A bovine model of a respiratory Parachlamydia acanthamoebae infection.

The aim of this study was to evaluate the pathogenicity of Parachlamydia (P.) acanthamoebae as a potential agent of lower respiratory tract disease in a bovine model of induced lung infection. Intrabronchial inoculation with P. acanthamoebae was performed in healthy calves aged 2-3 months using two challenge doses: 10(8) and 10(10) bacteria per animal. Controls received 10(8) heat-inactivated bacteria. Challenge with 10(8) viable Parachlamydia resulted in a mild degree of general indisposition, whereas 10(10) bacteria induced a more severe respiratory illness becoming apparent 1-2 days post inoculation (dpi), affecting 9/9 (100%) animals and lasting for 6 days. The extent of macroscopic pulmonary lesions was as high as 6.6 (6.0)% [median (range)] of lung tissue at 2-4 dpi and correlated with parachlamydial genomic copy numbers detected by PCR, and with bacterial load estimated by immunohistochemistry in lung tissue. Clinical outcome, acute phase reactants, pathological findings and bacterial load exhibited an initial dose-dependent effect on severity. Animals fully recovered from clinical signs of respiratory disease within 5 days. The bovine lung was shown to be moderately susceptible to P. acanthamoebae, exhibiting a transient pneumonic inflammation after intrabronchial challenge. Further studies are warranted to determine the precise pathophysiologic pathways of host-pathogen interaction.

Reduction of respiratory motion artifacts for free-breathing whole-heart coronary MRA by weighted iterative reconstruction.

PURPOSE: To combine weighted iterative reconstruction with self-navigated free-breathing coronary magnetic resonance angiography for retrospective reduction of respiratory motion artifacts. METHODS: One-dimensional self-navigation was improved for robust respiratory motion detection and the consistency of the acquired data was estimated on the detected motion. Based on the data consistency, the data fidelity term of iterative reconstruction was weighted to reduce the effects of respiratory motion. In vivo experiments were performed in 14 healthy volunteers and the resulting image quality of the proposed method was compared to a navigator-gated reference in terms of acquisition time, vessel length, and sharpness. RESULT: Although the sampling pattern of the proposed method contained 60% more samples with respect to the reference, the scan efficiency was improved from 39.5 ± 10.1% to 55.1 ± 9.1%. The improved self-navigation showed a high correlation to the standard navigator signal and the described weighting efficiently reduced respiratory motion artifacts. Overall, the average image quality of the proposed method was comparable to the navigator-gated reference. CONCLUSION: Self-navigated coronary magnetic resonance angiography was successfully combined with weighted iterative reconstruction to reduce the total acquisition time and efficiently suppress respiratory motion artifacts. The simplicity of the experimental setup and the promising image quality are encouraging toward future clinical evaluation. Magn Reson Med 73:1885-1895, 2015. © 2014 Wiley Periodicals, Inc.

Role of rhinovirus load in the upper respiratory tract and severity of symptoms in lung transplant recipients.

BACKGROUND: Rhinovirus is the most common cause of respiratory viral infections and leads to frequent respiratory symptoms in lung transplant recipients. However, it remains unknown whether the rhinovirus load correlates with the severity of symptoms. OBJECTIVES: This study aimed to better characterize the pathogenesis of rhinoviral infection and the way in which viral load correlates with symptoms. STUDY DESIGN: We assessed rhinovirus load in positive upper respiratory specimens of patients enrolled prospectively in a cohort of 116 lung transplant recipients. Rhinovirus load was quantified according to a validated in-house, real-time, reverse transcription polymerase chain reaction in pooled nasopharyngeal and pharyngeal swabs. Symptoms were recorded in a standardised case report form completed at each screening/routine follow-up visit, or during any emergency visit occurring during the 3-year study. RESULTS: Rhinovirus infections were very frequent, including in asymptomatic patients not seeking a specific medical consultation. Rhinovirus load ranged between 4.1 and 8.3 log copies/ml according to the type of visit and clinical presentation. Patients with highest symptom scores tended to have higher viral loads, particularly those presenting systemic symptoms. When considering symptoms individually, rhinovirus load was significantly higher in the presence of symptoms such as sore throat, fever, sputum production, cough, and fatigue. There was no association between tacrolimus levels and rhinovirus load. CONCLUSIONS: Rhinovirus infections are very frequent in lung transplant recipients and rhinoviral load in the upper respiratory tract is relatively high even in asymptomatic patients. Patients with the highest symptom scores tend to have a higher rhinovirus load.

Horizontal transfer of exosomal microRNAs transduce apoptotic signals between pancreatic beta-cells.

BACKGROUND: Diabetes mellitus is a common metabolic disorder characterized by dysfunction of insulin-secreting pancreatic beta-cells. MicroRNAs are important regulators of beta-cell activities. These non-coding RNAs have recently been discovered to exert their effects not only inside the cell producing them but, upon exosome-mediated transfer, also in other recipient cells. This novel communication mode remains unexplored in pancreatic beta-cells. In the present study, the microRNA content of exosomes released by beta-cells in physiological and physiopathological conditions was analyzed and the biological impact of their transfer to recipient cells investigated. RESULTS: Exosomes were isolated from the culture media of MIN6B1 and INS-1 derived 832/13 beta-cell lines and from mice, rat or human islets. Global profiling revealed that the microRNAs released in MIN6B1 exosomes do not simply reflect the content of the cells of origin. Indeed, while a subset of microRNAs was preferentially released in exosomes others were selectively retained in the cells. Moreover, exposure of MIN6B1 cells to inflammatory cytokines changed the release of several microRNAs. The dynamics of microRNA secretion and their potential transfer to recipient cells were next investigated. As a proof-of-concept, we demonstrate that if cel-miR-238, a C. Elegans microRNA not present in mammalian cells, is expressed in MIN6B1 cells a fraction of it is released in exosomes and is transferred to recipient beta-cells. Furthermore, incubation of untreated MIN6B1 or mice islet cells in the presence of microRNA-containing exosomes isolated from the culture media of cytokine-treated MIN6B1 cells triggers apoptosis of recipient cells. In contrast, exosomes originating from cells not exposed to cytokines have no impact on cell survival. Apoptosis induced by exosomes produced by cytokine-treated cells was prevented by down-regulation of the microRNA-mediating silencing protein Ago2 in recipient cells, suggesting that the effect is mediated by the non-coding RNAs. CONCLUSIONS: Taken together, our results suggest that beta-cells secrete microRNAs that can be transferred to neighboring beta-cells. Exposure of donor cells to pathophysiological conditions commonly associated with diabetes modifies the release of microRNAs and affects survival of recipient beta-cells. Our results support the concept that exosomal microRNAs transfer constitutes a novel cell-to-cell communication mechanism regulating the activity of pancreatic beta-cells.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.

Impact of the Spanish smoking control law on exposure to second-hand smoke and respiratory health in hospitality workers: a cohort study

A smoke-free law came into effect in Spain on 1st January 2006, affecting all enclosed workplaces except hospitality venues, whose proprietors can choose among totally a smoke-free policy, a partial restriction with designated smoking areas, or no restriction on smoking on the premises. We aimed to evaluate the impact of the law among hospitality workers by assessing second-hand smoke (SHS) exposure and the frequency of respiratory symptoms before and one year after the ban.