Strong Structural Controllability and Zero Forcing

In this chapter, we study controllability and output controllability of systems defined over graphs. Specifically, we consider a family of state-space systems, where the state matrix of each system has a zero/non-zero structure that is determined by a given directed graph. Within this setup, we investigate under which conditions all systems in this family are controllable, a property referred to as strong structural controllability. Moreover, we are interested in conditions for strong structural output controllability. We will show that the graph-theoretic concept of zero forcing is instrumental in these problems. In particular, as our first contribution, we prove necessary and sufficient conditions for strong structural controllability in terms of so-called zero forcing sets. Second, we show that zero forcing sets can also be used to state both a necessary and a sufficient condition for strong structural output controllability. In addition to these main results, we include interesting results on the controllability of subfamilies of systems and on the problem of leader selection.</p

Quantifying resilience of humans and other animals

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of micro-recoveries observed in natural time series. Such dynamic indicators of resilience (DIORs) may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethink of our approach to the adaptive management of health and resilience

Specific gut microbial, biological, and psychiatric profiling related to binge eating disorders: A cross-sectional study in obese patients

Background & aimsBinge eating disorder (BED) is a frequent eating disorder associated with obesity and co-morbidities including psychiatric pathologies, which represent a big health burden on the society.The biological processes related to BED remain unknown. Based on psychological testing, anthropometry, clinical biology, gut microbiota analysis and metabolomic assessment, we aimed to examine the complex biological and psychiatric profile of obese patients with and without BED.MethodsPsychological and biological characteristics (anthropometry, plasma biology, gut microbiota, blood pressure) of 101 obese subjects from the Food4Gut cohort were analysed to decipher the differences between BED and Non BED patients, classified based on the Questionnaire for Eating Disorder Diagnosis (Q-EDD). Microbial 16S rDNA sequencing and plasma non-targeted metabolomics (liquid chromatography-mass spectrometry) were performed in a subcohort of 91 and 39 patients respectively.ResultsBED subjects exhibited an impaired affect balance, deficits in inhibition and self-regulation together with marked alterations of eating behaviour (increased emotional and external eating). BED subjects displayed a lower blood pressure and hip circumference. A decrease in Akkermansia and Intestimonas as well as an increase in Bifidobacterium and Anaerostipes characterized BED subjects. Interestingly, metabolomics analysis revealed that BED subjects displayed a higher level of one food contaminants, Bisphenol A bis(2,3-dihydroxypropyl) ether (BADGE.2H(2)O) and a food derived-metabolite the Isovalerylcarnitine.ConclusionsNon-targeted omics approaches allow to select specific microbial genera and two plasma metabolites that characterize BED obese patients. Further studies are needed to confirm their potential role as drivers or biomarkers of binge eating disorder

Model-based assessment of mammalian cell metabolic functionalities using omics data.

Omics experiments are ubiquitous in biological studies, leading to a deluge of data. However, it is still challenging to connect changes in these data to changes in cell functions because of complex interdependencies between genes, proteins, and metabolites. Here, we present a framework allowing researchers to infer how metabolic functions change on the basis of omics data. To enable this, we curated and standardized lists of metabolic tasks that mammalian cells can accomplish. Genome-scale metabolic networks were used to define gene sets associated with each metabolic task. We further developed a framework to overlay omics data on these sets and predict pathway usage for each metabolic task. We demonstrated how this approach can be used to quantify metabolic functions of diverse biological samples from the single cell to whole tissues and organs by using multiple transcriptomic datasets. To facilitate its adoption, we integrated the approach into GenePattern (www.genepattern.org-CellFie)

Sparse Matrix Factorizations for Fast Linear Solvers with Application to Laplacian Systems

In solving a linear system with iterative methods, one is usually confronted with the dilemma of having to choose between cheap, ineffcient iterates over sparse search directions (e.g., coordinate descent), or expensive iterates in well-chosen search directions (e.g., conjugate gradients). In this paper, we propose to interpolate between these two extremes, and show how to perform cheap iterations along nonsparse search directions, provided that these directions can be extracted from a new kind of sparse factorization. For example, if the search directions are the columns of a hierarchical matrix, then the cost of each iteration is typically logarithmic in the number of variables. Using some graph-Theoretical results on low-stretch spanning trees, we deduce as a special case a nearly linear time algorithm to approximate the minimal norm solution of a linear system Bx = b where B is the incidence matrix of a graph. We thereby can connect our results to recently proposed nearly linear time solvers for Laplacian systems, which emerge here as a particular application of our sparse matrix factorization

Muscle fat infiltration in obese patients is associated with NAFLD related fibrosis severity - results from a prospective imaging study

Background and aims: The association between NAFLD and visceral adipose tissue or sarcopenia has been reported, although results are discordant. The goal of this study is to analyze the spectrum of NAFLD among obese patients recruited prospectively and to detect clinical, biological and imaging data associated with steatosis or fibrosis. Methods: Baseline data of obese patients (BMI ≥ 30) randomized in a single center (Food4Gut study) were recorded. Transient elastography (TE) was done to quantify both liver steatosis by controlled attenuation parameter (CAP) measurement and liver fibrosis by liver stiffness measurement (LSM). Body composition was evaluated using bioelectrical impedance analysis. Subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), muscle areas and muscle fat infiltration (MFI) were measured on CT-scan images at the third lumbar level. Results Fifty-two Caucasian patients (mean age: 50 years, 50 % male, mean BMI 35.8) were included. TE was successful in 49 patients (94%). XL probe was used in 20 patients (38%). Mean LSM was low (6.5 kPa). Mean CAP result was high (324 dB/m) with the majority of the patients (73%) presenting severe steatosis (CAP ≥ 296 dB/m). 12 patients (24%) had advanced fibrosis defined by LSM ≥ 7.8 kPa (M probe) or ≥ 6.4 kPa (XL probe). Factors associated with severe steatosis and advanced fibrosis are summarized in the table. Interestingly, severe steatosis was associated with higher muscle quantity and severe fibrosis with a lower muscle density index, compatible with MFI. In a multivariate logistic regression analysis, MFI was the strongest predictor of advanced liver fibrosis. Conclusion In summary, among obese patients, a high proportion of severe steatosis was diagnosed and advanced liver fibrosis was suspected in 24% of the patients. MFI provides a robust, skeletal muscle-specific characteristic linked to advanced fibrosis in NAFLD, suggesting a muscle-liver axis in the pathogenesis of NAFLD complications

Landslide susceptibility assessment in Limbe (SW Cameroon) : a field calibrated seed cell and information value method

The dissected volcanic terrains around Limbe, SW Cameroon are frequently affected by small scale but destructive landslides. In this study, a raster-based data driven method involving seed cells is used to build a landslide susceptibility model for the Limbe area. Factors considered to be potential controls of slope failure within this area include slope gradient, rock type, distance from roads, slope orientation, mean annual precipitation, soil type, land cover type, stream density and distance from stream. 63 small to very small translational and rotational landslide scars were identified through extensive field work. Landslide data is randomly divided into a training (75%) and validation set (25%) and seed cells are generated by creating 25 m buffer zones around the head scarp of each scar. The quantitative relationship between landslide seed cells and the above-mentioned factors is established by a data driven approach to obtain weighted factor classes. Summing weighted factor layers, a continuous scale of susceptibility indices is obtained and reclassified into 5 susceptibility classes. Seed cells obtained from the validation data set were used to evaluate the quality of several models involving different controlling factors. Our preferred model combines the weight of 6 factors (i.e. slope gradient, land cover, mean annual precipitation, stream density, proximity to roads and slope orientation). 78% of the validation seed cells are located within the high to very high susceptibility class, which occupy 16.9% of the study area. The obtained susceptibility map is combined with the outline of urban areas and key infrastructures to evaluate zones that are vulnerable to the impact of future slope failures. Such an approach will assist civil protection and urban planning efforts in SW Cameroon

Lower abundance of Clostridium sensu stricto is associated with liver steatosis and fibrosis severity in a prospective cohort of obese patients with metabolic dysfunction-associated fatty liver disease

Introduction: There is an increasing evidence for the role of the gut microbiota in the pathogenesis of obesity, insulin resistance and metabolic dysfunction-associated fatty liver disease (MAFLD). Deciphering the bacterial signature associated with liver alterations would be interesting as a new indicator for MAFLD pathogenesis. Aim: Here, we describe the microbiome composition of a cohort of obese patients well characterized for MAFLD severity (i.e. steatosis and fibrosis degree) and link them with other obesity-related extra-hepatic alterations. Methods: Obese patients recruited prospectively at St-Luc Hospital (FOOD4GUT project) were included. Liver stiffness (LSM) and controlled attenuation parameter (CAP) measurements were performed using liver transient elastography (TE). Physical examination, blood and stool samples and computed tomography (CT) were also assessed. The fecal gut microbiota was analyzed by Illumina sequencing of the 16S rRNA gene. Results: Stool samples were available for 37 patients. Liver TE allowed us to classify the patients in three groups based on CAP and LSM: LS (low steatosis defined as CAP < 296 dB/m, n=10), HS (high steatosis defined as CAP ≥ 296 dB/m, n=18) and HS+F (high steatosis + fibrosis defined as CAP ≥ 296 dB/m and LSM ≥ 7.8 kPa with M probe or ≥ 6.4 kPa with XL probe, n=9). Both α- and β- diversity indices of the overall gut microbiota composition were not different between the three groups. Moreover, no changes in the gut microbiota composition were observed at the phylum level between the three groups. At the taxa level, only Clostridium sensu stricto significantly decreased with the severity of liver steatosis and fibrosis (p=0.021 for HS+F vs HS and p=0.002 for HS+F vs LS). Microbes discriminant for liver alterations were determined through a pairwise comparison using linear discriminant analysis effect size (LEfSe) analysis. For the LS-HS comparison, Flavonifractor and Faecalibacterium are more represented in the HS group. Regarding the HS and HS+F comparison, we interestingly found that Clostridium sensu stricto characterized the HS group (without fibrosis) whereas Escherichia/Shigella are more represented in the gut microbiota from subjects with fibrosis. An analysis based on amplicon sequence variants (ASV) revealed 19 bacterial sequences significantly affected according to liver steatosis and/or fibrosis. Among them, Spearman’s correlations showed that C. sensu stricto was significantly negatively associated with LSM, CAP, the waist to hip ratio and muscle fat infiltration evaluated by muscle density on CT. Conclusions: Our study allowed us to elaborate the link between MAFLD severity and extra-hepatic alterations incriminating adiposity, skeletal muscle dysfunction and the gut microbiome. We identified Clostridium sensu stricto as the only genus decreasing with the development of steatosis and fibrosis. This genus also negatively correlated abdominal adiposity and muscle fat infiltration. Those data suggest a gut-liver-muscle axis in the pathogenesis of MAFLD complications