Vagus nerve stimulation: State of the art of stimulation and recording strategies to address autonomic function neuromodulation

International audienceObjective. Neural signals along the vagus nerve (VN) drive many somatic and autonomic functions. The clinical interest of VN stimulation (VNS) is thus potentially huge and has already been demonstrated in epilepsy. However, side effects are often elicited, in addition to the targeted neuromodulation. Approach. This review examines the state of the art of VNS applied to two emerging modulations of autonomic function: heart failure and obesity, especially morbid obesity. Main results. We report that VNS may benefit from improved stimulation delivery using very advanced technologies. However, most of the results from fundamental animal studies still need to be demonstrated in humans

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Algorithms for metabolic pathway discovery and analysis in the human microbiome

The human microbiome is a good source of natural products and other types of small molecules that can profoundly affect human homeostasis. In the last decade, several studies have elucidated and characterized the presence of certain metabolites at relevant concentrations, which, given their role in microbe-microbe and microbe-host interactions, can be used as biological markers. The molecules that are known to date can be classified into two major groups based on their function; the ones that are involved in energy metabolism or primary metabolism and the ones used for protection against biotic and abiotic stresses that derive from bacterial secondary metabolism. Examples of specialized primary metabolites are indole and trimethylamine (TMA). Indole, which is derived from tryptophan and is the precursor of indoxyl sulfate, has been associated with a decrease in bacterial pathogenicity when found at high concentrations. TMA in contrast, is synthesized from carnitine or choline and is a marker for cardiovascular diseases. Oftentimes, the genes responsible for the synthesis of these molecules are clustered together in the genome, in loci also known as metabolic gene clusters (MGCs) or more specifically, biosynthetic gene clusters (BGCs) when they are responsible for secondary metabolite biosynthesis.Given the evidence that the production of specialized primary metabolites is encoded in metabolic gene clusters and that these metabolites have an important role in microbe-microbe and microbe-host interactions, the aim of this thesis is to provide new tools to functionally profile the human microbiome. This implies designing different methods not only to predict such MGCs, but also to assess the taxonomic distribution and architectural diversity of MGCs, and correlate their co-abundance and co-expression patterns in samples with specific phenotypes to better comprehend the roles they play in these complex ecosystems. Ultimately, the objective is to make use of all these tools and apply them to real datasets from public repositories, in order to make significant leaps in our understanding of the molecular mechanisms behind microbially derived phenotypic traits.The thesis has five different chapters that attempt to fill the gaps in knowledge in different research areas having, with as a central point the analysis and prediction of gene clusters.In Chapter 2, the antiSMASH database version 2 is introduced. The database was provided with an updated infrastructure that stores compressed information of BGCs from a diverse bacterial genome collection chosen using average nucleotide identity on a large set of publicly available genomes to remove redundant ones. This database is a comprehensive resource that allows to perform cross-genome searches. In Chapter 3, we highlight the usefulness of phylogenomics to uncover putative gene clusters reinforcing the accumulating evidence that large numbers of MGCs exist that encode yet-unknown metabolic pathways. Hence, this chapter shows a prospective potential to elucidate novel pathways and therefore how can help to functionally annotate novel genes. Based on this principle and tackling the need within the field to metabolically profile the gut microbiome, we built gutSMASH (Chapter 4). This is a new tool that not only allows to systematically profile specialized primary MGCs and bioenergetics-related gene clusters from anaerobes but also putative MGCs, which represent good candidates with unknown function to study further. Moreover, we also designed the gutSMASH web server, a user-friendly platform that allows any researcher without bioinformatic background to run their analysis (Chapter 5). Finally, since analysing single “omic” layers (e.g. genomic functional potential) provides limited ability to fully establish causation between microbiome host-pheno- types, we designed BiG-MAP (Chapter 6). This tool represents a step forward to combine different omics data and obtain more biological insights at different molecular levels. More specifically, BiG-MAP allows to profile gene clusters’ abundance and expression patterns that can ultimately help identify which gene clusters are most likely involved in conferring phenotypes of interest and prioritize them for further experimental characterization.&nbsp

Vortex force decomposition—forces associated with individual elements of a vorticity field

The impulse theory used to calculate the force from a vorticity distribution in two-dimensional, incompressible flow, is re-cast with the aim of approximating, to a first order, the forces generated by a specific flow feature, such as a free vortex passing by an object. To achieve this, the force acting on the body is split up into several core contributions. The first component arises from the time variation of the body’s boundary layer. The second is generated by the advection of any free vorticity located in the flowfield by the object’s boundary layer vorticity. The final force contribution is due to new vorticity being shed. To test the theory, it is applied to two multi-body flowfields consisting of a circular cylinder and a flat plate wing at incidence in close proximity. Force balance measurements and planar particle image velocimetry data are simultaneously obtained at Reynolds numbers of 10000 and 20000. The forces acting on the cylinder are successfully recovered from the vorticity data using the derived formulation, verifying its accuracy. Subsequently, the proposed force formulation is used to create force heat maps that demonstrate how the location of a leading edge vortex affects its force contribution around a pitching NACA-0021 wing translating at a Reynolds number of 10000

Immunité et allergie (les allergènes en odonto-stomatologie)

TOULOUSE3-BU Santé-Centrale (315552105) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Computational genomic discovery of diverse gene clusters harbouring Fe-S flavoenzymes in anaerobic gut microbiota

The gut contains an enormous diversity of simple as well as complex molecules from highly diverse food sources, together with host-secreted molecules. This presents a large metabolic opportunity for the gut microbiota, but little is known about how gut microbes are able to catabolize this large chemical diversity. Recently, Fe-S flavoenzymes were found to be key in the transformation of bile acids, catalysing the key step in the 7α-dehydroxylation pathway that allows gut bacteria to transform cholic acid into deoxycholic acid, an exclusively microbe-derived molecule with major implications for human health. While this enzyme family has also been implicated in a limited number of other catalytic transformations, little is known about the extent to which it is of more global importance in gut microbial metabolism. Here, we perform a large-scale computational genomic analysis to show that this enzyme superfamily has undergone a remarkable expansion in Clostridiales, and occurs throughout a diverse array of >1000 different families of putative metabolic gene clusters. Analysis of the enzyme content of these gene clusters suggests that they encode pathways with a wide range of predicted substrate classes, including saccharides, amino acids/peptides and lipids. Altogether, these results indicate a potentially important role of this protein superfamily in the human gut, and our dataset provides significant opportunities for the discovery of novel pathways that may have significant effects on human health.</p

Simulation and Detection of Some Properties of Hybrid System Based Differential Predicate-Transition Petri Nets by Means of VHDL-AMS

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