Application of principal component analysis on temporal evolution of COVID-19

The COVID-19 is one of the worst pandemics in modern history. We applied principal component analysis (PCA) to the daily time series of the COVID-19 death cases and confirmed cases for the top 25 countries from April of 2020 to February of 2021. We calculated the eigenvalues and eigenvectors of the cross-correlation matrix of the changes in daily accumulated data over monthly time windows. The largest eigenvalue describes the overall evolution dynamics of the COVID-19 and indicates that evolution was faster in April of 2020 than in any other period. By using the first two PC coefficients, we can identify the group dynamics of the COVID-19 evolution. We observed groups under critical states in the loading plot and found that American and European countries are represented by strong clusters in the loading plot. The first PC plays an important role and the correlations (C1) between the normalized logarithmic changes in deaths or confirmed cases and the first PCs may be used as indicators of different phases of the COVID-19. By varying C1 over time, we identified different phases of the COVID-19 in the analyzed countries over the target time period.

Metabolite Profiling of Different Solvent Extracts of the Microalgae Chlorella Vulgaris Via 1H NMR-Based Metabolomics

Introduction: In the present study, profiling of the cultured Chlorella vulgaris metabolome was carried out via 1H NMR metabolite profiling of 6 different solvent extracts. The results indicated that the six solvent extracts have metabolite profiles which are clearly different from each other. Methods: Multivariate data analysis (MVA) reveal that ethyl acetate and ethanol extracts were well separated from the aqueous extract by PC1 while being well separated from each other by PC2. The same observations were seen with chloroform and 50% ethanol extracts. In contrast, the chemical shift signals for hexane extract clusters in-between that of chloroform and 50% ethanol, indicating that they have similar chemical profiles. Using partial least square discriminative analysis (PLS-DA), compounds responsible for the group separation were identified from the loading plot. Detailed examination of the loading plot shows that ethanol and ethyl acetate extracts contain significantly higher amounts of carotenoids, amino acids, vitamins and fatty acids. A total of 35 compounds were detected from the 6 different solvents upon which the ethanolic and ethyl acetate extracts was identified to contain more metabolites and in wider range than the other organic solvent extracts. Results: Hence, these two extracts would be more appropriate in metabolite extraction for analysis and for medicinal purposes. Therefore, NMR spectroscopy in compliment with right choice of solvent for extraction could be utilized by relevant industries to evaluate and obtain maximum important metabolites in a shorter time. Conclusion: In addition to possession of high diverse metabolites, the microalgae C. vulgaris could serve as an important functional food ingredient in aquaculture industry and may possibly be considered as a source of biofuel.

Metabolite Profile Evaluation of Indonesian Roasted Robusta Coffees by 1H NMR Technique and Chemometrics

In this work, 1H NMR analysis, along with a chemometrics approach, had been applied for investigating metabolite profiles of Indonesian roasted Robusta coffees obtained from Lampung and Aceh. In total, 24 compounds had been successfully detected in the 1H NMR spectra of the Robusta coffee extracts. Concentrations of some identified metabolites present in the coffees were determined by the quantitative 1H NMR technique. Orthogonal projection to latent structure-discriminant analysis (OPLSDA) was used as a primary method for the chemometric approach. OPLSDA had classified clearly the Robusta coffee samples corresponding to their origin. Loading plot and S-plot of the OPLSDA revealed characteristic metabolites for each Robusta coffee. The results indicated that quinic acid, mannose, arabinoses, and acetic acid were an important discriminant compound for Lampung Robusta coffees. Meanwhile, lipids, lactic acid, and 5-caffeoylquinic acid were found as characteristic metabolites for Aceh Robusta coffee. This report provided knowledge about the chemical composition of Lampung and Aceh Robusta coffees and shed more light on the diversity of Indonesian Robusta coffees. Furthermore, it confirmed that 1H NMR analysis coupled with chemometrics was a powerful method for evaluating and classifying metabolite profiles of the roasted Robusta coffees.

Optimization of electronic sensors for detecting pollution due to organic gases using PARAFAC

<span>The principle point of this examination work is to recognize the butane, Acetone, Propane, ethane, LPG and other natural gases from the strong waste and do condition checking. Here the arrangement of sensors used to identify the poison gases from strong waste. Here our point is to build up a sensor cluster framework which will identify most extreme contamination gases and which is very responsive, minimal effort and low power devouring. We have assumed three sensors in position of six sensors and given the outcomes as fluctuation, score plot and stacking plot. Here we utilize the parallel factor analysis (PARAFAC) for identification of gases and contrast it and the key part investigation Principal component analysis (PCA). We confiscated three sensors in position of six sensors and given the outcomes as variance, score plot and loading plot. Electronic noses have given a plenty of advantages in different logical research fields. Here our point is to build up a sensor exhibit framework which will distinguish most extreme contamination gases and which is profoundly responsive, exact and minimal effort and low power expending. Here we utilize the parallel factor investigation method (PARAFAC) for discovery of gases and contrast it and the primary segment examination (PCA).</span>

DIFFERENTIATION OF BOVINE AND PORCINE GELATINES USING LC-MS/MS AND CHEMOMETRICS

Objective: To differentiate porcine gelatin and bovine gelatins using specific peptide markers as determined by liquid chromatography-mass spectrometry tandem with mass spectrometry (LC-MS/MS) and classify both gelatins using retention time and m/z as variables in principal component analysis (PCA). Methods: Porcine and bovine gelatins were digested using trypsin enzyme and then subjected to LC-MS/MS analysis. The specific peptides were identified. The classification between porcine and bovine gelatins was carried out using chemometrics of PCA using retention times and mass to charge ratio (m/z) as variables. Results: PCA using singvariables retention times (tR) and m/z could successfully classify porcine gelatin and bovine gelatin based on score plots of first principle component (PC1) and second principle component (PC2). The loading plot analysis showed that variable of tR32 and m/z32 contributed for the separation of both gelatins. Conclusion: The chromatograms of LC-MS/MS combined with PCA offered reliable method for differentiation between porcine and bovine gelatins. The developed method could be extended for halal authentication of food and pharmaceutical products via detection of porcine gelatin, non-halal gelatin.

Nor-kurarinone Characteristic of Chinese Sophora flavescens

The root of Sophora flavescens is used as a Chinese crude drug for treating various disorders. S. flavescens is grown in Japan, China and Korea. We previously used Principle Component Analysis (PCA) to demonstrate that 1H NMR spectra of root extracts of S. flavescens can be used to identify the country of origin of the sample (Japan or China). In the present study we identified a compound characteristic of Chinese S. flavescens using NMR metabolomics. Loading plot analysis of the PCA results and an NMR metabolomics study identified NMR signals from a compound identified as nor-kurarinone and characteristic of Chinese S. flavescens grown in Hangzhou. This compound was confirmed by HPLC analysis to be a distinctive marker for Chinese S. flavescens.

Study of Methanol Extracts from Different Parts of Peganum harmala L. Using 1H-NMR Plant Metabolomics

A nuclear magnetic resonance- (NMR-) based metabolomics method was used to identify differential metabolites of methanol extracts obtained from six parts of Peganum harmala L. (P. harmala), namely, the root, stem, leaf, flower, testa, and seed. Two multivariate statistical analysis methods, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), were combined to clearly distinguish among the P. harmala samples from the six different parts. Eleven differential components were screened by the PLS-DA loading plot, and the relative contents were calculated by univariate analysis of variance. Chemometric results showed significant differences in the metabolites of the different parts of P. harmala. The seeds contained large amounts of harmaline, harmine, and vasicine compared to other organs. The acetic acid, proline, lysine, and sucrose contents of the roots were significantly higher than those of the other parts. In the testa, the vasicine, asparagine, choline, and 4-hydroxyisoleucine contents were clearly dominant. The obtained data revealed the distribution characteristics of the metabolomes of the different P. harmala parts and provided fundamental knowledge for the rational development of its medicinal parts.

Ethylene-Induced Vinblastine Accumulation Is Related to Activated Expression of Downstream TIA Pathway Genes inCatharanthus roseus

We selected different concentrations of ethephon, to stressC. roseus. We used qRT-PCR and HPLC followed by PCA to obtain comprehensive profiling of the vinblastine biosynthesis in response to ethephon. Based on our findings, the results showed that the high concentration of ethephon had a positive effect at both transcriptional and metabolite level. Meanwhile, there was a remarkable decrease of hydrogen peroxide content and a promoted peroxidase activity in leaves. The loading plot combination with correlation analysis suggested thatCrPrx1could be regarded as a positive regulator and interacts with ethylene response factor (ERF) to play a key role in vinblastine content and peroxidase (POD) activity. This study provides the foundation for a better understanding of the regulation and accumulation of vinblastine in response to ethephon.

Identification of a Xanthine Oxidase-inhibitory Component from Sophora Flavescens using NMR-based Metabolomics

We demonstrate that NMR-based metabolomics studies can be used to identify xanthine oxidase-inhibitory compounds in the diethyl ether soluble fraction prepared from a methanolic extract of Sophora flavescens. Loading plot analysis, accompanied by direct comparison of 1H NMR spectra exhibiting characteristic signals, identified compounds exhibiting inhibitory activity. NMR analysis indicated that these characteristic signals were attributed to flavanones such as sophoraflavanone G and kurarinone. Sophoraflavanone G showed inhibitory activity towards xanthine oxidase in an in vitro assay.

High Frequency of RBC Transfusions in the STOP Study Was Associated with Reduction in Serum Biomarkers of Neurodegeneration, Vascular Remodeling and Inflammation

Abstract 244 Stroke is a major cause of morbidity and mortality among children with sickle cell anemia (SCA). Children with SCA at risk for stroke can be identified by transcranial Doppler (TCD) ultrasound screening for abnormally high cerebral artery blood flow velocity and strokes can be prevented by chronic packed red blood cell (RBC) transfusion. However, the mechanisms that lead to cerebral vasculopathy and stroke in SCA and that explain the beneficial effects of chronic RBC transfusions in stroke prevention are poorly understood. We have previously shown that pre-treatment serum levels of brain derived neurotropic factor (BDNF) and platelet derived growth factor (PDGF) subtypes, biomarkers of cerebral ischemia and arterial remodeling, were associated with both high TCD velocity and development of stroke. We hypothesized that frequency of RBC transfusion would be associated with altered serum levels of neurodegenerative, inflammatory and angiogenic markers in SCA children with high TCD velocity and tested this hypothesis by assaying levels of these markers in post-STOP serum samples. Frozen serum samples drawn one year after subject's exit from the STOP clinical trial phase were utilized. Given the positive trial results, all but 9 subjects had been on chronic transfusion regimen for at least one year at the time of sample collection. Eighty samples were assayed using multiplex antibody immobilized beads (Millipore Corp, Billerica, MA). The mean fluorescent intensity was measured using the Milliplex xMAP system powered by Luminex (Bio-Rad, Hercules, CA). Ten biologically related neurodegenerative, inflammatory and angiogenic biomarkers were tested. The total number (frequency) of RBC transfusions recorded over the study period (4 years) for each participant was categorized into High (≥ 40), Moderate (20 – 39) or Low (< 20) frequency of transfusion. Median distribution with 10 – 90th percentile of the levels of biomarkers and TCD velocity were expressed using box-plots and the differences in median distribution between groups based on frequency of transfusion was estimated using Kruskal-Wallis test. A principal component analysis (PCA) loading plot was used to demonstrate the biological relationships between the biomarkers, taking into consideration linear correlations and spatial relationships between them. There were no significant differences in the hematological and anthropometric measures between groups. Overall, our result showed that low transfusion frequency was associated with high serum levels of biomarkers and vice versa, despite no significant difference in hemoglobin level between groups. The high frequency transfusion group had lower serum levels of BDNF (p = 0.02), sVCAM-1 (p < 0.001), PDGF-AA (p < 0.001), CCL5 (p < 0.01), tPAI-1 (p < 0.01) and NCAM (p < 0.01) levels compared with the low frequency transfusion group (figure 1 a – e). Although not shown in the figures, the same pattern was observed with TCD velocity which was lower (160, 115.7 – 204.9 cm/s) in the low compared with the high (195, 154 – 272 cm/s) frequency transfusion group. In addition, the medium frequency transfusion group had significantly lower serum sVCAM-1 (p < 0.01) compared with the low frequency transfusion group and higher PDGF-AA (p < 0.01) compared with the high frequency transfusion group. A PCA loading plot (figure 2) shows clustering of the biomarkers that are most closely biologically related, these are also the biomarkers that were significantly affected by the frequency of transfusion. Red blood cell transfusions in the STOP study were associated with reduced serum levels of biomarkers of angiogenesis (PDGF-AA and sVCAM-1), cerebral ischemia/neuronal survival adaptation (BDNF and NCAM) and inflammation (RANTES/CCL5), and this effect was most pronounced in the group with the highest frequency of transfusions (equivalent to most chronic transfusion regimen). This suggests that the protective effects of chronic RBC transfusions on stroke development in children with SCA may be attributable to improved cerebral perfusion, reduced inflammation and down-regulation of hypoxia-induced angiogenic responses that promote arterial remodeling. One or more in this group of biologically-related and relevant markers may be useful for monitoring children with SCA receiving stroke prevention therapies and for designing treatment targets. Disclosures: No relevant conflicts of interest to declare.