Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure

The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-β signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis

High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs

Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of $10$ to $10^3$ depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.Comment: work presented in NYSDS 201

The expression profile analysis of NKX2-5 knock-out embryonic mice to explore the pathogenesis of congenital heart disease

AbstractBackgroundMutation of NKX2-5 could lead to the development of congenital heart disease (CHD) which is a common inherited disease. This study aimed to investigate the pathogenesis of CHD in NKX2-5 knock-out embryonic mice.MethodsThe expression profile in the NKX2-5 knock-out embryonic mice (GSE528) was downloaded from Gene Expression Omnibus. The heart tissues from the null/heterozygous embryonic day 12.5 mice were compared with wild-type mice to identify differentially expressed genes (DEGs), and then DEGs corresponding to the transcriptional factors were filtered out based on the information in the TRANSFAC database. In addition, a transcriptional regulatory network was constructed according to transcription factor binding site information from the University of California Santa Cruz database. A pathway interaction network was constructed by latent pathways identification analysis.ResultsThe 42 DEGs corresponding to transcriptional factors from the null and heterozygous embryos were identified. The transcriptional regulatory networks included five down-regulated DEGs (SP1, SRY, JUND, STAT6, and GATA6), and six up-regulated DEGs [POU2F1, NFY (NFYA/NFYB/NFYC), USF2 and MAX]. Latent pathways analysis demonstrated that ribosome, glycolysis/gluconeogenesis, and dilated cardiomyopathy pathways significantly interacted.ConclusionThe identified DEGs and latent pathways could provide new comprehensive view for understanding the pathogenesis of CHD

Mechanically enhanced electrical conductivity of polydimethylsiloxane-based composites by a hot embossing process

Electrically conductive polymer composites are in high demand for modern technologies, however, the intrinsic brittleness of conducting conjugated polymers and the moderate electrical conductivity of engineering polymer/carbon composites have highly constrained their applications. In this work, super high electrical conductive polymer composites were produced by a novel hot embossing design. The polydimethylsiloxane (PDMS) composites containing short carbon fiber (SCF) exhibited an electrical percolation threshold at 0.45 wt % and reached a saturated electrical conductivity of 49 S/m at 8 wt % of SCF. When reducing the sample thickness from 1.0 to 0.1 mm by the hot embossing process, a compression-induced percolation threshold occurred at 0.3 wt %, while the electrical conductivity was further enhanced to 378 S/m at 8 wt % SCF. Furthermore, the addition of a second nanofiller of 1 wt %, such as carbon nanotube or conducting carbon black, further increased the electrical conductivity of the PDMS/SCF (8 wt %) composites to 909 S/m and 657 S/m, respectively. The synergy of the densified conducting filler network by the mechanical compression and the hierarchical micro-/nano-scale filler approach has realized super high electrically conductive, yet mechanically flexible, polymer composites for modern flexible electronics applications

New Insights Into the Response of Metabolome of Escherichia coli O157:H7 to Ohmic Heating

The objective of this study was to investigate the effects of ohmic heating and water bath heating (WB) on the metabolome of Escherichia coli O157:H7 cells at the same inactivation levels. Compared to low voltage long time ohmic heating (5 V/cm, 8.50 min, LVLT) and WB (5.50 min), the high voltage short time ohmic heating (10 V/cm, 1.75 min, HVST) had much shorter heating time. Compared to the samples of control (CT), there were a total of 213 differential metabolites identified, among them, 73, 78, and 62 were presented in HVST, LVLT, and WB samples, revealing a stronger metabolomic response of E. coli cells to HVST and LVLT than WB. KEGG enrichment analysis indicated that the significantly enriched pathways were biosynthesis and metabolism of amino acids (alanine, arginine, aspartate, and glutamate, etc.), followed by aminoacyl-tRNA biosynthesis among the three treatments. This is the first metabolomic study of E. coli cells in response to ohmic heating and presents an important step toward understanding the mechanism of ohmic heating on microbial inactivation, and can serve as a theoretical basis for better application of ohmic heating in food products

Expanding the mutational and clinical spectrum of Chinese intellectual disability patients with two novel CTCF variants

CCCTC-Binding Factor (CTCF) is a protein-coding gene involved in transcriptional regulation, insulator activity, and regulation of chromatin structure, and is closely associated with intellectual developmental disorders. In this study, we report two unrelated Chinese patients with intellectual disability (ID). According to variant interpretation results from exome sequencing data and RNA-seq data, we present two novel heterozygous CTCF variants, NM_006565.3:c.1519_2184del (p. Glu507_Arg727delins47) and NM_006565.3:c.1838_1852del (p.Glu613_Pro617del), found in two distinct unrelated patients, respectively. Moreover, RNA-seq data of patient 1 indicated the absence of the mutant transcript, while in patient 2, the RNA-seq data revealed a CTCF mRNA transcript with a deletion of 15 nucleotides. Notably, the RNA sequencing data revealed 507 differentially expressed genes shared between these two patients. Specifically, among them, 194 were down-regulated, and 313 were up-regulated, primarily involved in gene regulation and cellular response. Our study expands the genetic and clinical spectrum of CTCF and advances our understanding of the pathogenesis of CTCF in vivo

Antimicrobial photodynamic inactivation as an alternative approach to inhibit the growth of Cronobacter sakazakii by fine-tuning the activity of CpxRA two-component system

Cronobacter sakazakii is an opportunistic foodborne pathogen primarily found in powdered infant formula (PIF). To date, it remains challenging to control the growth of this ubiquitous bacterium. Herein, antimicrobial photodynamic inactivation (aPDI) was first employed to inactivate C. sakazakii. Through 460 nm light irradiation coupled with hypocrellin B, the survival rate of C. sakazakii was diminished by 3~4 log. The photokilling effect was mediated by the attenuated membrane integrity, as evidenced by PI staining. Besides, scanning electron microscopy showed the deformed and aggregated cell cluster, and intracellular ROS was augmented by 2~3 folds when light doses increase. In addition to planktonic cells, the biofilm formation of C. sakazakii was also affected, showing an OD590nm decline from 0.85 to 0.25. In terms of molecular aspects, a two-component system called CpxRA, along with their target genes, was deregulated during illumination. Using the knock-out strain of ΔCpxA, the bacterial viability was reduced by 2 log under aPDI, a wider gap than the wildtype strain. Based on the promoted expression of CpxR and OmpC, aPDI is likely to play its part through attenuating the function of CpxRA-OmpC pathway. Finally, the aPDI system was applied to PIF, and C. sakazakii was inactivated under various desiccated or heated storage conditions. Collectively, aPDI serves as an alternative approach to decontaminate C. sakazakii, providing a new strategy to reduce the health risks caused by this prevalent foodborne pathogen