Sparse Partial-least-squares Discriminant Analysis for Different Geographical Origins of Salvia miltiorrhiza by 1 H-NMR-based Metabolomics

2013 ◽  
Vol 25 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Miaomiao Jiang ◽  
Chunhua Wang ◽  
Yu Zhang ◽  
Yifan Feng ◽  
Yuefei Wang ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Salvia Miltiorrhiza ◽  
H Nmr

scholarly journals 1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8151 ◽  
Author(s):  
Yan-Yan Liu ◽  
Zhong-Xian Yang ◽  
Li-Min Ma ◽  
Xu-Qing Wen ◽  
Huan-Lin Ji ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Discriminant Analysis ◽  
Nmr Spectroscopy ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Least Squares ◽  
Partial Least Squares ◽  
Early Stage ◽  
H Nmr ◽  
Potential Biomarkers

Background Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC. Methods Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using 1H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers. Results Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence. Conclusions 1H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

scholarly journals Exosome-Enriched Plasma Analysis as a Tool for the Early Detection of Hypertensive Gestations

2021 ◽  
Vol 12 ◽  
Author(s):  
Rodrigo Barbano Weingrill ◽  
Sandra Luft Paladino ◽  
Matheus Leite Ramos Souza ◽  
Eduardo Manoel Pereira ◽  
Aldilane Lays Xavier Marques ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Principal Component ◽  
Component Analysis ◽  
Proton Nuclear Magnetic Resonance ◽  
Hypertensive Disorders Of Pregnancy ◽  
H Nmr ◽  
Hypertensive Disorders

Hypertensive disorders of pregnancy are closely associated with prematurity, stillbirth, and maternal morbidity and mortality. The onset of hypertensive disorders of pregnancy (HDP) is generally noticed after the 20th week of gestation, limiting earlier intervention. The placenta is directly responsible for modulating local and systemic physiology by communicating using mechanisms such as the release of extracellular vesicles, especially exosomes. In this study, we postulated that an analysis of exosome-enriched maternal plasma could provide a more focused and applicable approach for diagnosing HDP earlier in pregnancy. Therefore, the peripheral blood plasma of 24 pregnant women (11 controls, 13 HDP) was collected between 20th and 24th gestational weeks and centrifuged for exosome enrichment. Exosome-enriched plasma samples were analyzed by Raman spectroscopy and by proton nuclear magnetic resonance metabolomics (1H NMR). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze the Raman data, from the spectral region of 600–1,800 cm–1, to determine its potential to discriminate between groups. Using principal component analysis, we were able to differentiate the two groups, with 89% of all variances found in the first three principal components. In patients with HDP, most significant differences in Raman bands intensity were found for sphingomyelin, acetyl CoA, methionine, DNA, RNA, phenylalanine, tryptophan, carotenoids, tyrosine, arginine, leucine, amide I and III, and phospholipids. The 1H NMR analysis showed reduced levels of D-glucose, L-proline, L-tyrosine, glycine, and anserine in HDP, while levels of 2-hydroxyvalerate, polyunsaturated fatty acids, and very-low-density lipoprotein (VLDL) were increased. 1H NMR results were able to assign an unknown sample to either the control or HDP groups at a precision of 88.3% using orthogonal partial least squares discriminant analysis and 87% using logistic regression analysis. Our results suggested that an analysis of exosome-enriched plasma could provide an initial assessment of placental function at the maternal-fetal interface and aid HDP diagnosis, prognosis, and treatment, as well as to detect novel, early biomarkers for HDP.

Authentication of Douro DO monovarietal red wines based on anthocyanin profile: Comparison of partial least squares – discriminant analysis, decision trees and artificial neural networks

Food Control ◽  
2021 ◽  
Vol 125 ◽  
pp. 107979
Author(s):  
Fernanda Cosme ◽  
Juliana Milheiro ◽  
Joana Pires ◽  
Fernanda Isabel Guerra-Gomes ◽  
Luís Filipe-Ribeiro ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Decision Trees ◽  
Partial Least Squares ◽  
Red Wines ◽  
Anthocyanin Profile ◽  
Artificial Neural

scholarly journals Patterns of Circulating Inflammatory Biomarkers in Older Persons with Varying Levels of Physical Performance: A Partial Least Squares-Discriminant Analysis Approach

2014 ◽  
Vol 1 ◽  
Author(s):  
Emanuele Marzetti ◽  
Francesco Landi ◽  
Federico Marini ◽  
Matteo Cesari ◽  
Thomas W. Buford ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Physical Performance ◽  
Older Persons ◽  
Inflammatory Biomarkers ◽  
Analysis Approach

Detection of flaxseed oil multiple adulteration by near-infrared spectroscopy and nonlinear one class partial least squares discriminant analysis

LWT ◽  
2020 ◽  
Vol 125 ◽  
pp. 109247 ◽  
Author(s):  
Zhe Yuan ◽  
Liangxiao Zhang ◽  
Du Wang ◽  
Jun Jiang ◽  
Peter de B. Harrington ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Flaxseed Oil

scholarly journals Human Melanoma-Cell Metabolic Profiling: Identification of Novel Biomarkers Indicating Metastasis

2020 ◽  
Vol 21 (7) ◽  
pp. 2436 ◽  
Author(s):  
Mariangela Kosmopoulou ◽  
Aikaterini F. Giannopoulou ◽  
Aikaterini Iliou ◽  
Dimitra Benaki ◽  
Aristeidis Panagiotakis ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
High Resolution ◽  
Least Squares ◽  
Partial Least Squares ◽  
Cell Lines ◽  
High Performance ◽  
Principal Component ◽  
Metastatic Tumor ◽  
Human Melanoma ◽  
Melanoma Metastasis

Melanoma is the most aggressive type of skin cancer, leading to metabolic rewiring and enhancement of metastatic transformation. Efforts to improve its early and accurate diagnosis are largely based on preclinical models and especially cell lines. Hence, we herein present a combinational Nuclear Magnetic Resonance (NMR)- and Ultra High Performance Liquid Chromatography-High-Resolution Tandem Mass Spectrometry (UHPLC-HRMS/MS)-mediated untargeted metabolomic profiling of melanoma cells, to landscape metabolic alterations likely controlling metastasis. The cell lines WM115 and WM2664, which belong to the same patient, were examined, with WM115 being derived from a primary, pre-metastatic, tumor and WM2664 clonally expanded from lymph-node metastases. Metabolite samples were analyzed using NMR and UHPLC-HRMS. Multivariate statistical analysis of high resolution NMR and MS (positive and negative ionization) results was performed by Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), while metastasis-related biomarkers were determined on the basis of VIP lists, S-plots and Student’s t-tests. Receiver Operating Characteristic (ROC) curves of NMR and MS data revealed significantly differentiated metabolite profiles for each cell line, with WM115 being mainly characterized by upregulated levels of phosphocholine, choline, guanosine and inosine. Interestingly, WM2664 showed notably increased contents of hypoxanthine, myo-inositol, glutamic acid, organic acids, purines, pyrimidines, AMP, ADP, ATP and UDP(s), thus indicating the critical roles of purine, pyrimidine and amino acid metabolism during human melanoma metastasis.

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