General performance of mOPLS-DA using four datasets.

<p>Features were selected from the training set to fit OVRSVM models using the individual feature selection method. Observations of the training and independent test sets were classified and predicted by the corresponding fitted model, and the number of misclassified observation was counted.</p><p>Key: ^athe number of features was optimized from 100 to 300 with the step of 10 and set to 160;</p><p>^b OVR, <i>one-versus-rest</i>;</p><p>^c KW, Kruskal–Wallis non-parametric one-way ANOVA;</p><p>^d cluster analysis.</p

S-plots for gene selection of three classes with subtypes.

<p>A, S-plot from the OPLS-DA model of AML and ALL. Twenty genes with increased and decreased levels, respectively, in AML were selected from this S-plot. B, S-plot of OPLS-DA of ALL-B and ALL-T. From this S-plot, five genes with elevated and reduced levels in ALL-B, respectively, were selected. C, A typical gene (M27891_at) with a profile of increased expression levels in AML and decreased levels in ALL-T and ALL-B. D, The levels of gene U05259_rna1_at upregulated in ALL-B and downregulated in ALL-T. Key: p(corr) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084253#pone.0084253-Eisen1" target="_blank">[1]</a> and w <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084253#pone.0084253-Eisen1" target="_blank">[1]</a> are the correlation coefficient and contribution coefficient vectors of the predictive component of the OPLS-DA model.</p

OPLS-DA models of three classes with subtypes and three classes in parallel using the training set.

<p>Keys: R²X, the cumulative fraction of Sum of Squares (SS) of X explained by components; R²Y, the cumulative Sum of Squares of all the y-variables explained by the extracted components; Q²Y, The fraction of the total variation of Y (PLS and OPLS) that can be predicted by the extracted components.</p

Feature selection of the top genes for the OVR-<i>t</i>-test.

<p>Feature selection of the top genes for the OVR-<i>t</i>-test.</p

A, OPLS-DA score plot of ALL-B vs. AML and ALL-T.

<p>B, OPLS-DA S-plot of AML vs. ALL-B and ALL-T, eleven and six up- and down-regulated genes, respectively, in AML were selected from this S-plot. C, OPLS-DA S-plot of ALL-B vs. AML and ALL-T. Twelve and five up- and downregulated genes, respectively, in ALL-B were selected. D, OPLS-DA S-plot of ALL-T vs. ALL-B and AML. Twelve and five up- and downregulated genes, respectively, in ALL-T were selected. E, PCA score plot of the training set with top 50 genes. F, PCA score plot of the test set with the selected top 50 genes.</p

Cluster analysis tree plot of the reduced training and test sets of the top 50 genes.

<p>A, Training set. B, Test set. Cluster analysis was computed using the Euclidean distance and complete linkage. Keys: B, ALL-B (red); T, ALL-T (yellow); M, AML (blue). AML- and AML+ indicate gene up- and downregulated expression levels in AML samples, respectively; ALL-B- and ALL-T+ represent down- and upregulated expression levels in ALL-B, respectively; ALL-T− and ALL-T+ indicate ALL-T samples with down- and upregulated expression levels, respectively.</p

PCA score plot and cluster analysis tree plot of training and test sets.

<p>A, PCA score plot of the training set using the top 50 genes. B, PCA score plot of the test set of the top 50 genes. C, Cluster analysis tree plot of the training set of the initial 3751 genes. #29 (in blue mark) was misclassified. D, Cluster analysis tree plot of the test set with 3751 genes. #54, 57, 60, 66 (in blue mark) and #9, 10 (in yellow mark) were misclassified. Cluster analysis trees of C and D were computed using the Euclidean distance and Ward’s linkage. E, Cluster analysis tree plot of the training set of the top 50 genes. F, Cluster analysis the tree plot of the test set of the reduced top 50 genes. Only #66 (in blue mark) was misclassified. Cluster analysis of E and F were carried out using the Euclidean distance and average linkage. Keys for C, D, E, F: B, ALL-B (red); T, ALL-T (yellow); M, AML, (blue).</p

PCA score plots of the new training and test sets.

<p>A, PCA score plot of all ALL-T samples. From this plot, we selected two informative samples (# 9 and 10) as new test samples for the ALL-T class. B, Score plot of the first and fourth principle component from PCA of the new training set. C, PCA score plot of second and third components from ALL-B and ALL-T. D, PCA score plot of the new test set.</p

Fructus Xanthii Attenuates Hepatic Steatosis in Rats Fed on High-Fat Diet

<div><p><i>Fructus Xanthii</i> (FX) has been widely used as a traditional herbal medicine for rhinitis, headache, cold, etc. Modern pharmacological studies revealed that FX possesses anti-inflammatory, anti-oxidative, and anti-hyperglycemic properties. The present study was designed to investigate the effects of FX on glucose and insulin tolerance, and hepatic lipid metabolism in rats fed on high-fat diet (HFD). Hepatic steatosis was induced by HFD feeding. Aqueous extraction fractions of FX or vehicle were orally administered by gavage for 6 weeks. Body weight and blood glucose were monitored. Glucose and insulin tolerance test were performed. Liver morphology was visualized by hematoxylin and eosin, and oil red O staining. Expression of liver lipogenic and lipolytic genes was measured by real-time PCR. We showed here that FX improved glucose tolerance and insulin sensitivity in HFD rats. FX significantly decreased the expression of lipogenic genes and increased the expression of lipolytic genes, ameliorated lipid accumulation and decreased the total liver triglyceride (TG) content, and thus attenuated HFD-induced hepatic steatosis. In conclusion, FX improves glucose tolerance and insulin sensitivity, decreases lipogenesis and increases lipid oxidation in the liver of HFD rats, implying a potential application in the treatment of non-alcoholic fatty liver disease.</p> </div

Effects of FX on body weight, relative tissue weight and serum ALT and AST levels in rats.

<p>Body weight (A), relative tissue weight (B), and serum levels of ALT and AST of rats fed on HFD (C) and on NCD (D). Data given are mean ± SE. (N = 10, ^#P<0.05, ^##P<0.01 vs. NCD group; *P<0.05 vs. HFD group. SCF: subcutaneous fat; EF: epididymal fat).</p