R&D modes and firm performance in high-tech companies: A research based on cross-boundary ambidexterity and network structures

This paper draws on the cross-boundary ambidexterity theory to propose that four different R&D modes impact firm performance differently and that cooperative network structure moderates the above relationships. The theoretical model is tested by using financial and patent data of 587 high-tech firms for 10 consecutive years in China. We find that different R&D modes have different impacts on a firm’s financial and innovative performance, and network structure plays different moderating roles. Practically, this work guides high-tech enterprises to optimize their resource allocation, select the most appropriate R&D mode, and establish efficient cooperative networks

The Stock-Bond Comovements and Cross-Market Trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock-bond return comovements and the changing market conditions. Agents’ collective investment behavior shapes the stock-bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty

The Stock-Bond Comovements and Cross-Market Trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock-bond return comovements and the changing market conditions. Agents’ collective investment behavior shapes the stock-bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty

Integrated analysis of long non-coding RNAs and mRNAs associated with glaucoma in vitro

IntroductionIn recent years, the biological functions and important roles of long non-coding RNAs (lncRNAs) have been widely reported in many diseases. Although glaucoma is the leading cause of blindness worldwide, the specific mechanisms of lncRNAs in the pathogenesis and progression of glaucoma remain unclear. Our research aims to elucidate the differentially expressed lncRNAs and mRNAs in glaucoma and to provide a basis for further exploration of the specific mechanism of action of lncRNAs in the progression of glaucoma.MethodsWe performed RNA sequencing on samples from a pressurized model of R28 cells and performed bioinformatics analyses on the sequencing results. The expression consistency of lncRNAs in clinical samples from patients with glaucoma or cataracts was detected using real-time quantitative polymerase chain reaction (RT-qPCR).ResultsRNA sequencing results showed that lncRNAs in cluster 5 were upregulated with increasing stress after typing all significantly altered lncRNAs using k-means in a cellular stress model. KEGG analysis indicated that they were associated with neurodegenerative diseases. Differentially expressed lncRNAs were verified by RT-qPCR, and the lncRNA expression levels of AC120246.2 and XLOC_006247 were significantly higher in the aqueous humor (AH) of patients with glaucoma than in those with cataracts. For LOC102551819, there was almost no expression in the AH and trabecular meshwork in patients with glaucoma but high expression was observed in the iris. ConclusionOur research proposes potential diagnostic or intervention targets for clinical applications as well as a theoretical basis for more in-depth research on the function of lncRNAs in glaucoma

Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

Schizophrenia (SCZ) is a polygenic disease with a heritability approaching 80%. Over 100 SCZ-related loci have so far been identified by genome-wide association studies (GWAS). However, the risk genes associated with these loci often remain unknown. We present a new risk gene predictor, rGAT-omics, that integrates multi-omics data under a Bayesian framework by combining the Hotelling and Box–Cox transformations. The Bayesian framework was constructed using gene ontology, tissue-specific protein–protein networks, and multi-omics data including differentially expressed genes in SCZ and controls, distance from genes to the index single-nucleotide polymorphisms (SNPs), and de novo mutations. The application of rGAT-omics to the 108 loci identified by a recent GWAS study of SCZ predicted 103 high-risk genes (HRGs) that explain a high proportion of SCZ heritability (Enrichment = 43.44 and p=9.30×10−9). HRGs were shown to be significantly (padj=5.35×10−7) enriched in genes associated with neurological activities, and more likely to be expressed in brain tissues and SCZ-associated cell types than background genes. The predicted HRGs included 16 novel genes not present in any existing databases of SCZ-associated genes or previously predicted to be SCZ risk genes by any other method. More importantly, 13 of these 16 genes were not the nearest to the index SNP markers, and them would have been difficult to identify as risk genes by conventional approaches while ten out of the 16 genes are associated with neurological functions that make them prime candidates for pathological involvement in SCZ. Therefore, rGAT-omics has revealed novel insights into the molecular mechanisms underlying SCZ and could provide potential clues to future therapies

Small-Signal Stability Analysis for Droop-Controlled Inverter-based Microgrids with Losses and Filtering

An islanded microgrid supplied by multiple distributed energy resources (DERs) often employs droop-control mechanisms for power sharing. Because microgrids do not include inertial elements, and low pass filtering of noisy measurements introduces lags in control, droop-like controllers may pose significant stability concerns. This paper aims to understand the effects of droop-control on the small-signal stability and transient response of the microgrid. Towards this goal, we present a compendium of results on the small-signal stability of droop-controlled inverter-based microgrids with heterogeneous loads, which distinguishes: (1) lossless vs. lossy networks; (2) droop mechanisms with and without filters, and (3) mesh vs. radial network topologies. Small-signal and transient characteristics are also studied using multiple simulation studies on IEEE test system

Foregut microbiome in development of esophageal adenocarcinoma

Esophageal adenocarcinoma (EA), the type of cancer linked to heartburn due to gastroesophageal reflux diseases (GERD), has increased six fold in the past 30 years. This cannot currently be explained by the usual environmental or by host genetic factors. EA is the end result of a sequence of GERD-related diseases, preceded by reflux esophagitis (RE) and Barrett’s esophagus (BE). Preliminary studies by Pei and colleagues at NYU on elderly male veterans identified two types of microbiotas in the esophagus. Patients who carry the type II microbiota are >15 fold likely to have esophagitis and BE than those harboring the type I microbiota. In a small scale study, we also found that 3 of 3 cases of EA harbored the type II biota. The findings have opened a new approach to understanding the recent surge in the incidence of EA. 

Our long-term goal is to identify the cause of GERD sequence. The hypothesis to be tested is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in GERD sequence. We will conduct a case control study to demonstrate the microbiome disease association in every stage of GERD sequence, as well as analyze the trend in changes in the microbiome along disease progression toward EA, by two specific aims. Aim 1 is to conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence. Furthermore, spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Aim 2 is to define the distal esophageal metagenome and demonstrate its association with GERD sequence. Detailed analyses will include pathway-disease and gene-disease associations. Archaea, fungi and viruses, if identified, also will be correlated with the diseases. A significant association between the foregut microbiome and GERD sequence, if demonstrated, will be the first step for eventually testing whether an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiota through use of antibiotics, probiotics, or prebiotics. Causative therapy of GERD could prevent its progression and reverse the current trend of increasing incidence of EA

Mechanism of Regulation of Big-Conductance Ca2+-Activated K+ Channels by mTOR Complex 2 in Podocytes

Podocytes, dynamic polarized cells wrapped around glomerular capillaries, are an essential component of the glomerular filtration barrier. BK channels consist of one of the slit diaphragm (SD) proteins in podocytes, interact with the actin cytoskeleton, and play vital roles in glomerular filtration. Mechanistic target of rapamycin (mTOR) complexes regulate expression of SD proteins, as well as cytoskeleton structure, in podocytes. However, whether mTOR complexes regulate podocyte BK channels is still unclear. Here, we investigated the mechanism of mTOR complex regulation of BK channels via real-time PCR, western blot, immunofluorescence, and patch clamping. Inhibiting mTORC1 with rapamycin or downregulating Raptor had no significant effect on BK channel mRNA and protein levels and bioactivity. However, the dual inhibitor of mTORC1 and mTORC2 AZD8055 and short hairpin RNA targeting Rictor downregulated BK channel mRNA and protein levels and bioactivity. In addition, MK2206, GF109203X, and GSK650394, which are inhibitors of Akt, PKCα, and SGK1, respectively, were employed to test the downstream signaling pathway of mTORC2. MK2206 and GF109203X had no effect on BK channel protein levels. MK2206 caused an obvious decrease in the current density of the BK channels. Moreover, GSK650394 downregulated the BK channel protein and mRNA levels. These results indicate mTORC2 not only regulates the distribution of BK channels through Akt, but also modulates BK channel protein expression via SGK1 in podocytes