80 research outputs found
Additional file 2 of Developing neural network diagnostic models and potential drugs based on novel identified immune-related biomarkers for celiac disease
Additional file 2: Fig. S1. GO and KEGG analysis of 58 differentially expressed immune-related genes. A GO enrichment results in differentially expressed immune-related genes. B KEGG enrichment results in differentially expressed immune-related genes. Fig. S2. Heatmap shows the overall landscape of CD patients' ssGSEA score of 28 immune gene sets. Fig. S3. Consensus matrix heatmap when K = 3β9. It is related to Fig. 3D. Fig. S4. The box plot shows the ssGSEA score of immune cells of the C1 and C2 groups. (ns, no significance, *P < 0.05, **P < 0.01, ***P < 0.001). Fig. S5. Validation of the IG score in the GSE164883 set. A The violin plot shows the IG score between the control and CD groups. B The ROC curve of the IG score in the GSE164883 validation set. Fig. S6. ROC analysis validated the diagnostic performance of HIGs. ROC curves of the indicated HIGs in the GSE11501 training set (A) and GSE164883 validation set (B). Fig. S7. Construction of artificial neural network (ANN) based on HIGs. A The construction of an artificial neural network (ANN) based on MR1, TNFSF13B, and CCL25. B The AUC of the training cohort with a value of 0.824. C The AUC of the test cohort with a value of 0.733. Fig. S8. 3D (left) and 2D (right) structure of complexes of HIGs and drugs. It is related to Fig. 7
Additional file 1 of Developing neural network diagnostic models and potential drugs based on novel identified immune-related biomarkers for celiac disease
Additional file 1: Table S1. 896 differentially expressed genes. Table S2. Results of three machine algorithms. Table S3. ssGSEA score of 28 immune gene sets in celiac disease patients. Table S4. IG score for GSE11501 training set based on HIGs. Table S5. IG score for GSE164883 validation set based on HIGs. Table S6. ANN diagnosis effect for the grouping of immune characteristics of celiac disease subtypes. Table S7. 2483 immune genes from the ImmPort database. Table S8. 28 immune gene sets from the TISIDB database
Summary of standardized major axis regression analyses for ground tissue area and xylem tissue area at four altitudinal sites on Gongga Mountain, southwestern China.
<p>A, B, C and D β=β corresponding species group respectively; n β=β the number of species included; CI β=β the confidence interval, Low CI does 95% β=β confidence lower limit, Upp CI β=β95% confidence upper limit.</p
The PCA biplot.
<p>Principal component analysis (PCA) based on trunk sprouts in natural sites (NH) and disturbed sites (DH), seed size, seed appendage, starch content in shoot and plant height variables. Circles show sampled species, with abbreviations being as for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112385#pone-0112385-t001" target="_blank">Table 1</a>.</p
The species properties and the mean sprout number per individual (meanΒ±SE) in natural habitat and in disturbed habitat for the 15 species studied.
<p>* denotes the p-level of student's t-tests for the species in the two habitats. * β=β p<0.05, ** β=β p<0.01, *** β=β p<0.001, ns β=β non-significant. Ss β=β small shrub (β€0.5 m), Ms β=β middle shrub (0.5β2 m), Ls β=β large shrub (2β5 m), St β=β small tree (5β8 m), Mt β=β middle tree (8β25 m), Lt β=β large tree (β₯25 m); NH & DH β=β sprout number in natural & in disturbed habitat, respectively; Abbr. β=β the abbreviation of the species studied. CS denotes climax species and LP does long-lived pioneer. The species are sorted according to the column of DH/NH.</p><p>The species properties and the mean sprout number per individual (meanΒ±SE) in natural habitat and in disturbed habitat for the 15 species studied.</p
The biplot of PCA.
<p>Association among tissue distribution in terminal shoot, growth form/height classes and altitude for 100 woody forest species on Mt. Gongga in southwest China. In the biplot, the horizontal and vertical axes (Ax1 and Ax2) denote the first and the second ordination axis of PCA, respectively. Tissue traits, altitude and species growth form are shown in the diagram. GF β=β growth form/height class, XA β=β xylem tissue area, VA β=β vascular tissue area, TA β=β terminal shoot cross-sectional area, PA β=β pith area, GA β=β ground tissue area, GR β=β ground tissue ratio, VR β=β vascular tissue ratio, XR β=β xylem tissue ratio.</p
Trait means within terminal shoot for the 100 woody broad-leaved species on Gongga Mountain, southwestern China, in which 103 species samples are included.
<p>Ground tissue area is the sum of cortex and pith area; vascular tissue area is the sum of xylem and phloem area. The classification of growth form and height class is defined by reference to Song, 2001<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062163#pone.0062163-Song1" target="_blank">[48]</a> and Moles et al., 2009 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062163#pone.0062163-Moles1" target="_blank">[49]</a>. Ss β=β small shrub (<0.5 m), Ms β=β middle shrub (0.5βΌ2 m), Ls β=β large shrub (2βΌ5 m), St β=β small tree (5βΌ8 m), Mt β=β middle tree (8βΌ25 m), Lt β=β large tree (>25 m).</p
The relationship of seed size vs. sprouts.
<p>The bivariate relationship between seed size and trunk sprouting number among climax species (CS) and long-lived pioneers (LP) in natural habitats in a subtropical broad-leaved forest in southwestern China. The two lines in the graph denote the fitted lines to the two functional groups (slope β=β common slope shared by the two functional groups) using the standardised major axis (SMA); broken line, CS species group; solid line, LP group.</p
Fibrillar Morphology of Derivatives of Poly(3-alkylthiophene)s by Solvent Vapor Annealing: Effects of Conformational Transition and Conjugate Length
A fibrillar
morphology was obtained, compared to the featherless
pristine films, via solvent annealing the films of a series of derivatives
of polyΒ(3-alkylthiophene)Βs (P3ATs): polyΒ(3-dodecylthiophene) (P3DDT),
polyΒ(3,3β΄-didodecyl-quaterthiophene) (PQT12), and polyΒ(2,5-bisΒ(3-dodecylthiophen-2-yl)ΒthienoΒ[3,2-<i>b</i>]Βthiophene) (pBTTT12). Among the solvents used, including
dichloromethane, chloroform, tetrahydrofuran, and carbon disulfide
(CS<sub>2</sub>), CS<sub>2</sub> was the best to induce fibril formation
because its solubility parameter is closest to those of the P3AT derivatives.
It was found that higher critical CS<sub>2</sub> vapor pressures were
needed to form crystal nuclei with increasing conjugation length and
molecular weight of the P3AT derivatives; i.e., the critical vapor
pressures for P3DDT 13.9k and PQT12 15.5k were 59.0% and 80.7%, respectively,
and there were no nuclei of fibrils for pBTTT12 15.6k with the highest
conjugation length, even at a CS<sub>2</sub> vapor pressure of 98.3%.
Meanwhile, at the highest vapor pressure, the fibril density decreased
with increasing conjugation length and molecular weight of the P3AT
derivatives. This is attributed to the rod-like conformation prevailing
for polymers with larger conjugation length and higher molecular weight
during solvent annealing, making the conformational transition toward
coils more difficult and hindering diffusion of molecules. The results
presented here are expected to be helpful for the design and processing
of conjugated semiconductor polymers
A terminal shoot cross-section.
<p>A photograph of <i>Acer sinense</i> var. <i>concolor</i> showing a typical anatomical structure of a terminal shoot.</p
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