dataset of 4385 fNIRS signals; (b) created a web interface to allow multiple users to manually label the signal quality of 510 10 s fNIRS segments. Finally, (c) a subset of the labeled dataset is used to develop a proof-of-concept ML model to automatically assess the quality of fNIRS signals. The developed ML models can serve as a more objective and efficient quality control check that minimizes error from manual inspection and the need for expertise with signal quality control.

A general procedure for establishing composite quality evaluation indices based on key quality attributes of traditional Chinese medicine

Licorice, a medicinal herb and food flavor ingredient, has been widely used in traditional Chinese medicine (TCM) for the past 4000 years. In this study, we propose a new quality evaluation approach for licorice quality control based on the key quality attributes commonly used in TCM. The high quality of TCM formulations is ensured by verifying the genuine origin and implementing good agricultural and collection practices for each medicinal herb. In our study, the genuine production area, the harvest season, and the number of growth years were considered the key quality attributes of TCM. To ensure the representativeness of our analysis, we obtained a total of 158 licorice sample batches that differed in the number of growth years, the location of the production areas, and the season for harvesting. Initially, the 158 sample batches were subjected to ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS). A preliminary screen identified 11 licorice compounds related to the three key quality attributes of TCM . An analysis by ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-TQ-MS/MS) verified the presence of 34 compounds in all licorice samples. These 34 compounds included the 11 compounds related to the three key quality attributes of the samples, along with other bioactive components identified in previous studies. After using UHPLC-TQ-MS/MS to assess the signal peak intensities of the 34 compounds, we selected 17 licorice compounds to establish sample content evaluation indices, which were determined by high-performance liquid chromatography at four different wavelengths in all 158 licorice sample batches. Finally, the screen identified nine compounds that were closely associated with the quality attributes of licorice based on principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Our results suggested that liquiritin and eight other compounds could be used as quality control indicators of licorice, which provided a foundation to establish the TCM quality composite evaluation index (TCM QCEI). In summary, this research concept can serve as a reference for research on quality markers and the evaluation of TCM.

Development of Quality Control Methods for Dispersibility and Stability of Single-Wall Carbon Nanotubes in an Aqueous Medium.

The attractive properties of single-wall carbon nanotubes (SWCNT) such as mechanical strength and high electrical and thermal conductivity are often undercut by their agglomeration and re-agglomeration tendencies. As a result, the application of SWCNT as additives in advanced composite materials remain far from their potential, with proper dispersion being the major inhibitor. This work presents a dispersion quality control approach for water-based SWCNT dispersions (dispersed by a unique combination of physical and chemical methods), using complementary and easily scalable, characterization methods. UV-Vis spectroscopy, rheological measurements, and precipitant sheet resistance were used to understand the properties of the initial solution through processing and application. From an industrial perspective, these methods are fast and easy to measure while giving a repetitive and quick indication of dispersion quality and stability. The methods were correlated with microscopy and Raman spectroscopy to validate dispersion and SWCNT quality under various dispersing energies. The protocol was then applied to estimate the stability of SWCNT solutions, as well as the effectiveness of different surfactants in aiding dispersion. The simple, fast, and scalable combination of different characterizations provides good SWCNT dispersion and can be used as a quality control system for industrial production and usage.

HPLC-potentiometric method for determination of biogenic amines in alcoholic beverages: A reliable approach for food quality control

Determination of ten biogenic amines in alcoholic beverages by HPLC coupled to a potentiometric detector for food quality control is herein presented. Biogenic amines were separated by ion-pair chromatography on a C18 column using a gradient mobile phase of acetic acid, acetonitrile, and butane-sulfonic acid. Detection was accomplished by a miniaturized amine-selective electrode. The method was validated following ICH and Eurachem guidelines. Linear regression models provided R2 values from 0.9870 ± 0.0019 to 0.9991 ± 0.0014 for tyramine and cadaverine, respectively. Detection and quantification limits depend on the molecular weight of BAs, ranging from 9.3 to 60.5 and from 31.1 to 202.3 µg L−1 for methylamine and spermine, respectively. Repeatability and intermediate precision showed RSD values lower than 5.8 and 8.3%, respectively. Accuracy of assays yielded recovery values from 86.4 to 109.9%. The biogenic amines content in red wine, white wine, and beer samples were 7.54, 5.24, and 4.58 mg L-1, respectively.

Application of an innovative metabolomics approach to discriminate geographical origin and processing of black pepper by untargeted UHPLC-Q-Orbitrap-HRMS analysis and mid-level data fusion

An untargeted metabolomics approach based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) fingerprinting was applied to investigate the metabolic differences of black pepper among three geographical origins (Sri Lanka, Vietnam, and Brazil) and two post-harvest processing (sterilized and non-sterilized spice). Principal component analysis (PCA) was employed to assess the overall clustering of samples, whereas supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was effectively used for discrimination purposes. OPLS-DA models were fully validated (R2Y and Q2 values > 0.5) and the variable importance in projection (VIP) approach was employed to provide valuable data about differential metabolites with high discrimination potential (8 markers were putatively identified). For origin differentiation, three markers were highlighted with VIP values > 1.5 (i.e. reynosin, artabsinolide D, and tatridin B). Fatty acid derivates were the most frequent markers within the metabolites annotated for processing discrimination (e.g. 10,16-dihydroxyhexadecanoic acid and 9-hydroperoxy-10E-octadecenoic acid). Additionally, different combinations of mid-level data fusion of chromatographic-mass spectrometric techniques (UHPLC and gas chromatography coupled to HRMS) and proton nuclear magnetic resonance spectroscopy (1H NMR) were evaluated for the first time for geographical and processing discrimination of black pepper. The NMR-UHPLC-GC mid-level fused model was preferred among the tested fusion approaches since good sample clustering and no misclassification were achieved. Enhanced correct classification rate was achieved by mid-level data fusion compared with the findings obtained for one of the individual techniques (1H NMR fingerprinting) (from 92% to 100% of samples correctly classified). This study opens the path to new metabolomics approaches for black pepper authentication and quality control.

Application of approach for development of hptlc identification and quantification methods for determination of phenolic compounds and terpenoids of several Thymus L. species

The aim of this work was to improve the approaches for standardization of Thymus L. species by development of HPTLC identification of phenolic compounds (flavonoids and phenylpropanoids) and terpenoids (essential oils and triterpenoids) and quantitative determination of rosmarinic acid and flavonoids for six Thymus L. species of Ukraine flora, as well as determination of chromatographic profiles of Thymus L. species’ extracts obtained using different extraction methods.
 Materials and methods. Objects were: samples of dry herb of Th.serpyllum, Th.vulgaris, Th.Marschallianus, Th.Pallasianus, Th.calcareus, and Th.moldavicus of Ukraine origin collected in 2019-2021 years or acquired commercially on Ukraine market. Instruments: CAMAG HPTLC Herbal System, visionCats 2.5. The analytical grade reagents were used. Reference substances were purchased from Extrasynthese, Sigma Aldrich. Chromatography was performed on HPTLC plates Si 60 F254, Merck according to the developed methods.
 Results. A new approach for quality control of different Thymus L. species of Ukraine flora included the development of HPTLC methods for identification of main groups of bioactive substances of these species, such as flavonoids and phenylpropanoids, essential oils, triterpenoids; development of quantification method of rosmarinic acid and assay of total flavonoids, expressed as luteolin-7-O-glucoside. The characteristic HPTLC fingerprints of six Thymus L. species in three mobile phases of different polarities that cover a wide range of bioactive substances were established. The content of rosmarinic acid in different Thymus L. species samples was in the range of 0,11-0,72 %: Th.moldavicus – 0,11 %; Th.Marschallianus – 0,19-0,27 %; Th.serpyllum – 0,38 %; Th.vulgaris – 0,51 %; Th.calcareus – 0,56 %; T.Pallasianus – 0,72 %. The total flavonoids content, expressed as luteolin-7-O-glucoside, was in the range of 0,8-2,72 %: Th.moldavicus – 0,8 %; Th.serpyllum – 0,87 %; Th.vulgaris – 1,06 %; Th.Pallasianus – 1,28 %; Th.Marschallianus – 1,89 %; Th.calcareus – 2,72 %.
 Conclusions. The proposed scientific approach for quality evaluation of Thymus L. species using HPTLC allows to determine comprehensive information of chemical composition and content of active substances of multiple samples in parallel, in a cost and time-efficient manner