ChemOS: An orchestration software to democratize autonomous discovery.

The current Edisonian approach to discovery requires up to two decades of fundamental and applied research for materials technologies to reach the market. Such a slow and capital-intensive turnaround calls for disruptive strategies to expedite innovation. Self-driving laboratories have the potential to provide the means to revolutionize experimentation by empowering automation with artificial intelligence to enable autonomous discovery. However, the lack of adequate software solutions significantly impedes the development of self-driving laboratories. In this paper, we make progress towards addressing this challenge, and we propose and develop an implementation of ChemOS; a portable, modular and versatile software package which supplies the structured layers necessary for the deployment and operation of self-driving laboratories. ChemOS facilitates the integration of automated equipment, and it enables remote control of automated laboratories. ChemOS can operate at various degrees of autonomy; from fully unsupervised experimentation to actively including inputs and feedbacks from researchers into the experimentation loop. The flexibility of ChemOS provides a broad range of functionality as demonstrated on five applications, which were executed on different automated equipment, highlighting various aspects of the software package.

Quality assessment of Coffea arabica commercial samples.

A simple and reliable HPLC method was developed and validated for the quality consistency evaluation of Coffea arabica commercial samples through establishing chromatographic fingerprint and simultaneous determination of bioactive constituents. In the HPLC fingerprint, thirteen common peaks were selected to assess the similarities of coffee samples of different geographical origin. A similarity analysis showed values from 0.434 to 0.950 for the analyzed samples, while quantitation of selected bioactive compounds revealed the highest content of caffeine and the lowest of p-coumaric acid and theobromine in coffee samples. Since phenolic compounds and alkaloids are commonly recognized as natural antioxidants, the antioxidant activity of coffee extracts was also evaluated. The correlation analysis and principal component analysis indicated that the combination of HPLC fingerprint and quantitative analysis can be readily utilized as a quality assessment tool for coffee and other plant products.

Comparison of two Polygonum chinense varieties used in Chinese cool tea in terms of chemical profiles and antioxidant/anti-inflammatory activities.

Despite the extensive use of Polygonum chinense (PC) as a detoxifying ingredient of Chinese cool tea, the efficacy of different PC varieties remains underexplored. Herein, we compare the chemical profiles and antioxidant/anti-inflammatory activities of the aqueous extracts of two PC varieties, namely P. chinense var. chinense (PCC) and P. chinense var. hispidum (PCH). Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MSMS) and multivariate analysis are used to rapidly identify extract components, while DPPH radical scavenging and xylene-induced mice ear edema assays are used to evaluate antioxidant and anti-inflammatory activities, respectively. Correlation analysis reveals that ellagic acid and quercitrin contents are positively correlated with the magnitude of the anti-inflammatory effect, and the adopted technique is concluded to allow for the rapid discrimination of PC varieties used in Chinese cool tea formulations.

Quantitative and Chemical Fingerprint Analysis of Desmodium styracifolium by High-Performance Liquid Chromatography Combined with Chemometrics.

In this study, a valid and comprehensive evaluation method for assessing the quality of Desmodium styracifolium (Osb.) Merr has been established, based on analysis of high-performance liquid chromatography fingerprint combined with the similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), discriminant analysis (DA) and the quantitative analysis multi-components by single marker (QAMS) method. Eleven peaks of the common model were obtained and analyzed using SA, HCA, PCA and DA analysis. These methods indicated a similar conclusion that 31 batches of D. styracifolium samples were categorized into two clusters basically coincident with their geographical regions of origin. Four peaks were identified as schaftoside, isoorientin, isoschaftoside and isovitexin. Schaftoside was selected as the internal standard, and the relative correction factors between schaftoside and the other three flavonoids were calculated using the QAMS method. The accuracy of the QAMS method was verified by comparing with the results calculated by the external standard method. No significant difference between the two methods was found. In conclusion, the established methods were scientifically applied in the quality evaluation of D. styracifolium.

International Ring Trial of a High Resolution Targeted Metabolomics and Lipidomics Platform for Serum and Plasma Analysis.

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.

Application of different chromatographic techniques and chemometric analysis in authenticity testing of plant protection products containing azoxystrobin as an active substance.

Azoxystrobin (methyl(2E)-2-{2-[6-(2-cyanophenoxy)pyrimidin-4-yloxy] phenyl}-3-methoxyacrylate) is an active ingredient used to protect crops against fungal diseases. The experience of the Polish control laboratory indicates relatively frequent cases of counterfeit plant protection products (PPPs) containing this active substance. The present study aimed to use chemometric methods to model chemical fingerprints obtained by different chromatographic techniques to verify the original formulation of PPPs containing the active substance azoxystrobin. The pesticides used in the study came from different sources (including stores and warehouses), were manufactured at a different time and came from different production batches. The results obtained with the HPLC-DAD and HS-GC-MS techniques were then modeled using principal component analysis (PCA) and soft independent modeling by class analogy (SIMCA) classifier. The proposed approach has been confirmed as useful for verifying the authenticity of PPPs and can be used in the routine control testing of SC pesticides containing azoxystrobin.

Quantitative fingerprint and quality control analysis of Compound Liquorice Tablet combined with antioxidant activities and chemometrics methods.

BACKGROUND: Herbal medicine (HM), as a complex system, is difficult to investigate their quality consistency effectively by chromatographic fingerprinting obtained in a single detection method. Moreover, active compound discovery affords no information about pharmacological activity until late in the discovery process, and the interaction between HMs in vitro is not yet clear, which requires sufficient practice to prove their effectiveness. PURPOSE: Therefore, the purpose of this study was to improve the quality control methods of Compound Liquorice Tablet (CLT) using multi-wavelength fusion fingerprinting, explore the possible antioxidant components and assess the interaction between herbs combined with bioactivity evaluation. METHODS AND DESIGN: Once the theoretical standard preparation obtained in combination of multi-wavelength fusion fingerprinting and hierarchical clustering analysis, averagely linear quantified fingerprint method could rapidly calculate the composition similarities and efficiently quantify the multiple components of CLTs without any chemical standard. Furthermore, the fingerprint-efficacy relationship was investigated by integrating high performance liquid chromatography fingerprints with antioxidant activity assessment using the partial least squares model, which was capable of directly discovering the bioactive ingredients. Hereafter, combination index value was introduced to evaluate the correlation between the two antioxidant herbs in CLT formula. RESULTS: The results showed that CLT samples were effectively identified and quantified, and their quality was accurately distinguished. By analyzing the antioxidant evaluation results, it was found that CLT had strong antioxidant activity, and through the study on PLS model and antioxidant activity assay of individual compounds, it was found that the order of chemical constituents responsible for antioxidant activity in CLT was as follows: flavonoids > saponins > alkaloids. Finally, it was determined that the CI value of GE-PPCE was in the range of 1.20-1.61, indicating that the interaction of the GE-PPCE pair was a slight antagonism. CONCLUSION: Thus, this study provided a preferred way for monitoring the quality consistency of HM, exploring possible bioactive components of HMs and assessing the interaction between herbs.

Working with log-ratios.

Instrumental signals of samples cannot be compared and/or analysed directly if their concentrations are unknown. Differences in overall concentration need to be removed at the data normalization step. The choice of normalization method has a profound effect on the final results of data analysis, and especially on biomarker identification. One of the possible approaches to deal with the 'size effect' is to work with size-irrelevant (log) ratios instead of the original variables. In the presented study, the performance of log-ratio methods, namely pairwise log-ratio (plr) and centered log-ratio (clr), is discussed for real and simulated data sets with different characteristics. It was found that the clr method can lead to distribution of local differences along an entire signal and as such, it should be avoided in all studies aiming to identify biomarkers.

MetNet: Metabolite Network Prediction from High-Resolution Mass Spectrometry Data in R Aiding Metabolite Annotation.

A major bottleneck of mass spectrometric metabolomic analysis is still the rapid detection and annotation of unknown m/ z features across biological matrices. This kind of analysis is especially cumbersome for complex samples with hundreds to thousands of unknown features. Traditionally, the annotation was done manually imposing constraints in reproducibility and automatization. Furthermore, different analysis tools are typically used at different steps which requires parsing of data and changing of environments. We present here MetNet, implemented in the R programming language and available as an open-source package via the Bioconductor project. MetNet, which is compatible with the output of the xcms/CAMERA suite, uses the data-rich output of mass spectrometry metabolomics to putatively link features on their relation to other features in the data set. MetNet uses both structural and quantitative information on metabolomics data for network inference and enables the annotation of unknown analytes.

Study on the source and characteristics of Evodia rutaecarpa based on chemical pattern recognition.

In this study, the appearance and texture of E. rutaecarpa were linked with the chemical constituents to explore methods of classification of E. rutaecarpa. The Chemometrics such as Hierarchical cluster analysis (HCA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) models were used for analysis. According to the models, samples of E. rutaecarpa were divided into three categories based on their source: Evodia, Stone Tiger and Sparse Evodia. The Evodia category could be subdivided into two categories, one representing large fruits with a greater degree of cracking and the other representing large fruits with little or no cracking. The method provided by this study combines chemometrics with HPLC fingerprints, which can provide a basis and reference for the identification of E. rutaecarpa and enables establishment of a grade standard.

HPLC-based Measurement of Glycated Hemoglobin using Dried Blood Spots Collected under Adverse Field Conditions.

Glycated hemoglobin (HbA1c) measured using high-performance liquid chromatography (HPLC) assays with venous blood and dried blood spots (DBS) are compared for 143 paired samples collected in Aceh, Indonesia. Relative to gold-standard venous-blood values, DBS-based values reported by the HPLC are systematically upward biased for HbA1c<8% and the fraction diabetic (HbA1c ≥ 6.5%) is overstated almost five-fold. Inspection of chromatograms from DBS assays indicates the % glycosylated calculated by the HPLC excludes part of the hemoglobin A which is misidentified as a hemoglobin variant. Taking this into account, unbiased DBS-based values are computed using data from the machine-generated chromatograms. When the DBS are collected in a clinic-like setting, under controlled humidity/temperature conditions, the recalculated values are almost identical to venous-based values. When DBS are collected under field conditions, the recalculated values are unbiased, but only about half the HbA1c values are measured reliably, calling into question the validity of the other half. The results suggest that collection conditions, particularly humidity, affect the quality of the DBS-based measures. Cross-validating DBS-based HbA1c values with venous samples collected under exactly the same environmental conditions is a prudent investment in population-based studies.

Discovery of markers for discriminating the age of cultivated ginseng by using UHPLC-QTOF/MS coupled with OPLS-DA.

BACKGROUND: Ginseng (Ginseng Radix et Rhizoma, Panax ginseng C.A. Meyer) is gaining more publicity in modern society due to its health benefit and huge value in market. In the practice of grading and pricing of ginseng, the age is one of the major factor influencing the price and grade of ginseng. Therefore, the age discrimination is an important task for the quality control of ginseng. However, the traditional morphological methods are too subjective to be reproductive in discrimination. PURPOSE: To establish a method that can discriminate the ginseng samples with different cultivation years. STUDY DESIGN: To analyze the correlation between chemical compositions and cultivation years of cultivated ginseng samples of different age and thus discover potential quality marker (Q-marker) for discriminating the age of cultivated ginseng. METHODS: In the present study, the ultra-high performance liquid chromatography coupled with the quadrupole-time of flight mass spectrometry (UHPLC-QTOF/MS) were utilized for the age discrimination and marker discovery. A statistical data processing procedure was established to screen markers and reduce the false positive rate. RESULTS: The results showed that the ginseng samples from 2- to 6-year-old could be well separated in the orthogonal projections on the latent structure - discrimination analysis (OPLS-DA) using the markers screened by the established statistical procedure, which could reduce approximately 20% of the insignificant markers and false positive discoveries. Ultimately, more than 50 compounds contributing to the age discrimination were identified including one new compound (malonylginsenoside). One negative marker (1038.4825@8.98) was discovered for the 2-year-old ginseng, and an equation was established to effectively predict the age of 3- to 6-year-old of ginseng. CONCLUSION: The constructed method can discriminate the ginseng samples with different cultivation years and is a complement to the traditional discrimination method of ginseng age.

E-nose, e-tongue and e-eye for edible olive oil characterization and shelf life assessment: A powerful data fusion approach.

The aim of this work was to investigate the applicability of e-senses (electronic nose, electronic tongue and electronic eye) for the characterization of edible olive oils (extra virgin, olive and pomace) and for the assessment of extra virgin olive oil and olive oil quality decay during storage at different temperatures. In order to obtain a complete description of oil samples, physico-chemical analyses on quality and nutritional parameters were also performed. Data were processed by PCA and a targeted data processing flow-sheet has been applied to physico-chemical and e-senses dataset starting from data pre-processing introducing an innovative normalization method, called t0 centering. On e-senses data a powerful mid-level data fusion approach has been employed to extract relevant information from different analytical sources combining their individual contributions. On physico-chemical data, an alternative approach for grouping extra virgin olive oil and olive oil samples on the basis of their freshness was applied and two classes were identified: fresh and oxidized. A k-NN classification rule was developed to test the performance of e-senses to classify samples in the two classes of freshness and the average value of correctly classified samples was 94%. Results demonstrated that the combined application of e-senses and the innovative data processing strategy allows to characterize edible olive oils of different categories on the basis of their sensorial properties and also to follow the evolution during storage of extra-virgin olive oil and olive oil sensorial properties thus assessing the quality decay of oils.

Haemoglobin variants may cause significant differences in haemoglobin A1c as measured by high-performance liquid chromatography and enzymatic methods in diabetic patients: a cross-sectional study.

Background We aimed to determine whether the discrepancy between haemoglobin A1c values determined by high-performance liquid chromatography and enzymatic haemoglobin A1c measurements in diabetic patients was clinically relevant. Methods We randomly recruited 1421 outpatients undergoing diabetic treatment and follow-up who underwent at least three haemoglobin A1c measurements between April 2014 and March 2015 at our clinic. In 6369 samples, haemoglobin A1c was simultaneously measured by HA-8160 and MetaboLead (enzymatic assay), and the values were compared. Results haemoglobin A1c measurements by high-performance liquid chromatography and enzymatic assay were strongly correlated (correlation coefficient: 0.9828, linear approximation curve y = 0.9986x - 0.2507). Mean haemoglobin A1c (6.8 ± 1.0%) measured by high-performance liquid chromatography was significantly higher than that measured by enzymatic assay (6.5 ± 1.0%, P < 0.0001). During the sample processing, four (0.3%) subjects presented consistently lower haemoglobin A1c values (<0.7%) by high-performance liquid chromatography than those from enzymatic assay. Of these, three had Hb Toranomon [ß112 (G14) Cys→Trp]. The fourth had Hb Ube-2 [α68 (E17) Asn→Asp]. One other subject presented consistently higher haemoglobin A1c values (>1%) by high-performance liquid chromatography than those from enzymatic assay and was diagnosed with a -77 (T > C) mutation in the δ-globin gene. These unrelated asymptomatic subjects had normal erythrocyte profiles, without anaemia. Conclusions We showed that haemoglobin A1c values measured by high-performance liquid chromatography were significantly higher than those measured by enzymatic assay in diabetic subjects. However, when an oversized deviation (>0.7%) between glycaemic control status and haemoglobin A1c is apparent, clinicians should check the methods used to measure haemoglobin A1c and consider the possible presence of a haemoglobin variant.

Statistical procedures for the determination of linearity, detection limits and measurement uncertainty: A deeper look into SPE-LC-Orbitrap mass spectrometry of pharmaceuticals in wastewater.

This research addresses some critical challenges regarding the validation of a quantitative multi-residue method for pharmaceuticals in wastewater making use of modern SPE-LC-Orbitrap high-resolution mass spectrometry. Particular attention is given to study in detail response linearity, to realistically estimate detection limits, and to express the measurement precision of the analyte concentration, obtained by external calibration. First, linearity of the Orbitrap response showed to be matrix dependent in a counter intuitive way: stronger deviations from linearity were observed for pure solvent standards than for complex matrices like wastewater. Second, detection limits risk to be overestimated for ubiquitously present compounds for which true blank matrix samples are hard to find, leading to false negative findings. A novel and easy applicable methodology is presented to allow a better estimation of detection limits using the response of the natural isotopes. Third, a statistical methodology to estimate the measurement precision of the analyte concentration using basic validation parameters is developed specifically for the context of multi-residue quantification.

Spectrophotometric determination of rosuvastatin in pharmaceutical formulations using quinalizarin

ABSTRACT This work presents the development of a methodology based on the formation of a charge transfer complex between quinalizarin and rosuvastatin, allowing for the spectrophotometric determination of rosuvastatin at 579 nm. The factors involved in the sensitivity of the technique were studied (nature and proportion of the solvent, reaction time, pH of aqueous phase and quinalizarin concentration). The proposed spectrophotometric procedures were validated with respect to linearity, ranges, precision, accuracy, detection and quantification limits. Calibration curves of the formed color products showed good linear relationships over the concentration range of 6-15 mg L-1. The proposed method has been successfully applied, which can be confirmed by interference test (comparison between the standard curves and addition of analyte), method precision (RSD 2.3% to 6 mg L-1), and by accuracy (statistically equivalent results between the proposed method and a chromatographic method of reference).

Application of a new method, orthogonal projection to latent structure (OPLS) combined with principal component analysis (PCA), to screening of prostaglandin E2 production inhibitory flavonoids in Scutellaria Root.

A new method consisting of orthogonal projection to latent structure (OPLS) and modified principal component analysis (PCA) was applied to a screening of bioactive compounds from natural products. In this report, extracts of 52 Scutellaria Root (the root of Scutellaria baicalensis Georgi) samples were analyzed by high-performance liquid chromatography (HPLC), and their inhibitory activities towards prostaglandin E2 (PGE2) production in a murine macrophage-like cell line J774.1 were examined. Wogonin and oroxylin A were predicted to be strong inhibitors of PGE2 production by OPLS analysis of the data. However, 6-methoxywogonin, which has been reported to have inhibitory activity, was omitted. Modified PCA was then applied to these data as a filter to exclude compounds less relevant to the activity, and OPLS analysis was applied to the modified data. As a result, this method predicted wogonin, oroxylin A and 6-methoxywogonin to be strong inhibitors of PGE2 production without any prior knowledge. The predictions by the OPLS combined with PCA method of PGE2 production inhibitory activities of 52 samples showed good agreement with the actual data. This method is simple and effective and can be used in screening of bioactive natural compounds without any prior knowledge.

Theoretical Models and QSRR in Retention Modeling of Eight Aminopyridines.

In this article, retention modeling of eight aminopyridines (synthesized and characterized at the Faculty of Pharmacy) in reversed-phase high performance liquid chromatography (RP-HPLC) was performed. No data related to their retention in the RP-HPLC system were found. Knowing that, it was recognized as very important to describe their retention behavior. The influences of pH of the mobile phase and the organic modifier content on the retention factors were investigated. Two theoretical models for the dependence of retention factor of organic modifier content were tested. Then, the most reliable and accurate prediction of log k was created, testing multiple linear regression model-quantitative structure-retention relationships (MLR-QSRR) and support vector regression machine-quantitative structure-retention relationships (SVM-QSRR). Initially, 400 descriptors were calculated, but four of them (POM, log D, M-SZX/RZX and m-RPCG) were included in the models. SVM-QSRR performed significantly better than the MLR model. Apart from aminopyridines, four structurally similar substances (indapamide, gliclazide, sulfamethoxazole and furosemide) were followed in the same chromatographic system. They were used as external validation set for the QSRR model (it performed well within its applicability domain, which was defined using a bounding box approach). After having described retention of eight aminopyridines with both theoretical and QSRR models, further investigations in this field can be conducted.

Fingerprint analysis, multi-component quantitation, and antioxidant activity for the quality evaluation of Salvia miltiorrhiza var. alba by high-performance liquid chromatography and chemometrics.

Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li has wide prospects in clinical practice. A useful comprehensive method was developed for the quality evaluation of S. miltiorrhiza var. alba by three quantitative parameters: high-performance liquid chromatography fingerprint, ten-component contents, and antioxidant activity. The established method was validated for linearity, precision, repeatability, stability, and recovery. Principal components analysis and hierarchical clustering analysis were both used to evaluate the quality of the samples from different origins. The results showed that there were category discrepancies in quality of S. miltiorrhiza var. alba samples according to the three quantitative parameters. Multivariate linear regression was adopted to explore the relationship between components and antioxidant activity. Three constituents, namely, danshensu, rosmarinic acid, and salvianolic acid B, significantly correlated with antioxidant activity, and were successfully elucidated by the optimized multivariate linear regression model. The combined use of high-performance liquid chromatography fingerprint analysis, simultaneous multicomponent quantitative analysis, and antioxidant activity for the quality evaluation of S. miltiorrhiza var. alba is a reliable, comprehensive, and promising approach, which might provide a valuable reference for other herbal products in general to improve their quality control.

Quality-by-design-based ultra high performance liquid chromatography related substances method development by establishing the proficient design space for sumatriptan and naproxen combination.

Quality-by-design-based methods hold greater level of confidence for variations and greater success in method transfer. A quality-by-design-based ultra high performance liquid chromatography method was developed for the simultaneous assay of sumatriptan and naproxen along with their related substances. The first screening was performed by fractional factorial design comprising 44 experiments for reversed-phase stationary phases, pH, and organic modifiers. The results of screening design experiments suggested phenyl hexyl column and acetonitrile were the best combination. The method was further optimized for flow rate, temperature, and gradient time by experimental design of 20 experiments and the knowledge space was generated for effect of variable on response (number of peaks ≥ 1.50 - resolution). Proficient design space was generated from knowledge space by applying Monte Carlo simulation to successfully integrate quantitative robustness metrics during optimization stage itself. The final method provided the robust performance which was verified and validated. Final conditions comprised Waters® Acquity phenyl hexyl column with gradient elution using ammonium acetate (pH 4.12, 0.02 M) buffer and acetonitrile at 0.355 mL/min flow rate and 30°C. The developed method separates all 13 analytes within a 15 min run time with fewer experiments compared to the traditional quality-by-testing approach.