Inference of S-system models of genetic networks using Product Unit Neural Networks

In this study, we proposed the method of inference of genetic networks which expresses the regulation of genes. The proposed method does not solve the differential equations, learns the genetic networks using Product-Unit-Neural- Network (PUNN) and infer the S-system model of genetic networks which describes a set of differential equations. The experimental results show the proposal method is 160 times faster than the previous method which estimated S-system model of genetic networks while maintaining equivalent performance to the previous method. © 2008 IEEE

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data

Patterns of microRNA Expression in Non-Human Primate Cells Correlate with Neoplastic Development In Vitro

MicroRNAs (miRNAs) are small noncoding RNAs that negatively regulate gene expression post-transcriptionally. They play a critical role in developmental and physiological processes and have been implicated in the pathogenesis of several diseases including cancer. To identify miRNA signatures associated with different stages of neoplastic development, we examined the expression profile of 776 primate miRNAs in VERO cells (a neoplastically transformed cell line being used for the manufacture of viral vaccines), progenitor primary African green monkey kidney (pAGMK) cells, and VERO cell derivatives: spontaneously immortalized, non-tumorigenic, low-passage VERO cells (10-87 LP); tumorigenic, high-passage VERO cells (10-87 HP); and a cell line (10-87 T) derived from a 10-87 HP cell tumor xenograft in athymic nude mice. When compared with pAGMK cells, the majority of miRNAs were expressed at lower levels in 10-87 LP, 10-87 HP, and 10-87 T cells. We identified 10 up-regulated miRNAs whose level of expression correlated with VERO cell evolution from a non-tumorigenic phenotype to a tumorigenic phenotype. The overexpression of miR-376a and the polycistronic cluster of miR-376a, miR-376b and miR-376c conferred phenotypic changes to the non-tumorigenic 10-87 LP cells that mimic the tumorigenic 10-87 HP cells. Thirty percent of miRNAs that were components of the identified miRNAs in our spontaneously transformed AGMK cell model are also dysregulated in a variety of human tumors. These results may prove to be relevant to the biology of neoplastic development. In addition, one or more of these miRNAs could be biomarkers for the expression of a tumorigenic phenotype

Functional annotation of human long noncoding RNAs via molecular phenotyping

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-todate lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.Peer reviewe

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution

Bone Augmentation Using Novel Unidirectional Porous Hydroxyapatite with Bone Morphogenetic Protein-2 on Rat Skull

Unidirectional porous hydroxyapatite (UDPHAp) is a material whose microstructure consists of cross-sectional oval pores with a pore diameter in the range of 100-300 mu m that penetrate through the material. UDPHAp has proven suitable for osteogenesis and angiogenesis. The present study was designed to evaluate the osteogenic effect of a newly developed UDPHAp as a carrier of recombinant human bone morphogenetic protein-2 (rhBMP-2) in a rat onlay graft model. UDPHAp was implanted beneath the calvarial periosteum of rats to simulate alveolar bone augmentation in a clinical condition. At 2 weeks after implantation, UDPHAp with rhBMP-2 resulted in active bone formation, and the augmented bone was connected directly with the original bone, whereas commercialized porous hydroxyapatite (PHAp) with rhBMP-2 showed little bone formation. These results suggest that UDPHAp in this model is suitable for onlay graft and is an effective biomaterial for the rhBMP-2 delivery system