Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test

Maximum likelihood haplotyping for general pedigrees. Human Heredity

Haplotype data is valuable in mapping disease-susceptibility genes, especially in the study of complex diseases. We present algorithms for inferring a most likely haplotype configuration for general pedigrees, implemented in the newest version of the genetic linkage analysis system superlink. In superlink, genetic linkage analysis problems are represented internally using Bayesian networks. The use of Bayesian networks enables efficient maximum likelihood haplotyping for more complex pedigrees than was previously possible. Furthermore, to support efficient haplotyping in larger pedigrees, we have also incorporated a novel algorithm for determining a better elimination order for the variables of the Bayesian network. The presented optimization algorithm also improves likelihood computations. We present experimental results for the new algorithms on a variety of real and semi-artificial data sets, and use our software to evaluate MCMC approximations for haplotyping.

Online System for Faster Multipoint Linkage Analysis via Parallel Execution on Thousands of Personal Computers

Computation of LOD scores is a valuable tool for mapping disease-susceptibility genes in the study of Mendelian and complex diseases. However, computation of exact multipoint likelihoods of large inbred pedigrees with extensive missing data is often beyond the capabilities of a single computer. We present a distributed system called “SUPERLINK-ONLINE,” for the computation of multipoint LOD scores of large inbred pedigrees. It achieves high performance via the efficient parallelization of the algorithms in SUPERLINK, a state-of-the-art serial program for these tasks, and through the use of the idle cycles of thousands of personal computers. The main algorithmic challenge has been to efficiently split a large task for distributed execution in a highly dynamic, nondedicated running environment. Notably, the system is available online, which allows computationally intensive analyses to be performed with no need for either the installation of software or the maintenance of a complicated distributed environment. As the system was being developed, it was extensively tested by collaborating medical centers worldwide on a variety of real data sets, some of which are presented in this article

Electronic Responses to Humidity in Monolayer and Multilayer AuNP Stripes Fabricated by Convective Self-Assembly

Nanoparticle devices employing electrical transduction mechanisms have been developed for various fields of application such as strain sensing, chemical detection, photo detectors, solar cells, memory devices, and so on. Since most devices are exposed and operated at ambient conditions, the humidity poses a problem, influencing their electrical properties via the interaction between the water molecules and NP materials. Here, the fabrication of multilayer and monolayer AuNP stripes with different dominating charge transport regimes is reported and their electronic responses to humidity are studied. It is shown that the humidity‐dependent electronic response is strongly correlated with the morphology and electron transport regimes in the AuNP stripes. Due to the differences in AuNP arrangements and the resulting dominant charge transport regime, the multilayer and mono layer AuNP stripes response differently to the humidity. This work reveals the possible mechanism accounting for their different responses and can help the development of high performance nanoparticle‐based devices