Screening and prioritization of antibiotics in drinking water source based on risk assessment, a case study in Guangzhou

Screening and prioritization of antibiotics in drinking water source based on risk assessment, a case study in Guangzhou | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Screening and prioritization of antibiotics in drinking water source based on risk assessment, a case study in Guangzhou Lulu Zhang, Lingyun Yu, Qianqian Yu, Xuan Yu, Sijia Liu, Zhanlu Lv, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7201162/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2026 Read the published version in Environmental Management → Version 1 posted 9 You are reading this latest preprint version Abstract Comprehensive assessment and screening of prioritized antibiotics are needed to control the increasing antibiotics contamination in drinking water sources. This study investigated 40 antibiotics in Liuxi River drinking water source in Guangzhou, screening and prioritization of antibiotics via toxicological priority index (ToxPi), which comprehensively considered their ecological risks, health risks, ecotoxicity, human health toxicity and other parameters. The total concentration of 40 antibiotics were much higher in the dry season than in the wet season. Among all the antibiotics, oxytetracycline and minocycline had highest levels in the dry season, while sulfamethoxazole had highest level in the wet season. Only minocycline and oxytetracycline had high and medium ecological risks in the dry season, respectively. Health risks of all the antibiotics were in an acceptable range. Ten antibiotics, e.g., oxytetracycline, minocycline, with the higher ToxPi score should be prioritized control to reduce their ecological and health risks. This study provides a soild reference for the screening and control of antibiotics in drinking water sources. Antibiotics Drinking Water Safety ToxPi Ecological Risk Health Risk Priority Control Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Antibiotics have been used extensively in the treatment of human and animal disease, livestock farming and aquaculture (Feng et al. 2020 ; Yang et al. 2018 ). Gradually rising global consumption of antibiotics has exceeded 100,000 tonnes per year (Liu et al. 2022 ; Zhang et al. 2023 ), and approximately 60% of them are released into the water environment (Cardoso et al. 2014 ; Liu et al. 2022 ). High levels of antibiotics greatly threat the security ecological environment and human health (Ma et al. 2023 ), i.e., antibiotics could interference the metabolism of algae and other aquatic organisms, and entering the animal and human body, cause allergic reactions or poisoning through the food chain (Zhou et al. 2022 ), and even lead the production of antibiotic resistance genes, which affects the therapeutic effect of antibiotics (Hu et al. 2021 ). Safety of drinking water source is a core issue for both ecosystem and human health. Although effective in removing conventional pollutants, traditional wastewater treatment processes generally exhibit limited effectiveness against antibiotics (Tian et al. 2025 ). Therefore, global researchers are consistently concerned about the antibiotics in drinking water sources until now, such as East China (Hu et al. 2021 ), reservoir in Germany (Voigt et al. 2020 ), and Piedmont of North Carolina (Gray et al. 2020 ). A Variety of antibiotics have been detected, and the concentration of antibiotics even reached more than 1000 ng L − 1 , e.g., Yangtze River basin in China (Jiang et al. 2023 ; Wang et al. 2023 ). High levels of antibiotics in drinking water sources presented high risks to both ecological environment and human health (Ma et al. 2023 ). Therefore, antibiotics are still of concern in drinking water sources globally despite the continuous emergence of new pollutants. Although more and more novel antibiotics have been detected in drinking water sources, there are no clear criterion for identifying and comparing their ecological and health risks, and hence hard to draw up targeted control suggestions to protect both ecosystem and human health (Zhang et al. 2023 ). It is urgent to conduct a holistic assessment of human health risks as well as ecological risks in drinking water sources, and carried out reasonable control of antibiotic under the lowest management cost. However, since the health risks and ecological risks of the antibiotics vary greatly (due to different health toxicity and ecotoxicity) (Huang et al. 2022 ), there still lack of a comprehensive assessment which can screen and grade of diversified antibiotics simultaneously. Recently, toxicological priority index (ToxPi) have been developed to aggregate data from different toxicity endpoints to show the combined effect of multiple factors (Reif et al. 2010 ), and then identify and classify the emerging contaminants in the watershed accurately (Feng et al. 2022 ; Zhao et al. 2023 ). This method can integrate different types of toxicity data and obtain comprehensive toxicity scores by setting different weights, so as to prioritize different pollutants. We designed a comprehensive method based on ToxPi, considered persistence, bioaccumulation, human toxicity and ecotoxicity, and other core factors comprehensively, which can help to solve the selection of priority control antibiotics in drinking water. Liuxi River Basin is the biggest drinking water source in Guangzhou, a highly urbanized region in South China (Wang et al. 2023 ). With the fast development of breeding industry and pharmaceutical companies, the middle and lower reaches of Liuxi River were gradually polluted by antibiotics (Wang et al. 2023 ). In this study, water samples of 15 sites in Liuxi River Basin were collected in both dry and wet seasons. We assessed ecological and human health risks in drinking water sources, and employed the ToxPi model to prioritize antibiotics for control based on their persistence, bioaccumulation, and toxicity. And targeted low-cost management strategies were proposed. This study provides important insights for risk identification and management of antibiotics in drinking water sources. 2. Materials and Methods 2.1 Sample collection and laboratory analysis Sampling sites were set at all 10 waterworks in the Liuxi River basin (W1, W2, W3, W4, W5, W6, W7, W8, W9, and W10) (Fig. 1 and Table S1 ). In addition, another 5 sampling sites (P1, P2, P3, P4, and P5) were selected, for there were much wastewater discharge enterprises located nearby, including chemical fiber manufacturing, chemical raw materials and chemical products manufacturing. Water samples were collected during the dry season (February) and the wet season (September) of 2023. The sampling procedure was in accordance with the technical specifications for surface water environmental quality monitoring (HJ 91.2—2022). Water samples were collected by a stainless steel bucket, and stored in 5.0 L ground brown glass bottles. The pH of the samples were adjusted to 5.0 to 7.0. The water samples were filtered with a stainless steel sieve (300 mesh) to remove impurities. The water samples were transported in iceboxes and pretreated within 24 h (Lu et al. 2020 ). A total of 40 target antibiotics were analyzed, including quinolones (n = 14), 16 sulfonamides (n = 16), tetracyclines (n = 8), macrolides (n = 2). Quinolones included pefloxacin (PFX), ofloxacin (OFL), enoxacin (ENO), norfloxacin (NOR), ciprofloxacin (CIP), enrofloxacin (ENR), danofloxacin (DAN), lomefloxacin (LOM), sarafloxacin (SAR), cinoxacin (CIN), oxolinic acid (OXO) flumequine (FLU), nalidixic acid (NDA) and pipemidic acid (PIPA); sulfonamides included sulfacetamide (SCM), sulfamethizole (SFT), sulfisoxazole (SIZ), sulfadiazine (SDZ), sulfachloropyridazine (SCP), sulfamethoxazole (SMX), sulfathiazole (STZ), sulfamethoxypyridazine (SMP), sulfamerazine (SMR), sulfadoxine (SD), sulfapyridine (SPD), sulfameter (SM), sulfamonomethoxine (SMM), sulfamethazine (SMT), sulfaphenazole (SPZ), and sulfadimethoxine (SDM); tetracyclines included minocycline (MINO), oxytetracycline (OTC), tetracycline (TC), demeclocycline (DMC), chlortetracycline (CTC), metacycline (MTC), doxycycline (DC), and anhydrotetracycline (AhTC); macrolides included erythromycin (ETM), and roxithromycin (RXM). Physicochemical properties of target antibiotics are shown in Table S2. The target antibiotics were extracted by solid-phase extraction, surrogate standards (sulfamethoxazole-d4, norfloxacin-d5 and roxithromycin-d7) were added prior to extraction. The water samples (3.0 L) were performed using a solid phase extraction column filled with 200 mg mixed adsorbent (HLB:WAX:WCX = 2:1:1). The target antibiotics on solid phase extraction column was eluted with 5.0 mL methanol, 5.0 mL 0.50% ammonia methanol and 5.0 mL 0.50% acetic methanol in sequence. After concentrated to 0.50 mL, internal standards (sulfamerazine-d4, ciprofloxacin-d8, and roxithromycin-d7) were added, and the sample was then filtered through a 0.22 µm filter membrane. The target antibiotics were detected by liquid chromatography (LC30-AD, Shimadzu, Japan) with tandem mass spectrometry (QTRAP 5500 MS/MS, AB SCIEX, MA). Waters ACQUITY-UPLC®-HSSC18 (2.1×100 mm, 1.8 µm) and ACQUITY-UPLC®-HSSC18 VanGuard™C18 (2.1×5 mm, 1.8 µm) chromatographic column was used and the temperature was at 40℃. The multiple reaction monitoring mode was used to collect positive ions. The injection volume was 2.0 µL and the flow rate was 0.30 mL min − 1 . Ultrapure water containing 0.10% (v/v) formic acid (phase A) and acetonitrile (phase B) were used as mobile phase solvents. The linear elution program for antibiotics was set as follows: from 0 to 1.0 min, 10% B; from 1.0 to 6.0 min, increased to 40% B; from 6.0 to 11.0 min, 70% B; from 11 to 12 min, maintained 70% B; from 12 to 15 min, 10% B. Surrogates standards was added to each water sample prior to analysis. Detailed quality assurance and quality control procedures are provided in the Supplementary material. 2.2 Ecological risk assessment The ecological risk of antibiotics in aquatic environments was assessed according to the risk quotient method outlined in the European Technical Guidance Document on Risk Assessment (2003). The risk quotient (RQ) and the combined risk quotient (RQs) were calculated using Eqs. ( 1 ) and ( 2 ), respectively (Quinn et al. 2008 ): $$\:{\text{RQ}}_{\text{i}}\text{=}\frac{{\text{MEC}}_{\text{i}}}{{\text{PNEC}}_{\text{i}}}$$ 1 $$\:\text{RQs=}\sum\:{\text{RQ}}_{\text{i}}$$ 2 where RQ i is the risk quotient of each antibiotics, MEC i and PNEC i refer to the measured concentrations of each antibiotic and predicted no effect concentrations, respectively. The predicted no effect concentration (PNEC) values (Table S3) were lowest values obtained from the NORMAN ecotoxicology database (Feng et al. 2022 ). The RQ classification has been used to assess the level of ecological risk (Jiang et al. 2023 ): RQs < 0.01 represents the lowest risk; 0.01 ≤ RQs < 0.1 is considered as low risk; 0.1 ≤ RQs < 1 indicates moderate risk; and RQs ≥ 1 represents high risk. 2.3 Health risk assessment Human health risk characterization is based on assessing HQs, where different life stages are taken into account to improve the accuracy of risk assessment (Huang et al. 2022 ). HQ was calculated using Eqs. ( 3 ) and ( 4 ): $$\:{\text{HQ}}_{\text{i}}\text{=}\frac{{\text{C}}_{\text{Si}}}{{\text{DWEL}}_{\text{i}}}$$ 3 $$\:{\text{DWEL}}_{\text{i}}\text{=}\frac{{\text{ADI}}_{\text{i}}\text{×BW×H}}{\text{DWI×AB×FOE}}$$ 4 $$\:\text{HQs=}\sum\:{\text{HQ}}_{\text{i}}$$ 5 where HQ i is the health risk quotient of each antibiotics, C si is the concentration of antibiotics in water (µg L − 1 ); DWEL i is drinking water equivalent level (µg L − 1 ); ADI is the acceptable daily intake (µg kg − 1 day − 1 ) calculated by no-observed-adverse-effect level and median lethal dose (United States Environmental Protection Agency, 1993) (Table S4); BW (kg) and DWI (L day − 1 ) are the average body weight and daily acceptable intake of drinking water, respectively. The United States Environmental Protection Agency (USEPA) recommended values of BW and DWI are shown in Table S5 (de Jesus Gaffney et al. 2015 ; Feng et al. 2020 ). H is the highest risk quotient, calculated by 1; AB is the gastrointestinal absorption rate, calculated as 1; FOE is the frequency of exposure (350 per year), calculated as 0.96. HQs 1, the adverse effect on human health effects might be likely occur (Tong et al. 2021 ). 2.4 ToxPi framework The ToxPi framework facilitated the screening and prioritization of antibiotics by integrating relevant data into a series of weighted slices, which subsequently offered a visual representation and a comparative score metric (Fleming et al. 2024 ; Reif et al. 2010 ). Currently, the method has been widely adopted in evaluating prioritization of pollutants in wastewater treatment (He et al. 2023 ), toxicology in contaminated groundwater (Arcega et al. 2023 ), and organophosphate esters risks to humans (Liu et al. 2024 ). In this study, the hazard potential (HP) of antibiotics was assessed through three components: persistence (P), bioaccumulation (B), and toxicity (T). Persistence data were estimated using the BIOWIN v4.11 module, while bioaccumulation potential was calculated with the BCFBAF v3.02 module within the USEPA EPI Suite v4.1. Toxicity evaluation integrated both ecotoxicological and human health effect. For ecotoxicological effects, the lowest PNEC values for algae, daphnids, and fish were derived from toxicity thresholds simulated by ECOSAR v2.2. Human health toxicity was quantified by molecular docking against 8 key proteins associated with antibiotic-induced toxic effects (Table S6). Using AutoDock Vina 1.5.7 (Trott and Olson 2010 ), binding energies (kcal mol − 1 ) were computed to represent ligand-protein affinities. Weighting coefficients and data processing protocols followed the framework established by Fu et al., ( 2024 ) (Table S7). Then, the ToxPi score is composed of multiple score factors of antibiotics in water such as environmental risk and health risk. Refer to the weight score setting of Cao et al., ( 2023 ), the ToxPi value of antibiotics was evaluated using the following four variables: the detected frequency (DF), HP, RQ and HQ. it is modified according to the importance to human health of drinking water source: HQ were set at 2, DF, HP and RQ were set at 1. The ToxPi score of each antibiotic were calculated using Eq. ( 6 ): $$\:{\text{ToxPi}}_{\text{i}}\text{=}{\text{w}}_{\text{1}}\frac{{\text{DF}}_{\text{i}}\text{-}{\text{DF}}_{\text{min}}}{{\text{DF}}_{\text{max}}\text{-}{\text{DF}}_{\text{min}}}\text{+}{\text{w}}_{\text{2}}\frac{{\text{HP}}_{\text{i}}\text{-}{\text{HP}}_{\text{min}}}{{\text{HP}}_{\text{max}}\text{-}{\text{HP}}_{\text{min}}}\text{+}{\text{w}}_{\text{3}}\frac{{\text{RQ}}_{\text{i}}\text{-}{\text{RQ}}_{\text{min}}}{{\text{RQ}}_{\text{max}}\text{-}{\text{RQ}}_{\text{min}}}\text{+}{\text{w}}_{\text{4}}\frac{{\text{HQ}}_{\text{i}}\text{-}{\text{HQ}}_{\text{min}}}{{\text{HQ}}_{\text{max}}\text{-}{\text{HQ}}_{\text{min}}}$$ 6 where w 1 = w 2 = w 3 = 1, w 4 = 2. Considered with the cost and capacity, antibiotics with top 10 ToxPi score were selected for priority control. 3. Result and Discussion 3.1 Occurrence of antibiotics The concentrations of the antibiotics are shown in Table 1 , further details, including the maximum, minimum, and median concentrations, are provided in Table S8. Among all the antibiotics, 39 were detected in the dry season, while 28 were detected in the wet season. The average concentrations of total antibiotics were 179 and 28 ng L − 1 for dry and wet seasons, respectively. Compared to other drinking water sources (Table S9), the concentrations of Liuxi river were higher than levels in North China Plain (Shi et al. 2022 ) and rural Eastern China (Wang et al. 2023 ), but lower than many levels which over 1000 ng L − 1 , e.g., lower Yangtze River (Wang et al. 2019 ), Wuhan (Jiang et al. 2023 ), and Piedmont of North Carolina (Gray et al. 2020 ). In particular, the concentration of waterworks (173 ng L − 1 in dry season and 31 ng L − 1 in wet season) were comparable with those in pollution sources (192 ng L − 1 in dry season and 21 ng L − 1 wet season), suggesting antibiotics were widely dispersed in the whole basin. This implies that risk identification and control should be conducted across the whole basin. The concentration of total antibiotics in the dry season was much higher than that in the wet season, which were similar to those of the Jiaozhou Bay (Lu et al. 2020 ) and the Pearl River Estuary (Liang et al. 2013 ). The high rainfall and surface runoff during the wet season diluted antibiotic concentrations (Shimizu et al. 2013 ; Yan et al. 2013 ). The distribution of various antibiotics were widely different for the two seasons. During the dry season, the concentration of tetracyclines (154 ng L − 1 ) was much higher than that of other antibiotics followed by quinolones (22 ng L − 1 ), sulfonamides (2.5 ng L − 1 ) and macrolides (1.3 ng L − 1 ). As a common veterinary medicine, tetracycline was the most commonly used antibiotics in China. Since they cannot be completely absorbed or degraded in natural waters, > 50% of administered doses enter the environment as parent compounds or metabolites (Jiang et al. 2023 ). While during the wet season, quinolones (16 ng L − 1 ) were in the majority, followed by sulfonamides (7.3 ng L − 1 ). The concentration of tetracyclines was significantly decreased to 3.7 ng L − 1 , and the macrolides (0.38 ng L − 1 ) were also decreased sharply. In general, the high concentration of antibiotics in the dry season was mainly due to the higher concentration of tetracyclines. Table 1 Concentrations of antibiotics in Liuxi River. Category antibiotics Abbreviation Dry season (ng L − 1 ) Wet season (ng L − 1 ) Average concentration detected frequency Average concentration detected frequency quinolones pefloxacin PFX 0.11 100% - - ofloxacin OFL 0.19 100% 3.3 100% enoxacin ENO 5.4 100% 0 0% norfloxacin NOR 3.3 100% 0.98 20% ciprofloxacin CIP 4.5 100% 2.8 60% enrofloxacin ENR 1.1 100% 4.0 93% danofloxacin DAN 1.9 100% 0 0% lomefloxacin LOM 0.20 100% 3.0 67% sarafloxacin SAR 1.4 100% 0 0% cinoxacin CIN 1.2 100% 0.87 47% oxolinic acid OXO 0 0% 0.91 40% flumequine FLU 0.031 100% 0.34 13% nalidixic acid NDA 1.2 100% 0.27 13% pipemidic acid PIPA 0.93 100% 0 0% sulfonamides sulfacetamide SCM 0.064 100% 0.0090 13% sulfamethizole SFT 0.025 100% 0 0% sulfisoxazole SIZ 0.065 100% 0.0020 6.7% sulfadiazine SDZ 0.19 100% 0.15 93% sulfachloropyridazine SCP 0.21 100% 0.012 47% sulfamethoxazole SMX 0.69 100% 6.7 100% sulfathiazole STZ 0.042 100% 0.0030 13% sulfamethoxypyridazine SMP 0.19 100% 0 0% sulfamerazine SMR 0.098 100% 0.010 40% sulfadoxine SD 0.045 100% 0.0020 6.7% sulfapyridine SPD 0.33 100% 0.074 93% sulfameter SM 0.017 67% 0.0070 27% sulfamonomethoxine SMM 0.023 80% 0.21 100% sulfamethazine SMT 0.28 100% 0.095 87% sulfaphenazole SPZ 0.20 100% 0.0050 20% sulfadimethoxine SDM 0.025 100% 0 0% tetracyclines minocycline MINO 38 100% 0.75 27% oxytetracycline OTC 95 100% 1.2 47% tetracycline TC 4.0 100% 0 0% demeclocycline DMC 4.1 100% 0.63 87% chlortetracycline CTC 2.4 100% 0.75 33% metacycline MTC 3.3 100% 0 0% doxycycline DC 7.7 100% 0.40 73% anhydrotetracycline AhTC 0.34 100% 0 0% macrolides erythromycin ETM 0.17 100% 0 0% roxithromycin RXM 1.2 100% 0.38 67% Among the 40 antibiotics, OTC and MINO had highest concentration in dry season (95 and 38 ng L − 1 , respectively). In wet season, SMX had highest concentration (6.7 ng L − 1 ), which was in accordance with another result in Pearl River Delta region (Sarmah et al. 2006 ). SMX had high stability and strong hydrophilicity, widely used as medical antibiotics made it enter the water environment abundantly through excretion, rain erosion and other ways (Sarmah et al. 2006 ). 3.2 Ecological risk assessment of antibiotics The RQs of antibiotics are shown in Fig. 2 . During the dry season, MINO and OTC had high or medium risk for all sites, which were corresponded to their high concentrations. Other antibiotics had low risk or lowest risk. The ∑RQs exceeded 1 at most sites (except W2), indicating high ecological risk from antibiotics collectively. During the wet season, all antibiotics had low risk or lowest risk, the ∑RQs were higher than 0.1 in W1, W3, W4, W5 and W10, while those at other sites were below 0.1. MINO, a broad-spectrum antibiotic and semi-synthetic tetracycline derivative, can alter biological metabolism and reduce microbial community diversity (Xing et al. 2021 ). However, it is highly persistent and difficult to degrade (Xing et al. 2021 ; Zhang et al. 2019 ). The RQs of MINO were higher in the lower reaches (from W5 to W10) than in the upper reaches (from W1 to W4), likely due to the river flowing through densely populated villages and towns, hospitals, and an international airport in this downstream region. The extensive use of MINO in cosmetics and food production (Ito and Uemura 2016 ; Liao et al. 2019 ) may contribute to its high ecological risk in the lower reaches. OTC, one of the most frequently detected antibiotics with the highest concentrations in Chinese surface waters (Zhang et al. 2023 ), is widely utilized in aquaculture and animal husbandry (Ma et al. 2023 ). Exposure to OTC has been demonstrated to delay the hatching of zebrafish embryos (Oliveira et al. 2013 ) and elevate oxidative stress in the muscles of silver catfish (Pês et al. 2018 ). Further research is needed to identify the specific sources of MINO and OTC within the basin and to fully assess their long-term impacts on the aquatic ecosystem. 3.3 Health risk assessment of antibiotics The HQs of the antibiotics are shown Fig. 3 . The HQs decreased with age, with infants of 0–3 months had the highest vales (0.038). HQs value of all antibiotics was less than 1 for all age groups, indicated the acceptable health risk in Liuxi River basin. Similar acceptable health risks were also found in other drinking water sources of China (Feng et al. 2020 ; Huang et al. 2022 ). OTC had the highest HQ values among the antibiotics in both seasons. OTC can accumulate in the human body through foods, and may affects the immune system, induce carcinogenicity and mutagenicity (Wu et al. 2022 ). Compared to other antibiotics, OTC exhibits lower bioaccumulation potential in organisms relative to environmental concentrations, which demonstrates relatively limited toxicity to organisms such as algae, daphnid and fish. However, it displays robust binding affinity to multiple human proteins (e.g., protein kinase B, B-cell lymphoma 2, Immunoglobulin G). These proteins are potentially associated with various chronic and immune-related diseases (such as Alzheimer's disease/lipid and atherosclerosis) (Cheng et al. 2025 ). Therefore, the health risks associated with OTC warrant great attention. Despite had higher concentrations than other antibiotics, MINO has limited toxicity to human health. 3.4 Screening and prioritization of antibiotics Prior to calculating the comprehensive ToxPi scores, the HP of each antibiotic was evaluated. The HP module within the ToxPi framework focuses specifically on the inherent properties of the contaminants that contribute to their long-term environmental threat and biological impact, independent of their current measured concentrations or site-specific risks. This assessment integrated data on four key characteristics: persistence, bioaccumulation, ecotoxicity, and human health toxicity. The results are presented in Fig. 4 , which identifies RXM, ETM, SAR, FLU, SDM, SPZ, CIN, CTC, LOM, and DAN as the top 10 antibiotics exhibiting the highest HP. Among these, RXM and ETM, representative macrolide antibiotics, demonstrated higher toxicity than other antibiotic classes. Macrolides are characterized by strong persistence, bioaccumulation potential, and ecotoxicity. They typically exhibit long environmental half-lives and exert significant biological toxicity on non-target aquatic organisms (Monahan et al. 2023 ). Consequently, they are recognized as among the antibiotics most likely to pose toxic risks to primary producers within food webs (Guo et al. 2015 ). SAR, CTC, LOM, and DAN also ranked highly due to their pronounced persistence and human health toxicity. Conversely, the elevated HP of FLU, SDM, SPZ, and CIN is primarily attributed to their high bioaccumulation potential and ecotoxicity. It is crucial to note that the HP reflects the compound's intrinsic capacity to cause harm besides to their environmental exposure. However, the actual priority for management within the Liuxi River basin requires consideration not only of this inherent hazard, but also of the compound's presence (DF) and the magnitude of the observed ecological and health risks (RQ and HQ) within this specific environment. This integration is achieved through the comprehensive ToxPi score. Prioritization scoring results for antibiotics in the Liuxi River are shown in Fig. 5 and Table 2 , The ToxPi scores for all antibiotics ranged from 0.39 to 4.05. Among them, the top 10 antibiotics with the highest ToxPi score were OTC (4.05), MINO (2.89), RXM (2.86), TC (2.73), DMC (2.72), ETM (2.65), SMX (2.61), LOM (2.59), DC (2.55) and CIP (2.52). OTC had the highest score due to the high detect frequency, ecological risk and health risk. Other nine antibiotics had high scores due to others factors, i.e., RXM and ETM had high hazard potential, DMC, SMX, and LOM had high detect frequency, while MINO, TC, CIP and DC had high ecological risk and health risk. Half of them belong to tetracycline, indicating that tetracycline need to be prioritized in drinking water source of Liuxi River. Two, two, and one antibiotics belong to macrolides, quinolones, and sulfonamides, respectively. Hence, priority control measures should be conducted to reduce their ecological and health risks. Several studies on non-targeted screening of emerging contaminants in water found the antibiotics (e.g., OTC, SMX and CIP) with high detection rates and concentrations need to be prioritized, which partly supported our results (Cao et al. 2023 ). While a study in the West River basin found that clarithromycin was the antibiotic that needed to be prioritized, which was not monitored in this study (Zhao et al. 2023 ). Table 2 ToxPi Score of each slice of antibiotic concentrations in Liuxi River. Antibiotics DF a HP b HQ c RQ d ToxPi Score Rank OTC 0.96 0.22 2.00 0.88 4.05 1 MINO 0.42 0.36 1.11 1.00 2.89 2 RXM 0.33 1.00 0.85 0.67 2.86 3 TC 1.00 0.32 0.72 0.69 2.73 4 DMC 0.67 0.32 1.00 0.74 2.72 5 ETM 0.96 0.97 0.34 0.39 2.65 6 SMX 0.96 0.22 0.79 0.64 2.61 7 LOM 0.54 0.24 0.94 0.79 2.59 8 DC 0.63 0.23 0.96 0.74 2.55 9 CIP 0.92 0.39 0.74 0.54 2.52 10 OFL 0.92 0.33 0.76 0.51 2.52 11 AhTC 0.38 0.38 0.93 0.68 2.43 12 DAN 0.46 0.39 0.88 0.63 2.36 13 CTC 0.67 0.36 0.77 0.53 2.35 14 ENR 0.42 0.37 1.08 0.56 2.32 15 OXO 0.38 0.22 0.78 0.70 2.28 16 SAR 0.58 0.63 0.52 0.41 2.14 17 NOR 0.83 0.19 0.84 0.42 2.07 18 ENO 0.50 0.27 0.78 0.50 2.04 19 FLU 0.46 0.44 0.39 0.48 1.94 20 SCP 0.75 0.23 0.52 0.33 1.84 21 CIN 0.38 0.53 0.72 0.32 1.84 22 SPZ 0.38 0.40 0.69 0.38 1.77 23 NDA 0.79 0.02 0.37 0.43 1.72 24 SMP 0.79 0.19 0.40 0.27 1.65 25 PFX 0.38 0.22 0.79 0.34 1.62 26 PIPA 0.88 0.30 0.27 0.17 1.61 27 SDZ 0.50 0.09 0.56 0.34 1.50 28 MTC 1.00 0.17 0.08 0.10 1.36 29 SFT 0.46 0.20 0.25 0.26 1.35 30 SDM 0.38 0.52 0.28 0.11 1.29 31 SMM 0.67 0.20 0.12 0.15 1.17 32 SD 0.00 0.19 0.26 0.42 1.14 33 SPD 0.38 0.18 0.01 0.28 0.87 34 SIZ 0.38 0.20 0.78 0.00 0.86 35 SMR 0.38 0.33 0.08 0.09 0.85 36 SMT 0.46 0.14 0.00 0.12 0.75 37 STZ 0.38 0.09 0.13 0.13 0.72 38 SM 0.38 0.21 0.09 0.07 0.72 39 SCM 0.38 0.00 0.02 0.00 0.39 40 a Detected frequency; b Hazard potential; c health risk quotients; d Risk quotients. At present, more and more antibiotics are regulated by several countries. European Union gradually banned the usage of antibiotics as growth-promoting feed additives (The European Parliament and The Council of The European Union, 2003 ), and further banned flavomycin, avilamycin, salinomycin, and monenomycin in 2006. U.S. conducted graded control over aminoglycosides, lincosamides, macrolides, penicillins, streptogramins, sulfonamides, and tetracyclines (U.S. Food and Drug Administration, 2013). China stopped the usage of LOM, PFX, OFL and NOR in food animals (Ministry of Agriculture of the PRC, 2015 ). Besides, the residue of CIP, DC, DAN, and sulfonamides were controlled by food safety standards. These regulations merely based on control rules in certain fields, e.g, food safety and agriculture safety, which lack of reliable and comprehensive criteria to prevent and control the environment antibiotics. Also, most of the these antibiotics have relatively low ToxPi scores in this study. Based on the prioritized screen of this study, we found more antibiotics should be controlled, which indicate the need of supplementing the current lists of chemicals management, and provide a more reliable control criteria for drinking water source. For Liuxi River, the environmental toxic risks of MINO and RXM should be further concerned, and more stringent standards should be applied to OTC and TC. We strongly suggest to comprehensively monitor the antibiotics globally, and screen the prioritized compounds in different regions, which help to improve chemicals management strategy and implement the current control lists. This study adopt a new screening method which consider a number of core factors, including toxicity, ecological risk, health risk and detection rate, which make the screening of antibiotics for priority control more reliable. The method can help to guide prevention and control of antibiotics, avoid excessive and insufficient control. In addition, different priority control antibiotics can be grouped according to similar ToxPi shape, provides the basis for the classification and control of antibiotics. The screening and prioritization methods on antibiotics can also be generalized in controlling other pollutants and in other basins. However, the limitations of screening method in this study still needs improvement. This case study only conducted screening and prioritization for 40 representative antibiotics, and the actual ecological and health risks may be higher considering the large number of unidentified antibiotics. Also, the antibiotic concentrations was measured in only two seasons, which may not wholly cover the seasonal variations of antibiotic concentrations. More frequent monitors and non-targeted screening are necessary for drinking water source, so as comprehensively master the antibiotic information and classify them, and obtain refined environmental control measures. 4. Conclusions In this study, 40 antibiotics were detected in drinking water source in Guangzhou. The concentrations of antibiotics were much higher in dry season than in wet season. OTC and MINO had the highest concentration in dry season and SMX had the highest concentration in wet season. Except for MINO and OTC in dry season, most antibiotics had low ecological risk levels. Health risk for different age groups of the antibiotics in Liuxi river were within an acceptable range. Based on ToxPi score, the ten antibiotics, OTC, MINO, RXM, TC, DMC, ETM, SMX, LOM, DC, and CIP should be prioritized control to reduce their ecological and health risks. The screening method of prioritized antibiotics in this study could effectively screen prior-control antibiotics, and it can be further optimized and applied to other river basins. Declarations Author Contribution Lulu Zhang: Conceptualization, Methodology, Investigation. Lingyun Yu: Formal analysis, Software, Writing-original draft. Qianqian Yu: Writing-review & editing. Xuan Yu: Writing-review & editing. Sijia Liu: Writing-review & editing. Han Zhang: Software. Zhanlu Lv: Software. Qiusen Huang: Writing-review & editing. Ling-Chuan Guo: Resources, Writing-review & editing, Supervision, Data curation. Jingru Zhang: Writing-review & editing Investigation, Formal analysis, Resources, Supervision. Acknowledgement This work was financially supported by the Program Special fund project for environmental protection of Guangdong province (2022-18) and Special fund project for environmental protection of Guangdong province (2023-12). 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Supplementary material Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2026 Read the published version in Environmental Management → Version 1 posted Editorial decision: Revision requested 26 Nov, 2025 Reviews received at journal 26 Nov, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers invited by journal 19 Aug, 2025 Editor assigned by journal 13 Aug, 2025 Submission checks completed at journal 24 Jul, 2025 First submitted to journal 23 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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sites.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/ad5aa91e36cd3fa9c9eb495c.jpeg"},{"id":90465758,"identity":"62fb3b23-a358-4032-840e-ce1c19b64b71","added_by":"auto","created_at":"2025-09-03 05:32:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":47624,"visible":true,"origin":"","legend":"\u003cp\u003eEcological risk heat-map of the antibiotics in dry season (A) and wet season (B) in 15 sample sites of Liuxi river.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/583e44b91d4ff6e7a9a1372a.png"},{"id":90464711,"identity":"1b611251-d338-4614-8aaf-2e5adf3a76ce","added_by":"auto","created_at":"2025-09-03 05:11:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":51581,"visible":true,"origin":"","legend":"\u003cp\u003eHealth risk heat-map for different age groups of the antibiotics in dry season (A) and wet season (B) of Liuxi river (M: months, Y: years)\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/e324c39f402bcd1153889644.png"},{"id":90463341,"identity":"86b5ccae-c119-414a-b02f-65e3d889d930","added_by":"auto","created_at":"2025-09-03 05:03:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":87020,"visible":true,"origin":"","legend":"\u003cp\u003eTop 10 antibiotics ranked by hazard potential in the Liuxi River based on the ToxPi model. Each pie chart consists of slices representing the normalized value of the variables and the width indicates the relative weight of these variables.\u003c/p\u003e","description":"","filename":"Onlinefloatimage41.png","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/1828ccadc205931fb7b52079.png"},{"id":90463337,"identity":"43f5ec02-b023-4c0d-ad1e-a34b4dd84728","added_by":"auto","created_at":"2025-09-03 05:03:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":94237,"visible":true,"origin":"","legend":"\u003cp\u003ePrioritization scoring results for the detected antibiotics in the Liuxi River. ToxPi slices are displayed for the top 10 antibiotics. Each pie chart consists of 6 slices representing the normalized value of the variables (i.e., RQ, HQ, HP, and RQ) and the width indicates the relative weight of these variables.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/249b464ac3596a80e4fe60a0.png"},{"id":102785161,"identity":"af0814e3-294f-4035-a554-822730eb9104","added_by":"auto","created_at":"2026-02-16 16:00:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1753899,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/a910faa9-922c-4e72-a7a5-a7e5cfd0e235.pdf"},{"id":90465753,"identity":"f8e05a5b-ed1e-47b4-9b10-1d797496b71a","added_by":"auto","created_at":"2025-09-03 05:32:01","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":88658,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAppendix A. Supplementary material\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7201162/v1/a61f2ebafbed72ca8044239e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Screening and prioritization of antibiotics in drinking water source based on risk assessment, a case study in Guangzhou","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAntibiotics have been used extensively in the treatment of human and animal disease, livestock farming and aquaculture (Feng et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Gradually rising global consumption of antibiotics has exceeded 100,000 tonnes per year (Liu et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and approximately 60% of them are released into the water environment (Cardoso et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). High levels of antibiotics greatly threat the security ecological environment and human health (Ma et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), i.e., antibiotics could interference the metabolism of algae and other aquatic organisms, and entering the animal and human body, cause allergic reactions or poisoning through the food chain (Zhou et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and even lead the production of antibiotic resistance genes, which affects the therapeutic effect of antibiotics (Hu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSafety of drinking water source is a core issue for both ecosystem and human health. Although effective in removing conventional pollutants, traditional wastewater treatment processes generally exhibit limited effectiveness against antibiotics (Tian et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, global researchers are consistently concerned about the antibiotics in drinking water sources until now, such as East China (Hu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), reservoir in Germany (Voigt et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Piedmont of North Carolina (Gray et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A Variety of antibiotics have been detected, and the concentration of antibiotics even reached more than 1000 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, e.g., Yangtze River basin in China (Jiang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). High levels of antibiotics in drinking water sources presented high risks to both ecological environment and human health (Ma et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, antibiotics are still of concern in drinking water sources globally despite the continuous emergence of new pollutants.\u003c/p\u003e\u003cp\u003eAlthough more and more novel antibiotics have been detected in drinking water sources, there are no clear criterion for identifying and comparing their ecological and health risks, and hence hard to draw up targeted control suggestions to protect both ecosystem and human health (Zhang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It is urgent to conduct a holistic assessment of human health risks as well as ecological risks in drinking water sources, and carried out reasonable control of antibiotic under the lowest management cost. However, since the health risks and ecological risks of the antibiotics vary greatly (due to different health toxicity and ecotoxicity) (Huang et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), there still lack of a comprehensive assessment which can screen and grade of diversified antibiotics simultaneously. Recently, toxicological priority index (ToxPi) have been developed to aggregate data from different toxicity endpoints to show the combined effect of multiple factors (Reif et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and then identify and classify the emerging contaminants in the watershed accurately (Feng et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This method can integrate different types of toxicity data and obtain comprehensive toxicity scores by setting different weights, so as to prioritize different pollutants. We designed a comprehensive method based on ToxPi, considered persistence, bioaccumulation, human toxicity and ecotoxicity, and other core factors comprehensively, which can help to solve the selection of priority control antibiotics in drinking water.\u003c/p\u003e\u003cp\u003eLiuxi River Basin is the biggest drinking water source in Guangzhou, a highly urbanized region in South China (Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). With the fast development of breeding industry and pharmaceutical companies, the middle and lower reaches of Liuxi River were gradually polluted by antibiotics (Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, water samples of 15 sites in Liuxi River Basin were collected in both dry and wet seasons. We assessed ecological and human health risks in drinking water sources, and employed the ToxPi model to prioritize antibiotics for control based on their persistence, bioaccumulation, and toxicity. And targeted low-cost management strategies were proposed. This study provides important insights for risk identification and management of antibiotics in drinking water sources.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Sample collection and laboratory analysis\u003c/h2\u003e\u003cp\u003eSampling sites were set at all 10 waterworks in the Liuxi River basin (W1, W2, W3, W4, W5, W6, W7, W8, W9, and W10) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In addition, another 5 sampling sites (P1, P2, P3, P4, and P5) were selected, for there were much wastewater discharge enterprises located nearby, including chemical fiber manufacturing, chemical raw materials and chemical products manufacturing. Water samples were collected during the dry season (February) and the wet season (September) of 2023. The sampling procedure was in accordance with the technical specifications for surface water environmental quality monitoring (HJ 91.2\u0026mdash;2022). Water samples were collected by a stainless steel bucket, and stored in 5.0 L ground brown glass bottles. The pH of the samples were adjusted to 5.0 to 7.0. The water samples were filtered with a stainless steel sieve (300 mesh) to remove impurities. The water samples were transported in iceboxes and pretreated within 24 h (Lu et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA total of 40 target antibiotics were analyzed, including quinolones (n\u0026thinsp;=\u0026thinsp;14), 16 sulfonamides (n\u0026thinsp;=\u0026thinsp;16), tetracyclines (n\u0026thinsp;=\u0026thinsp;8), macrolides (n\u0026thinsp;=\u0026thinsp;2). Quinolones included pefloxacin (PFX), ofloxacin (OFL), enoxacin (ENO), norfloxacin (NOR), ciprofloxacin (CIP), enrofloxacin (ENR), danofloxacin (DAN), lomefloxacin (LOM), sarafloxacin (SAR), cinoxacin (CIN), oxolinic acid (OXO) flumequine (FLU), nalidixic acid (NDA) and pipemidic acid (PIPA); sulfonamides included sulfacetamide (SCM), sulfamethizole (SFT), sulfisoxazole (SIZ), sulfadiazine (SDZ), sulfachloropyridazine (SCP), sulfamethoxazole (SMX), sulfathiazole (STZ), sulfamethoxypyridazine (SMP), sulfamerazine (SMR), sulfadoxine (SD), sulfapyridine (SPD), sulfameter (SM), sulfamonomethoxine (SMM), sulfamethazine (SMT), sulfaphenazole (SPZ), and sulfadimethoxine (SDM); tetracyclines included minocycline (MINO), oxytetracycline (OTC), tetracycline (TC), demeclocycline (DMC), chlortetracycline (CTC), metacycline (MTC), doxycycline (DC), and anhydrotetracycline (AhTC); macrolides included erythromycin (ETM), and roxithromycin (RXM). Physicochemical properties of target antibiotics are shown in Table S2.\u003c/p\u003e\u003cp\u003eThe target antibiotics were extracted by solid-phase extraction, surrogate standards (sulfamethoxazole-d4, norfloxacin-d5 and roxithromycin-d7) were added prior to extraction. The water samples (3.0 L) were performed using a solid phase extraction column filled with 200 mg mixed adsorbent (HLB:WAX:WCX\u0026thinsp;=\u0026thinsp;2:1:1). The target antibiotics on solid phase extraction column was eluted with 5.0 mL methanol, 5.0 mL 0.50% ammonia methanol and 5.0 mL 0.50% acetic methanol in sequence. After concentrated to 0.50 mL, internal standards (sulfamerazine-d4, ciprofloxacin-d8, and roxithromycin-d7) were added, and the sample was then filtered through a 0.22 \u0026micro;m filter membrane.\u003c/p\u003e\u003cp\u003eThe target antibiotics were detected by liquid chromatography (LC30-AD, Shimadzu, Japan) with tandem mass spectrometry (QTRAP 5500 MS/MS, AB SCIEX, MA). Waters ACQUITY-UPLC\u0026reg;-HSSC18 (2.1\u0026times;100 mm, 1.8 \u0026micro;m) and ACQUITY-UPLC\u0026reg;-HSSC18 VanGuard\u0026trade;C18 (2.1\u0026times;5 mm, 1.8 \u0026micro;m) chromatographic column was used and the temperature was at 40℃. The multiple reaction monitoring mode was used to collect positive ions. The injection volume was 2.0 \u0026micro;L and the flow rate was 0.30 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Ultrapure water containing 0.10% (v/v) formic acid (phase A) and acetonitrile (phase B) were used as mobile phase solvents. The linear elution program for antibiotics was set as follows: from 0 to 1.0 min, 10% B; from 1.0 to 6.0 min, increased to 40% B; from 6.0 to 11.0 min, 70% B; from 11 to 12 min, maintained 70% B; from 12 to 15 min, 10% B. Surrogates standards was added to each water sample prior to analysis. Detailed quality assurance and quality control procedures are provided in the Supplementary material.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Ecological risk assessment\u003c/h2\u003e\u003cp\u003eThe ecological risk of antibiotics in aquatic environments was assessed according to the risk quotient method outlined in the European Technical Guidance Document on Risk Assessment (2003). The risk quotient (RQ) and the combined risk quotient (RQs) were calculated using Eqs.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and (\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), respectively (Quinn et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{\\text{RQ}}_{\\text{i}}\\text{=}\\frac{{\\text{MEC}}_{\\text{i}}}{{\\text{PNEC}}_{\\text{i}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{RQs=}\\sum\\:{\\text{RQ}}_{\\text{i}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere RQ\u003csub\u003ei\u003c/sub\u003e is the risk quotient of each antibiotics, MEC\u003csub\u003ei\u003c/sub\u003e and PNEC\u003csub\u003ei\u003c/sub\u003e refer to the measured concentrations of each antibiotic and predicted no effect concentrations, respectively. The predicted no effect concentration (PNEC) values (Table S3) were lowest values obtained from the NORMAN ecotoxicology database (Feng et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The RQ classification has been used to assess the level of ecological risk (Jiang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e): RQs\u0026thinsp;\u0026lt;\u0026thinsp;0.01 represents the lowest risk; 0.01\u0026thinsp;\u0026le;\u0026thinsp;RQs\u0026thinsp;\u0026lt;\u0026thinsp;0.1 is considered as low risk; 0.1\u0026thinsp;\u0026le;\u0026thinsp;RQs\u0026thinsp;\u0026lt;\u0026thinsp;1 indicates moderate risk; and RQs\u0026thinsp;\u0026ge;\u0026thinsp;1 represents high risk.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Health risk assessment\u003c/h2\u003e\u003cp\u003eHuman health risk characterization is based on assessing HQs, where different life stages are taken into account to improve the accuracy of risk assessment (Huang et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). HQ was calculated using Eqs.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and (\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e):\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{\\text{HQ}}_{\\text{i}}\\text{=}\\frac{{\\text{C}}_{\\text{Si}}}{{\\text{DWEL}}_{\\text{i}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{\\text{DWEL}}_{\\text{i}}\\text{=}\\frac{{\\text{ADI}}_{\\text{i}}\\text{\u0026times;BW\u0026times;H}}{\\text{DWI\u0026times;AB\u0026times;FOE}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:\\text{HQs=}\\sum\\:{\\text{HQ}}_{\\text{i}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere HQ\u003csub\u003ei\u003c/sub\u003e is the health risk quotient of each antibiotics, C\u003csub\u003esi\u003c/sub\u003e is the concentration of antibiotics in water (\u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e); DWEL\u003csub\u003ei\u003c/sub\u003e is drinking water equivalent level (\u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e); ADI is the acceptable daily intake (\u0026micro;g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) calculated by no-observed-adverse-effect level and median lethal dose (United States Environmental Protection Agency, 1993) (Table S4); BW (kg) and DWI (L day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) are the average body weight and daily acceptable intake of drinking water, respectively. The United States Environmental Protection Agency (USEPA) recommended values of BW and DWI are shown in Table S5 (de Jesus Gaffney et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Feng et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). H is the highest risk quotient, calculated by 1; AB is the gastrointestinal absorption rate, calculated as 1; FOE is the frequency of exposure (350 per year), calculated as 0.96. HQs\u0026thinsp;\u0026lt;\u0026thinsp;1 is considered an acceptable evaluation criterion. When HQs\u0026thinsp;\u0026gt;\u0026thinsp;1, the adverse effect on human health effects might be likely occur (Tong et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 ToxPi framework\u003c/h2\u003e\u003cp\u003eThe ToxPi framework facilitated the screening and prioritization of antibiotics by integrating relevant data into a series of weighted slices, which subsequently offered a visual representation and a comparative score metric (Fleming et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Reif et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Currently, the method has been widely adopted in evaluating prioritization of pollutants in wastewater treatment (He et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), toxicology in contaminated groundwater (Arcega et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and organophosphate esters risks to humans (Liu et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, the hazard potential (HP) of antibiotics was assessed through three components: persistence (P), bioaccumulation (B), and toxicity (T). Persistence data were estimated using the BIOWIN v4.11 module, while bioaccumulation potential was calculated with the BCFBAF v3.02 module within the USEPA EPI Suite v4.1. Toxicity evaluation integrated both ecotoxicological and human health effect. For ecotoxicological effects, the lowest PNEC values for algae, daphnids, and fish were derived from toxicity thresholds simulated by ECOSAR v2.2. Human health toxicity was quantified by molecular docking against 8 key proteins associated with antibiotic-induced toxic effects (Table S6). Using AutoDock Vina 1.5.7 (Trott and Olson \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), binding energies (kcal mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were computed to represent ligand-protein affinities. Weighting coefficients and data processing protocols followed the framework established by Fu et al., (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) (Table S7). Then, the ToxPi score is composed of multiple score factors of antibiotics in water such as environmental risk and health risk. Refer to the weight score setting of Cao et al., (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the ToxPi value of antibiotics was evaluated using the following four variables: the detected frequency (DF), HP, RQ and HQ. it is modified according to the importance to human health of drinking water source: HQ were set at 2, DF, HP and RQ were set at 1. The ToxPi score of each antibiotic were calculated using Eq.\u0026nbsp;(\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e):\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:{\\text{ToxPi}}_{\\text{i}}\\text{=}{\\text{w}}_{\\text{1}}\\frac{{\\text{DF}}_{\\text{i}}\\text{-}{\\text{DF}}_{\\text{min}}}{{\\text{DF}}_{\\text{max}}\\text{-}{\\text{DF}}_{\\text{min}}}\\text{+}{\\text{w}}_{\\text{2}}\\frac{{\\text{HP}}_{\\text{i}}\\text{-}{\\text{HP}}_{\\text{min}}}{{\\text{HP}}_{\\text{max}}\\text{-}{\\text{HP}}_{\\text{min}}}\\text{+}{\\text{w}}_{\\text{3}}\\frac{{\\text{RQ}}_{\\text{i}}\\text{-}{\\text{RQ}}_{\\text{min}}}{{\\text{RQ}}_{\\text{max}}\\text{-}{\\text{RQ}}_{\\text{min}}}\\text{+}{\\text{w}}_{\\text{4}}\\frac{{\\text{HQ}}_{\\text{i}}\\text{-}{\\text{HQ}}_{\\text{min}}}{{\\text{HQ}}_{\\text{max}}\\text{-}{\\text{HQ}}_{\\text{min}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1, \u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2. Considered with the cost and capacity, antibiotics with top 10 ToxPi score were selected for priority control.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Result and Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Occurrence of antibiotics\u003c/h2\u003e\u003cp\u003eThe concentrations of the antibiotics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, further details, including the maximum, minimum, and median concentrations, are provided in Table S8. Among all the antibiotics, 39 were detected in the dry season, while 28 were detected in the wet season. The average concentrations of total antibiotics were 179 and 28 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for dry and wet seasons, respectively. Compared to other drinking water sources (Table S9), the concentrations of Liuxi river were higher than levels in North China Plain (Shi et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and rural Eastern China (Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but lower than many levels which over 1000 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, e.g., lower Yangtze River (Wang et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Wuhan (Jiang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Piedmont of North Carolina (Gray et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In particular, the concentration of waterworks (173 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in dry season and 31 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in wet season) were comparable with those in pollution sources (192 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in dry season and 21 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e wet season), suggesting antibiotics were widely dispersed in the whole basin. This implies that risk identification and control should be conducted across the whole basin.\u003c/p\u003e\u003cp\u003eThe concentration of total antibiotics in the dry season was much higher than that in the wet season, which were similar to those of the Jiaozhou Bay (Lu et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the Pearl River Estuary (Liang et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The high rainfall and surface runoff during the wet season diluted antibiotic concentrations (Shimizu et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Yan et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The distribution of various antibiotics were widely different for the two seasons. During the dry season, the concentration of tetracyclines (154 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was much higher than that of other antibiotics followed by quinolones (22 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), sulfonamides (2.5 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and macrolides (1.3 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). As a common veterinary medicine, tetracycline was the most commonly used antibiotics in China. Since they cannot be completely absorbed or degraded in natural waters, \u0026gt;\u0026thinsp;50% of administered doses enter the environment as parent compounds or metabolites (Jiang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While during the wet season, quinolones (16 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were in the majority, followed by sulfonamides (7.3 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The concentration of tetracyclines was significantly decreased to 3.7 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and the macrolides (0.38 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were also decreased sharply. In general, the high concentration of antibiotics in the dry season was mainly due to the higher concentration of tetracyclines.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eConcentrations of antibiotics in Liuxi River.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eantibiotics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAbbreviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eDry season (ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eWet season (ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAverage \u003c/p\u003e\u003cp\u003econcentration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003edetected frequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAverage \u003c/p\u003e\u003cp\u003econcentration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003edetected frequency\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003equinolones\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003epefloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePFX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eenoxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eENO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enorfloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eciprofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCIP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eenrofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003edanofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elomefloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esarafloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecinoxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCIN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eoxolinic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOXO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eflumequine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFLU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enalidixic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNDA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003epipemidic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePIPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esulfonamides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfacetamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamethizole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSFT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfisoxazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSIZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfadiazine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSDZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfachloropyridazine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSCP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamethoxazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSMX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfathiazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSTZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamethoxypyridazine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamerazine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSMR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfadoxine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfapyridine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSPD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e93%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfameter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamonomethoxine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSMM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfamethazine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSMT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e87%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfaphenazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSPZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esulfadimethoxine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003etetracyclines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eminocycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMINO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e27%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eoxytetracycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003etetracycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003edemeclocycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e87%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echlortetracycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emetacycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003edoxycycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e73%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eanhydrotetracycline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAhTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emacrolides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eerythromycin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eETM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eroxithromycin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRXM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e67%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAmong the 40 antibiotics, OTC and MINO had highest concentration in dry season (95 and 38 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively). In wet season, SMX had highest concentration (6.7 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), which was in accordance with another result in Pearl River Delta region (Sarmah et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). SMX had high stability and strong hydrophilicity, widely used as medical antibiotics made it enter the water environment abundantly through excretion, rain erosion and other ways (Sarmah et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Ecological risk assessment of antibiotics\u003c/h2\u003e\u003cp\u003eThe RQs of antibiotics are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. During the dry season, MINO and OTC had high or medium risk for all sites, which were corresponded to their high concentrations. Other antibiotics had low risk or lowest risk. The \u0026sum;RQs exceeded 1 at most sites (except W2), indicating high ecological risk from antibiotics collectively. During the wet season, all antibiotics had low risk or lowest risk, the \u0026sum;RQs were higher than 0.1 in W1, W3, W4, W5 and W10, while those at other sites were below 0.1.\u003c/p\u003e\u003cp\u003eMINO, a broad-spectrum antibiotic and semi-synthetic tetracycline derivative, can alter biological metabolism and reduce microbial community diversity (Xing et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, it is highly persistent and difficult to degrade (Xing et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The RQs of MINO were higher in the lower reaches (from W5 to W10) than in the upper reaches (from W1 to W4), likely due to the river flowing through densely populated villages and towns, hospitals, and an international airport in this downstream region. The extensive use of MINO in cosmetics and food production (Ito and Uemura \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liao et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) may contribute to its high ecological risk in the lower reaches.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOTC, one of the most frequently detected antibiotics with the highest concentrations in Chinese surface waters (Zhang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), is widely utilized in aquaculture and animal husbandry (Ma et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Exposure to OTC has been demonstrated to delay the hatching of zebrafish embryos (Oliveira et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and elevate oxidative stress in the muscles of silver catfish (P\u0026ecirc;s et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Further research is needed to identify the specific sources of MINO and OTC within the basin and to fully assess their long-term impacts on the aquatic ecosystem.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Health risk assessment of antibiotics\u003c/h2\u003e\u003cp\u003eThe HQs of the antibiotics are shown Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The HQs decreased with age, with infants of 0\u0026ndash;3 months had the highest vales (0.038). HQs value of all antibiotics was less than 1 for all age groups, indicated the acceptable health risk in Liuxi River basin. Similar acceptable health risks were also found in other drinking water sources of China (Feng et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOTC had the highest HQ values among the antibiotics in both seasons. OTC can accumulate in the human body through foods, and may affects the immune system, induce carcinogenicity and mutagenicity (Wu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Compared to other antibiotics, OTC exhibits lower bioaccumulation potential in organisms relative to environmental concentrations, which demonstrates relatively limited toxicity to organisms such as algae, daphnid and fish. However, it displays robust binding affinity to multiple human proteins (e.g., protein kinase B, B-cell lymphoma 2, Immunoglobulin G). These proteins are potentially associated with various chronic and immune-related diseases (such as Alzheimer's disease/lipid and atherosclerosis) (Cheng et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Therefore, the health risks associated with OTC warrant great attention. Despite had higher concentrations than other antibiotics, MINO has limited toxicity to human health.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Screening and prioritization of antibiotics\u003c/h2\u003e\u003cp\u003ePrior to calculating the comprehensive ToxPi scores, the HP of each antibiotic was evaluated. The HP module within the ToxPi framework focuses specifically on the inherent properties of the contaminants that contribute to their long-term environmental threat and biological impact, independent of their current measured concentrations or site-specific risks. This assessment integrated data on four key characteristics: persistence, bioaccumulation, ecotoxicity, and human health toxicity. The results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, which identifies RXM, ETM, SAR, FLU, SDM, SPZ, CIN, CTC, LOM, and DAN as the top 10 antibiotics exhibiting the highest HP. Among these, RXM and ETM, representative macrolide antibiotics, demonstrated higher toxicity than other antibiotic classes. Macrolides are characterized by strong persistence, bioaccumulation potential, and ecotoxicity. They typically exhibit long environmental half-lives and exert significant biological toxicity on non-target aquatic organisms (Monahan et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, they are recognized as among the antibiotics most likely to pose toxic risks to primary producers within food webs (Guo et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). SAR, CTC, LOM, and DAN also ranked highly due to their pronounced persistence and human health toxicity. Conversely, the elevated HP of FLU, SDM, SPZ, and CIN is primarily attributed to their high bioaccumulation potential and ecotoxicity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIt is crucial to note that the HP reflects the compound's intrinsic capacity to cause harm besides to their environmental exposure. However, the actual priority for management within the Liuxi River basin requires consideration not only of this inherent hazard, but also of the compound's presence (DF) and the magnitude of the observed ecological and health risks (RQ and HQ) within this specific environment. This integration is achieved through the comprehensive ToxPi score. Prioritization scoring results for antibiotics in the Liuxi River are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, The ToxPi scores for all antibiotics ranged from 0.39 to 4.05. Among them, the top 10 antibiotics with the highest ToxPi score were OTC (4.05), MINO (2.89), RXM (2.86), TC (2.73), DMC (2.72), ETM (2.65), SMX (2.61), LOM (2.59), DC (2.55) and CIP (2.52). OTC had the highest score due to the high detect frequency, ecological risk and health risk. Other nine antibiotics had high scores due to others factors, i.e., RXM and ETM had high hazard potential, DMC, SMX, and LOM had high detect frequency, while MINO, TC, CIP and DC had high ecological risk and health risk. Half of them belong to tetracycline, indicating that tetracycline need to be prioritized in drinking water source of Liuxi River. Two, two, and one antibiotics belong to macrolides, quinolones, and sulfonamides, respectively. Hence, priority control measures should be conducted to reduce their ecological and health risks. Several studies on non-targeted screening of emerging contaminants in water found the antibiotics (e.g., OTC, SMX and CIP) with high detection rates and concentrations need to be prioritized, which partly supported our results (Cao et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While a study in the West River basin found that clarithromycin was the antibiotic that needed to be prioritized, which was not monitored in this study (Zhao et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eToxPi Score of each slice of antibiotic concentrations in Liuxi River.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntibiotics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDF\u003cem\u003ea\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHP\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHQ\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRQ\u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eToxPi Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMINO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRXM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eETM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSMX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAhTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDAN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOXO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eENO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFLU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSCP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNDA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePFX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSDZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSFT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSMM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSIZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSMR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSMT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSTZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003eDetected frequency; \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003eHazard potential; \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003ehealth risk quotients; \u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003eRisk quotients.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAt present, more and more antibiotics are regulated by several countries. European Union gradually banned the usage of antibiotics as growth-promoting feed additives (The European Parliament and The Council of The European Union, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and further banned flavomycin, avilamycin, salinomycin, and monenomycin in 2006. U.S. conducted graded control over aminoglycosides, lincosamides, macrolides, penicillins, streptogramins, sulfonamides, and tetracyclines (U.S. Food and Drug Administration, 2013). China stopped the usage of LOM, PFX, OFL and NOR in food animals (Ministry of Agriculture of the PRC, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Besides, the residue of CIP, DC, DAN, and sulfonamides were controlled by food safety standards. These regulations merely based on control rules in certain fields, e.g, food safety and agriculture safety, which lack of reliable and comprehensive criteria to prevent and control the environment antibiotics. Also, most of the these antibiotics have relatively low ToxPi scores in this study. Based on the prioritized screen of this study, we found more antibiotics should be controlled, which indicate the need of supplementing the current lists of chemicals management, and provide a more reliable control criteria for drinking water source. For Liuxi River, the environmental toxic risks of MINO and RXM should be further concerned, and more stringent standards should be applied to OTC and TC. We strongly suggest to comprehensively monitor the antibiotics globally, and screen the prioritized compounds in different regions, which help to improve chemicals management strategy and implement the current control lists.\u003c/p\u003e\u003cp\u003eThis study adopt a new screening method which consider a number of core factors, including toxicity, ecological risk, health risk and detection rate, which make the screening of antibiotics for priority control more reliable. The method can help to guide prevention and control of antibiotics, avoid excessive and insufficient control. In addition, different priority control antibiotics can be grouped according to similar ToxPi shape, provides the basis for the classification and control of antibiotics. The screening and prioritization methods on antibiotics can also be generalized in controlling other pollutants and in other basins. However, the limitations of screening method in this study still needs improvement. This case study only conducted screening and prioritization for 40 representative antibiotics, and the actual ecological and health risks may be higher considering the large number of unidentified antibiotics. Also, the antibiotic concentrations was measured in only two seasons, which may not wholly cover the seasonal variations of antibiotic concentrations. More frequent monitors and non-targeted screening are necessary for drinking water source, so as comprehensively master the antibiotic information and classify them, and obtain refined environmental control measures.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eIn this study, 40 antibiotics were detected in drinking water source in Guangzhou. The concentrations of antibiotics were much higher in dry season than in wet season. OTC and MINO had the highest concentration in dry season and SMX had the highest concentration in wet season. Except for MINO and OTC in dry season, most antibiotics had low ecological risk levels. Health risk for different age groups of the antibiotics in Liuxi river were within an acceptable range. Based on ToxPi score, the ten antibiotics, OTC, MINO, RXM, TC, DMC, ETM, SMX, LOM, DC, and CIP should be prioritized control to reduce their ecological and health risks. The screening method of prioritized antibiotics in this study could effectively screen prior-control antibiotics, and it can be further optimized and applied to other river basins.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLulu Zhang: Conceptualization, Methodology, Investigation. Lingyun Yu: Formal analysis, Software, Writing-original draft. Qianqian Yu: Writing-review \u0026amp; editing. Xuan Yu: Writing-review \u0026amp; editing. Sijia Liu: Writing-review \u0026amp; editing. Han Zhang: Software. Zhanlu Lv: Software. Qiusen Huang: Writing-review \u0026amp; editing. Ling-Chuan Guo: Resources, Writing-review \u0026amp; editing, Supervision, Data curation. Jingru Zhang: Writing-review \u0026amp; editing Investigation, Formal analysis, Resources, Supervision.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was financially supported by the Program Special fund project for environmental protection of Guangdong province (2022-18) and Special fund project for environmental protection of Guangdong province (2023-12).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArcega RD, Chen R, Chih P, Huang Y, Chang W, Kong T, Lee C, Mahmudiono T, Tsui C, Hou W, Hsueh H, Chen H (2023) Toxicity prediction: An application of alternative testing and computational toxicology in contaminated groundwater sites in Taiwan. 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Sci Total Environ 807:151040. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2021.151040\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.151040\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emvm","sideBox":"Learn more about [Environmental Management](http://link.springer.com/journal/267)","snPcode":"267","submissionUrl":"https://submission.nature.com/new-submission/267/3","title":"Environmental Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Antibiotics, Drinking Water Safety, ToxPi, Ecological Risk, Health Risk, Priority Control","lastPublishedDoi":"10.21203/rs.3.rs-7201162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7201162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eComprehensive assessment and screening of prioritized antibiotics are needed to control the increasing antibiotics contamination in drinking water sources. This study investigated 40 antibiotics in Liuxi River drinking water source in Guangzhou, screening and prioritization of antibiotics via toxicological priority index (ToxPi), which comprehensively considered their ecological risks, health risks, ecotoxicity, human health toxicity and other parameters. The total concentration of 40 antibiotics were much higher in the dry season than in the wet season. Among all the antibiotics, oxytetracycline and minocycline had highest levels in the dry season, while sulfamethoxazole had highest level in the wet season. Only minocycline and oxytetracycline had high and medium ecological risks in the dry season, respectively. Health risks of all the antibiotics were in an acceptable range. Ten antibiotics, e.g., oxytetracycline, minocycline, with the higher ToxPi score should be prioritized control to reduce their ecological and health risks. This study provides a soild reference for the screening and control of antibiotics in drinking water sources.\u003c/p\u003e","manuscriptTitle":"Screening and prioritization of antibiotics in drinking water source based on risk assessment, a case study in Guangzhou","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 05:03:26","doi":"10.21203/rs.3.rs-7201162/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-26T14:47:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-26T14:45:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245555657249329182491988554339997678795","date":"2025-10-21T09:49:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T20:38:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"243275825246102315260712033354998679918","date":"2025-09-02T07:57:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-19T13:10:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-13T16:42:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-24T06:21:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Management","date":"2025-07-24T03:55:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emvm","sideBox":"Learn more about [Environmental Management](http://link.springer.com/journal/267)","snPcode":"267","submissionUrl":"https://submission.nature.com/new-submission/267/3","title":"Environmental Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b4e09540-5e4f-4b01-b0a9-d9570feceb76","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T15:59:53+00:00","versionOfRecord":{"articleIdentity":"rs-7201162","link":"https://doi.org/10.1007/s00267-026-02391-7","journal":{"identity":"environmental-management","isVorOnly":false,"title":"Environmental Management"},"publishedOn":"2026-02-13 15:57:03","publishedOnDateReadable":"February 13th, 2026"},"versionCreatedAt":"2025-09-03 05:03:26","video":"","vorDoi":"10.1007/s00267-026-02391-7","vorDoiUrl":"https://doi.org/10.1007/s00267-026-02391-7","workflowStages":[]},"version":"v1","identity":"rs-7201162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7201162","identity":"rs-7201162","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}