A metagenomic comparison of endemic viruses from broiler chickens with runting stunting syndrome and from normal birds

Runting-stunting syndrome (RSS) in broiler chickens is an enteric disease that causes significant economic losses to poultry producers worldwide due to elevated feed conversion ratios, decreased body weight during growth, and excessive culling. Of specific interest are the viral agents associated with RSS which have been difficult to fully characterise to date. Past research into the aetiology of RSS has implicated a wide variety of RNA and DNA viruses however, to date, no individual virus has been identified as the main agent of RSS and the current opinion is that it may be caused by a community of viruses, collectively known as the virome. This paper attempts to characterise the viral pathogens associated with 2 – 3 week old RSS-affected and unaffected broiler chickens using next-generation sequencing and comparative metagenomics. Analysis of the viromes identified a total of 20 DNA & RNA viral families, along with 2 unidentified categories, comprised of 31 distinct viral genera and 7 unclassified genera. The most abundant viral families identified in this study were the Astroviridae, Caliciviridae, Picornaviridae, Parvoviridae, Coronaviridae, Siphoviridae, and Myoviridae. This study has identified historically significant viruses associated with the disease such as chicken astrovirus, avian nephritis virus, chicken parvovirus, and chicken calicivirus along with relatively novel viruses such as chicken megrivirus and sicinivirus 1 and will help expand the knowledge related to enteric disease in broiler chickens, provide insights into the viral constituents of a healthy avian gut, and identify a variety of enteric viruses and viral communities appropriate for further study.

Long-term statin therapy in patients with systolic heart failure and normal cholesterol:effects on elevated serum markers of collagen turnover, inflammation, and B-type natriuretic peptide

BACKGROUND: The role of statin therapy in heart failure (HF) is unclear. The amino-terminal propeptide of procollagen type III (PIIINP) predicts outcome in HF, and yet there are conflicting reports of statin therapy effects on PIIINP.

OBJECTIVES: This study determined whether there was an increase in serum markers of inflammation, fibrosis (including PIIINP), and B-type natriuretic peptide (BNP) in patients with systolic HF and normal total cholesterol and determined the effects of long-term treatment with atorvastatin on these markers.

METHODS: Fifty-six white patients with systolic HF and normal cholesterol levels (age 72 [13] years; 68% male; body mass index 27.0 [7.3] kg/m(2); ejection fraction 35 [13]%; 46% with history of smoking) were randomly allocated to atorvastatin treatment for 6 months, titrated to 40 mg/d (A group) or not (C group). Age- and/or sex-matched subjects without HF (N group) were also recruited. Biomarkers were measured at baseline (all groups) and 6 months (A and C groups).

RESULTS: Serum markers of collagen turnover, inflammation, and BNP were significantly elevated in HF patients compared with normal participants (all P < 0.05). There were correlations between these markers in HF patients but not in normal subjects. Atorvastatin treatment for 6 months caused a significant reduction in the following biomarkers compared with baseline: BNP, from median (interquartile range) 268 (190-441) pg/mL to 185 (144-344) pg/mL; high-sensitivity C-reactive protein (hs-CRP), from 5.26 (1.95 -9.29) mg/L to 3.70 (2.34-6.81) mg/L; and PIIINP, from 4.65 (1.86) to 4.09 (1.25) pg/mL (all P < 0.05 baseline vs 6 months). Between-group differences were significant for PIIINP only (P = 0.027). There was a positive interaction between atorvastatin effects and baseline hs-CRP and PIIINP (P < 0.01).

CONCLUSIONS: Long-term statin therapy reduced PIIINP in this small, selected HF population with elevated baseline levels. Further evaluation of statin therapy in the management of HF patients with elevated PIIINP is warranted.

Insights into the multistep transformation of MGUS to myeloma using microarray expression analysis.

To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.

Massive MIMO with I/Q imbalance: Performance analysis and compensation

In this paper, we consider the uplink of a single-cell massive multiple-input multiple-output (MIMO) system with inphase and quadrature-phase imbalance (IQI). This scenario is of particular importance in massive MIMO systems, where the deployment of lower-cost, lower-quality components is desirable to make massive MIMO a viable technology. Particularly, we investigate the effect of IQI on the performance of massive MIMO employing maximum-ratio combining (MRC) receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that IQI can substantially downgrade the performance of MRC receivers. Moreover, a low-complexity IQI compensation scheme, suitable for massive MIMO, is proposed which is based on the IQI coefficients' estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic achievable rate and providing the asymptotic power scaling laws assuming transmission over Rayleigh fading channels with log-normal large-scale fading. Finally, we show that massive MIMO effectively suppresses the residual IQI effects, as long as, the compensation scheme is applied.

Abnormal Pedestrian Trajectory analysis based on arbitrary-length clustering

This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.