PCR-DGGE fingerprints of microbial successional changes during fermentation of cereal-legume weaning foods

Phenotypic identification and monitoring of the dynamics of naturally occurring microbial community responsible for the spontaneous fermentation of different cereal-legume weaning blends was carriedout. Enumeration using culture-dependent method showed that cell counts increased within the first 24 h with the highest total viable count of 1.2 x 1012 cfu g-1 in maize-legume (1A) blend. Yeast countsincreased drastically and no enterobacteria were observed within the first 24 h. At all fermentation times, acidity increased within 48 h and lowest pH value (3.60) was reached in maize–based blend. Phenotypic identification revealed that the isolated bacteria belong to the genera Bacillus species, Staphylococcus aureus, and Escherichia coli. The yeast isolates were identified as Saccharomyces cerevisiae, Saccharomyces species and Hansenula species while Lactobacillus plantarum and Pediococcus acidilactici were the predominant lactic acid bacteria (LAB). The analysis of the denaturing gradient gel electrophoresis (DGGE) pattern obtained with bacterial and LAB primers targeting the V3 region of the 16S rDNA genes clearly demonstrated that there was a major shift in the communitystructure within the first 24 h

Beyond clustering: mean-field dynamics on networks with arbitrary subgraph composition

Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher than expected frequency of triangles, and this has led to the principle of constructing networks from such building blocks. This approach has been generalised to networks being constructed from a set of more exotic subgraphs. As long as these are fully connected, it is then possible to derive mean-field models that approximate epidemic dynamics well. However, there are virtually no results for non-fully connected subgraphs. In this paper, we provide a general and automated approach to deriving a set of ordinary differential equations, or mean-field model, that describes, to a high degree of accuracy, the expected values of system-level quantities, such as the prevalence of infection. Our approach offers a previously unattainable degree of control over the arrangement of subgraphs and network characteristics such as classical node degree, variance and clustering. The combination of these features makes it possible to generate families of networks with different subgraph compositions while keeping classical network metrics constant. Using our approach, we show that higher-order structure realised either through the introduction of loops of different sizes or by generating networks based on different subgraphs but with identical degree distribution and clustering, leads to non-negligible differences in epidemic dynamics

Edge-Based Compartmental Modeling for Infectious Disease Spread Part III: Disease and Population Structure

We consider the edge-based compartmental models for infectious disease spread introduced in Part I. These models allow us to consider standard SIR diseases spreading in random populations. In this paper we show how to handle deviations of the disease or population from the simplistic assumptions of Part I. We allow the population to have structure due to effects such as demographic detail or multiple types of risk behavior the disease to have more complicated natural history. We introduce these modifications in the static network context, though it is straightforward to incorporate them into dynamic networks. We also consider serosorting, which requires using the dynamic network models. The basic methods we use to derive these generalizations are widely applicable, and so it is straightforward to introduce many other generalizations not considered here

Gut Microbial Changes, Interactions, and Their Implications on Human Lifecycle: An Ageing Perspective.

Gut microbiota is established during birth and evolves with age, mostly maintaining the commensal relationship with the host. A growing body of clinical evidence suggests an intricate relationship between the gut microbiota and the immune system. With ageing, the gut microbiota develops significant imbalances in the major phyla such as the anaerobic Firmicutes and Bacteroidetes as well as a diverse range of facultative organisms, resulting in impaired immune responses. Antimicrobial therapy is commonly used for the treatment of infections; however, this may also result in the loss of normal gut flora. Advanced age, antibiotic use, underlying diseases, infections, hormonal differences, circadian rhythm, and malnutrition, either alone or in combination, contribute to the problem. This nonbeneficial gastrointestinal modulation may be reversed by judicious and controlled use of antibiotics and the appropriate use of prebiotics and probiotics. In certain persistent, recurrent settings, the option of faecal microbiota transplantation can be explored. The aim of the current review is to focus on the establishment and alteration of gut microbiota, with ageing. The review also discusses the potential role of gut microbiota in regulating the immune system, together with its function in healthy and diseased state

Danger Invariants

Static analysers search for overapproximating proofs of safety commonly known as safety invariants. Conversely, static bug finders (e.g. Bounded Model Checking) give evidence for the failure of an assertion in the form of a counterexample trace. As opposed to safety invariants, the size of a counterexample is dependent on the depth of the bug, i.e., the length of the execution trace prior to the error state, which also determines the computational effort required to find them. We propose a way of expressing danger proofs that is independent of the depth of bugs. Essentially, such danger proofs constitute a compact representation of a counterexample trace, which we call a danger invariant. Danger invariants summarise sets of traces that are guaranteed to be able to reach an error state. Our conjecture is that such danger proofs will enable the design of bug finding analyses for which the computational effort is independent of the depth of bugs, and thus find deep bugs more efficiently. As an exemplar of an analysis that uses danger invariants, we design a bug finding technique based on a synthesis engine. We implemented this technique and compute danger invariants for intricate programs taken from SV-COMP 2016

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and the Netherlands using respondent-driven sampling

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand

Gut Microbial Changes, Interactions, and Their Implications on Human Lifecycle: An Ageing Perspective

Gut microbiota is established during birth and evolves with age, mostly maintaining the commensal relationship with the host. A growing body of clinical evidence suggests an intricate relationship between the gut microbiota and the immune system. With ageing, the gut microbiota develops significant imbalances in the major phyla such as the anaerobic Firmicutes and Bacteroidetes as well as a diverse range of facultative organisms, resulting in impaired immune responses. Antimicrobial therapy is commonly used for the treatment of infections; however, this may also result in the loss of normal gut flora. Advanced age, antibiotic use, underlying diseases, infections, hormonal differences, circadian rhythm, and malnutrition, either alone or in combination, contribute to the problem. This nonbeneficial gastrointestinal modulation may be reversed by judicious and controlled use of antibiotics and the appropriate use of prebiotics and probiotics. In certain persistent, recurrent settings, the option of faecal microbiota transplantation can be explored. The aim of the current review is to focus on the establishment and alteration of gut microbiota, with ageing. The review also discusses the potential role of gut microbiota in regulating the immune system, together with its function in healthy and diseased state

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

On the gauge boson's properties in a candidate technicolor theory

The technicolor scenario replaces the Higgs sector of the standard model with a strongly interacting sector. One candidate for a realization of such a sector is two-technicolor Yang-Mills theory coupled to two degenerate flavors of adjoint, massless techniquarks. Using lattice gauge theory the properties of the technigluons in this scenario are investigated as a function of the techniquark mass towards the massless limit. For that purpose the minimal Landau gauge two-point and three-point correlation functions are determined, including a detailed systematic error analysis. The results are, within the relatively large systematic uncertainties, compatible with a behavior very similar to QCD at finite techniquark mass. However, the limit of massless techniquarks exhibits features which could be compatible with a (quasi-)conformal behavior.Comment: 27 pages, 17 figures, 1 table; v2: persistent notational error corrected, some minor modification