25 research outputs found
On Investigating the Conservative Property of Score-Based Generative Models
Existing Score-based Generative Models (SGMs) can be categorized into
constrained SGMs (CSGMs) or unconstrained SGMs (USGMs) according to their
parameterization approaches. CSGMs model probability density functions as
Boltzmann distributions, and assign their predictions as the negative gradients
of some scalar-valued energy functions. On the other hand, USGMs employ
flexible architectures capable of directly estimating scores without the need
to explicitly model energy functions. In this paper, we demonstrate that the
architectural constraints of CSGMs may limit their modeling ability. In
addition, we show that USGMs' inability to preserve the property of
conservativeness may lead to degraded sampling performance in practice. To
address the above issues, we propose Quasi-Conservative Score-based Generative
Models (QCSGMs) for keeping the advantages of both CSGMs and USGMs. Our
theoretical derivations demonstrate that the training objective of QCSGMs can
be efficiently integrated into the training processes by leveraging the
Hutchinson trace estimator. In addition, our experimental results on the
CIFAR-10, CIFAR-100, ImageNet, and SVHN datasets validate the effectiveness of
QCSGMs. Finally, we justify the advantage of QCSGMs using an example of a
one-layered autoencoder
Intra- and Inter-Individual Variance of Gene Expression in Clinical Studies
BACKGROUND: Variance in microarray studies has been widely discussed as a critical topic on the identification of differentially expressed genes; however, few studies have addressed the influence of estimating variance. METHODOLOGY/PRINCIPAL FINDINGS: To break intra- and inter-individual variance in clinical studies down to three levels--technical, anatomic, and individual--we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of "inter-individual variable genes" were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduces/eliminates the effects of underestimated variance. CONCLUSIONS/SIGNIFICANCE: Our data demonstrated that correct variance evaluation is critical in selecting significant genes. If the degree of variance is underestimated, "noisy" genes are falsely identified as differentially expressed genes. These genes are the noise associated with biological interpretation, reducing the biological significance of the gene set. Our results also indicate that applying a higher number of fold change as the selection criteria reduces/eliminates the differences between distinct estimations of variance
Microarray meta-analysis database (M2DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database
<p>Abstract</p> <p>Background</p> <p>Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency.</p> <p>Results</p> <p>M<sup>2</sup>DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M<sup>2</sup>DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading.</p> <p>Conclusion</p> <p>M<sup>2</sup>DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.</p
Amphiregulin induces CCN2 and fibronectin expression by TGF-β through EGFR-dependent pathway in lung epithelial cells
Abstract Background Airway fibrosis is one of the pathological characteristics of severe asthma. Transforming growth factor (TGF)-β has been known to promote epithelial-mesenchymal transition formation and to play a role in the progression of tissue fibrosis. Cellular communication network factor 2 (CCN2) and fibronectin (FN) are well-known markers of EMT and fibrosis. However, whether AREG is involved in TGF-β-induced CCN2 and FN expression in human lung epithelial cells is unknown. Methods AREG and FN were analyzed by immunofluorescence staining on ovalbumin-challenged mice. CCN2 and FN expression were evaluated in human lung epithelial (A459) cells following TGF or AREG treatment for the indicated times. Secreted AREG from A549 cells was detected by ELISA. Cell migration was observed by a wound healing assay. Chromatin immunoprecipitation was used to detect the c-Jun binding to the CCN2 promoter. Results AREG and FN expression colocalized in lung tissues from mice with ovalbumin-induced asthma by immunofluorescence staining. Moreover, TGF-β caused the release of AREG from A549 cells into the medium. Smad3 siRNA down-regulated AREG expression. AREG also stimulated CCN2 and FN expression, JNK and c-Jun phosphorylation, and cell migration in A549 cells. AREG small interfering (si) RNA inhibited TGF-β-induced expression of CCN2, FN, and cell migration. Furthermore, AREG-induced CCN2 and FN expression were inhibited by EGFR siRNA, a JNK inhibitor (SP600125), and an activator protein-1 (AP-1) inhibitor (curcumin). EGFR siRNA attenuated AREG-induced JNK and c-Jun phosphorylation. Moreover, SP600125 downregulated AREG-induced c-Jun phosphorylation. Conclusion These results suggested that AREG mediates the TGF-β-induced EMT in human lung epithelial cells through EGFR/JNK/AP-1 activation. Understanding the role of AREG in the EMT could foster the development of therapeutic strategies for airway remodeling in severe asthma
TGF-β Induced CTGF Expression in Human Lung Epithelial Cells through ERK, ADAM17, RSK1, and C/EBPβ Pathways
Background: Lung epithelial cells play critical roles in idiopathic pulmonary fibrosis. Methods: In the present study, we investigated whether transforming growth factor-β (TGF-β)-induced expression of connective tissue growth factor (CTGF) was regulated by the extracellular signal-regulated kinase (ERK)/a disintegrin and metalloproteinase 17 (ADAM17)/ribosomal S6 kinases 1 (RSK1)/CCAAT/enhancer-binding protein β (C/EBPβ) signaling pathway in human lung epithelial cells (A549). Results: Our results revealed that TGF-β-induced CTGF expression was weakened by ADAM17 small interfering RNA (ADAM17 siRNA), TNF-α processing inhibitor-0 (TAPI-0, an ADAM17 inhibitor), U0126 (an ERK inhibitor), RSK1 siRNA, and C/EBPβ siRNA. TGF-β-induced ERK phosphorylation as well as ADAM17 phosphorylation was attenuated by U0126. The TGF-β-induced increase in RSK1 phosphorylation was inhibited by TAPI-0 and U0126. TGF-β-induced C/EBPβ phosphorylation was weakened by U0126, ADAM17 siRNA, and RSK1 siRNA. In addition, TGF-β increased the recruitment of C/EBPβ to the CTGF promoter. Furthermore, TGF-β enhanced fibronectin (FN), an epithelial–mesenchymal transition (EMT) marker, and CTGF mRNA levels and reduced E-cadherin mRNA levels. Moreover, TGF-β-stimulated FN protein expression was reduced by ADAM17 siRNA and CTGF siRNA. Conclusion: The results suggested that TGF-β induces CTGF expression through the ERK/ADAM17/RSK1/C/EBPβ signaling pathway. Moreover, ADAM17 and CTGF participate in TGF-β-induced FN expression in human lung epithelial cells
Abnormal ADAM17 expression causes airway fibrosis in chronic obstructive asthma
Patients with chronic obstructive asthma (COA) develop airflow obstruction caused by subepithelial fibrosis. Although a disintegrin and metalloproteinase 17 (ADAM17) has been implicated in lung inflammation and tissue fibrosis, its role in airway fibrosis in COA has not been explored. Here, we found marked overexpression of ADAM17, phosphorylated ADAM17, and connective tissue growth factor (CTGF) in human airway fibroblasts from COA patients, compared with those of normal subjects. Similarly, levels of ADAM17, CTGF, α-smooth muscle actin (α-SMA), and collagen were increased in endobronchial biopsies from COA patients, but not in controls. In an ovalbumin-challenge asthma model, airway fibrosis was inhibited in ADAM17f/f/Cre+ mice compared to control mice. TGF-β- and thrombin-induced fibrotic protein expression was reduced by ADAM17 small interfering (si)RNA, TAPI-0 (an ADAM17 inhibitor), and EGFR siRNA. In addition, exogenous HB-EGF reversed fibrotic response in ADAM17 knockdown human lung fibroblasts. ADAM17 causes subepithelial fibrosis through regulation of enhanced extracellular matrix production and fibroblast differentiation and is the common pathway for airway fibrosis mediated by TGF-β and thrombin through an aberrant ADAM17/EGFR signalling pathway
Significant score of Gene Ontology terms for the significant gene sets determined by distinct significant criteria.
<p>The number in the table is the significant sore for GO terms. The significant score is –log (EASE Score) where EASE Score is a modified Fisher Exact P Value obtained by DAVID.</p>§<p>The criteria of averaged fold change.</p>¥<p>The significant score is evaluated by technical variance.</p>#<p>The significant score is evaluated by anatomic variance.</p
Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch
Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices—namely, the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson’s correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients’ OSA severity. The high supine percentage of sleep may cause OSA indices’ overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis
Clinical information of pregnancy outcomes (n = 9).
#<p>indicates the number of times the mother has been pregnant, regardless of whether these pregnancies were carried to term. A current pregnancy, if any, is included in this count.</p>&<p>indicates the number of viable (>20 wks) births. Pregnancies consisting of multiples, such as twins or triplets, count as ONE birth for the purpose of this notation.</p>%<p>is a simple and repeatable method to quickly and summarily assess the health of newborn children immediately after birth.</p>*<p>is standard variation.</p
The scatter plot of averaged fold change and p values, and the selection of inter-individual variable gene.
<p>(a) The scatter plot of log<sub>2</sub> (averaged fold change) and –log (p value). Pa is the p value determined by applying anatomic variance. Pt is the p value determined by applying technical variance. (b) The enlarged area of the rectangle in (a). The red arrows indicate the corresponding p value of FDR 5%. The gray arrows indicate the averaged fold change criteria: 1.2, 1.3, 1.4, and 1.5. (c) The number of inter-individual variable gene selected by the criteria of FDR 5%, evaluated by technical and anatomic variance (The red arrows in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038650#pone-0038650-g003" target="_blank">Figure 3b</a>), and distinct averaged fold changes (The gray arrows in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038650#pone-0038650-g003" target="_blank">Figure 3b</a>).</p