Deep Machine Learning for the PANDA Software Trigger

Deep machine learning methods have been studied for the software trigger of the future PANDA experiment at FAIR, using Monte Carlo simulated data from the GEANT-based detector simulation framework PandaRoot. Ten physics channels that cover the main physics topics, including electromagnetic, exotic, charmonium, open charm, and baryonic reaction channels, have been investigated at four different anti-proton beam momenta. Binary and multi-class classification together with seven different network architectures have been studied. Finally a residual convolutional neural network with four residual blocks in a binary classification scheme has been chosen due to its extendability, performance and stability. The presented study represents a feasibility study of a completely software-based trigger system. Compared to a conventional selection method, the deep machine learning approach achieved a significant efficiency gain of up to 200\%, while keeping the background reduction factor at the required level of 1/1000. Furthermore, it is shown that the use of additional input variables can improve the data quality for subsequent analysis. This study shows that the PANDA software trigger can benefit greatly from the deep machine learning methods.Comment: 13 pages, 9 figures, submitted for publication in EPJ-

A Novel YY1-miR-1 Regulatory Circuit in Skeletal Myogenesis Revealed by Genome-Wide Prediction of YY1-miRNA Network

microRNAs (miRNAs) are non-coding RNAs that regulate gene expression post-transcriptionally, and mounting evidence supports the prevalence and functional significance of their interplay with transcription factors (TFs). Here we describe the identification of a regulatory circuit between muscle miRNAs (miR-1, miR-133 and miR-206) and Yin Yang 1 (YY1), an epigenetic repressor of skeletal myogenesis in mouse. Genome-wide identification of potential down-stream targets of YY1 by combining computational prediction with expression profiling data reveals a large number of putative miRNA targets of YY1 during skeletal myoblasts differentiation into myotubes with muscle miRs ranking on top of the list. The subsequent experimental results demonstrate that YY1 indeed represses muscle miRs expression in myoblasts and the repression is mediated through multiple enhancers and recruitment of Polycomb complex to several YY1 binding sites. YY1 regulating miR-1 is functionally important for both C2C12 myogenic differentiation and injury-induced muscle regeneration. Furthermore, we demonstrate that miR-1 in turn targets YY1, thus forming a negative feedback loop. Together, these results identify a novel regulatory circuit required for skeletal myogenesis and reinforce the idea that regulatory circuitries involving miRNAs and TFs are prevalent mechanisms

Functional characterization of D9, a novel deazaneplanocin a (DZNep) analog, in targeting acute myeloid leukemia (AML)

10.1371/journal.pone.0122983PLoS ONE104e012298

Noninvasive Prenatal Diagnosis of Fetal Trisomy 21 by Allelic Ratio Analysis Using Targeted Massively Parallel Sequencing of Maternal Plasma DNA

BACKGROUND: Plasma DNA obtained from a pregnant woman contains a mixture of maternal and fetal DNA. The fetal DNA proportion in maternal plasma is relatively consistent as determined using polymorphic genetic markers across different chromosomes in euploid pregnancies. For aneuploid pregnancies, the observed fetal DNA proportion measured using polymorphic genetic markers for the aneuploid chromosome would be perturbed. In this study, we investigated the feasibility of analyzing single nucleotide polymorphisms using targeted massively parallel sequencing to detect such perturbations in mothers carrying trisomy 21 fetuses. METHODOLOGY/PRINCIPAL FINDINGS: DNA was extracted from plasma samples collected from fourteen pregnant women carrying singleton fetuses. Hybridization-based targeted sequencing was used to enrich 2 906 single nucleotide polymorphism loci on chr7, chr13, chr18 and chr21. Plasma DNA libraries with and without target enrichment were analyzed by massively parallel sequencing. Genomic DNA samples of both the mother and fetus for each case were genotyped by single nucleotide polymorphism microarray analysis. For the targeted regions, the mean sequencing depth of the enriched samples was 225-fold higher than that of the non-enriched samples. From the targeted sequencing data, the ratio between fetus-specific and shared alleles increased by approximately 2-fold on chr21 in the paternally-derived trisomy 21 case. In comparison, the ratio is decreased by approximately 11% on chr21 in the maternally-derived trisomy 21 cases but with much overlap with the ratio of the euploid cases. Computer simulation revealed the relationship between the fetal DNA proportion, the number of informative alleles and the depth of sequencing. CONCLUSIONS/SIGNIFICANCE: Targeted massively parallel sequencing of single nucleotide polymorphism loci in maternal plasma DNA is a potential approach for trisomy 21 detection. However, the method appears to be less robust than approaches using non-polymorphism-based counting of sequence tags in plasma

Inhibition of miR-29 by TGF-beta-Smad3 Signaling through Dual Mechanisms Promotes Transdifferentiation of Mouse Myoblasts into Myofibroblasts

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression in post-transcriptional fashion, and emerging studies support their importance in regulating many biological processes, including myogenic differentiation and muscle development. miR-29 is a promoting factor during myogenesis but its full spectrum of impact on muscle cells has yet to be explored. Here we describe an analysis of miR-29 affected transcriptome in C2C12 muscle cells using a high throughput RNA-sequencing platform. The results reveal that miR-29 not only functions to promote myogenic differentiation but also suppresses the transdifferentiation of myoblasts into myofibroblasts. miR-29 inhibits the fibrogenic differentiation through down-regulating both extracellular matrix genes and cell adhesion genes. We further demonstrate that miR-29 is under negative regulation by TGF-beta (TGF-β)–Smad3 signaling via dual mechanisms of both inhibiting MyoD binding and enhancing Yin Yang 1 (YY1)-recruited Polycomb association. Together, these results identify miR-29 as a pleiotropic molecule in both myogenic and fibrogenic differentiation of muscle cells

Anti-Allergic Inflammatory Activity of Interleukin-37 Is Mediated by Novel Signaling Cascades in Human Eosinophils

IL-1 family regulatory cytokine IL-37b can suppress innate immunity and inflammatory activity in inflammatory diseases. In this study, IL-37b showed remarkable in vitro suppression of inflammatory tumor necrosis factor-α, IL-1β, IL-6, CCL2, and CXCL8 production in the coculture of human primary eosinophils and human bronchial epithelial BEAS-2B cells with the stimulation of bacterial toll-like receptor-2 ligand peptidoglycan, while antagonizing the activation of intracellular nuclear factor-κB, PI3K–Akt, extracellular signal-regulated kinase 1/2, and suppressing the gene transcription of allergic inflammation-related PYCARD, S100A9, and CAMP as demonstrated by flow cytometry, RNA-sequencing, and bioinformatics. Results therefore elucidated the novel anti-inflammation-related molecular mechanisms mediated by IL-37b. Using the house dust mite (HDM)-induced humanized asthmatic NOD/SCID mice for preclinical study, intravenous administration of IL-37b restored the normal plasma levels of eosinophil activators CCL11 and IL-5, suppressed the elevated concentrations of Th2 and asthma-related cytokines IL-4, IL-6, and IL-13 and inflammatory IL-17, CCL5, and CCL11 in lung homogenate of asthmatic mice. Histopathological results of lung tissue illustrated that IL-37b could mitigate the enhanced mucus, eosinophil infiltration, thickened airway wall, and goblet cells. Together with similar findings using the ovalbumin- and HDM-induced allergic asthmatic mice further validated the therapeutic potential of IL-37b in allergic asthma. The above results illustrate the novel IL-37-mediated regulation of intracellular inflammation mechanism linking bacterial infection and the activation of human eosinophils and confirm the in vivo anti-inflammatory activity of IL-37b on human allergic asthma

Noninvasive Prenatal Diagnosis of Fetal Trisomy 18 and Trisomy 13 by Maternal Plasma DNA Sequencing

Massively parallel sequencing of DNA molecules in the plasma of pregnant women has been shown to allow accurate and noninvasive prenatal detection of fetal trisomy 21. However, whether the sequencing approach is as accurate for the noninvasive prenatal diagnosis of trisomy 13 and 18 is unclear due to the lack of data from a large sample set. We studied 392 pregnancies, among which 25 involved a trisomy 13 fetus and 37 involved a trisomy 18 fetus, by massively parallel sequencing. By using our previously reported standard z-score approach, we demonstrated that this approach could identify 36.0% and 73.0% of trisomy 13 and 18 at specificities of 92.4% and 97.2%, respectively. We aimed to improve the detection of trisomy 13 and 18 by using a non-repeat-masked reference human genome instead of a repeat-masked one to increase the number of aligned sequence reads for each sample. We then applied a bioinformatics approach to correct GC content bias in the sequencing data. With these measures, we detected all (25 out of 25) trisomy 13 fetuses at a specificity of 98.9% (261 out of 264 non-trisomy 13 cases), and 91.9% (34 out of 37) of the trisomy 18 fetuses at 98.0% specificity (247 out of 252 non-trisomy 18 cases). These data indicate that with appropriate bioinformatics analysis, noninvasive prenatal diagnosis of trisomy 13 and trisomy 18 by maternal plasma DNA sequencing is achievable

Bioinformatics Approaches for Fetal DNA Fraction Estimation in Noninvasive Prenatal Testing

The discovery of cell-free fetal DNA molecules in plasma of pregnant women has created a paradigm shift in noninvasive prenatal testing (NIPT). Circulating cell-free DNA in maternal plasma has been increasingly recognized as an important proxy to detect fetal abnormalities in a noninvasive manner. A variety of approaches for NIPT using next-generation sequencing have been developed, which have been rapidly transforming clinical practices nowadays. In such approaches, the fetal DNA fraction is a pivotal parameter governing the overall performance and guaranteeing the proper clinical interpretation of testing results. In this review, we describe the current bioinformatics approaches developed for estimating the fetal DNA fraction and discuss their pros and cons

Emerging frontiers of cell-free DNA fragmentomics

Analysis of cell-free DNA (cfDNA) in the blood has shown promise for monitoring a variety of biological processes. Plasma cfDNA is a mixture comprising DNA molecules released from various bodily tissues, mediated by characteristic DNA fragmentations occurring during cell death. Fragmentation of cfDNA is non-random and contains tissue-of-origin information, which has been demonstrated in circulating fetal, tumoral, and transplanted organ-derived cfDNA molecules. Many studies have elucidated a plurality of fragmentomic markers for noninvasive prenatal, cancer, and organ transplantation assessment, such as fragment sizes, fragment ends, end motifs, and nucleosome footprints. Recently, researchers have further revealed the large population of previously unidentified long cfDNA molecules (kilobases in size) in the plasma DNA pool. This review focuses on the emerging biological properties of cfDNA, together with a discussion on its potential clinical implications