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Lateral flow immuno-assays, such as the home pregnancy test, are rapid point-of-care diagnostics that use antibody-coated nanoparticles to bind antigens/analytes (e.g., viruses, toxins or hormones). Ease of use, no need for centralized infrastructure and low-cost, makes these devices appealing for rapid disease identification, especially in low-resource environments. Here glycosylated polymer-coated nanoparticles are demonstrated for the sensitive, label-free detection of lectins in lateral flow and flow-through. The systems introduced here use glycans, not antibodies, to provide recognition: a "lateral flow glyco-assay," providing unique biosensing opportunities. Glycans are installed onto polymer termini and immobilized onto gold nanoparticles, providing colloidal stability but crucially also introducing assay tunability and selectivity. Using soybean agglutinin and Ricinus communis agglutinin I (RCA 120 ) as model analytes, the impact of polymer chain length and nanoparticle core size are evaluated, with chain length found to have a significant effect on signal generation-highlighting the need to control the macromolecular architecture to tune response. With optimized systems, lectins are detectable at subnanomolar concentrations, comparable to antibody-based systems. Complete lateral flow devices are also assembled to show how these devices can be deployed in the "real world." This work shows that glycan-binding can be a valuable tool in rapid diagnostics.

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.

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