scholarly journals Metabolic Profile of Patients with Severe Endometriosis: a Prospective Experimental Study

2020 ◽  
Author(s):  
Federica Murgia ◽  
Stefano Angioni ◽  
Maurizio Nicola D’Alterio ◽  
Silvia Pirarba ◽  
Antonio Noto ◽  
...  
Keyword(s):  
Roc Curves ◽  
Partial Least Square ◽  
Least Square ◽  
Reproductive Age ◽  
Common Disease ◽  
Hydroxybutyric Acid ◽  
Serum Samples ◽  
Multivariate Statistical ◽  
Delay In Diagnosis ◽  
H Nmr

Abstract Endometriosis is a common disease affecting women in reproductive age. There are several hypotheses on the pathogenesis of this disease. Often, its lesions and symptoms overlap with those of many other medical and surgical conditions, causing a delay in diagnosis. Metabolomics represents a useful diagnostic tool for the study of metabolic changes during a different physiological or pathological status. We used 1H-NMR to explore metabolic alteration in a cohort of patients with endometriosis in order to contribute to a better understanding of the pathophysiology of the disease and to suggest new useful biomarkers. Thirty-seven patients were recruited for the metabolomic analysis: 22 patients affected by symptomatic endometriosis and 15 not affected by it. Their serum samples were collected and analyzed with 1H-NMR. Multivariate statistical analysis was conducted, followed by univariate and pathway analyses. Partial Least Square Discriminant Analysis (PLS-DA) was performed to determine the presence of any differences between the non-endometriosis and endometriosis samples (R2X = 0.596, R2Y = 0.713, Q2 = 0.635, and p < 0.0001). β-hydroxybutyric acid and glutamine were significantly increased, whereas tryptophan was significantly decreased in the endometriosis patients. ROC curves were built to test the diagnostic power of the metabolites (β-hydroxybutyric acid: AUC = 0.85 CI = 0.71–0.99; glutamine: AUC = 0.83 CI = 0.68–0.98; tryptophan: AUC = 0.75 CI = 0.54–0.95; β-hydroxybutyric acid + glutamine + tryptophan AUC = 0.92 CI = 0.81–1). The metabolomic approach enabled the identification of several metabolic alterations occurring in women with endometriosis. These findings may provide new bases for a better understanding of the pathophysiological mechanisms of the disease and for the discovery of new biomarkers. Trial registration number NCT02337816

scholarly journals 1H nuclear magnetic resonance-based metabolite profiling of guava leaf extract: an attempt to develop a prototype for standardization of plant extracts

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Manasi S. Gholkar ◽  
Jia V. Li ◽  
Poonam G. Daswani ◽  
P. Tetali ◽  
Tannaz J. Birdi
Keyword(s):  
Ferulic Acid ◽  
Gallic Acid ◽  
Plant Extracts ◽  
Nmr Spectra ◽  
Leaf Extract ◽  
Partial Least Square ◽  
Least Square ◽  
E Coli ◽  
H Nmr ◽  
Guava Leaf

Abstract Background Herbal medicines are fast gaining popularity. However, their acceptability by modern practitioners is low which is often due to lack of standardization. Several approaches towards standardization of herbals have been employed. The current study attempted to recognize key peaks from 1H NMR spectra which together would comprise of a spectral fingerprint relating to efficacy of Psidium guajava (guava) leaf extract as an antidiarrhoeal when a number of unidentified active principles are involved. Methods Ninety samples of guava leaves were collected from three locations over three seasons. Hydroalcoholic (water and ethanol, 50:50) extracts of these samples were prepared and their 1H NMR spectra were acquired. Spectra were also obtained for quercetin, ferulic acid and gallic acid as standards. Eight bioassays reflecting different stages of diarrhoeal pathogenesis were undertaken and based on pre-decided cut-offs, the extracts were classified as ‘good’ or ‘poor’ extracts. The bioactivity data was then correlated with the 1H NMR profiles using Regression or Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Results OPLS-DA showed seasonal and regional segregation of extracts. Significant models were established for seven bioassays, namely those for anti-bacterial activity against Shigella flexneri and Vibrio cholerae, adherence of E. coli, invasion of E. coli and S. flexneri and production and binding of toxin produced by V. cholerae. It was observed that none of the extracts were good or bad across all the bioassays. The spectral analysis showed multiple peaks correlating with a particular activity. Based on NMR and LC-MS/MS, it was noted that the extracts contained quercetin, ferulic acid and gallic acid. However, they did not correlate with the peaks that segregated extracts with good and poor activity. Conclusions The current study identified key peaks in 1H NMR spectra contributing to the anti-diarrhoeal activity of guava leaf extracts. The approach of using spectral fingerprinting employed in the present study can thus be used as a prototype towards standardization of plant extracts with respect to efficacy.

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

2019 ◽  
Vol 14 (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.

Wood discrimination analyses of Pterocarpus tinctorius and endangered Pterocarpus santalinus using DART-FTICR-MS coupled with multivariate statistics

IAWA Journal ◽  
2019 ◽  
Vol 40 (1) ◽  
pp. 58-74 ◽  
Author(s):  
Maomao Zhang ◽  
Guang Jie Zhao ◽  
Bo Liu ◽  
Tuo He ◽  
Juan Guo ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Information ◽  
Ion Cyclotron Resonance ◽  
Timber Species ◽  
Multivariate Statistical ◽  
Fticr Ms ◽  
Pterocarpus Santalinus

ABSTRACT Pterocarpus santalinus, listed in CITES Appendix II, is an endangered timber species as a result of illegal harvesting due to its high value and commercial demand. The growing demand for P. santalinus and timbers with the morphologically similar Pterocarpus tinctorius has resulted in confusion as well as identification problems. Therefore, it is of vital importance to explore reliable ways to accurately discriminate between P. santalinus and P. tinctorius. In this study, the method of direct analysis in real time and fourier transform ion cyclotron resonance mass spectrometry (DART-FTICR-MS), combined with multivariate statistical analysis, was used to extract chemical information from xylarium wood specimens and to explore the feasibility of distinguishing these two species. Significant differences were observed in their DART-FTICR-MS spectra. Orthogonal partial least square-discriminant analysis (OPLS-DA) showed the highest prediction, with an accuracy of 100%. These findings demonstrate the feasibility of authenticating wood types using DART-FTICR-MS coupled with multivariate statistical analysis.

scholarly journals Applying Discriminant and Cluster Analyses to Separate Allergenic from Non-allergenic Proteins

2019 ◽  
Vol 17 (1) ◽  
pp. 401-407 ◽  
Author(s):  
L. Naneva ◽  
M. Nedyalkova ◽  
S. Madurga ◽  
F. Mas ◽  
V. Simeonov
Keyword(s):  
Cluster Analysis ◽  
Structural Parameters ◽  
Three Dimensional ◽  
Surface Protein ◽  
Partial Least Square ◽  
Least Square ◽  
Multivariate Statistical ◽  
Genomics And Proteomics ◽  
Cross Covariance ◽  
Allergenic Proteins

AbstractAs a result of increased healthcare requirements and the introduction of genetically modified foods, the problem of allergies is becoming a growing health problem. The concept of allergies has prompted the use of new methods such as genomics and proteomics to uncover the nature of allergies. In the present study, a selection of 1400 food proteins was analysed by PLS-DA (Partial Least Square-based Discriminant Analysis) after suitable transformation of structural parameters into uniform vectors. Then, the resulting strings of different length were converted into vectors with equal length by Auto and Cross-Covariance (ACC) analysis. Hierarchical and non-hierarchical (K-means) Cluster Analysis (CA) was also performed in order to reach a certain level of separation within a small training set of plant proteins (16 allergenic and 16 non-allergenic) using a new three-dimensional descriptor based on surface protein properties in combination with amino acid hydrophobicity scales. The novelty of the approach in protein differentiation into allergenic and non-allergenic classes is described in the article.The general goal of the present study was to show the effectiveness of a traditional chemometric method for classification (PLS–DA) and the options of Cluster Analysis (CA) to separate by multivariate statistical methods allergenic from non-allergenic proteins.

Modeling of Giant Magnetostrictive Material Based on Multivariate Statistical Analysis

2012 ◽  
Vol 457-458 ◽  
pp. 46-49
Author(s):  
Xue Jun Zhu ◽  
Zhi Wen Zhu
Keyword(s):  
Significance Test ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Hysteresis Phenomenon ◽  
Multivariate Statistical ◽  
Final Model ◽  
Magnetostrictive Material ◽  
Giant Magnetostrictive Material ◽  
Set Up

In this paper, a kind of giant magnetostrictive material (GMM) model based on hysteretic nonlinear theory was developed. Van de Pol nonlinear difference item was introduced to interpret the hysteresis phenomenon of the strain-magnetic field intensity (MFI) curve of GMM. The coupling relationship between MFI and frequency was obtained in partial least-square regression method to describe the driftage phenomenon of the strain-MFI curves of GMM in different frequencies. Based on above, the final relationship among strain, MFI and frequency was set up. The result of significance test shows that the effects of all of the items in the final model are remarkable, and that of forecast test shows that the model can describe the characteristics of GMA in different frequencies well. The new GMM model broadens the region of controlling frequency, and is easy to be analyzed in theory, which is helpful to vibration control.

scholarly journals ANALISIS KUALITAS PELAYANAN INTERNET INDIHOME PADA PT. X DENGAN PENDEKATAN PART LEAST SQUARE

2019 ◽  
Vol 20 (1) ◽  
pp. 77
Author(s):  
Kukuh Winarso ◽  
Moh. Jufriyanto
Keyword(s):  
Hypothesis Test ◽  
Partial Least Square ◽  
Least Square ◽  
P Value ◽  
Test Results ◽  
Multivariate Statistical ◽  
Internet Service ◽  
Analysis Techniques ◽  
Inner Model

PT. X Provides paid internet services known as Indihome. The problem that occurs in Indihome Internet service is that there are 42.36% complaints from consumers to the service process provided by PT. X and there is a 7.46% complaint about the amount of the bill. The purpose of this study is to model and know what variables affect the quality of the Indihome Internet service. The method used is Partial Least Square (PLS). Partial Least Square (PLS) is one of the multivariate statistical analysis techniques that can handle multiple response variables and an explanatory variable. The variables used are tangible, empathy, assurance, reliability and responsiveness. The results of the research are the increase of R square value after the implementation of the A5 indicator that does not meet the model PLS. All five variables affect the quality of indihome Internet service is 76,1%. Based on the hypothesis test results on the outer model It is said that the variable indicator is valid with p-value = 0 < 0,05. In testing the inner model obtained that the variable tangible and responsiveness has no significant effect on the quality of Internet service Indihome, while the variable empathy, assurance, reliability significantly affect the quality of service Indihome Internet.

scholarly journals Designing Interface of Mobile Parental Information System based on Users’ Perception Using Kansei Engingeering

2018 ◽  
Vol 1 (1) ◽  
pp. 10-19 ◽  
Author(s):  
Ana Hadiana
Keyword(s):  
Information System ◽  
User Interface ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Multivariate Statistical ◽  
Emotional Factor ◽  
Emotional Factors ◽  
System Data ◽  
Parental Information

Users’ psychological emotion plays important role in designing an interface of software including application of information system. This research attempted to implement Kansei Engineering Type I (KEPack) as a method to analyze kinds of emotional factor related to user interface for mobile Parental Information System. This research used Kansei Words to explore users’ requirements based on psychological factors. Eighteen words were used for Kansei Words that have relationship with Parental Information System. Ten samples of mobile information system were selected as specimens considered suitable for designing interface of Parental Information System. Data questionnaires collected from thirty respondents were processed using multivariate statistical analysis such as Factor Analysis (FA) and Partial Least Square (PLS). This research found that the two important emotional factors i.e funny and informative have to be considered for designing user interface for mobile Parental Information System.

scholarly journals Heat stress modifies the lactational performances and the urinary metabolomic profile related to gastrointestinal microbiota of dairy goats

2018 ◽  
Author(s):  
Alexandra Contreras-Jodar ◽  
Nazri Nayan ◽  
Soufiane Hamzaoui ◽  
Gerardo Caja ◽  
Ahmed A.K. Salama
Keyword(s):  
Heat Stress ◽  
Milk Yield ◽  
Partial Least Square ◽  
Least Square ◽  
Proton Nuclear Magnetic Resonance ◽  
Metabolomic Profile ◽  
Dairy Goats ◽  
Gastrointestinal Microbiota ◽  
Toxic Compounds ◽  
H Nmr

AbstractThe aim of the study was to identify the candidate biomarkers of heat stress (HS) in the urine of lactating dairy goats through the application of proton Nuclear Magnetic Resonance (1H NMR)-based metabolomic analysis. Dairy does (n = 16) in mid-lactation were submitted to thermal neutral (TN; indoors; 15 to 20°C; 40 to 45% humidity) or HS (climatic chamber; 37°C day, 30°C night; 40% humidity) conditions according to a crossover design (2 periods of 21 days). Thermophysiological traits and lactational performances were recorded and milk composition analyzed during each period. Urine samples were collected at day 15 of each period for 1H NMR spectroscopy analysis. Principal component analysis (PCA) and partial least square–discriminant analysis (PLS-DA) assessment with cross validation were used to identify the goat urinary metabolome from Human Metabolome Data Base. HS increased rectal temperature (1.2°C), respiratory rate (3.5-fold) and water intake (74%), but decreased feed intake (35%) and body weight (5%) of the lactating does. No differences were detected in milk yield, but HS decreased the milk contents of fat (9%), protein (16%) and lactose (5%). Metabolomics allowed separating TN and HS urinary clusters by PLS-DA. Most discriminating metabolites were hippurate and other phenylalanine (Phe) derivative compounds, which increased in HS vs. TN does. The greater excretion of these gut-derived toxic compounds indicated that HS induced a harmful gastrointestinal microbiota overgrowth, which should have sequestrated aromatic amino acids for their metabolism and decreased the synthesis of neurotransmitters and thyroid hormones, with negative impact on milk yield and composition. In conclusion, HS markedly changed the thermophysiological traits and lactational performances of dairy goats, which were translated into their urinary metabolomic profile through the presence of gut-derived toxic compounds. Hippurate and other Phe-derivative compounds are suggested as urinary biomarkers to detect heat stressed dairy animals in practice.

Metabolic characterization of amniotic fluids of fetuses with enlarged nuchal translucency

2019 ◽  
Vol 47 (3) ◽  
pp. 311-318 ◽  
Author(s):  
Ambra Iuculano ◽  
Federica Murgia ◽  
Cristina Peddes ◽  
Maria Laura Santoru ◽  
Laura Tronci ◽  
...  
Keyword(s):  
High Performance ◽  
First Trimester ◽  
Nuchal Translucency ◽  
Partial Least Square ◽  
Least Square ◽  
Proton Nuclear Magnetic Resonance ◽  
Control Group ◽  
Aneuploidy Screening ◽  
H Nmr

Abstract Background In prenatal diagnosis, a thickened nuchal translucency (NT) is one of the most sensitive and specific markers for several defects but it may also be found in 5% of healthy fetuses. The pathophysiological causes that lead to an increase in NT are not yet fully understood. Metabolomics represents a new promising approach, useful for studying different metabolites in biological organisms in response to environmental stressors. The aim of our study was to investigate the metabolomic profile of the amniotic fluid samples (AFS) of euploid fetuses with enlarged nuchal translucency (ENT) compared to a control group (C group). Methods This study was carried out on a group of women who underwent second-trimester amniocentesis for advanced maternal age (C group) or for NT ≥95th percentile (ENT group) found during first-trimester aneuploidy screening. AFS were analyzed with proton nuclear magnetic resonance (1H-NMR) and high-performance liquid chromatography (HPLC), and subsequent multivariate and univariate statistical analyses were conducted, followed by pathway analysis. Results In total, 67 AFS from the C group and 23 from the ENT group were analyzed. Partial least square discriminate analysis was carried out (R2X=0.784, R2Y=0.658, Q2=0.622, P<0.0001). A different metabolic profile was observed in the ENT group compared with the C group, suggesting an energetic shift to a glycolytic phenotype in an oxidative environment in the ENT group compared to the C group. Conclusion Metabolomic studies enable the identification of metabolic alterations occurring in fetuses with ENT. These findings may provide a new basis for better understanding the pathophysiological mechanisms in this prenatal phenomenon.

scholarly journals Serum Metabolomic Profiling of Rats by Intervention of Aconitum soongaricum

2015 ◽  
Vol 10 (12) ◽  
pp. 1934578X1501001
Author(s):  
Fan Zhang ◽  
Jiao Liu ◽  
Jun Lei ◽  
Wenjing He ◽  
Yun Sun
Keyword(s):  
Statistical Analysis ◽  
Nmr Spectroscopy ◽  
Metabolic Profiles ◽  
Metabolomic Analysis ◽  
Serum Samples ◽  
Multivariate Statistical ◽  
H Nmr ◽  
Metabolomic Profiling ◽  
Clinical Detection ◽  
Endogenous Metabolites

To understand the toxic mechanism and to find the changes in the endogenous metabolites of Aconitum soongaricum Stapf for clinical detection, a combination of 1H NMR spectroscopy and multivariate statistical analysis was applied to examine the metabolic profiles of the blood serum samples collected from the rat model. In total, thirteen biomarkers of A. soongaricum were found and identified. It turned out that A. soongaricum treatment may partially disorder the metabolism. The study has shown the potential application of NMR-based metabolomic analysis in providing further insights into the toxicity caused by A. soongaricum.

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