Bacteria can cause numerous infectious diseases and has been a major threat to human humans. Although antibiotics have partially succeeded in treating bacteria, owing to antibiotic abuse, the emergence of multidrug‐resistant (MDR) bacteria has drastically diminished their potency. Since the invention of laser, the combination of light and photosensitizers, photodynamic therapy (PDT), has become an effective noninvasive treatment along with photothermal therapy (PTT), in which heat is generated by nonradiative relaxation. Antimicrobial PDT and PTT are emerging as effective treatments for bacterial infection, particularly against MDR bacteria. This mini review covers the recent progresses in PDT and PTT for bacterial treatment.

Waterborne outbreaks of enteric viruses are a major public health concern. The present study has been carried out to assess the presence of enteric viruses responsible for human acute gastroenteritis (AGE) in groundwater intended for drinking and produce washing. In total, 62 samples from groundwater for drinking and produce washing collected from Dec 2007 to Dec 2008 in Seoul were tested for enteric viruses using conventional RT-PCR, ELISA, and real-time RT-PCR. Our results showed that enteric viruses were detected in 7 (8.8%) groundwater samples. Rotaviruses were detected in 3 (4.8%) of the samples by ELISA; human adenoviruses were detected in 2 (3.2%) of the samples by ELISA; and nested RT-PCR detected noroviruses in 2 (3.2%) of the samples. In one of the groundwater sample, the norovirus RNA was detected by conventional RT-PCR which was confirmed positive by real-time RT-PCR. Additionally, real-time RT-PCR successfully detected norovirus RNA in five out of 62 water samples (8.1%). The data demonstrate that real-time RT-PCR will be useful as a rapid and sensitive method for detecting norovirus in water samples. Phylogenetic analysis revealed that the noroviruses detected in two of the groundwater samples belonged to GII-4. These studies can provide important information for the prevalence of enteric viruses in Korean groundwater.

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We developed a classification model and a real-time prediction model for short-term dissolved oxygen (DO) at the junction of the Han River in Anyangcheon, where water quality accidents occur frequently. The classification model is an analysis model that derives the main factors affecting DO changes in the Anyangcheon mobile water quality monitoring network using decision tree, random forest, and XGBoost. The model identified the key factors affecting DO changes to be electrical conductivity, cumulative precipitation, total nitrogen, and water temperature. Random forest (sensitivity, 0.9962; accuracy, 0.9981) and XGBoost (sensitivity, 1.0000; accuracy, 0.9822) showed excellent classification performance. The real-time prediction model for short-term DO we developed adopted artificial neural network (ANN), long short-term memory (LSTM), and gated recurrent unit (GRU) algorithms. LSTM (R2 = 0.93 − 0.97, first half; R2 = 0.95 − 0.96, second half) and GRU (R2 = 0.94 − 0.98, first half; R2 = 0.96 − 0.98, second half) significantly outperformed ANN (R2 = 0.64 − 0.86). The LSTM and GRU models we developed used real-time automatic measurement data, targeting urban rivers that are sensitive to water quality changes and are waterfront areas for citizens. They can quickly reflect and simulate short-term, real-time changes in water quality compared with existing static models.

In this study, a customized WQI (Seoul water quality index, S-WQI) for urban rivers that can ultimately reflect their characteristics was developed by modifying and supplementing the existing Bascarόn WQI calculation method through linkage with statistical methods such as factor analysis. We used the water quality data generated monthly at 17 water quality monitoring networks (WQMNs) in Seoul for 18 years, from 2002 to 2019. Result of a research, the monthly S-WQI showed an average 70 out of 100, ‘good (II)’ grades, whereas the average water quality grade according to the environmental standards was ‘slightly good (II),’ with an R2 value of 0.8298. The annual S-WQI was found to be 39 (bad) to 97 (very good), with an average of 72 (good). Through this study, S-WQI, a customized WQI for urban rivers, was judged to be a reasonable index that can represent the characteristics of urban river water quality. This is because it is easy to apply and is a calculation method that uses relatively fewer water quality items than the WQI calculated in the past, and it is highly likely to be linked to the currently implemented water quality grade system. In addition, to extend the application of WQI to various water quality survey points, based on the calculation methodology performed to derive the indices in this study, such as modified S-WQI (MS-WQI), by adding new water quality items and changing some items, it is also possible to develop an advanced customized WQI for urban rivers considering watershed characteristics and measurement items.