A personal glucose meter-utilized strategy for portable and label-free detection of hydrogen peroxide.

Rapid and precise detection of hydrogen peroxide (H2O2) holds great significance since it is linked to numerous physiological and inorganic catalytic processes. We herein developed a label-free and washing-free strategy to detect H2O2 by employing a hand-held personal glucose meter (PGM) as a signal readout device. By focusing on the fact that the reduced redox mediator ([Fe(CN)6]4-) itself is responsible for the final PGM signal, we developed a new PGM-based strategy to detect H2O2 by utilizing the target H2O2-mediated oxidation of [Fe(CN)6]4- to [Fe(CN)6]3- in the presence of horseradish peroxidase (HRP) and monitoring the reduced PGM signal in response to the target amount. Based on this straightforward and facile design principle, H2O2 was successfully determined down to 3.63 µM with high specificity against various non-target molecules. We further demonstrated that this strategy could be expanded to identify another model target choline by detecting H2O2 produced through its oxidation promoted by choline oxidase. Moreover, we verified its practical applicability by reliably determining extracellular H2O2 released from the breast cancer cell line, MDA-MB-231. This work could evolve into versatile PGM-based platform technology to identify various non-glucose target molecules by employing their corresponding oxidase enzymes, greatly advancing the portable biosensing technologies.

Assessment of sources variability of riverine particulate organic matter with land use and rainfall changes using a three-indicator (δ13C, δ15N, and C/N) Bayesian mixing model.

In intensive agricultural watersheds, riverine particulate organic matter (POM) may be transported from many sources such as rice paddies, crop uplands, forests, and livestock farming areas during rainy seasons. However, the impacts of land-use and rainfall changes on the POM sources are not well understood. In this study, changes in the sources of riverine POM were investigated in an agricultural area of Korea between 2014 and 2020/21. During this period, land-use and rainfall patterns changed dramatically. The δ13C, δ15N, and C/N of the POM sources as well as those of riverine POM were analyzed, and a stable isotope analysis in R (SIAR) model was utilized for source apportionment. There were differences in δ13C, δ15N, and C/N among the sources. For example, manure had higher δ13C (-22.6 ± 3.3‰) and δ15N (+10.6 ± 5.9‰) than soils (from -28.0 ± 0.8‰ to -25.1 ± 1.2‰ for δ13C and +3.6 ± 1.7‰ to +9.8 ± 1.4‰ for δ15N). For soils, the δ13C and δ15N were higher for upland soils, while C/N was greater for forest soils than for others. For riverine POM, the δ15N marginally changed; however, the δ13C and C/N increased from -26.1 ± 0.9‰ to -20.8 ± 5.3‰ and from +7.7 ± 1.7 to +18.8 ± 8.3 between 2014 and 2020/21, respectively. The SIAR model showed that the contributions of paddy (from 41.0% to 14.9%) and upland fields (from 48.1% to 23.7%) to riverine POM decreased between the periods due to decreased paddy area and the implementation of best management practice on upland fields, respectively. However, the contribution of forests (from 3.5% to 28.0%) and manure (from 7.4% to 33.5%) increased probably due to improper management of forest clear-cutting sites and livestock manure storage sites. The contributions of agricultural soils to riverine POM decreased in drier years. Our study suggests that land management rather than land-use area is critical in riverine POM management, particularly in wetter years.

Rice straw cover decreases soil erosion and sediment-bound C, N, and P losses but increases dissolved organic C export from upland maize fields as evidenced by δ13C.

Soil surface with crop residue is effective in reducing soil erosion and carbon (C), nitrogen (N), and phosphorus (P) losses from sloping fields. However, there is a high possibility that surface cover increases export of dissolved organic C (DOC) though relevant field studies under natural rainfall are lacking. In this study, the effects of surface cover with rice (Oryza sativa L.) straw on soil and CNP losses in both dissolved and sediment-bound forms from maize (Zea mays L.) fields were investigated under two fertilization levels (standard and double) × two types of runoff experiments (natural rainfall and artificial irrigation). Changes in soil properties including moisture, temperature, nutrients, and C concentration as well as maize yield were also examined. Surface cover decreased soil and total CNP losses by up to 82% across the experimental plots with some exceptions. However, surface cover increased DOC export in both natural (by 68-82% in total across all events) and artificial (by 3-4 fold) runoff, suggesting that crop residue cover may act as a DOC pollution source of water bodies. The contribution of rice straw to DOC, which was calculated using the δ13C of DOC from covered plots (-24.1 to -28.0‰) and control plots (-19.6 to -25.1‰), was 52.5-95.8%. The concentrations of K2SO4-extractable and microbial biomass C of the soils did not differ between covered and control plots, suggesting that DOC produced from rice straw was not incorporated into the soils, but rather, was washed out with surface runoff in this study. Surface cover increased maize growth and yield, particularly in double fertilization plots, through improved soil moisture, temperature, and nutrient conditions. To take full advantage of surface cover with crop residue, a further study on reducing DOC loss from crop residue needs to be conducted.