Protein interaction networks define the genetic architecture of preterm birth

The likely genetic architecture of complex diseases is that subgroups of patients share variants in genes in specific networks sufficient to express a shared phenotype. We combined high throughput sequencing with advanced bioinformatic approaches to identify such subgroups of patients with variants in shared networks. We performed targeted sequencing of patients with 2 or 3 generations of preterm birth on genes, gene sets and haplotype blocks that were highly associated with preterm birth. We analyzed the data using a multi-sample, protein–protein interaction (PPI) tool to identify significant clusters of patients associated with preterm birth. We identified shared protein interaction networks among preterm cases in two statistically significant clusters, p < 0.001. We also found two small control-dominated clusters. We replicated these data on an independent, large birth cohort. Separation testing showed significant similarity scores between the clusters from the two independent cohorts of patients. Canonical pathway analysis of the unique genes defining these clusters demonstrated enrichment in inflammatory signaling pathways, the glucocorticoid receptor, the insulin receptor, EGF and B-cell signaling, These results support a genetic architecture defined by subgroups of patients that share variants in genes in specific networks and pathways which are sufficient to give rise to the disease phenotype.

SHARED NETWORKS: THE PATHS OF LATIN-CENTRIC INDIGENOUS NETWORKS TO A PLURIVERSAL INTERNET

This research paper examines the emergence of shared networks in Tseltal and Zapoteco communities in Chiapas and Oaxaca (Mexico): internet first mile signal-sharing practices that articulate interconnection infrastructure and coexistence values to extend the internet to areas where the services of existing larger internet service providers are unsatisfactory or unavailable. In the case studies analyzed, indigenous people become internet codesigners by infrastructuring for their own local networks and interconnecting to the global internet. The paper argues that a hybrid materializes at the level of network interconnection when comunalidad, or the way of these communities, supported by unlicensed frequencies of the electromagnetic spectrum, towers, radio antennas, houses rooftops, routers, and cables meet the values of the internet service providers and their policies. Shared networks are a result of what these arrangements both enact and constrain, and the evidence of vivid struggles of Latin-centric indigenous networks towards a pluriversal internet.

A Secure Anonymous D2D Mutual Authentication and Key Agreement Protocol for IoT Environments

Internet of Things (IoT) is a developing technology in our time that is prone to security problems as it uses wireless and shared networks. A challenging scenario in IoT environments is Device-to-Device (D2D) communication that an authentication server as a trusted third-party, does not involve in the authentication and key agreement process. It is only involved in the process of allocating long-term secret keys and their update. A lot of authentication protocols have been suggested for such situations. This article demonstrated that three state-of-the-art related protocols failed to remain anonymous, insecure against key compromise impersonation (KCI) attack, and clogging attack. To counter the pitfalls of them, a new D2D mutual authentication and key agreement protocol is designed here. The proposed protocol is anonymous, untraceable, and highly secure. Moreover, there is no need for a secure channel to generate a pair of private and public keys in the registration phase.) Formal security proof and security analysis using BAN logic, Real-Or-Random (ROR) model, and Scyther tool showed that our proposed protocol satisfied security requirements. Furthermore, communication cost, computation cost, and energy consumption comparisons denoted our schema has better performance, compared to other protocols.

Toward Just-in-Time Data Communications over Shared Networks and Computational Resources on Massive Client Environment

Intelligent driving has been benefiting from advances in automotive big data analysis and on-demand data communications, where efficient vehicle-to-cloud communication is a key technology able to collect a huge amount of data from vehicles. However, as the capacities of the network and computational resources of the cloud are not unlimited, simultaneous data transfer based on a best-effort manner results in a resource starvation problem. Therefore, an application is needed to prioritize data communication to alleviate the problem and complete the data transfer just in time. This paper highlights the problem of resource starvation led by best-effort data transfers. It proposes protocols for data communication and control that could enable just-in-time data communication, notably for data collection. We demonstrate through experiments that the proposed mechanism enables efficient and effective data collection over the shared network resources.

Integrated Protein Network Analysis of Whole Exome Sequencing Study of Severe Preeclampsia

To identify clusters of patients with shared networks of genes associated with early onset severe preeclampsia from whole exome sequencing data through novel bioinformatic analysis.We performed a case-control study using whole exome sequencing (WES) on early onset preeclamptic mothers with severe features delivering < 34 weeks and mothers who delivered ≥ 37 weeks. Genotype testing identified variants that were differentially abundant between cases and controls. A Protein-Protein interaction (PPI) analysis and visualization tool, Proteinarium, was implemented to identify clusters of patients with shared networks associated with severe preeclampsia.A total of 61 early onset preeclamptic women with severe features and 82 race and ethnicity matched control women at term were sequenced. We identified 8,867 predicted deleterious variants. 21 of these variants were nominally associated with preeclampsia by genotype testing. Using Proteinarium129 out of the 143 sequenced patients were assigned to statistically significant clusters, Cluster A and B (p< 0.0001). Case dominated Cluster A contained 47 of the 61 case subjects. There were 13 unique genes in the PPI network of Cluster A compared to control dominated Cluster B. Amongst these unique genes, LAMB2, PTK2, RAC1, QSOX1, FN1, and VCAM1 have known associations with the pathogenic mechanisms of preeclampsia.Our network analysis identified genes that were unique to a large cluster of patients with shared networks that provide insights for severe preeclampsia. We also identified genes imputed from the interactome that may otherwise have not been identified by conventional analysis. Strict phenotyping of both cases and controls improved the likelihood of identifying these otherwise difficult to find genetic associations. These uniquely identified genes and their associated variants are potential candidates for developing polygenic risk scores for severe preeclampsia. These results support our hypothesis on the genetic architecture of complex diseases and are generalizable to other phenotypes.

Not a home: Shelter families living in Canadian motels

Given the precarity and mobility of neoliberalism, there has been increasing interest into constructs of ‘home’. In this article, the author defines ‘home’ as an active and relational process encompassing interactions between materiality and immateriality. Participant observation research conducted amongst shelter families in Toronto, Canada, living in motels can shed light on some of these larger global conversations about what ‘home’ is, and particularly, what it is not. These motels are utilized as part of the City of Toronto Shelter, Support and Housing Administration providing free shelter to impoverished families in need. Social workers, shelter managers and local faith group volunteers assert that the motels should be considered ‘home’ and the problem is that the women living in the motels with their children treat the physical space as transitory. In contrast, the women assert that the motel space is not a home and can never be made into one. The author argues that for these women, there are three critical elements missing in the motel: control over space, safety/security and privacy. The assertion that the motel space is not a home is a significant form of resistance to the regulatory bureaucratic structuring of daily life. However, despite this absence of home, the women feel strong identification as mothers and have formed systems of informal shared networks. This research helps to further illuminate not only our understandings of ‘home’, but also deepen and complicate normative associations equating ‘home’ with physical structure, domesticity and family.

Protein Interaction Networks Define the Genetic Architecture of Preterm Birth

Rather than pathogenic variants in single genes, the likely genetic architecture of complex diseases is that subgroups of patients share variants in genes in specific networks and pathways sufficient to give rise to a shared phenotype. We combined high throughput sequencing with advanced bioinformatic approaches to identify subgroups of patients with shared networks and pathways associated with preterm birth (PTB). We previously identified genes, gene sets and haplotype blocks that were highly associated with preterm birth. We performed targeted sequencing on these genes and genomic regions on highly phenotyped patients with 2 or 3 generations of preterm birth, and term controls with no family history of preterm birth. We performed a genotype test for differential abundance of variants between cases and controls. We used the genotype association statistics for ranking purposes in order to analyze the data using a multi-sample, protein-protein interaction (PPI) tool to identify significant clusters of patients associated with preterm birth. We identified shared interaction networks of proteins among 45 preterm cases in two statistically significant clusters, p<0.001. We also found two small control-dominated clusters. For replication, we compared our data to an independent, large birth cohort. Sequence data on 60 cases and 321 controls identified 34 preterm cases with shared networks of proteins distributed in two significant clusters. Analysis of the layered PPI networks of these clusters showed significant similarity scores between the clusters from the two independent cohorts of patients. Canonical pathway analysis of the unique genes defining these clusters demonstrated enrichment in inflammatory signaling pathways, the glucocorticoid receptor, the insulin receptor, EGF and B-cell signaling, These results provide insights into the genetics of PTB and support a genetic architecture defined by subgroups of patients that share variants in genes in specific networks and pathways which are sufficient to give rise to the disease phenotype.