Dataset Information

Biological Visual Detection for Advanced Photocatalytic Oxidation toward Pesticide Detoxification.

ABSTRACT: Photocatalytic oxidation treatment is an emerging and fast developed eco-friendly, energy-saving, and efficient advanced oxidation technology for degrading hazardous pesticides. The conventional chemical detection to evaluate the effects for this process depends on the broken chemical structure, only giving residual content and product chemical composition. However, it misses direct visual detection on the toxicity and the quantitative analysis of pesticide detoxification. Here, we develop a novel strategy to combine photocatalytic oxidation with a zebrafish biological model to provide a direct visual detection on the environmental detoxification. The mortality or deformity of zebrafish embryos (ZEs) acts as an indicator. Over the irradiation duration threshold, the mortality of ZEs decreases to 23.3% for pure chlorothalonil (CTL-P) after photocatalytic oxidation treatment for 1 h, and the deformity reduces to 13.3% for commercial CTL (CTL-C) after 30 min and to 3.33% for tetramethylthiuram disulfide (TMTD) after 20 min. The toxicity of CTL-C and TMTD could be completely removed by photocatalytic oxidation treatment and causes no damage to the ZE developmental morphology. Chemical analyses demonstrate the degradation of CTL into inorganic compounds and TMTD into small organic molecules. Among these highlighted heterogeneous photocatalysts (g-C3N4, BiVO4, Ag3PO4, and P25), g-C3N4 exhibits the highest photocatalytic detoxification for CTL-P, CTL-C, and TMTD.

SUBMITTER: Hao M

PROVIDER: S-EPMC6881827 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Biological Visual Detection for Advanced Photocatalytic Oxidation toward Pesticide Detoxification.

Hao Mingjiao M Wang Jinghui J Zhao Jiadi J Liu Nan N Feng Chi C Wang Ziping Z Sun Danhui D Hu Quanli Q Wang Zhiyu Z Wang Feng F Yang Jingfeng J Lu Luhua L Dong Wu W Duan Limei L Liu Zhengang Z Liu Jinghai J

ACS omega 20191114 22

Photocatalytic oxidation treatment is an emerging and fast developed eco-friendly, energy-saving, and efficient advanced oxidation technology for degrading hazardous pesticides. The conventional chemical detection to evaluate the effects for this process depends on the broken chemical structure, only giving residual content and product chemical composition. However, it misses direct visual detection on the toxicity and the quantitative analysis of pesticide detoxification. Here, we develop a nov ...[more]

PMID: 31788596

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Project description:BackgroundStatistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available.This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases.MethodsThe method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2nd version (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest.ResultsThe method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED).Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data.ConclusionUsing human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected.

Dataset Information

Biological Visual Detection for Advanced Photocatalytic Oxidation toward Pesticide Detoxification.

Publications

Biological Visual Detection for Advanced Photocatalytic Oxidation toward Pesticide Detoxification.

Similar Datasets

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