QUANTITATIVE EVALUATION OF MULTIVARIATE ANALYSIS METHODS FOR EXCITATION–EMISSION SPECTROSCOPY

2013 ◽  
Vol 25 (02) ◽  
pp. 1250027 ◽  
Author(s):  
Chun Yu ◽  
Tzu-Chien Hsiao ◽  
Chii-Wann Lin
Keyword(s):  
Multivariate Analysis ◽  
System Integration ◽  
Multivariable Analysis ◽  
Principal Component ◽  
Automatic Measurement ◽  
Partial Least Square ◽  
Least Square ◽  
Prediction Ability ◽  
Analysis Methods ◽  
The Difference

Multivariable Analysis Methods have been used widely in Spectroscopy Analysis. Partial least square (PLS) and principal component analysis (PCA) are the two most popular methods due to their excellent ability in data components analysis and results prediction. This work derived 1D/2D PLS and 1D/2D PCA based on the viewpoint of three-layer artificial neural networks, and uses theoretical proving to figure out the essences of these two methods. Two 2D experimental dataset was used to verify the calibration and prediction ability, furthermore, the similarity and dissimilarity of PLS and PCA. The finding showed that both the 1D/2D PLS and 1D/2D PCA methods use maximum covariance and minimum sum of square error to figure out the relationship between independent and dependent variables. The dissimilarity is that, weight vectors calibration of PLS is cross-correlation, and that of PCA is autocorrelation. The difference causes that the PCA method would keep more principal characters than PLS under insufficient sample among and provides better calibration ability. PLS would provide higher performance in prediction under sufficient sample among. For the needs of system implementation of spectroscopic measurement and analysis, this study designed "Multivariate Analysis Toolkits for LabVIEW" for the convenient implementation in automatic measurement system integration.

scholarly journals Global metabolomic and lipidomic analysis reveals the potential mechanisms of hemolysis effect of Ophiopogonin D and Ophiopogonin D' in vivo

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Huan-Hua Xu ◽  
Zhen-Hong Jiang ◽  
Cong-Shu Huang ◽  
Yu-Ting Sun ◽  
Long-Long Xu ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Practical Significance ◽  
Plasma Metabolites ◽  
Active Components ◽  
The Difference

Abstract Background OPD and OPD' are the two main active components of Ophiopogon japonicas in Shenmai injection (SMI). Being isomers of each other, they are supposed to have similar pharmacological activities, but the actual situation is complicated. The difference of hemolytic behavior between OPD and OPD' in vivo and in vitro was discovered and reported by our group for the first time. In vitro, only OPD' showed hemolysis reaction, while in vivo, both OPD and OPD' caused hemolysis. In vitro, the primary cause of hemolysis has been confirmed to be related to the difference between physical and chemical properties of OPD and OPD'. In vivo, although there is a possible explanation for this phenomenon, the one is that OPD is bio-transformed into OPD' or its analogues in vivo, the other one is that both OPD and OPD' were metabolized into more activated forms for hemolysis. However, the mechanism of hemolysis in vivo is still unclear, especially the existing literature are still difficult to explain why OPD shows the inconsistent hemolysis behavior in vivo and in vitro. Therefore, the study of hemolysis of OPD and OPD' in vivo is of great practical significance in response to the increase of adverse events of SMI. Methods Aiming at the hemolysis in vivo, this manuscript adopted untargeted metabolomics and lipidomics technology to preliminarily explore the changes of plasma metabolites and lipids of OPD- and OPD'-treated rats. Metabolomics and lipidomics analyses were performed on ultra-high performance liquid chromatography (UPLC) system tandem with different mass spectrometers (MS) and different columns respectively. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to screen the differential metabolites and lipids. Results Both OPD and OPD' groups experienced hemolysis, Changes in endogenous differential metabolites and differential lipids, enrichment of differential metabolic pathways, and correlation analysis of differential metabolites and lipids all indicated that the causes of hemolysis by OPD and OPD' were closely related to the interference of phospholipid metabolism. Conclusions This study provided a comprehensive description of metabolomics and lipidomics changes between OPD- and OPD'-treated rats, it would add to the knowledge base of the field, which also provided scientific guidance for the subsequent mechanism research. However, the underlying mechanism require further research.

scholarly journals Meat and Fish Freshness Assessment by a Portable and Simplified Electronic Nose System (Mastersense)

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3225 ◽  
Author(s):  
Grassi ◽  
Benedetti ◽  
Opizzio ◽  
Nardo ◽  
Buratti
Keyword(s):  
Electronic Nose ◽  
Ad Hoc ◽  
Low Cost ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Oxide Semiconductor ◽  
Prediction Ability ◽  
Nearest Neighbours ◽  
Electronic Nose System

The evaluation of meat and fish quality is crucial to ensure that products are safe and meet the consumers’ expectation. The present work aims at developing a new low-cost, portable, and simplified electronic nose system, named Mastersense, to assess meat and fish freshness. Four metal oxide semiconductor sensors were selected by principal component analysis and were inserted in an “ad hoc” designed measuring chamber. The Mastersense system was used to test beef and poultry slices, and plaice and salmon fillets during their shelf life at 4 °C, from the day of packaging and beyond the expiration date. The same samples were tested for Total Viable Count, and the microbial results were used to define freshness classes to develop classification models by the K-Nearest Neighbours’ algorithm and Partial Least Square–Discriminant Analysis. All the obtained models gave global sensitivity and specificity with prediction higher than 83.3% and 84.0%, respectively. Moreover, a McNemar’s test was performed to compare the prediction ability of the two classification algorithms, which resulted in comparable values (p > 0.05). Thus, the Mastersense prototype implemented with the K-Nearest Neighbours’ model is considered the most convenient strategy to assess meat and fish freshness.

scholarly journals A study of new antimalarial artemisinins through molecular modeling and multivariate analysis

2010 ◽  
Vol 75 (11) ◽  
pp. 1533-1548 ◽  
Author(s):  
João Ferreira ◽  
Antonio Figueiredo ◽  
Jardel Barbosa ◽  
Maria Cristino ◽  
Williams Macedo ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Antimalarial Activity ◽  
External Validation ◽  
Geometry Optimization ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Partial Least Square ◽  
Least Square ◽  
Basis Set ◽  
Validation Parameters

Artemisinin and 18 derivatives with antimalarial activity against W-2 strains of Plasmodium falciparum were studied through quantum chemistry and multivariate analysis. The geometry optimization of the structures was realized with the Hartree-Fock (HF) theory and 3-21G basis set. Maps of molecular electrostatic potential (MEP) and molecular docking were used to investigate the interaction between the ligands and the receptor (heme). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were employed to select the most important descriptors related to activity. A predictive model was generated by the Partial Least Square (PLS) method through 15 molecules and 4 used as an external validation set, which were selected in the training set, the validation parameters of which are Q2 = 0.85 and R2 = 0.86. The model included as molecular parameters, the radial distribution function, RDF060e, the hydration energy, HE, and the distance between the O1 atom from the ligand and the iron atom from heme, d(Fe-O1). Thus, the synthesis of new derivatives may follow the results of the MEP maps and the PLS analysis.

scholarly journals Global Metabolomic and Lipidomic Analysis Reveals the Potential Mechanisms of Hemolysis Effect of Ophiopogonin D and Ophiopogonin D’ in vivo

2020 ◽  
Author(s):  
Xu Huan-Hua ◽  
Zhen-Hong Jiang ◽  
Cong-Shu Huang ◽  
Yu-Ting Sun ◽  
Long-Long Xu ◽  
...  
Keyword(s):  
Principal Component ◽  
Phospholipid Metabolism ◽  
Partial Least Square ◽  
Least Square ◽  
Practical Significance ◽  
Plasma Metabolites ◽  
Active Components ◽  
The Difference

Abstract Background: OPD and OPD' are the two main active components of Ophiopogon japonicas in Shenmai injection (SMI). Being isomers of each other, they are supposed to have similar pharmacological activities, but the actual situation is complicated. The difference of hemolytic behavior between OPD and OPD' in vivo and in vitro was discovered and reported by our group for the first time. In vitro, only OPD' showed hemolysis reaction, while in vivo, both OPD and OPD' caused hemolysis. The primary cause of hemolysis in vitro has been confirmed to be related to the difference between physical and chemical properties of OPD and OPD', but the mechanism of hemolysis in vivo is still unclear, especially the existing research are still difficult to explain why OPD shows the inconsistent hemolysis behavior in vivo and in vitro. Therefore, the study of hemolysis of OPD and OPD' in vivo is of great practical significance in response to the increase of adverse events of SMI.Methods: Aiming at the hemolysis in vivo, this manuscript adopted untargeted metabolomics and lipidomics technology to preliminarily explore the changes of plasma metabolites and lipids of OPD- and OPD'-treated rats. Metabolomics and lipidomics analyses were performed on ultra-high performance liquid chromatography (UPLC) system tandem with different mass spectrometers (MS) and different columns respectively. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to screen the differential metabolites and lipids.Results: Both OPD and OPD' groups experienced hemolysis, Changes in endogenous differential metabolites and differential lipids, enrichment of differential metabolic pathways, and correlation analysis of differential metabolites and lipids all indicated that the causes of hemolysis by OPD and OPD' were closely related to the interference of phospholipid metabolism.Conclusions: This study confirmed that interference of phospholipid metabolism was the main cause of hemolysis of OPD and OPD'. This study provided a comprehensive description of metabolome and lipidomic changes under the condition of hemolysis which caused by OPD and OPD'. It can also provide clues for research on the hemolysis mechanism of traditional Chinese medicine.

scholarly journals Looking beyond chemistry – XRD for exploration and processing of ores

2014 ◽  
Vol 70 (a1) ◽  
pp. C952-C952
Author(s):  
Uwe König ◽  
Martijn Fransen
Keyword(s):  
High Speed ◽  
Raw Materials ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
X Ray Diffraction ◽  
Ore Bodies ◽  
Adequate Sampling ◽  
The Difference

Decreasing ore qualities and increasing prices for raw materials require a better control of processed ore and a more efficient use of energy. Traditionally quality control in mining industries has relied on time consuming wet chemistry or the analysis of the elemental composition. The mineralogy that defines the physical properties is often monitored infrequently, if at all. The use of high speed detectors has turned X-ray diffraction (XRD) into an important tool for fast and accurate process control. XRD data and their interpretation do make the difference in the identification of minerals, in describing their distribution in ore bodies and in their beneficiation during processing. The use of modern techniques such Partial Least Square Regression (PLSR), Principal Component Analysis (PCA) or full pattern Rietveld quantification will be discussed during the presentation as well as the importance of adequate sampling and the correlation with sample chemistry. The practical use will be illustrated on case studies.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches

2018 ◽  
Vol 72 (7) ◽  
pp. 1047-1056 ◽  
Author(s):  
Jun-Ho Yang ◽  
Jack J Yoh
Keyword(s):  
Multivariate Analysis ◽  
Laser Scanning ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Laser Induced Breakdown Spectroscopy ◽  
Latent Fingerprints ◽  
Breakdown Spectroscopy ◽  
Real Time Analysis ◽  
Laser Induced Breakdown

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

scholarly journals Global Metabolomic and Lipidomic Analysis Reveals the Potential Mechanisms of Hemolysis Effect of Ophiopogonin D and Ophiopogonin D’ in vivo

2020 ◽  
Author(s):  
Xu Huan-Hua ◽  
Zhen-Hong Jiang ◽  
Cong-Shu Huang ◽  
Yu-Ting Sun ◽  
Long-Long Xu ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Practical Significance ◽  
Plasma Metabolites ◽  
Shenmai Injection ◽  
The Difference

Abstract Background OPD and OPD’ are the two main active monomers of Ophiopogon japonicus in Shenmai injection, being isomers of each other with the same chemical formula and similar chemical structure. According to common sense, they are supposed to have similar pharmacological activities, but the actual situation is exactly the opposite. The difference of distinct hemolytic behavior between OPD and OPD’ in vivo and in vitro was discovered and reported by our group for the first time. In the hemolysis experiment in vitro, only OPD’ showed hemolysis reaction, while in vivo, both OPD and OPD’ revealed hemolysis reaction. The primary cause of hemolysis in vitro has been confirmed to be related to the difference between physical and chemical properties of OPD and OPD’, but the mechanism of hemolysis in vivo is still unclear, especially the existing research are still difficult to explain why OPD shows the inconsistent hemolysis behavior in vivo and in vitro. However, the detection of hemolysis of OPD and OPD’ in vivo is of great practical significance in response to the increase of adverse events of Shenmai injection. Methods Aiming at the phenomenon of hemolysis in vivo, this paper adopted untargeted metabolomics and lipidomics technology to preliminarily explore the changes of plasma metabolites and lipids of OPD and OPD’ in vivo during the occurrence of hemolysis. Metabolomics and lipidomics analysis was performed on ultra-high performance liquid chromatography (UPLC) system tandem with different mass spectrometer and different columns respectively. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to screen the differential metabolites and lipids. Results Both OPD and OPD’ groups experienced hemolysis, Changes in endogenous differential metabolites and differential lipids, enrichment of differential metabolic pathways, and correlation analysis of differential metabolites and lipids all indicated that the causes of hemolysis by OPD and OPD’ were closely related to the interference of phospholipid metabolism. Conclusions This study provided a comprehensive description of metabolomics and lipidomic changes between OPD and OPD’ treated rats, which also provided scientific guidance for the subsequent mechanism research, and the underlying mechanism require further research.

scholarly journals Global Metabolomic and Lipidomic Analysis Reveals the Potential Mechanisms of Hemolysis Effect of Ophiopogonin D and Ophiopogonin D’ in vivo

2020 ◽  
Author(s):  
Xu Huan-Hua ◽  
Zhen-Hong Jiang ◽  
Cong-Shu Huang ◽  
Yu-Ting Sun ◽  
Long-Long Xu ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Practical Significance ◽  
Plasma Metabolites ◽  
Active Components ◽  
The Difference

Abstract Background: OPD and OPD' are the two main active components of Ophiopogon japonicas in Shenmai injection (SMI). Being isomers of each other, they are supposed to have similar pharmacological activities, but the actual situation is complicated. The difference of hemolytic behavior between OPD and OPD' in vivo and in vitro was discovered and reported by our group for the first time. In vitro, only OPD' showed hemolysis reaction, while in vivo, both OPD and OPD' caused hemolysis. In vitro, the primary cause of hemolysis has been confirmed to be related to the difference between physical and chemical properties of OPD and OPD'. In vivo, although there is a possible explanation for this phenomenon, the one is that OPD is bio-transformed into OPD' or its analogues in vivo, the other one is that both OPD and OPD' were metabolized into more activated forms for hemolysis. However, the mechanism of hemolysis in vivo is still unclear, especially the existing literature are still difficult to explain why OPD shows the inconsistent hemolysis behavior in vivo and in vitro. Therefore, the study of hemolysis of OPD and OPD' in vivo is of great practical significance in response to the increase of adverse events of SMI.Methods: Aiming at the hemolysis in vivo, this manuscript adopted untargeted metabolomics and lipidomics technology to preliminarily explore the changes of plasma metabolites and lipids of OPD- and OPD'-treated rats. Metabolomics and lipidomics analyses were performed on ultra-high performance liquid chromatography (UPLC) system tandem with different mass spectrometers (MS) and different columns respectively. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to screen the differential metabolites and lipids.Results: Both OPD and OPD' groups experienced hemolysis, Changes in endogenous differential metabolites and differential lipids, enrichment of differential metabolic pathways, and correlation analysis of differential metabolites and lipids all indicated that the causes of hemolysis by OPD and OPD' were closely related to the interference of phospholipid metabolism.Conclusions: This study provided a comprehensive description of metabolomics and lipidomics changes between OPD- and OPD'-treated rats, it would add to the knowledge base of the field, which also provided scientific guidance for the subsequent mechanism research. However, the underlying mechanism require further research.

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

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.

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

Molecules ◽  
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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