JMassBalance: mass-balanced randomization and analysis of metabolic networks

Summary: Analysis of biological networks requires assessing the statistical significance of network-based predictions by using a realistic null model. However, the existing network null model, switch randomization, is unsuitable for metabolic networks, as it does not include physical constraints and generates unrealistic reactions. We present JMassBalance, a tool for mass-balanced randomization and analysis of metabolic networks. The tool allows efficient generation of large sets of randomized networks under the physical constraint of mass balance. In addition, various structural properties of the original and randomized networks can be calculated, facilitating the identification of the salient properties of metabolic networks with a biologically meaningful null model

The impact of primary health care and specialist physician supply on amenable mortality in Mexico (2000–2015): Panel data analysis using system-Generalized Method of Moments

The study had a three-fold objective: (i) to estimate the amenable mortality rates and trends at a national and state level between 2000 and 2015 in Mexico; (ii) to estimate the contribution and trends of various causes of death to overall amenable mortality; and (iii) to determine the association between health system inputs and amenable mortality for the period 2000–2015. We used a panel dataset for the period 2000–2015. The following health care inputs were used in the analysis: density of general practitioners, specialists and nurses, as well as density of hospital beds. We find that amenable mortality fell from 136 per 100,000 in 2000, to 124.1 per 100,000 in 2015 nationally, with significant heterogeneity in the trends across states. Mortality due to infectious diseases, diseases of childhood, and cardiovascular diseases decreased, while deaths due to other non-communicable diseases, such as diabetes, increased. There was a significant negative association between the density of general practitioners and specialist physicians, and amenable mortality. Our results indicate that reducing the burden of non-communicable diseases must be a health system priority. Improvements in primary health care could lead to improved disease detection and earlier diagnosis which could further reduce amenable mortality in Mexico

Integrative Comparative Analyses of Transcript and Metabolite Profiles from Pepper and Tomato Ripening and Development Stages Uncovers Species-Specific Patterns of Network Regulatory Behavior

Integrative comparative analyses of transcript and metabolite levels from climacteric and nonclimacteric fruits can be employed to unravel the similarities and differences of the underlying regulatory processes. To this end, we conducted combined gas chromatography-mass spectrometry and heterologous microarray hybridization assays in tomato (Solanum lycopersicum; climacteric) and pepper (Capsicum chilense; nonclimacteric) fruits across development and ripening. Computational methods from multivariate and network-based analyses successfully revealed the difference between the covariance structures of the integrated data sets. Moreover, our results suggest that both fruits have similar ethylene-mediated signaling components; however, their regulation is different and may reflect altered ethylene sensitivity or regulators other than ethylene in pepper. Genes involved in ethylene biosynthesis were not induced in pepper fruits. Nevertheless, genes downstream of ethylene perception such as cell wall metabolism genes, carotenoid biosynthesis genes, and the never-ripe receptor were clearly induced in pepper as in tomato fruit. While signaling sensitivity or actual signals may differ between climacteric and nonclimacteric fruit, the evidence described here suggests that activation of a common set of ripening genes influences metabolic traits. Also, a coordinate regulation of transcripts and the accumulation of key organic acids, including malate, citrate, dehydroascorbate, and threonate, in pepper fruit were observed. Therefore, the integrated analysis allows us to uncover additional information for the comprehensive understanding of biological events relevant to metabolic regulation during climacteric and nonclimacteric fruit development

Patient Choice of Health Care Providers in China: Primary Care Facilities versus Hospitals

As China’s health system is faced with challenges of overcrowded hospitals, there is a great need to better understand the recent patterns and determinants of people’s choice between primary care facilities and hospitals for outpatient care. Based on recent individual-level data from the China Health and Retirement Longitudinal Survey (CHARLS) and official province-level data from China health statistical yearbooks, we examine the patterns of outpatient visits to primary care facilities versus hospitals among middle-aged and older individuals and explore both supply- and demand-side correlates that explain these patterns. We find that 53% of outpatient visits were paid to primary care facilities as opposed to hospitals in 2015, compared to 60% in 2011. Both supply and demand factors were associated with this decline. On the supply side, we find that the density of primary care facilities did not account for this decline, but higher densities of hospitals and licensed doctors were associated with lower use of primary care facilities. On the demand side, we find that individuals with higher socioeconomic status and greater health care needs were less likely to use primary health care facilities. Our findings suggest that a high concentration of health care professionals in hospitals diverts patients away from primary care facilities. Staffing the primary care facilities with a well-trained health care workforce is the key to a well-functioning primary care system. The findings also suggest a need to address demand-side inequality issues

Enhance the Efficiency of Heuristic Algorithm for Maximizing Modularity Q

Modularity Q is an important function for identifying community structure in complex networks. In this paper, we prove that the modularity maximization problem is equivalent to a nonconvex quadratic programming problem. This result provide us a simple way to improve the efficiency of heuristic algorithms for maximizing modularity Q. Many numerical results demonstrate that it is very effective.Comment: 9 pages, 3 figure

Probabilistic Inductive Classes of Graphs

Models of complex networks are generally defined as graph stochastic processes in which edges and vertices are added or deleted over time to simulate the evolution of networks. Here, we define a unifying framework - probabilistic inductive classes of graphs - for formalizing and studying evolution of complex networks. Our definition of probabilistic inductive class of graphs (PICG) extends the standard notion of inductive class of graphs (ICG) by imposing a probability space. A PICG is given by: (1) class B of initial graphs, the basis of PICG, (2) class R of generating rules, each with distinguished left element to which the rule is applied to obtain the right element, (3) probability distribution specifying how the initial graph is chosen from class B, (4) probability distribution specifying how the rules from class R are applied, and, finally, (5) probability distribution specifying how the left elements for every rule in class R are chosen. We point out that many of the existing models of growing networks can be cast as PICGs. We present how the well known model of growing networks - the preferential attachment model - can be studied as PICG. As an illustration we present results regarding the size, order, and degree sequence for PICG models of connected and 2-connected graphs.Comment: 15 pages, 6 figure

Size reduction of complex networks preserving modularity

The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.Comment: 14 pages, 2 figure

Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

Introduction: To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism. Objective: This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues. Methods: The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses. Results: Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism. Conclusions: Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.Fil: Nunes Nesi, Adriano. Max Planck Institute Of Molecular Plant Physiology; Alemania. Universidade Federal de Viçosa.; BrasilFil: Alseekh, Saleh. Center Of Plant Systems Biology And Biotechnology; Bulgaria. Max Planck Institute Of Molecular Plant Physiology; AlemaniaFil: de Oliveira Silva, Franklin Magnum. Universidade Federal de Viçosa.; BrasilFil: Omranian, Nooshin. Max Planck Institute Of Molecular Plant Physiology; Alemania. Center Of Plant Systems Biology And Biotechnology; BulgariaFil: Lichtenstein, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Mirnezhad, Mohammad. Leiden University; Países BajosFil: Romero González, Roman R.. Leiden University; Países BajosFil: Sabio y Garcia, Julia Veronica. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Conte, Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Leiss, Kirsten A.. Leiden University; Países BajosFil: Klinkhamer, Peter G. L.. Leiden University; Países BajosFil: Nikoloski, Zoran. University of Potsdam; Alemania. Max Planck Institute of Molecular Plant Physiology; AlemaniaFil: Carrari, Fernando Oscar. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Fernie, Alisdair R.. Max Planck Institute of Molecular Plant Physiology; Alemania. Center of Plant System Biology and Biotechnology; Bulgari