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1.
Karen Beatriz Méndez-Rodríguez Nicté Figueroa-Vega César Arturo Ilizaliturri-Hernandez Mónica Cardona-Alvarado Jaime Antonio Borjas-García Carlos Kornhauser Juan Manuel Malacara Rogelio Flores-Ramírez Francisco Javier Pérez-Vázquez 《Biomedical chromatography : BMC》2020,34(12):e4956
Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice. 相似文献
2.
Multivariate curve resolution methods, frequently used in analyzing bilinear data sets, result in ambiguous decomposition in general. Implementing the adequate constraints may lead to reduce the so-called rotational ambiguity drastically, and in the most favorable cases to the unique solution. However, in some special cases, non-negativity constraint as minimal information of the system is a sufficient condition to resolve profiles uniquely. Although, several studies on exploring the uniqueness of the bilinear non-negatively constrained multivariate curve resolution methods have been made in the literature, it has still remained a mysterious question. In 1995, Manne published his profile-based theorems giving the necessary and sufficient conditions of the unique resolution. In this study, a new term, i.e., data-based uniqueness is defined and investigated in details, and a general procedure is suggested for detection of uniquely recovered profile(s) on the basis of data set structure in the abstract space. Close inspection of Borgen plots of these data sets leads to realize the comprehensive information of local rank, and these argumentations furnish a basis for data-based uniqueness theorem. The reported phenomenon and its exploration is a new stage (it can be said fundament) in understanding and describing the bilinear (matrix-type) chemical data in general. 相似文献
3.
Qi Yongcheng 《数学年刊B辑(英文版)》1998,19(4):499-510
1.IntroductionLet{X.,n21}beasequenceoflidry'swithanondegeneratedistributionfunctionF(x).Supposethereexistsomeconstantsan>0,b.6RandsomeacERsuchthatwhereG.standsforoneoftheextremevaluedistributions:Heretheindex7ERisarealparameter(interpret(1 box)--'/ryase--"for7~0).Theestimationoftheextreme-valueindex7isveryimportantbothintheextremevaluetheoryandinpractice.Manystatistics,suchasHillestimator(forcaseac>0),PickandsestimatorandDekkers-EinmahLdeHaan'smomentestimatorwhicharebasedonafinitesample,… 相似文献
4.
In this paper, the authors studied certain properties of the estimate of Liang and Krishnaiah (1985, J. Multivariate Anal. 16, 162–172) for multivariate binary density. An alternative shrinkage estimate is also obtained. The above results are generalized to general orthonormal systems. 相似文献
5.
LIU Jixue ZHANG Sanguo & CHEN Xiru Department of Statistics Finance University of Science Technology of China Hefei China Department of Mathematics Graduate School of Chinese Academy of Sciences Beijing China 《中国科学A辑(英文版)》2006,49(6):752-769
This paper studies the linear EV model when replicate observations are made only on independent variables. We construct the estimates of regression coefficients and prove the consistency and asymptotic normality under some proper conditions. Results obtained reveal the difference between the case where the independent and dependent variables are observed repeatedly and simultaneously and the case studied in this article. 相似文献
6.
Lubomír Kubáček 《Applications of Mathematics》2006,51(6):565-582
Some remarks to problems of point and interval estimation, testing and problems of outliers are presented in the case of multivariate
regression model.
This work was supported by the Council of Czech Government J14/98:153100011. 相似文献
7.
We obtain exponential upper bounds for tails of distributions of generalized L-statistics based on a sample from an exponential distribution. We prove the asymptotic normality of generalized L-statistics based on a sample from the uniform distribution on [0,1] and of L-statistics with decomposed kernels (without any restrictions on the sample distribution type). 相似文献
8.
本文讨论由L2深度修正得到的L2深度相应的样本深度的性质,得到了样本深度的相合性和渐近正态性,并证明了它在任意紧集上的一致相合性.最后,基于上述性质简要讨论了样本深度等高的一些性质. 相似文献
9.
10.
《Surface and interface analysis : SIA》2004,36(9):1304-1313
For rough heterogeneous samples, the contrast observed in XPS images may result from both changes in elemental or chemical composition and sample topography. Background image acquisition and subtraction are frequently utilized to minimize topographical effects so that images represent concentration variations in the sample. This procedure may significantly increase the data acquisition time. Multivariate statistical methods can assist in resolving topographical and chemical information from multispectral XPS images. Principal component analysis (PCA) is one method for identification of the highest correlation/variation between the images. Topography, which is common to all of the images, will be resolved in the first most significant component. The score of this component contains spatial information about the topography of the surface, whereas the loading is a quantitative representation of the topography contribution to each elemental/chemical image. The simple‐to‐use self‐modelling mixture analysis (Simplisma) method is a pure variable method that searches for the source of most differences in the data and therefore has the potential to distinguish between chemical and topographical phases in images. The mathematical background correction scheme is developed and validated by comparing results to the experimental background correction for samples with differing degrees of topography. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献