This article is concerned with the spectral behavior of p-dimensional linear processes in the moderately high-dimensional case when both dimensionality p and sample size n tend to infinity so that p/n→0. It is shown that, under an appropriate set of assumptions, the empirical spectral distributions of the renormalized and symmetrized sample autocovariance matrices converge almost surely to a nonrandom limit distribution supported on the real line. The key assumption is that the linear process is driven by a sequence of pdimensional real or complex random vectors with i.i.d. entries possessing zero mean, unit variance and finite fourth moments, and that the p × p linear process coefficient matrices are Hermitian and simultaneously diagonalizable. Several relaxations of these assumptions are discussed. The results put forth in this paper can help facilitate inference on model parameters, model diagnostics and prediction of future values of the linear process.

This article is concerned with the spectral behavior of $p$-dimensional linear processes in the moderately high-dimensional case when both dimensionality $p$ and sample size $n$ tend to infinity so that $p/n\to0$. It is shown that, under an appropriate set of assumptions, the empirical spectral distributions of the renormalized and symmetrized sample autocovariance matrices converge almost surely to a nonrandom limit distribution supported on the real line. The key assumption is that the linear process is driven by a sequence of $p$-dimensional real or complex random vectors with i.i.d. entries possessing zero mean, unit variance and finite fourth moments, and that the $p\times p$ linear process coefficient matrices are Hermitian and simultaneously diagonalizable. Several relaxations of these assumptions are discussed. The results put forth in this paper can help facilitate inference on model parameters, model diagnostics and prediction of future values of the linear process.

Abstract Background The speed at which biological datasets are being accumulated stands in contrast to our ability to integrate them meaningfully. Large-scale biological databases containing datasets of genes, proteins, cells, organs, and diseases are being created but they are not connected. Integration of these vast but heterogeneous sources of information will allow the systematic and comprehensive analysis of molecular and clinical datasets, spanning hundreds of dimensions and thousands of individuals. This integration is essential to capitalize on the value of current and future molecular- and cellular-level data on humans to gain novel insights about health and disease. Results We describe a new open-source Cytoscape plugin named iCTNet (integrated Complex Traits Networks). iCTNet integrates several data sources to allow automated and systematic creation of networks with up to five layers of omics information: phenotype-SNP association, protein-protein interaction, disease-tissue, tissue-gene, and drug-gene relationships. It facilitates the generation of general or specific network views with diverse options for more than 200 diseases. Built-in tools are provided to prioritize candidate genes and create modules of specific phenotypes. Conclusions iCTNet provides a user-friendly interface to search, integrate, visualize, and analyze genome-scale biological networks for human complex traits. We argue this tool is a key instrument that facilitates systematic integration of disparate large-scale data through network visualization, ultimately allowing the identification of disease similarities and the design of novel therapeutic approaches. The online database and Cytoscape plugin are freely available for academic use at: http://www.cs.queensu.ca/ictnet

ABSTRACT Motivation Metagenome assembly from short next-generation sequencing data is a challenging process due to its large scale and computational complexity. Clustering short reads before assembly offers a unique opportunity for parallel downstream assembly of genomes with individualized optimization. However, current read clustering methods suffer either false negative (under-clustering) or false positive (over-clustering) problems. Results Based on a previously developed scalable read clustering method on Apache Spark, SpaRC, that has very low false positives, here we extended its capability by adding a new method to further cluster small clusters. This method exploits statistics derived from multiple samples in a dataset to reduce the under-clustering problem. Using a synthetic dataset from mouse gut microbiomes we show that this method has the potential to cluster almost all of the reads from genomes with sufficient sequencing coverage. We also explored several clustering parameters that deferentially affect genomes with various sequencing coverage. Availability https://bitbucket.org/berkeleylab/jgi-sparc/ . Contact zhongwang@lbl.gov

Metagenome assembly from short next-generation sequencing data is a challenging process due to its large scale and computational complexity. Clustering short reads by species before assembly offers a unique opportunity for parallel downstream assembly of genomes with individualized optimization. However, current read clustering methods suffer either false negative (under-clustering) or false positive (over-clustering) problems. Here we extended our previous read clustering software, SpaRC, by exploiting statistics derived from multiple samples in a dataset to reduce the under-clustering problem. Using synthetic and real-world datasets we demonstrated that this method has the potential to cluster almost all of the short reads from genomes with sufficient sequencing coverage. The improved read clustering in turn leads to improved downstream genome assembly quality.

Background

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising tool for disease modeling and drug development. However, hiPSC-CMs remain functionally immature, which hinders their utility as a model of human cardiomyocytes.

Objective

To improve the electrophysiological maturation of hiPSC-CMs.

Methods and results

On day 16 of cardiac differentiation, hiPSC-CMs were treated with 100 nmol/L triiodothyronine (T3) and 1 μmol/L Dexamethasone (Dex) or vehicle for 14 days. On day 30, vehicle- and T3 + Dex-treated hiPSC-CMs were dissociated and replated either as cell sheets or single cells. Optical mapping and patch-clamp technique were used to examine the electrophysiological properties of vehicle- and T3 + Dex-treated hiPSC-CMs. Compared to vehicle, T3 + Dex-treated hiPSC-CMs had a slower spontaneous beating rate, more hyperpolarized resting membrane potential, faster maximal upstroke velocity, and shorter action potential duration. Changes in spontaneous activity and action potential were mediated by decreased hyperpolarization-activated current (I_f) and increased inward rectifier potassium currents (I_K1), sodium currents (I_Na), and the rapidly and slowly activating delayed rectifier potassium currents (I_Kr and I_Ks, respectively). Furthermore, T3 + Dex-treated hiPSC-CM cell sheets (hiPSC-CCSs) exhibited a faster conduction velocity and shorter action potential duration than the vehicle. Inhibition of I_K1 by 100 μM BaCl₂ significantly slowed conduction velocity and prolonged action potential duration in T3 + Dex-treated hiPSC-CCSs but had no effect in the vehicle group, demonstrating the importance of I_K1 for conduction velocity and action potential duration.

Conclusion

T3 + Dex treatment is an effective approach to rapidly enhance electrophysiological maturation of hiPSC-CMs.

Intervertebral disk degeneration (IVDD) is a spinal disk condition caused by an inflammatory response induced by various proinflammatory cytokines, such as interleukin (IL)-1β and tumor necrosis factor (TNF)-α. cyclin-dependent kinase 9 (CDK9) is a transcriptional regulator and potential therapeutic target for many diseases, especially in regulating the activation of primary inflammatory response genes. Our study investigated a highly selective CDK9 inhibitor, atuveciclib, which protects nucleus pulposus (NP) cells from proinflammatory stimuli-induced catabolism. The effects of CDK9 inhibition were determined in human and rat NP cells treated with IL-1β in the presence or absence of atuveciclib or small interfering RNA target CDK9. Inhibition of CDK9 led to the attenuation of inflammatory response. In addition, rat intervertebral disk (IVD) explants were used to determine the role of CDK9 inhibition in extracellular matrix degradation. The rat IVDD model also proved that CDK9 inhibition attenuated IVDD, as validated using magnetic resonance imaging and immunohistochemistry. Taken together, CDK9 is a potential therapeutic target to prevent IVDD.

Layered graphene oxide membranes (GOM) with densely packed sub-nanometer-wide lamellar channels show exceptional ionic and molecular transport properties. Mass and charge transport in existing materials follows their concentration gradient, whereas attaining anti-gradient transport, also called active transport, remains a great challenge. Here, we demonstrate a coupled photon-electron-ion transport phenomenon through the GOM. Upon asymmetric light illumination, cations are able to move thermodynamically uphill over a broad range of concentrations, at rates much faster than that via simple diffusion. We propose, as a plausible mechanism, that light irradiation reduces the local electric potential on the GOM following a carrier diffusion mechanism. When the illumination is applied to an off-center position, an electric potential difference is built that can drive the transport of ionic species. We further develop photonic ion switches, photonic ion diodes, and photonic ion transistors as the fundamental elements for active ion sieving and artificial photosynthesis on synthetic nanofluidic circuits.

Objectives

Circular RNAs (circRNAs) are noncoding RNAs that compete against other endogenous RNA species, such as microRNAs, and have been implicated in many diseases. In this study, we investigated the role of a new circRNA (circSLC7A2) in osteoarthritis (OA).

Materials and methods

The relative expression of circSLC7A2 was significantly lower in OA tissues than it was in matched controls, as shown by real-time quantitative polymerase chain reaction (RT-qPCR). Western blotting, RT-qPCR and immunofluorescence experiments were employed to evaluate the roles of circSLC7A2, miR-4498 and TIMP3. The in vivo role and mechanism of circSLC7A2 were also conformed in a mouse model.

Results

circSLC7A2 was decreased in OA model and the circularization of circSLC7A2 was regulated by FUS. Loss of circSLC7A2 reduced the sponge of miR-4498 and further inhibited the expression of TIMP3, subsequently leading to an inflammatory response. We further determined that miR-4498 inhibitor reversed circSLC7A2-knockdown-induced OA phenotypes. Intra-articular injection of circSLC7A2 alleviated in vivo OA progression in a mouse model of anterior cruciate ligament transection (ACLT).

Conclusions

The circSLC7A2/miR-4498/TIMP3 axis of chondrocytes catabolism and anabolism plays a critical role in OA development. Our results suggest that circSLC7A2 may serve as a new therapeutic target for osteoarthritis.