Whole blood transcriptional signatures distinguishing active tuberculosis patients from asymptomatic latently infected individuals exist. Consensus has not been achieved regarding the optimal reduced gene sets as diagnostic biomarkers that also achieve discrimination from other diseases. Here we show a blood transcriptional signature of active tuberculosis using RNA-Seq, confirming microarray results, that discriminates active tuberculosis from latently infected and healthy individuals, validating this signature in an independent cohort. Using an advanced modular approach, we utilise the information from the entire transcriptome, which includes overabundance of type I interferon-inducible genes and underabundance of IFNG and TBX21, to develop a signature that discriminates active tuberculosis patients from latently infected individuals or those with acute viral and bacterial infections. We suggest that methods targeting gene selection across multiple discriminant modules can improve the development of diagnostic biomarkers with improved performance. Finally, utilising the modular approach, we demonstrate dynamic heterogeneity in a longitudinal study of recent tuberculosis contacts.

Based on empirical research in case study areas in six European countries, this paper examines the roles of social capital and identity in contemporary rural development. We argue that a focus on networks of social relationships can help us understand the dynamics of and relationships between social capital and identity. Comparing the case study areas, we draw attention to the position of identity in rural development and focus in particular on area‐branding initiatives. Other non‐agricultural networks are then presented, prefaced by a brief discussion of the role of governance. We argue that development emerges from a dialectic of existing networking practices and networks that are instigated for the purposes of development. Our research underlines the importance of social process in rural development, particularly in regard to the relationship between continuity and change.

Whole blood transcriptional signatures distinguishing patients with active tuberculosis from asymptomatic latently infected individuals have been described but, no consensus exists for the composition of optimal reduced gene sets as diagnostic biomarkers that also achieve discrimination from other diseases. We have recapitulated a blood transcriptional signature of active tuberculosis using RNA-Seq, previously reported by microarray that discriminates active tuberculosis from latently infected and healthy individuals, also validated in an independent cohort. We show that an advanced modular approach, which preserves and presents a signature of the entire transcriptome, can better discriminate patients with active tuberculosis from both latently infected and acute viral and bacterial infections. We suggest a method of targeted gene selection across modules for constructing diagnostic biomarkers, more representative of the transcriptome that overcomes some limitations of existing techniques. Finally, we utilise the modular approach to demonstrate dynamic heterogeneity in a longitudinal study of recent tuberculosis contacts.Tuberculosis (TB) is the leading cause of global mortality from an infectious disease. In 2016, there were 6.3 million new cases of TB disease and 1.67 million deaths and its diagnosis is problematic 1 . However, clinical disease represents one end of a spectrum of infection states. It is estimated that up to one third of all individuals worldwide have been infected with the causative pathogen, Mycobacterium tuberculosis, but the vast majority remain clinically asymptomatic with no radiological or microbiological evidence for active infection. This is termed latent TB infection (LTBI) and conceptually denotes a state in which M. tuberculosis persists within its host, while maintaining viability with the potential to replicate and cause symptomatic disease. Indeed, LTBI represents the primary reservoir for future incident TB, with 90% of all TB cases estimated to arise from reactivation of existing infection 1,2 . The risk of incident TB arising from existing LTBI is heterogeneous, poorly characterised and modifiable with anti-tuberculous treatment. Modelling studies indicate effective TB prevention to significantly reduce future TB incidence requires policies directed at the identification and treatment of LTBI 3 . However, implementation of mass screening programmes for this purpose are severely constrained by the size of the target population. Transformative advances in diagnostic tools that can effectively stratify TB risk in the LTBI population are therefore implicit to the realisation of systematic screening.The basis for LTBI heterogeneity rests with the limited scope of the tools we have available to identify the state. LTBI is inferred solely through evidence that immune sensitization has occurred, by the tuberculin skin test (TST) or the M. tuberculosis antigen-specific interferon-gamma (IFN-g) release assay (IGRA). Although these tests are both sensitive and specific for identi...