Different Metabolites in the Roots, Seeds, and Leaves of Acanthopanax senticosus and Their Role in Alleviating Oxidative Stress

In this study, we examined the metabolites from different parts of Acanthopanax senticosus and their role in alleviating damage caused by oxidative stress. We used UHPLC-QTOF-MS to analyze the chemical components in the root, seed, and leaf extracts of A. senticosus. Two multivariate statistical analysis methods—namely, principal component analysis and partial least square discriminant analysis—were used to distinguish the samples obtained from different parts of the plant. Using univariate statistics, 130 different metabolites were screened out. Among these, the relative content of flavonoids and terpenoids was found to be highest in the leaves, the lignin and phenolic acid content was highest in the roots, and the amino acid and phenolic acid levels were highest in seeds. An MTT assay was used to test the anti-H2O2 oxidative damage to PC12 cells in different parts of the sample. Lastly, using Pearson’s correlation analysis, various metabolites from different parts of A. senticosus were correlated with their antioxidant effects from the corresponding parts. Fifty-two related different metabolites were found, of which 20 metabolites that were positively correlated to oxidative stress were present at a relatively higher level in the roots, whereas 32 metabolites that were negatively correlated were present at relatively higher levels in the seeds and leaves. The results of this study reveal the distribution characteristics and the antioxidant activity of different metabolites of A. senticosus and provide a reference for the rational development of its medicinal parts.

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A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

Journal of Near Infrared Spectroscopy ◽

10.1177/0967033520987315 ◽

2021 ◽

pp. 096703352098731

Author(s):

Adenilton C da Silva ◽

Lívia PD Ribeiro ◽

Ruth MB Vidal ◽

Wladiana O Matos ◽

Gisele S Lopes

Keyword(s):

Quality Control ◽

Discriminant Analysis ◽

Near Infrared ◽

Nir Spectroscopy ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Chemical Components ◽

Linear Discriminant ◽

Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

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Metabolomics profiling of Polygoni Multiflori Radix and Polygoni Multiflori Radix Preparata extracts using UPLC-Q/TOF-MS

Chinese Medicine ◽

10.1186/s13020-019-0268-3 ◽

2019 ◽

Vol 14 (1) ◽

Cited By ~ 1

Author(s):

Zhaoyan Zhang ◽

Liang Yang ◽

Xiaoyan Huang ◽

Yue Gao

Keyword(s):

High Performance ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Alpha Linolenic Acid ◽

Multivariate Statistical ◽

Biochemical Indicators ◽

Flight Mass Spectrometry ◽

Underlying Mechanisms ◽

Tof Ms

Abstract Background The side effects caused by Polygoni Multiflori Radix (PMR) and Polygoni Multiflori Radix Praeparata (PMRP) have often appeared globally. There is no research on the changes of endogenous metabolites among PMR- and PMRP-treated rats. The aim of this study was to evaluate the varying metabolomic effects between PMR- and PMRP-treated rats. We tried to discover relevant differences in biomarkers and endogenous metabolic pathways. Methods Hematoxylin and eosin staining and immunohistochemistry staining were performed to find pathological changes. Biochemical indicators were also measured, one-way analysis of variance with Dunnett’s multiple comparison test was used for biochemical indicators comparison among various groups. Metabolomics analysis based on ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-Q/TOF-MS) was performed to find the changes in metabolic biomarkers. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to reveal group clustering trend, evaluate and maximize the discrimination between the two groups. MetaboAnalyst 4.0 was performed to find and confirm the pathways. Results PMR extracts exhibited slight hepatotoxic effects on the liver by increasing aspartate and alanine aminotransferase levels. Twenty-nine metabolites were identified as biomarkers, belonging to five pathways, including alpha-linolenic acid metabolism, taurine and hypotaurine metabolism, glycerophospholipid metabolism, arginine and proline metabolism, and primary bile acid biosynthesis. Conclusion This study provided a comprehensive description of metabolomic changes between PMR- and PMRP-treated rats. The underlying mechanisms require further research.

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Chemical Composition and Antimicrobial Activity of Three Essential Oils from Curcuma wenyujin

Natural Product Communications ◽

10.1177/1934578x1300800430 ◽

2013 ◽

Vol 8 (4) ◽

pp. 1934578X1300800 ◽

Cited By ~ 3

Author(s):

Jingjing Zhu ◽

Agnieszka D. Lower-Nedza ◽

Meng Hong ◽

Song Jiec ◽

Zhimin Wang ◽

...

Keyword(s):

Antimicrobial Activity ◽

Essential Oils ◽

Herbal Medicines ◽

Principal Component ◽

Antimicrobial Activities ◽

Inhibitory Effect ◽

Partial Least Square ◽

Least Square ◽

Chemical Components ◽

Potent Inhibitory Effect

Curcuma wenyujin is a traditional medicinal plant in China. The non-steamed rhizomes, steamed rhizomes and steamed roots of this plant are used as herbal medicines in three clinics, namely Pian-jiang-huang (PJH), Wen-e-zhu (WEZ), and Wen-yu-jin (WYJ), and are officially listed in the Chinese Pharmacopoeia. The purpose of this study was to conduct a comparative analysis of the three essential oils extracted from the C. wenyujin rhizomes and roots using GC-MS, and in doing so thirty compounds were identified. Principal component analysis (PCA) effectively distinguished the samples taken from the three different groups. Monoterpenoids, including camphene, linalool, camphor, isoborneol, borneol and eucalyptol, were characteristic components of the PJH oil, while β-elemene, β-elemenone, γ-elemene and δ-elemene were typical components of the WEZ oil, and propanenitrile, caryophyllene oxide, (-)-caryophyllene, germacrene B, pogostol and α-humulene were representative ingredients of the WYJ oil. The ratio of sesquiterpenoids to monoterpenoids in PJH, WEZ, and WYJ were 2:1, 5:1 and 7:1, respectively. The antimicrobial activities of the three essential oils and of the six main ingredients were tested against two bacterial and one fungal strains using agar diffusion and broth dilution methods. The essential oil of PJH was shown to present a higher antimicrobial activity than that of WEZ and WYJ. Based on the Partial Least Square Model (PLS), the correlation between the antimicrobial activity of the tested oils and the identified chemical components was discussed and potential components of the antimicrobial activity were predicted according to Variable Importance in the Project (VIP) Value. The tested monoterpenes eucalyptol and isoborneol demonstrated a higher inhibitory activity than the sesquiterpenes germacrone, curdione and β-elemene. Therefore, the potent inhibitory effect of the PJH oil might be attributed to its higher content of monoterpenes. The MIC values for the essential oils and their ingredients ranged from 62.5 to 500 μg/mL.

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Implementasi Kansei Engineering pada Aplikasi E-learning Untuk Sekolah Menengah Kejuruan

JURNAL SISTEM INFORMASI BISNIS ◽

10.21456/vol9iss2pp165-176 ◽

2019 ◽

Vol 9 (2) ◽

pp. 165

Author(s):

Yoga Megasyah

Keyword(s):

Teaching And Learning ◽

Logical Consequence ◽

Principal Component ◽

Word List ◽

Partial Least Square ◽

Least Square ◽

Kansei Engineering ◽

Multivariate Statistical ◽

Coefficient Corrélation ◽

E Learning

E-learning is the basis and logical consequence of the development of information and communication technology. With E-learning, teaching and learning methods in schools that use technology through electronic media such as computers, laptops, netbooks, or smartphones with internet networks or others. This study uses Kansei Word to detect the feelings of users of E-learning applications. The Kansei Word list is used as many 15 words related to the appearance of the E-learning application. E-learning application specimens used 8 specimens. This study involved 80 participants consisting of 40 students from SMK PGRI 3 Cimahi, 40 students from SMK 4 Padalarang. The questionnaire results from participants were then processed using multivariate statistical analysis, namely Cronbach's Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) and Partial Least Square (PLS) analysis. This study produced 3 recommendations for the design of E-learning application. This recommendation is the result of the Kansei Engineering process which comes from 3 groups of participant data, namely groups of data of all participants, participants of SMK PGRI 3 Cimahi students and participants of SMK 4 Padalarang students.

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Evaluation of Metabolomic Profile and Growth of Moringa oleifera L. Cultivated with Vermicompost under Different Soil Types

Agronomy ◽

10.3390/agronomy11102061 ◽

2021 ◽

Vol 11 (10) ◽

pp. 2061

Author(s):

Luis Alberto Manzano-Gómez ◽

Jorge Martín Guzmán-Albores ◽

Reiner Rincón-Rosales ◽

Robert Winkler ◽

Clara Ivette Rincón-Molina ◽

...

Keyword(s):

Moringa Oleifera ◽

Principal Component ◽

Dry Weight ◽

Partial Least Square ◽

Least Square ◽

Soil Types ◽

Metabolomic Profile ◽

Leaf Extracts ◽

Wide Range ◽

Induced Changes

Moringa oleifera is a highly versatile plant with potential use in the agro-food and biochemical industry. The goals of this study were to evaluate the effect of chemical fertilization and vermicompost on plant growth, and to analyze the metabolomic profile of M. oleifera crops cultivated over agricultural and native soils. The extracts were obtained from 90-day-old leaves via extraction with a hydroalcoholic mixture. Multivariate data analyses, such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA), were used to differentiate the distribution of leaf metabolites according to the soils or types of fertilizers used for the cultivation of Moringa oleifera. The results indicated that there was no significant effect on parameters such as plant height, root length and dry weight of leaves (p < 0.05). UPLC-ESI-MS/MS analysis of leaf extracts revealed a wide range of flavonoids, alkaloids and organic acids. The results of PCA and PLS-DA confirmed that the type of fertilizer had an effect on the metabolomic profile of M. oleifera leaves. The application of vermicompost induced changes in the metabolomic profile, but not in the morphometric variables of Moringa oleifera. These results are important for metabolite production via organic cultures and over different soil types in the industrialization of Moringa.

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Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

Xplore Journal of Statistics ◽

10.29244/xplore.v8i1.275 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Khairunnisa Khairunnisa ◽

Rizka Pitri ◽

Victor P Butar-Butar ◽

Agus M Soleh

Keyword(s):

Statistical Downscaling ◽

General Circulation ◽

Principal Component Regression ◽

Circulation Model ◽

Principal Component ◽

Meteorological Station ◽

Grid Size ◽

Partial Least Square ◽

Least Square ◽

Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

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A Novel Validated Injectable Colistimethate Sodium Analysis Combining Advanced Chemometrics and Design of Experiments

Molecules ◽

10.3390/molecules26061546 ◽

2021 ◽

Vol 26 (6) ◽

pp. 1546

Author(s):

Ioanna Dagla ◽

Anthony Tsarbopoulos ◽

Evagelos Gikas

Keyword(s):

Design Of Experiments ◽

High Performance ◽

Similarity Index ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Distance Measures ◽

Linear Regression Models ◽

Colistimethate Sodium

Colistimethate sodium (CMS) is widely administrated for the treatment of life-threatening infections caused by multidrug-resistant Gram-negative bacteria. Until now, the quality control of CMS formulations has been based on microbiological assays. Herein, an ultra-high-performance liquid chromatography coupled to ultraviolet detector methodology was developed for the quantitation of CMS in injectable formulations. The design of experiments was performed for the optimization of the chromatographic parameters. The chromatographic separation was achieved using a Waters Acquity BEH C8 column employing gradient elution with a mobile phase consisting of (A) 0.001 M aq. ammonium formate and (B) methanol/acetonitrile 79/21 (v/v). CMS compounds were detected at 214 nm. In all, 23 univariate linear-regression models were constructed to measure CMS compounds separately, and one partial least-square regression (PLSr) model constructed to assess the total CMS amount in formulations. The method was validated over the range 100–220 μg mL−1. The developed methodology was employed to analyze several batches of CMS injectable formulations that were also compared against a reference batch employing a Principal Component Analysis, similarity and distance measures, heatmaps and the structural similarity index. The methodology was based on freely available software in order to be readily available for the pharmaceutical industry.

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The inflammatory profile of cerebrospinal fluid, plasma, and saliva from patients with severe neuropathic pain and healthy controls-a pilot study

BMC Neuroscience ◽

10.1186/s12868-021-00608-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Mika Jönsson ◽

Björn Gerdle ◽

Bijar Ghafouri ◽

Emmanuel Bäckryd

Keyword(s):

Cerebrospinal Fluid ◽

Neuropathic Pain ◽

Pain Intensity ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Therapeutic Interventions ◽

Healthy Controls ◽

Inflammatory Profile

Abstract Background Neuropathic pain (NeuP) is a complex, debilitating condition of the somatosensory system, where dysregulation between pro- and anti-inflammatory cytokines and chemokines are believed to play a pivotal role. As of date, there is no ubiquitously accepted diagnostic test for NeuP and current therapeutic interventions are lacking in efficacy. The aim of this study was to investigate the ability of three biofluids - saliva, plasma, and cerebrospinal fluid (CSF), to discriminate an inflammatory profile at a central, systemic, and peripheral level in NeuP patients compared to healthy controls. Methods The concentrations of 71 cytokines, chemokines and growth factors in saliva, plasma, and CSF samples from 13 patients with peripheral NeuP and 13 healthy controls were analyzed using a multiplex-immunoassay based on an electrochemiluminescent detection method. The NeuP patients were recruited from a clinical trial of intrathecal bolus injection of ziconotide (ClinicalTrials.gov identifier NCT01373983). Multivariate data analysis (principal component analysis and orthogonal partial least square regression) was used to identify proteins significant for group discrimination and protein correlation to pain intensity. Proteins with variable influence of projection (VIP) value higher than 1 (combined with the jack-knifed confidence intervals in the coefficients plot not including zero) were considered significant. Results We found 17 cytokines/chemokines that were significantly up- or down-regulated in NeuP patients compared to healthy controls. Of these 17 proteins, 8 were from saliva, 7 from plasma, and 2 from CSF samples. The correlation analysis showed that the most important proteins that correlated to pain intensity were found in plasma (VIP > 1). Conclusions Investigation of the inflammatory profile of NeuP showed that most of the significant proteins for group separation were found in the less invasive biofluids of saliva and plasma. Within the NeuP patient group it was also seen that proteins in plasma had the highest correlation to pain intensity. These preliminary results indicate a potential for further biomarker research in the more easily accessible biofluids of saliva and plasma for chronic peripheral neuropathic pain where a combination of YKL-40 and MIP-1α in saliva might be of special interest for future studies that also include other non-neuropathic pain states.

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Characterization of the Volatile Profile of Cultivated and Wild-Type Italian Celery (Apium graveolens L.) Varieties by HS-SPME/GC-MS

Applied Sciences ◽

10.3390/app11135855 ◽

2021 ◽

Vol 11 (13) ◽

pp. 5855

Author(s):

Samantha Reale ◽

Valter Di Cecco ◽

Francesca Di Donato ◽

Luciano Di Martino ◽

Aurelio Manzi ◽

...

Keyword(s):

Solid Phase ◽

Principal Component ◽

Apium Graveolens ◽

Gas Chromatography Mass Spectrometry ◽

Bioactive Metabolites ◽

Chemical Components ◽

Volatile Profile ◽

Wild Type ◽

Multivariate Statistical ◽

Clear Differentiation

Celery (Apium graveolens L.) is a vegetable belonging to the Apiaceae family that is widely used for its distinct flavor and contains a variety of bioactive metabolites with healthy properties. Some celery ecotypes cultivated in specific territories of Italy have recently attracted the attention of consumers and scientists because of their peculiar sensorial and nutritional properties. In this work, the volatile profiles of white celery “Sedano Bianco di Sperlonga” Protected Geographical Indication (PGI) ecotype, black celery “Sedano Nero di Torricella Peligna” and wild-type celery were investigated using head-space solid-phase microextraction combined with gas-chromatography/mass spectrometry (HS-SPME/GC-MS) and compared to that of the common ribbed celery. Exploratory multivariate statistical analyses were conducted using principal component analysis (PCA) on HS-SPME/GC-MS patterns, separately collected from celery leaves and petioles, to assess similarity/dissimilarity in the flavor composition of the investigated varieties. PCA revealed a clear differentiation of wild-type celery from the cultivated varieties. Among the cultivated varieties, black celery “Sedano Nero di Torricella Peligna” exhibited a significantly different composition in volatile profile in both leaves and petioles compared to the white celery and the prevalent commercial variety. The chemical components of aroma, potentially useful for the classification of celery according to the variety/origin, were identified.

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