Essential role of Rnd1 in innate immunity during viral and bacterial infections

Intracellular and cell surface pattern-recognition receptors (PRRs) are an essential part of innate immune recognition and host defense. Here, we have compared the innate immune responses between humans and bats to identify a novel membrane-associated protein, Rnd1, which defends against viral and bacterial infection in an interferon-independent manner. Rnd1 belongs to the Rho GTPase family, but unlike other small GTPase members, it is constitutively active. We show that Rnd1 is induced by pro-inflammatory cytokines during viral and bacterial infections and provides protection against these pathogens through two distinct mechanisms. Rnd1 counteracts intracellular calcium fluctuations by inhibiting RhoA activation, thereby inhibiting virus internalisation. On the other hand, Rnd1 also facilitates pro-inflammatory cytokines IL-6 and TNF-α through Plxnb1, which are highly effective against intracellular bacterial infections. These data provide a novel Rnd1-mediated innate defense against viral and bacterial infections.Subject terms: Viral infection, Pattern recognition receptors     

Non-Gated Laser Induced Breakdown Spectroscopy Provides a Powerful Segmentation Tool on Concomitant Treatment of Characteristic and Continuum Emission

We demonstrate the application of non-gated laser induced breakdown spectroscopy (LIBS) for characterization and classification of organic materials with similar chemical composition. While use of such a system introduces substantive continuum background in the spectral dataset, we show that appropriate treatment of the continuum and characteristic emission results in accurate discrimination of pharmaceutical formulations of similar stoichiometry. Specifically, our results suggest that near-perfect classification can be obtained by employing suitable multivariate analysis on the acquired spectra, without prior removal of the continuum background. Indeed, we conjecture that pre-processing in the form of background removal may introduce spurious features in the signal. Our findings in this report significantly advance the prior results in time-integrated LIBS application and suggest the possibility of a portable, non-gated LIBS system as a process analytical tool, given its simple instrumentation needs, real-time capability and lack of sample preparation requirements.     

Signals from the edges: The cortical hem and antihem in telencephalic development

The early cortical primordium develops from a sheet of neuroepithelium that is flanked by distinct signaling centers. Of these, the hem and the antihem are positioned as longitudinal stripes, running rostro-caudally along the medial and lateral faces, respectively, of each telencepahlic hemisphere. In this review we examine the similarities and differences in how these two signaling centers arise, their roles in patterning adjacent tissues, and the cells and structures they contribute to. Since both the hem and the antihem have been identified across many vertebrate phyla, they appear to be part of an evolutionary conserved set of mechanisms that play fundamental roles in forebrain development.     

Structure and Dynamics of ER: Minimal Networks and Biophysical Constraints

The endoplasmic reticulum (ER) in live cells is a highly mobile network whose structure dynamically changes on a number of timescales. The role of such drastic changes in any system is unclear, although there are correlations with ER function. A better understanding of the fundamental biophysical constraints on the system will allow biologists to determine the effects of molecular factors on ER dynamics. Previous studies have identified potential static elements that the ER may remodel around. Here, we use these structural elements to assess biophysical principles behind the network dynamics. By analyzing imaging data of tobacco leaf epidermal cells under two different conditions, i.e., native state (control) and latrunculin B (treated), we show that the geometric structure and dynamics of ER networks can be understood in terms of minimal networks. Our results show that the ER network is well modeled as a locally minimal-length network between the static elements that potentially anchor the ER to the cell cortex over longer timescales; this network is perturbed by a mixture of random and deterministic forces. The network need not have globally minimum length; we observe cases where the local topology may change dynamically between different Euclidean Steiner network topologies. The networks in the treated cells are easier to quantify, because they are less dynamic (the treatment suppresses actin dynamics), but the same general features are found in control cells. Using a Langevin approach, we model the dynamics of the nonpersistent nodes and use this to show that the images can be used to estimate both local viscoelastic behavior of the cytoplasm and filament tension in the ER network. This means we can explain several aspects of the ER geometry in terms of biophysical principles.     

Deciphering the assembly pathway of Sm-class U snRNPs

The assembly of the Sm-class of uridine-rich small nuclear ribonucleoproteins (U snRNPs), albeit spontaneous in vitro, has recently been shown to be dependent on the aid of a large number of assisting factors in vivo. These factors are organized in two interacting units termed survival motor neuron (SMN)- and protein arginine methyltransferase 5 (PRMT5)-complexes, respectively. While the PRMT5-complex acts early in the assembly pathway by activating common proteins of U snRNPs, the SMN-complex functions to join proteins and RNA in a highly ordered, apparently regulated manner. Here, we summarize recent progress in the understanding of this process and discuss the influence exerted by the aforementioned trans-acting factors.     

Lack of change in urate deposition by dual-energy computed tomography among clinically stable patients with long-standing tophaceous gout: a prospective longitudinal study

Introduction

Dual-energy computed tomography (DECT) has potential for monitoring urate deposition in patients with gout. The aim of this prospective longitudinal study was to analyse measurement error of DECT urate volume measurement in clinically stable patients with tophaceous gout.

Methods

Seventy-three patients with tophaceous gout on stable therapy attended study visits at baseline and twelve months. All patients had a comprehensive clinical assessment including serum urate testing and DECT scanning of both feet. Two readers analysed the DECT scans for the total urate volume in both feet. Analysis included inter-reader intraclass correlation coefficients (ICCs) and limits of agreement, and calculation of the smallest detectable change.

Results

Mean (standard deviation) serum urate concentration over the study period was 0.38 (0.09) mmol/L. Urate-lowering therapy was prescribed in 70 (96%) patients. The median (interquartile range) baseline DECT urate volume was 0.49 (0.16, 2.18) cm³, and change in DECT urate volume was -0.01 (-0.40, 0.28) cm³. Inter-reader ICCs were 1.00 for baseline DECT volumes and 0.93 for change values. Inter-reader bias (standard deviation) for baseline volumes was -0.18 (0.63) cm³ and for change was -0.10 (0.93) cm³. The smallest detectable change was 0.91 cm³. There were 47 (64%) patients with baseline DECT urate volumes <0.91 cm³. Higher serum urate concentrations were observed in patients with increased DECT urate volumes above the smallest detectable change (P = 0.006). However, a relationship between changes in DECT urate volumes and serum urate concentrations was not observed in the entire group.

Conclusions

In patients with tophaceous gout on stable conventional urate-lowering therapy the measurement error for DECT urate volume assessment is substantially greater than the median baseline DECT volume. Analysis of patients commencing or intensifying urate-lowering therapy should clarify the optimal use of DECT as a potential outcome measure in studies of chronic gout.     

Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records

To reduce costs and improve clinical relevance of genetic studies, there has been increasing interest in performing such studies in hospital-based cohorts by linking phenotypes extracted from electronic medical records (EMRs) to genotypes assessed in routinely collected medical samples. A fundamental difficulty in implementing such studies is extracting accurate information about disease outcomes and important clinical covariates from large numbers of EMRs. Recently, numerous algorithms have been developed to infer phenotypes by combining information from multiple structured and unstructured variables extracted from EMRs. Although these algorithms are quite accurate, they typically do not provide perfect classification due to the difficulty in inferring meaning from the text. Some algorithms can produce for each patient a probability that the patient is a disease case. This probability can be thresholded to define case–control status, and this estimated case–control status has been used to replicate known genetic associations in EMR-based studies. However, using the estimated disease status in place of true disease status results in outcome misclassification, which can diminish test power and bias odds ratio estimates. We propose to instead directly model the algorithm-derived probability of being a case. We demonstrate how our approach improves test power and effect estimation in simulation studies, and we describe its performance in a study of rheumatoid arthritis. Our work provides an easily implemented solution to a major practical challenge that arises in the use of EMR data, which can facilitate the use of EMR infrastructure for more powerful, cost-effective, and diverse genetic studies.     

Nanoparticulate systems for polynucleotide delivery

Nanotechnology has tremendously influenced gene therapy research in recent years. Nanometer-size systems have been extensively investigated for delivering genes at both local and systemic levels. These systems offer several advantages in terms of tissue penetrability, cellular uptake, systemic circulation, and cell targeting as compared to larger systems. They can protect the polynucleotide from a variety of degradative and destabilizing factors and enhance delivery efficiency to the cells. A variety of polymeric and non-polymeric nanoparticles have been investigated in an effort to maximize the delivery efficiency while minimizing the toxic effects. This article provides a review on the most commonly used nanoparticulate systems for gene delivery. We have discussed frequently used polymers, such as, polyethyleneimine, poly (lactide-co-glycolide), chitosan, as well as non-polymeric materials such as cationic lipids and metallic nanoparticles. The advantages and limitations of each system have been elaborated.