An ultra low-cost smartphone device for in-situ monitoring of acute organophosphorus poisoning for agricultural workers.

In this work, we present an ultra-low-cost smartphone device for in situ quantification of OP poisoning severity. The performance of the lens-less smartphone spectrum apparatus (LeSSA) is evaluated using standard human Interleukin-6 (IL-6) immunoassay kits. Upon dose-response curve fitting, LeSSA demonstrates an accuracy of 99.5%. The limit of detection (LOD) of LeSSA was evaluated through comparison of 6.4 pg/ml with standard laboratory grade UV-vis spectrophotometer at 5.5 pg/ml. Evaluating the capacity of LeSSA in spike solution by combining plasma cholinesterase (PChE) and human plasma shows consistency at agreement of 97.6% between LeSSA and the laboratory instrument. For application demonstration, the activity of PChE for 24 agricultural workers' plasma samples was measured with LeSSA, showing exceptional agreement (r2 = 0.92) with the laboratory instrument reference. In addition to near laboratory grade accuracy, the total manufacturing cost of LeSSA is only $20 USD highlighting it's affordability. With LeSSA, clinicians can evaluate OP poisoning severity without the need to transport patient samples to facilities at far distances. Utilizing LeSSA, immediate results can be used for administration of appropriate treatment.

WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures.

BACKGROUND: An important focus of genomic science is the discovery and characterization of all functional elements within genomes. In silico methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets. METHODS: This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA word space and (2) scores words with a distributed Markov chain model. RESULTS: A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of Arabidopsis thaliana; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center. CONCLUSION: WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data.