Specific Immunoassays Confirm Association of Mycobacterium avium Subsp. paratuberculosis with Type-1 but Not Type-2 Diabetes Mellitus

Mycobacterium avium subspecies paratuberculosis (MAP) is a versatile pathogen with a broad host range. Its association with type-1 diabetes mellitus (T1DM) has been recently proposed. Rapid identification of infectious agents such as MAP in diabetic patients at the level of clinics might be helpful in deciphering the role of chronic bacterial infection in the development of autoimmune diseases such as T1DM.We describe use of an ELISA method to identify live circulating MAP through the detection of a cell envelope protein, MptD by a specific M13 phage--fMptD. We also used another ELISA format to detect immune response to MptD peptide. Both the methods were tested with blood plasma obtained from T1DM, type-2 diabetes (T2DM) patients and non-diabetic controls. Our results demonstrate MptD and fMptD ELISA assays to be accurate and sensitive to detect MAP bacilli in a large fraction (47.3%) of T1DM patients as compared to non-diabetic controls (12.6%) and those with confirmed T2DM (7.7%). Comparative analysis of ELISA assays performed here with 3 other MAP antigen preparations, namely HbHA, Gsd and whole cell MAP lysates confirmed comparable sensitivity of the MptD peptide and the fMptD based ELISA assays. Moreover, we were successful in demonstrating positive bacterial culture in two of the clinical specimen derived from T1DM patients.The MptD peptide/fMptD based ELISA or similar tests could be suggested as rapid and specific field level diagnostic tests for the identification of MAP in diabetic patients and for finding the explanations towards the occurrence of type-1 or type-2 diabetes in the light of an active infectious trigger

Consistency of aortic distensibility and pulse wave velocity estimates with respect to the Bramwell-Hill theoretical model: a cardiovascular magnetic resonance study

<p>Abstract</p> <p>Background</p> <p>Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance (CMR) data.</p> <p>Results</p> <p>Forty-six healthy subjects underwent carotid-femoral pulse wave velocity measurements (<it>CF_PWV</it>) by applanation tonometry and CMR with steady-state free-precession and phase contrast acquisitions at the level of the aortic arch. These data were used for the automated evaluation of the aortic arch pulse wave velocity (<it>Arch_PWV</it>), and the ascending aorta distensibility (<it>AA_Distc, AA_Distb)</it>, which were estimated from ascending aorta strain (<it>AA_Strain</it>) combined with either carotid or brachial pulse pressure. The local ascending aorta pulse wave velocity <it>AA_PWVc </it>and <it>AA_PWVb </it>were estimated respectively from these carotid and brachial derived distensibility indices according to the Bramwell-Hill theoretical model, and were compared with the <it>Arch_PWV</it>. In addition, a reproducibility analysis of <it>AA_PWV </it>measurement and its comparison with the standard <it>CF_PWV </it>was performed. Characterization according to the Bramwell-Hill equation resulted in good correlations between <it>Arch_PWV </it>and both local distensibility indices <it>AA_Distc </it>(r = 0.71, p < 0.001) and <it>AA_Distb </it>(r = 0.60, p < 0.001); and between <it>Arch_PWV </it>and both theoretical local indices <it>AA_PWVc </it>(r = 0.78, p < 0.001) and <it>AA_PWVb </it>(r = 0.78, p < 0.001). Furthermore, the <it>Arch_PWV </it>was well related to <it>CF_PWV </it>(r = 0.69, p < 0.001) and its estimation was highly reproducible (inter-operator variability: 7.1%).</p> <p>Conclusions</p> <p>The present work confirmed the consistency and robustness of the regional index <it>Arch_PWV </it>and the local indices <it>AA_Distc and AA_Distb </it>according to the theoretical model, as well as to the well established measurement of <it>CF_PWV</it>, demonstrating the relevance of the regional and local CMR indices.</p

The inv dup (15) or idic (15) syndrome (Tetrasomy 15q)

The inv dup(15) or idic(15) syndrome displays distinctive clinical findings represented by early central hypotonia, developmental delay and intellectual disability, epilepsy, and autistic behaviour. Incidence at birth is estimated at 1 in 30,000 with a sex ratio of almost 1:1. Developmental delay and intellectual disability affect all individuals with inv dup(15) and are usually moderate to profound. Expressive language is absent or very poor and often echolalic. Comprehension is very limited and contextual. Intention to communicate is absent or very limited. The distinct behavioral disorder shown by children and adolescents has been widely described as autistic or autistic-like. Epilepsy with a wide variety of seizure types can occur in these individuals, with onset between 6 months and 9 years. Various EEG abnormalities have been described. Muscle hypotonia is observed in almost all individuals, associated, in most of them, with joint hyperextensibility and drooling. Facial dysmorphic features are absent or subtle, and major malformations are rare. Feeding difficulties are reported in the newborn period

The energy–diversity relationship of complex bacterial communities in Arctic deep-sea sediments

The availability of nutrients and energy is a main driver of biodiversity for plant and animal communities in terrestrial and marine ecosystems, but we are only beginning to understand whether and how energy–diversity relationships may be extended to complex natural bacterial communities. Here, we analyzed the link between phytodetritus input, diversity and activity of bacterial communities of the Siberian continental margin (37–3427 m water depth). Community structure and functions, such as enzymatic activity, oxygen consumption and carbon remineralization rates, were highly related to each other, and with energy availability. Bacterial richness substantially increased with increasing sediment pigment content, suggesting a positive energy–diversity relationship in oligotrophic regions. Richness leveled off, forming a plateau, when mesotrophic sites were included, suggesting that bacterial communities and other benthic fauna may be structured by similar mechanisms. Dominant bacterial taxa showed strong positive or negative relationships with phytodetritus input and allowed us to identify candidate bioindicator taxa. Contrasting responses of individual taxa to changes in phytodetritus input also suggest varying ecological strategies among bacterial groups along the energy gradient. Our results imply that environmental changes affecting primary productivity and particle export from the surface ocean will not only affect bacterial community structure but also bacterial functions in Arctic deep-sea sediment, and that sediment bacterial communities can record shifts in the whole ocean ecosystem functioning

DNA methylation and methyl-CpG binding proteins: developmental requirements and function

DNA methylation is a major epigenetic modification in the genomes of higher eukaryotes. In vertebrates, DNA methylation occurs predominantly on the CpG dinucleotide, and approximately 60% to 90% of these dinucleotides are modified. Distinct DNA methylation patterns, which can vary between different tissues and developmental stages, exist on specific loci. Sites of DNA methylation are occupied by various proteins, including methyl-CpG binding domain (MBD) proteins which recruit the enzymatic machinery to establish silent chromatin. Mutations in the MBD family member MeCP2 are the cause of Rett syndrome, a severe neurodevelopmental disorder, whereas other MBDs are known to bind sites of hypermethylation in human cancer cell lines. Here, we review the advances in our understanding of the function of DNA methylation, DNA methyltransferases, and methyl-CpG binding proteins in vertebrate embryonic development. MBDs function in transcriptional repression and long-range interactions in chromatin and also appear to play a role in genomic stability, neural signaling, and transcriptional activation. DNA methylation makes an essential and versatile epigenetic contribution to genome integrity and function

Toward an improved representation of middle atmospheric dynamics thanks to the ARISE project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the "Automatic Cardiac Diagnosis Challenge" dataset (ACDC), the largest publicly available and fully annotated dataset for the purpose of cardiac MRI (CMR) assessment. The dataset contains data from 150 multi-equipments CMRI recordings with reference measurements and classification from two medical experts. The overarching objective of this paper is to measure how far state-of-the-art deep learning methods can go at assessing CMRI, i.e., segmenting the myocardium and the two ventricles as well as classifying pathologies. In the wake of the 2017 MICCAI-ACDC challenge, we report results from deep learning methods provided by nine research groups for the segmentation task and four groups for the classification task. Results show that the best methods faithfully reproduce the expert analysis, leading to a mean value of 0.97 correlation score for the automatic extraction of clinical indices and an accuracy of 0.96 for automatic diagnosis. These results clearly open the door to highly accurate and fully automatic analysis of cardiac CMRI. We also identify scenarios for which deep learning methods are still failing. Both the dataset and detailed results are publicly available online, while the platform will remain open for new submissions