Effect of data normalization on fuzzy clustering of DNA microarray data

BACKGROUND: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. RESULTS: In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. CONCLUSION: Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods when samples have varying expression patterns or are noisy. In particular, the FCM method slightly outperformed the hard clustering methods when the expression patterns of genes overlapped and was advantageous in finding co-regulated genes. Thus, the FCM approach offers a convenient method for finding subsets of genes that are strongly associated to a given cluster

Effects of Radix Adenophorae and Cyclosporine A on an OVA-Induced Murine Model of Asthma by Suppressing to T Cells Activity, Eosinophilia, and Bronchial Hyperresponsiveness

The present study is performed to investigate the inhibitory effects of Radix Adenophorae extract (RAE) on ovalbumin-induced asthma murine model. To study the anti-inflammatory and antiasthmatic effects of RAE, we examined the development of pulmonary eosinophilic inflammation and inhibitory effects of T cells in murine by RAE and cyclosporine A (CsA). We examined determination of airway hyperresponsiveness, flow cytometric analysis (FACS), enzyme-linked immunosorbent assay (ELISA), quantitative real time (PCR), hematoxylin-eosin staining, and Masson trichrome staining in lung tissue, lung weight, total cells, and eosinophil numbers in lung tissue. We demonstrated how RAE suppressed development on inflammation and decreased airway damage

Rationale of decreasing low-density lipoprotein cholesterol below 70 mg/dL in patients with coronary artery disease: A retrospective virtual histology-intravascular ultrasound study

Background: The associations between statin and coronary plaque compositional changes were re­ported according to the use of high dose or not. An evaluation of the impact of low-density lipoprotein cholesterol (LDL-C) < 70 mg/dL by using real world dosages of statin on coronary plaque composition was undertaken. Methods: The study subjects consisted of 61 patients (mean 59.9 years old, 45 males) who underwent percutaneous coronary intervention, baseline and follow-up (F/U; mean 8.4 months) virtual histology- -intravascular ultrasound (VH-IVUS) examination. Change of plaque composition at peri-stent area, which was selected in order to measure the identical site at F/U study, was compared according to the F/U LDL-C level. Results: Body mass index, prevalence of dyslipidemia, baseline total cholesterol and baseline LDL-C were significantly lower in F/U LDL-C < 70 mg/dL group (14 segments in 10 patients) than F/U LDL-C ≥ 70 mg/dL group (79 segments in 51 patients). F/U high-density lipoprotein cholesterol (HDL-C, OR 1.06, 95% CI 1.00–1.11, p = 0.054) and F/U LDL-C < 70 mg/dL (OR 3.43, 95% CI 0.97–12.17, p = 0.056) showed strong tendency of regression of necrotic core volume (NCV) ≥ 10%. In multivariable logis­tic regression analysis, F/U HDL-C (OR 1.07, 95% CI 1.01–1.14, p = 0.020) and F/U LDL-C < 70 mg/dL (OR 8.02, 95% CI 1.58–40.68, p = 0.012) were the independent factors for regression of NCV ≥ 10%. Conclusions: Follow-up LDL-C level < 70 mg/dL with any types of statins and increase of HDL-C were associated with regression of NCV ≥ 10% in patients with coronary artery disease

BallGAN: 3D-aware Image Synthesis with a Spherical Background

3D-aware GANs aim to synthesize realistic 3D scenes such that they can be rendered in arbitrary perspectives to produce images. Although previous methods produce realistic images, they suffer from unstable training or degenerate solutions where the 3D geometry is unnatural. We hypothesize that the 3D geometry is underdetermined due to the insufficient constraint, i.e., being classified as real image to the discriminator is not enough. To solve this problem, we propose to approximate the background as a spherical surface and represent a scene as a union of the foreground placed in the sphere and the thin spherical background. It reduces the degree of freedom in the background field. Accordingly, we modify the volume rendering equation and incorporate dedicated constraints to design a novel 3D-aware GAN framework named BallGAN. BallGAN has multiple advantages as follows. 1) It produces more reasonable 3D geometry; the images of a scene across different viewpoints have better photometric consistency and fidelity than the state-of-the-art methods. 2) The training becomes much more stable. 3) The foreground can be separately rendered on top of different arbitrary backgrounds.Comment: Project Page: https://minjung-s.github.io/ballga

Hepatoprotective and Antioxidative Activities of Cornus officinalis against Acetaminophen-Induced Hepatotoxicity in Mice

The fruit of Cornus officinalis Sieb. et Zucc. is commonly prescribed in Asian countries as a tonic formula. In this study, the hepatoprotective effect of ethanolic extracts of the fruit of C. officinalis (ECO) was investigated in a mouse model of acetaminophen- (APAP-) induced liver injury. Pretreatment of mice with ECO (100, 250, and 500 mg/kg for 7 days) significantly prevented the APAP (200 mg/kg) induced hepatic damage as indicated by the serum marker enzymes (AST, ALT, and LDH). Parallel to these changes, ECO treatment also prevented APAP-induced oxidative stress in the mice liver by inhibiting lipid peroxidation (MDA) and restoring the levels of antioxidant enzymes (SOD, CAT, and HO-1) and glutathione. Liver injury and collagen accumulation were assessed using histological studies by hematoxylin and eosin staining. Our results indicate that ECO can prevent hepatic injuries associated with APAP-induced hepatotoxicity by preventing or alleviating oxidative stress

Identification of novel peptides that stimulate human neutrophils

Neutrophils play a key role in innate immunity, and the identification of new stimuli that stimulate neutrophil activity is a very important issue. In this study, we identified three novel peptides by screening a synthetic hexapeptide combinatorial library. The identified peptides GMMWAI, MMHWAM, and MMHWFM caused an increase in intracellular Ca2+ in a concentration-dependent manner via phospholipase C activity in human neutrophils. The three peptides acted specifically on neutrophils and monocytes and not on other non-leukocytic cells. As a physiological characteristic of the peptides, we observed that the three peptides induced chemotactic migration of neutrophils as well as stimulated superoxide anion production. Studying receptor specificity, we observed that two of the peptides (GMMWAI and MMHWFM) acted on formyl peptide receptor (FPR)1 while the other peptide (MMHWAM) acted on FPR2. Since the three novel peptides were specific agonists for FPR1 or FPR2, they might be useful tools to study FPR1- or FPR2-mediated immune response and signaling

In-stent restenosis-prone coronary plaque composition: A retrospective virtual histology-intravascular ultrasound study

  Background: The mechanism of in-stent restenosis (ISR) is multifactorial, which includes biological, mechanical and technical factors. This study hypothesized that increased inflammatory reaction, which is known to be an important atherosclerotic process, at a culprit lesion may lead to higher restenosis rates. Methods: The study population consisted of 241 patients who had undergone percutaneous coronary intervention with virtual histology-intravascular ultrasound (VH-IVUS) and a 9-month follow-up coronary angiography. Compared herein is the coronary plaque composition between patients with ISR and those without ISR. Results: Patients with ISR (n = 27) were likely to be older (66.2 ± 9.5 years vs. 58.7 ± 11.7 years, p = 0.002) and have higher levels of high-sensitivity C-reactive protein (hs-CRP, 1.60 ± 3.59 mg/dL vs. 0.31 ± 0.76 mg/dL, p < 0.001) than those without ISR (n = 214). VH-IVUS examination showed that percent necrotic core volume (14.3 ± 8.7% vs. 19.5 ± 9.1%, p = 0.005) was higher in those without ISR than those with ISR. Multivariate analysis revealed that hs-CRP (odds ratio [OR] 3.334, 95% con­fidence interval [CI] 1.158–9.596, p = 0.026) and age (OR 3.557, 95% CI 1.242–10.192, p = 0.018) were associated with ISR. Conclusions: This study suggests that ISR is not associated with baseline coronary plaque composition but is associated with old age and increased expression of the inflammatory marker of hs-CRP. (Cardiol J 2018; 25, 1: 7–13

Knockdown of Ant2 Reduces Adipocyte Hypoxia And Improves Insulin Resistance in Obesity.

Decreased adipose tissue oxygen tension and increased HIF-1α expression can trigger adipose tissue inflammation and dysfunction in obesity. Our current understanding of obesity-associated decreased adipose tissue oxygen tension is mainly focused on changes in oxygen supply and angiogenesis. Here, we demonstrate that increased adipocyte O2 demand, mediated by ANT2 activity, is the dominant cause of adipocyte hypoxia. Deletion of adipocyte Ant2 improves obesity-induced intracellular adipocyte hypoxia by decreasing obesity-induced adipocyte oxygen demand, without effects on mitochondrial number or mass, or oligomycin-sensitive respiration. This led to decreased adipose tissue HIF-1α expression and inflammation with improved glucose tolerance and insulin resistance in both a preventative or therapeutic setting. Our results suggest that ANT2 may be a target for the development of insulin sensitizing drugs and that ANT2 inhibition might have clinical utility

The efficacy of memory load on speech-based detection of Alzheimer’s disease

IntroductionThe study aims to test whether an increase in memory load could improve the efficacy in detection of Alzheimer’s disease and prediction of the Mini-Mental State Examination (MMSE) score.MethodsSpeech from 45 mild-to-moderate Alzheimer’s disease patients and 44 healthy older adults were collected using three speech tasks with varying memory loads. We investigated and compared speech characteristics of Alzheimer’s disease across speech tasks to examine the effect of memory load on speech characteristics. Finally, we built Alzheimer’s disease classification models and MMSE prediction models to assess the diagnostic value of speech tasks.ResultsThe speech characteristics of Alzheimer’s disease in pitch, loudness, and speech rate were observed and the high-memory-load task intensified such characteristics. The high-memory-load task outperformed in AD classification with an accuracy of 81.4% and MMSE prediction with a mean absolute error of 4.62.DiscussionThe high-memory-load recall task is an effective method for speech-based Alzheimer’s disease detection