Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p

Lower risk of atopic dermatitis among infants born extremely preterm compared with higher gestational age

International audienceBackground It is not yet known whether the risk of developing atopic dermatitis (AD) is influenced by preterm birth. Moreover, AD risk has not been assessed in a large sample of extremely preterm infants (<29weeks' gestation). Objectives To determine whether the risk of AD is influenced by preterm birth. Methods We investigated the relationship between gestational age (GA) and AD using data from two independent population-based cohorts, including a total of 2329 preterm infants, of whom 479 were born extremely preterm. Results There was a lower percentage of children with AD in the extremely preterm group compared with those born at a greater GA (Epipage cohort, 2-year outcome: 133% for 24-28weeks, 176% for 29-32weeks, 218% for 33-34weeks, P=002; LIFT cohort, 5-year outcome: 11% for 24-28weeks, 215% for 29-32weeks, 196% for 33-34weeks, P=011). After adjusting for confounding variables, a lower GA (<29weeks) was significantly associated with decreased risk of AD in the Epipage cohort [adjusted odds ratio (aOR) 057, 95% confidence interval (CI) 037-087; P=0009] and the LIFT cohort (aOR 041, 95% CI 018-090; P=003). Conclusions Very low GA (<29weeks) was associated with a lower risk of AD compared with higher GA (29-34weeks) and full-term birth

SAW pressure sensor on quartz membrane lapping

National audienceThe fabrication of SAW quartz-based pressure sensors has received a strong interest for many years, yielding various development using either delay lines or resonators. However, most approaches have been developed exploiting quartz machining along standard chemical or mechanical etching, rarely compatible with batch processes as used for Micro-ElectroMechanical Systems (MEMS). In this work, we propose a temperature/pressure sensor fabricated on compound Quartz/Silicon substrates obtained by Au/Au bonding at room temperature and lapping/polishing of Quartz. This approach allows for a collective and accurate production of sensors, the sensor sensitivity being controlled by the membrane thickness and diameter. As the pressure is intricately connected with temperature, an objective estimation of this parameter requires accurate temperature measurements as well. As a consequence, the proposed sensor combines a reference resonator designed to be temperature compensated (AT,X cut of quartz) together with a resonator which propagation direction is chosen according the targeted temperature coefficient of frequency in order to give access to a linear differential temperature measurement. In addition, a third resonator with propagation axis along X is placed at the right center of a circular membrane. When the membrane is bent by pressure effects, the corresponding resonance frequency drifts linearly, allowing for another differential pressure measurement. Hence, with three resonators, one can easily demonstrate the unambiguous determination of temperature and pressure at once. Until now pressure sensor based on SAW with quartz material are unity processed. This process allows us a collective manufacturing of sensors. We start by seal the quartz wafer with the silicon substrate using the thin gold layer. This process yields an homogeneous and high quality bond. It is subsequently thinned and polished to an overall thickness of 100 microns. Aluminum electrodes are deposited on the quartz to achieve three SAW resonators. Process flow based on collective manufacturing is now developed. Electrical responses of SAW resonators are done. Results show the operability of the sensors and the responses are conformed to the design. Electrical test under pressure is currently under development

Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys

In humans, the posterior cingulate cortex contains an area sensitive to visual cues to self-motion. This cingulate sulcus visual area (CSv) is structurally and functionally connected with several (multi)sensory and (pre)motor areas recruited during locomotion. In nonhuman primates, electrophysiology has shown that the cingulate cortex is also related to spatial navigation. Recently, functional MRI in macaque monkeys identified a cingulate area with similar visual properties to human CSv. In order to bridge the gap between human and nonhuman primate research, we examined the structural and functional connectivity of putative CSv in three macaque monkeys adopting the same approach as in humans based on diffusion MRI and resting-state functional MRI. The results showed that putative monkey CSv connects with several visuo-vestibular areas (e.g., VIP/FEFsem/VPS/MSTd) as well as somatosensory cortex (e.g., dorsal aspects of areas 3/1/2), all known to process sensory signals that can be triggered by self-motion. Additionally, strong connections are observed with (pre)motor areas located in the dorsal prefrontal cortex (e.g., F3/F2/F1) and within the anterior cingulate cortex (e.g., area 24). This connectivity pattern is strikingly reminiscent of that described for human CSv, suggesting that the sensorimotor control of locomotion relies on similar organizational principles in human and nonhuman primates

Evaluation of proton density fat fraction (PDFF) obtained from a vendor-neutral MRI sequence and MRQuantif software

International audienceObjectiveTo validate the proton density fat fraction (PDFF) obtained by the MRQuantif software from 2D chemical shift encoded MR (CSE-MR) data in comparison with the histological steatosis data.MethodsThis study, pooling data from 3 prospective studies spread over time between January 2007 and July 2020, analyzed 445 patients who underwent 2D CSE-MR and liver biopsy. MR derived liver iron concentration (MR-LIC) and PDFF was calculated using the MRQuantif software. The histological standard steatosis score (SS) served as reference. In order to get a value more comparable to PDFF, histomorphometry fat fraction (HFF) were centrally determined for 281 patients. Spearman correlation and the Bland and Altman method were used for comparison.ResultsStrong correlations were found between PDFF and SS (r(s) = 0.84, p &lt; 0.001) or HFF (r(s) = 0.87, p &lt; 0.001). Spearman's coefficients increased to 0.88 (n = 324) and 0.94 (n = 202) when selecting only the patients without liver iron overload. The Bland and Altman analysis between PDFF and HFF found a mean bias of 5.4% and PLUSMN; 5.7 [95% CI 4.7, 6.1]. The mean bias was 4.7% and PLUSMN; 3.7 [95% CI 4.2, 5.3] and 7.1% and PLUSMN; 8.8 [95% CI 5.2, 9.0] for the patients without and with liver iron overload, respectively.ConclusionThe PDFF obtained by MRQuantif from a 2D CSE-MR sequence is highly correlated with the steatosis score and very close to the fat fraction estimated by histomorphometry. Liver iron overload reduced the performance of steatosis quantification and joint quantification is recommended. This device-independent method can be particularly useful for multicenter studies