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Tanzania’s child mortality rate—between 103 and 130 deaths per 1000 live births–is well above the world average. The data from the Tanzania HIV/AIDS and Malaria Indicator Survey 2007/08 were used in order. There were 27,511 children included in the analysis. Regression analysis focused on child mortality based on maternal and fertility behaviours. Children belonging to the group of higher birth order faced 0.17 odds of dying. A birth spacing of 24 months or longer was observed in the successive birth interval for 76% of the respondents. Focusing on the study’s findings, encouraging longer breastfeeding practice is one way to help produce a healthy baby. [ABSTRACT FROM AUTHOR]

Background We have recently shown by formally modelling human protein interaction networks (PINs) as metric spaces and classified proteins into zones based on their distance from the topological centre that hub proteins are primarily centrally located. We also showed that zones closest to the network centre are enriched for critically important proteins and are also functionally very specialised for specific 'house keeping' functions. We proposed that proteins closest to the network centre may present good therapeutic targets. Here, we present multiple pieces of novel functional evidence that provides strong support for this hypothesis. Results We found that the human PINs has a highly connected signalling core, with the majority of proteins involved in signalling located in the two zones closest to the topological centre. The majority of essential, disease related, tumour suppressor, oncogenic and approved drug target proteins were found to be centrally located. Similarly, the majority of proteins consistently expressed in 13 types of cancer are also predominantly located in zones closest to the centre. Proteins from zones 1 and 2 were also found to comprise the majority of proteins in key KEGG pathways such as MAPK-signalling, the cell cycle, apoptosis and also pathways in cancer, with very similar patterns seen in pathways that lead to cancers such as melanoma and glioma, and non-neoplastic diseases such as measles, inflammatory bowel disease and Alzheimer's disease. Conclusions Based on the diversity of evidence uncovered, we propose that when considered holistically, proteins located centrally in the human PINs that also have similar functions to existing drug targets are good candidate targets for novel therapeutics. Similarly, since disease pathways are dominated by centrally located proteins, candidates shortlisted in genome scale disease studies can be further prioritized and contextualised based on whether they occupy central positions in the human PINs. [ABSTRACT FROM AUTHOR]

The pursuit to identify vertex-transitive non-Cayley graphs has been deliberate for some time now. In that vein, Alspach and Parsons [1] introduced metacirculant graphs. They are defined on two cyclic groups with adjacency resembling twisting that is typically used in defining semi-direct products of groups. In this sequel we generalise the construction to general groups and introduce a class of graphs we call meta-Cayley graphs. [ABSTRACT FROM PUBLISHER]

Abstract: Having presented layered hierarchies of symmetry of vertex-transitive graphs by exploring various classes of algebraic systems, in this note we extend the class of generalised Petersen graphs into higher dimensions and show which ones are Cayley and quasi-Cayley. [Copyright &y& Elsevier]

Background In the post-genomic era, a central and overarching question in the analysis of protein-protein interaction networks continues to be whether biological characteristics and functions of proteins such as lethality, physiological malfunctions and malignancy are intimately linked to the topological role proteins play in the network as a mathematical structure. One of the key features that have implicitly been presumed is the existence of hubs, highly connected proteins considered to play a crucial role in biological networks. We explore the structure of protein interaction networks of a number of organisms as metric spaces and show that hubs are non randomly positioned and, from a distance point of view, centrally located. Results By analysing how the human functional protein interaction network, the human signalling network, Saccharomyces cerevisiae, Arabidopsis thaliana and Escherichia coli protein-protein networks from various databases are distributed as metric spaces, we found that proteins interact radially through a central node, high degree proteins coagulate in the centre of the network, and those far away from the centre have low degree. We further found that the distribution of proteins from the centre is in some hierarchy of importance and has biological significance. Conclusions We conclude that structurally, protein interaction networks are mathematical entities that share properties between organisms but not necessarily with other networks that follow power-law. We therefore conclude that (i) if there are hubs defined by degree, they are not distributed randomly; (ii) zones closest to the centre of the network are enriched for critically important proteins and are also functionally very specialised for specific 'house keeping' functions); (iii) proteins closest to the network centre are functionally less dispensable and may present good targets for therapy development; and (iv) network biology requires its own network theory modelled on actual biological evidence and that simply adopting theories from the social sciences may be misleading. [ABSTRACT FROM AUTHOR]

For any prime p, we consider p-ary linear codes obtained from the row span of incidence matrices of line graphs of triangular graphs and adjacency matrices of their line graphs. We determine parameters of the codes, their automorphism groups and exhibit permutation decoding sets (PD-sets) for partial permutation decoding. [ABSTRACT FROM AUTHOR]

The successful determination of reliable protein interaction networks (PINs) in several species in the post-genomic era has hitherto facilitated the quest to understanding systems and structural properties of such networks. It is envisaged that a clearer understanding of their intrinsic topological properties would elucidate evolutionary and biological topography of organisms. This, in turn, may inform the understanding of diseases' aetiology. By analysing sub-networks that are induced in various layers identified by zones defined as distance from central proteins, we show that zones of human PINs display self-similarity patterns. What is observed at a global level is repeated at lower levels of inducement. Furthermore, it is observed that these levels of strength point to refinement and specialisations in these layers. This may point to the fact that various levels of representations in the self-similarity phenomenon offer a way of measuring and distinguishing the importance of proteins in the network. To consolidate our findings, we have also considered a gene co-expression network and a class of gene regulatory networks in the same framework. In all cases, the phenomenon is significantly evident. In particular, the truly unbiased regulatory networks show finer level of articulation of self-similarity. [ABSTRACT FROM AUTHOR]