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Due to the increase in electric energy consumption and the significant growth in the number of electric vehicles (EV) at the level of the distribution network, new networks have started using new fuels such as hydrogen to improve environmental indicators and at the same time better efficiency from the excess capacity of renewable resources. In this article, the services that can be provided by hydrogen refueling stations and charging electric vehicles in the optimal performance of microgrids have been investigated. The model proposed in this paper includes a two-stage stochastic framework for scheduling resources in microgrids, especially hydrogen refueling stations and electric vehicle charging. In this model, two main goals of cost minimization and greenhouse gas emissions are considered. In the proposed framework and in the first stage, the service range of microgrids is determined precisely according to the electrical limitations of distribution systems in emergency situations. Then, in the second stage, the problem of energy management in each microgrid will be solved centrally. In this situation, various indicators including the output energy of renewable sources, smart charging of hydrogen and electric vehicle charging stations (EV/FCV) and flexible loads (FL) are evaluated. The final mathematical model is implemented as a multivariate integer multiple linear problem (MILP) using the GUROBI solver in GAMS software. The simulation results on the modified IEEE 118-Bus network show the positive effect of the presence of flexible loads and smart charging strategies by charging stations. Also, the numerical derivation shows that the operating costs of the entire system can be reduced by 4.77% and the use of smart charging strategies can reduce greenhouse gas emissions by 49.13%. • Embedding network security constraints to ensure that each microgrid operates within safe voltage levels and avoids line capacity. • Examining the impacts of flexible loads and the charging patterns of EVs and FCVs on operational costs. • Incorporating hydrogen storage systems and refueling stations in the model to mitigate the adverse effects of renewable energy fluctuations. • Establishing a multi-objective model to consider both economic and environmental aspects of energy management in the proposed model. [ABSTRACT FROM AUTHOR]

The extent of pollution in areas near industrial activities and Yamuna River has increased tremendously and to determine the overall water quality status in these locations is utmost important. This paper presents a comprehensive study on assessing the water quality and gain insights into the overall water quality status in the vicinity of industries and along the Yamuna River in Delhi. To achieve this, water samples were collected from Central Pollution Control Board (CPCB) for the last eight years (2013-2021) and was converted into a machine-readable format to facilitate further analysis. These samples were analysed for several water quality parameters, including pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), nutrient levels, heavy metals, and other relevant pollutants. By understanding these factors, a deeper understanding of the pollution sources and their impact on water quality is gained. Time series methods are applied to forecast future trends and values of the water quality parameters. This allows for predicting potential changes in water quality over time. A remarkable accuracy of 93.6% is attained in predicting water quality values up to the present time. The analysis reveals that water quality in the NCR region falls below acceptable standards. However, there has been a marginal enhancement in the water quality at Khajori Paltoon (Location L3) post-COVID. To achieve a more significant improvement in water quality, it is imperative to implement new policies. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance in the laying hen production industry has become a serious public health problem. The antimicrobial resistance and phylogenetic relationships of the common conditional pathogen Enterococcus along the laying hen production chain have not been systematically clarified. 105 Enterococcus isolates were obtained from 115 environmental samples (air, dust, feces, flies, sewage, and soil) collected along the laying hen production chain (breeding chicken, chick, young chicken, and commercial laying hen). These Enterococcus isolates exhibited resistance to some clinically relevant antibiotics, such as tetracycline (92.4%), streptomycin (92.4%), and erythromycin (91.4%), and all strains had multidrug resistance phenotypes. Whole genome sequencing characterized 29 acquired antibiotic resistance genes (ARGs) that conferred resistance to 11 classes of antibiotics in 51 pleuromutilin-resistant Enterococcus isolates, and lsa(E) , which mediates resistance to pleuromutilins, always co-occurred with lnu(B). Alignments with the Mobile Genetic Elements database identified four transposons (Tn554, Tn558, Tn6261, and Tn6674) with several ARGs (erm(A), ant(9)-la, fex(A) , and optrA) that mediated resistance to many clinically important antibiotics. Moreover, we identified two new transposons that carried ARGs in the Tn554 family designated as Tn7508 and Tn7492. A complementary approach based on conventional multi-locus sequence typing and whole genome single nucleotide polymorphism analysis showed that phylogenetically related pleuromutilin-resistant Enterococcus isolates were widely distributed in various environments on different production farms. Our results indicate that environmental contamination by antimicrobial-resistant Enterococcus requires greater attention, and they highlight the risk of pleuromutilin-resistant Enterococcus and ARGs disseminating along the laying hen production chain, thereby warranting effective disinfection. [Display omitted] [ABSTRACT FROM AUTHOR]

Despite the high frequency and clinical relevance of canine pyometra, its pathogenesis remains poorly understood. In this study, the clinical data, histopathological alterations, and microbiological findings of 39 dogs with pyometra were analyzed to assess possible associations. The mean age of the affected animals was 9.6 ± 3.8 years; 76.3 % (29/38) had open cervix pyometra, 88 % (22/25) had tachypnea, 71 % (27/38) had anorexia, and 60.5 % (23/38) had leukocytosis. Histopathological analysis revealed that 66.5 % (26/39) of the uteri had a high degree of inflammation (score 4). Third-degree hyperplasia of the endometrial epithelium (72 %, 28/39) and intralesional or intrauterine bacteria (66.5 %, 26/39) were identified in most animals. Bacterial isolates were obtained from 82 % (32/39) of the uterine contents and five bacterial species were identified. Escherichia coli , classified in phylogroup B2, is associated with virulent adhesion genes (fimH , focG , and papC), and serum resistance (traT) was the most common isolate. There was an association between the detection of papC in E. coli isolates and higher necrosis scores. Additionally, the necrosis score was positively associated with the length of hospitalization, with each point increase in the necrosis score leading to two more days of hospitalization. These results suggest that papC -positive E. coli play an important role in the severity of pyometra in dogs. The present study revealed the possibility of using this virulence gene to better understand the prognosis of the disease in an affected animal. • A total of 39 dogs with pyometra were deeply investigated. • Most animals had open cervix pyometra and hyperplasia of the endometrial epithelium. • Escherichia coli from the phylogroup B2 was the most common bacteria isolated. • Detection of papC in E. coli isolates was associated with higher uterine necrosis. • Dogs with higher uterine necrosis needed higher length of hospitalization. [ABSTRACT FROM AUTHOR]

Since many waterborne diseases are caused by human pathogenic viruses, virus monitoring of drinking water (DW) and DW sources is crucial for public health. Therefore, the aim of this review was to describe the occurrence of human pathogenic viruses in DW and DW sources; the occurrence of two viruses proposed as novel indicators of human faecal contamination (Pepper mild mottle virus and Tobacco mosaic virus) was also reported. This research was focused on articles that assessed viral occurrence using molecular methods in the surface water used for DW production (SW-D), groundwater used for DW production (GW-D), DW and bottled-DW (BW). A total of 1544 studies published in the last 10 years were analysed, and 79 were ultimately included. In considering the detection methods, filtration is the most common concentration technique, while quantitative polymerase chain reaction is the most common quantification technique. Regarding virus occurrence in SW-D, GW-D, and DW, high percentages of positive samples were reported for adenovirus, polyomavirus and Pepper mild mottle virus. Viral genomes were frequently detected in SW-D and rarely in GW-D, suggesting that GW-D may be a safe DW source. Viral genomes were also detected in DW, posing a possible threat to human health. The lowest percentages of positive samples were found in Europe, while the highest were found in Asia and South America. Only three articles assessed viral occurrence in BW. This review highlights the lack of method standardization and the need for legislation updates. [Display omitted] [ABSTRACT FROM AUTHOR]

Dangerous drug multi-resistant strains of bacteria from the Enterobacteriaceae family are responsible for the deaths of thousands of people every year. The intestinal bacilli are found in large amounts in wastewater and sewage sludge as they are transported with human and animal feces. In the study, microbiological analysis of raw dewatered sewage sludge was performed using Microgen's GNA + B biochemical multi-tests. Isolation of intestinal bacteria was carried out on ENDO agar. Determination of susceptibility of isolated and identified intestinal bacteria to drugs was carried out using ampicillin, co-amoxiclav, cefazolin, cefuroxime, ceftazidime, amikacin, gentamicin, and ciprofloxacin. Antibiograms were performed using Mueller-Hinton II agar. The presence of seven species of intestinal bacteria was found before liming of sewage sludge, including two strains of Escherichia coli which demonstrate resistance to ampicillin and amoxicillin with clavulanic acid. Furthermore, the following bacteria from the Enterobacteriaceae family were also present: Klebsiella pneumoniae, Morganella morganii, Citrobacter freundii, Yersinia aldovae, Serratia marcescens and Enteric Group 68. They showed typical susceptibility to the antibiotics used in the study. The bacteria count in species isolated on ENDO agar ranged from 3.6 to 4.9 x 108 CFU/g. Three doses of Ca(OH)2 expressed as CaO weight were used for liming: 0.1, 0.2, and 0.4 kg/kg·d.m. of dewatered sludge. After a three-month process, the following intestinal bacilli were detected in the tested material: Morganella morganii, Serratia odorifera, Providencia rettgeri, Providencia stuartii, Proteus vulgaris. Providencia stuartii, Proteus vulgaris, Morganella morganii and Serratia odorifera proved to be drug-resistant. Bacteria from the Alcaligenes faecalis, Pseudomonas stutzeri, Pseudomonas fluorescens and Acinetobacter lwoffi species were also found. Liming process led to a reduction in the number of intestinal bacteria of 6-8 orders of magnitude of the baseline values. None of the doses were able to eliminate Enterobacteriaceae bacteria from the sludge. [ABSTRACT FROM AUTHOR]

[Display omitted] • The gut virome research in colorectal cancer and adenoma includes >1,200 samples. • Siphoviridae and Microviridae viruses were notably different between controls and CRC patients. • The viral markers of colorectal cancer and adenoma were identified. • For CRC patients, our model had better predictive ability than other bacteria-based models. • The virome analysis achieved an optimal AUC of 0.772 to distinct adenoma patients and controls. Viruses have been reported as inducers of tumorigenesis. Little studies have explored the impact of the gut virome on the progression of colorectal cancer. However, there is still a problem with the repeatability of viral signatures across multiple cohorts. The present study aimed to reveal the repeatable gut vial signatures of colorectal cancer and adenoma patients and decipher the potential of viral markers in disease risk assessment for diagnosis. 1,282 available fecal metagenomes from 9 published studies for colorectal cancer and adenoma were collected. A gut viral catalog was constructed via a reference-independent approach. Viral signatures were identified by cross-cohort meta -analysis and used to build predictive models based on machine learning algorithms. New fecal samples were collected to validate the generalization of predictive models. The gut viral composition of colorectal cancer patients was drastically altered compared with healthy, as evidenced by changes in some Siphoviridae and Myoviridae viruses and enrichment of Microviridae, whereas the virome variation in adenoma patients was relatively low. Cross-cohort meta -analysis identified 405 differential viruses for colorectal cancer, including several phages of Porphyromonas, Fusobacterium, and Hungatella that were enriched in patients and some control-enriched Ruminococcaceae phages. In 9 discovery cohorts, the optimal risk assessment model obtained an average cross-cohort area under the curve of 0.830 for discriminating colorectal cancer patients from controls. This model also showed consistently high accuracy in 2 independent validation cohorts (optimal area under the curve, 0.906). Gut virome analysis of adenoma patients identified 88 differential viruses and achieved an optimal area under the curve of 0.772 for discriminating patients from controls. Our findings demonstrate the gut virome characteristics in colorectal cancer and adenoma and highlight gut virus-bacterial synergy in the progression of colorectal cancer. The gut viral signatures may be new targets for colorectal cancer treatment. In addition, high repeatability and predictive power of the prediction models suggest the potential of gut viral biomarkers in non-invasive diagnostic tests of colorectal cancer and adenoma. [ABSTRACT FROM AUTHOR]

A typical anthropogenically disturbed urban river polluted by a combination of conventional pollutants (nitrogen and phosphorus pollution) and heavy metals was investigated along a 238 km stretch. Changes in the bacterial community were evaluated using high-throughput sequencing, and the relationships between bacteria, heavy metals, and conventional pollutants were investigated. There was large spatial heterogeneity in the bacterial community along the river, and bacterial diversity in the upstream and midstream sections was much higher than in the downstream section. Heavy metals and conventional pollutants both exhibited close correlations with bacterial diversity and composition. For instance, potential fecal indicator bacteria, sewage indicator bacteria and pathogenic bacteria, such as Ruminococcus and Pseudomonas , were closely associated with Cu, Zn, and NH 4 +-N. Rather than conventional pollutants, heavy metals were the main driving factors of the microbial community characteristics. These results confirm that bacterial communities play a crucial role in biogeochemical cycles. Therefore, heavy metals could be used as biomarkers of complex pollution to indicate the pollution status of riverine ecosystems and contribute to the restoration of habitats in anthropogenically disturbed urban rivers. [Display omitted] [ABSTRACT FROM AUTHOR]

This study explored the effects of H 2 O 2 on Cyanobacteria and non-target microbes using fluorometry, microscopy, flow cytometry, and high throughput DNA sequencing of the 16S rRNA gene during a series of mesocosm and whole-ecosystem experiments in a eutrophic pond in NY, USA. The addition of H 2 O 2 (8 mg/L) significantly reduced Cyanobacteria concentrations during a majority of experiments (66%; 6 of 9) and significantly increased eukaryotic green and unicellular brown algae in 78% and 45% of experiments, respectively. While heterotrophic bacteria declined significantly following H 2 O 2 addition in all experiments, bacteria indicative of potential fecal contamination (Escherichia coli, Enterococcus , fecal coliform bacteria) consistently and significantly increased in response to H 2 O 2 , evidencing a form of 'pollution swapping'. H 2 O 2 more effectively reduced Cyanobacteria in enclosed mesocosms compared to whole-ecosystem applications. Ten whole-pond H 2 O 2 applications over a two-year period temporarily reduced cyanobacterial levels but never reduced concentrations below bloom thresholds and populations always rebounded in two weeks or less. The bacterial phyla of Cyanobacteria, Actinobacteria, and Planctomycetes were the most negatively impacted by H 2 O 2. Microcystis was always reduced by H 2 O 2 , as was the toxin microcystin, but Microcystis remained dominant even after repeated H 2 O 2 treatments. Although H 2 O 2 favored the growth of eukaryotic algae over potentially harmful Cyanobacteria, the inability of H 2 O 2 to end cyanobacterial blooms in this eutrophic waterbody suggests it is a non-ideal mitigation approach in high biomass ecosystems and should be used judiciously due to potential negative impacts on non-target organisms and promotion of bacteria indicative of fecal contamination. [Display omitted] [ABSTRACT FROM AUTHOR]

• Stormwater microbial contamination arising from human fecal matter was studied. • The human fecal contamination analog (HFCA) describes stormwater contamination. • Human pathogens and microbial source tracking markers were used to estimate HFCA. • Human tracking markers datasets were more appropriate than pathogen datasets. • HFCA estimates will inform stormwater treatment targets based on intended end uses. Stormwater capture and use (SCU) projects have the potential to provide a significant portion of municipal water demand. However, uncertainty about the degree of microbial contamination in stormwater and the required treatment is a barrier for implementation of SCU projects. Stormwater runoff could become contaminated with human fecal matter in areas with deteriorating infrastructure where raw wastewater exfiltrates from sewer networks to stormwater collection networks, homeless encampments exist, or sanitary sewer overflows (SSOs) occur. Estimation of human fecal contamination can inform selection of stormwater treatment targets. This study investigates stormwater microbial contamination originating from human fecal matter using observed detections and concentrations of human microbial source tracking (MST) markers and potentially human-infectious pathogens (PHIPs). First, a systematic review complied measurements of human MST markers in wet and dry weather stormwater flows and influent wastewater. In addition, measurements of viral pathogens (e.g., adenoviruses, norovirus GI+GII, and enteroviruses) and protozoan pathogens (e.g., Giardia lamblia and Cryptosporidium parvum) in wet weather flows and influent wastewater were assessed. Human MST marker and PHIP data were statistically analyzed and applied to estimate a human fecal contamination analog (HFCA) which is an estimate of the amount of human fecal matter based on relative concentrations of microbial contaminants in stormwater compared to municipal wastewater. Human MST-based HFCAs in wet and dry weather flows ranged from <10−7.0 to 10−1.5 (median = 10−4.5) and 10−12 to 10−2.6 (median = 10−7.0), respectively. PHIP-based HFCAs in wet weather flows ranged from ∼10−8 to 10−0.14. Estimates of human MST-based HFCAs are more reliable than PHIP-based HFCAs because the current PHIP datasets are generally limited by the number of data points, percent detection, variability observed within the statistical distributions, and the geographical span of sampling locations. The use of human MST-based HFCAs is recommended to guide the selection of stormwater treatment process trains that are protective of public health based on the intended end use. Application of HFCA 10−1 (i.e., sewage dilution 10−1) remains a reasonable conservative estimate of human fecal contamination in stormwater to inform selection of pathogen log reduction targets based on the data presently available. [Display omitted] [ABSTRACT FROM AUTHOR]

Raw milk is considered a high-risk source of Campylobacter due to faecal contamination from healthy cattle and farm environments, thus linking raw milk consumption to global outbreaks. Detection of Campylobacter in raw milk poses challenges due to low contamination levels and antibacterial properties of the milk. Culture-based protocols for Campylobacter detection in milk vary, mainly with regard to pH adjustment and the choice of enrichment broth. This European collaborative study was organised by the EU Reference Laboratory (EURL) for Campylobacter together with eight EU National Reference Laboratories (NRL) for Campylobacter with the purpose to evaluate methods for culture-based detection of Campylobacter in raw cow's milk. The study was divided into two parts, an interlaboratory part and an intralaboratory part, both organised around the same two protocols. The aim of protocol 1 was to evaluate the impact of pH adjustment and storage of the milk on the culturability of Campylobacter over time. Aliquots of the spiked milk were adjusted either to pH 7.0 or pH 7.6 or left unadjusted. The milk was stored up to 48 h at refrigerated temperature and Campylobacter was quantified according to ISO 10272-2 on day 0, 1 and 2. The aim of protocol 2 was to evaluate which enrichment broth, Bolton broth (BB) or Preston broth (PB), showed highest sensitivity in detection of Campylobacter. The spiked milk was enriched in BB and PB as described in ISO 10272-1:2017 or ISO 10272-1:2017/Amd1.2023. In the interlaboratory part, each milk batch was collected locally by each participating NRL/EURL and inoculated with the same Campylobacter strain. In the follow-up intralaboratory part, the EURL- Campylobacter repeated the tests in protocol 1 and 2 but used different Campylobacter strains and strains subjected to thermal stress prior to inoculation. The results show that pH adjustment of raw milk has a negligible impact on culture-based detection of Campylobacter , regardless of strain and level of environmental stress. The composition of milk and properties of the inoculated strain influence culture-based detection of Campylobacter over storage time, and strains subjected to additional stress prior to inoculation in milk are reduced in culturability much faster than the same strains prepared under normal conditions. Finally, the study showed that PB without Campylobacter growth supplement is less effective than BB in detecting Campylobacter in raw milk. • Adjustment of pH in raw milk has a negligible impact on culture-based detection of Campylobacter. • The milk composition and Campylobacter strain influence culture-based detection of Campylobacter over time • Raw milk should be analysed within 24 hours for detection of Campylobacter • Preston broth without FBP is less effective than Bolton broth in detecting Campylobacter in raw milk [ABSTRACT FROM AUTHOR]

The burden of foodborne disease due to the consumption of animal-sourced foods is substantial in low- and middle-income countries (LMICs). Open air markets, while providing fresh and affordable foods, often have unhygienic practices that may contribute to contamination during the slaughter and processing of chicken meat. This study examines whether and how the common practice of rinse water (stored water used for rinsing broiler carcasses during processing) reuse leads to accumulation of pathogens, with potential cross contamination of chicken meat. To assess the accumulation of Campylobacter jejuni/coli , Salmonella spp., and the indicator of fecal contamination, Escherichia coli , in rinse water used during the slaughtering process at open air food markets in Maputo, Mozambique. We conducted a time-series study at three open air food markets. In a first experiment, we collected paired rinse water (N = 70), water used for chicken processing, and broiler chicken carcass (N = 60) samples from 10 vendors at 75-min intervals starting prior to any processing activity. In a second experiment, we collected 100, 50 mL rinse water samples, immediately before and after processing, from 10 vendors. Chicken processing activity and associated hygiene practices were captured through direct observation. Vendors processed 24 chickens per day, on average. In the first experiment, C. jejuni/coli and E. coli were detected in 30 % and 80 % of rinse water samples, respectively, prior to processing (baseline), and no Salmonella was detected. After the first carcass rinse, C. jejuni/coli and E. coli were detected in 100 % of samples, and Salmonella spp. was detected in 42 % of rinse water samples and 48 % of carcass samples. C. jejuni/coli showed an average 0.1 log 10 copies (95 % CI 0.0, 0.2) increase in rinse water and carcass samples every 75 min. In the second experiment, no C. jejuni/coli or Salmonella spp. were detected in baseline rinse water samples, and E. coli were detected in 78 % of baseline rinse water samples. After processing the first carcass, C. jejuni/coli were detected in 100 % of remaining samples, Salmonella spp. were detected in 28 % of pre-final rinse and 36 % of post-final rinse samples, and E. coli were detected in 81 % of pre-final rinse and 100 % of post-final rinse samples. Our results reveal that consumers are at a high risk of purchasing chicken meat contaminated with human enteropathogens. Once contaminated, rinse water stays contaminated throughout the day. Low-cost and feasible interventions implemented at the carcass wash step are needed to reduce microbial hazards on chicken meat before purchase. • Chicken at markets in Maputo, Mozambique was contaminated with C. jejuni , Salmonella , and E. coli. • Enteric pathogens accumulate and remain elevated in slaughter rinse water throughout the day. • The rinse step during slaughter is insufficient in improving the microbial quality of chicken meat. • Sufficient water quality and quantity are critical for hygienic chicken processing. [ABSTRACT FROM AUTHOR]

This study investigates radon concentration in drinking water from twenty samples collected at two tertiary Institutions in Ikorodu, Lagos State, using the RAD-7 detector. The objective is to evaluate the health risks associated with radon exposure, a known carcinogen linked to lung and stomach cancer. Radon in drinking water contributes to approximately 168 cancer deaths annually, predominantly from lung cancer due to inhalation of radon released indoors and stomach cancer from ingesting contaminated water. The measured radon concentrations ranged from 4.5 ± 1.1 Bq/m³ to 25.5 ± 2.1 Bq/m³, with 70% of samples exceeding the EPA's maximum contamination level of 11.1 Bq/L. Despite these high levels, the annual effective doses from ingestion and inhalation varied from 0.4545 to 24.37 μSv/y, remaining below the global average of 300 μSv/y and WHO limit of 100 μSv/y. While the presence of radon in Ikorodu's water sources indicates a radiological risk, the associated health risks are comparatively low according to international standards. These findings underscore the importance of ongoing monitoring and potential mitigation measures to ensure the continued safety of drinking water in the region. • RAD7 was used to measure radon gas concentrations in various water sources from the Ikorodu axis of Lagos State, Nigeria. •70% of the collected water samples exceeded the maximum contamination level of 11.1 Bq/L. •These water sources may not be entirely safe for human consumption and daily use. •Monitoring and mitigation measures may still be warranted to ensure the continued safety of these water sources. [ABSTRACT FROM AUTHOR]

In Ontario, monitoring, maintenance, and treatment of private drinking systems (e.g. wells) are the responsibility of the well owner. Fecal contamination of drinking water threatens public health, particularly in rural communities which are often fully reliant on unregulated private groundwater as a primary drinking water source. Private well users face a higher risk of acute gastrointestinal illness compared to those served by municipally operated systems (Murphy et al., 2016). Accordingly, the current study sought to characterize the fecal indicator, E. coli , isolated from southeastern Ontario private groundwater wells, including phylogroups and host source. Results were examined in the context of antecedent climate and local hydrogeological setting to elucidate likely contaminant sources and pathways. A total of 737 E. coli isolates from 260 private wells were assigned to phylogroups using the Clermont PCR phylotyping method, with likely host source determined using host-specific Bacteroidales 16S rRNA RT qPCR assays. Multivariate models were developed for the main E. coli phylogroups (A, B1, B2, and D) and all microbial source tracking markers. Models were coupled for interpretation where possible, based on associations between phylogroups and MST markers. Preferential subsurface flow, and to a lesser degree, overland flow, were likely mechanisms of contamination across all models. Distinct temporal associations were found based on the fecal source. Multiple models were developed and will be discussed, in an attempt to elucidate source-specific contamination mechanisms, in support of risk assessment and appropriate protective actions. [Display omitted] • Collected 737 E. coli isolates from 260 private wells over two years. • Multivariate models of contamination using E. coli phylogroup and MST markers. • Distinct temporal associations found based on fecal source. • Preferential subsurface flow a likely contamination mechanism across all models. • Concurrent model suggests multiple simultaneous contamination mechanisms. [ABSTRACT FROM AUTHOR]

• The FEAST microbial source tracking tool correctly identifies dominant faecal sources. • Proportional source attribution was generally underestimated. • When interpreted appropriately, FEAST may be a useful addition to the toolbox for faecal source identification. Faecal contamination of freshwater and marine environments represents a significant risk for public health, recreational activity and food safety, and tools for evaluating complex multi-source contamination remain largely in the development phase. We evaluated the efficacy of the Fast Expectation Maximization (FEAST) microbial source tracking (MST) algorithm to apportion sources of faecal contamination among four mammalian species of interest in coastal waters in New Zealand. Using 16S ribosomal DNA metabarcoding of faecal samples from cows, fur seals, and sheep, as well as human wastewater, we aimed to differentiate and quantify the contribution of these sources in mixed faecal samples. Multivariate analysis confirmed significant differences in the microbial communities associated with each mammalian source, with specific bacterial classes indicative of different sources. The FEAST algorithm was tested using mixed DNA and mixed faecal samples, and we found that the algorithm correctly assigned the dominant source from all samples, but underestimated the dominant source's proportional contribution. This underestimation suggests the need for further refinement and validation to ensure accurate source apportionment in environmental samples where the faecal signal is likely to be a minor component. Despite these limitations, the findings of our study, in combination with the evidence from others who have tested the FEAST algorithm in environmental settings, indicates that it represents an advance on existing tools for microbial source tracking and may become a useful addition to the toolbox for environmental management. [Display omitted] [ABSTRACT FROM AUTHOR]

• MHP of CLPs exhibited a stronger sequence homology within each genus group. • CLPs were detected in 91.52% of humans. • Group VI showed the highest prevalence, nearly twice that of p-crAssphage. • CLPs were not detected in animal feces except in raccoons. CrAssphage has been recognized as the most abundant and human-specific bacteriophage in the human gut. Consequently, crAssphage has been used as a microbial source tracking (MST) marker to monitor human fecal contamination. Many crAss-like phages (CLPs) have been recently discovered, expanding the classification into the new order Crassvirales. This study aims to assess CLP prevalence in South Korea and develop a detection system for MST applications. Thirteen CLPs were identified in six human fecal samples and categorized into seven genera via metagenomic analysis. The major head protein (MHP) displayed increased sequence similarity within each genus. Eight PCR primer candidates, designed from MHP sequences, were evaluated in animal and human feces. CLPs were absent in animal feces except for those from raccoons, which hosted genera VI, VIIa, and VIIb. CLPs were detected in 91.52% (54/59) of humans, with genus VI (38 out of 59) showing the highest prevalence, nearly double that of p-crAssphage in genus I (22 out of 59). This study highlights genus VI as a potent MST marker, broadening the detection range for CLPs. Human-specific and selectively targeted MST markers can significantly impact hygiene regulations, lowering public health costs through their application in screening liver, sewage, wastewater, and various environmental samples. [Display omitted] [ABSTRACT FROM AUTHOR]

• Fecal pollution is the primary source of virus contamination in urban aquifers. • Viral passive samplers increase the likelihood of virus detection in groundwater. • Target enrichment sequencing unveiled a broad spectrum of human and animal viruses. • VPS offers a time-integrated method for sampling multiple wells simultaneously. • Virome characterization of groundwater can influence local groundwater management. Aquifers, which provide drinking water for nearly half the world's population, face significant challenges from microbial contamination, particularly from waterborne viruses such as human adenovirus (HAdV), norovirus (NoV) and enterovirus (EV). This study, conducted as part of the UPWATER project, investigates the sources of urban groundwater contamination using viral passive sampling (VPS) and target enrichment sequencing (TES). We assessed the abundance of eight viral pathogens (HAdV, EV, NoV genogroup I and II, rotavirus, influenza A virus, hepatitis E virus and SARS-CoV-2) and investigated the virome diversity of groundwater in the aquifer of the Besòs River Delta in Catalonia. Over a period of 7 months, we collected 114 samples from the aquifer using nylon and nitrocellulose membranes to adsorb viruses over a 10-day period. Human faecal contamination was detected in nearly 50 % of the groundwater samples, with mean HAdV total counts ranging from 1.23E+02 to 3.66E+03 GC, and occasional detections of EV and NoV GI and GII. In addition, deep sequencing revealed a diverse virome in the aquifer, with detection of human pathogens, including adenovirus, astrovirus, calicivirus, enterovirus, herpesvirus, papillomavirus and rotavirus. Time-integrated sampling using VPS increases the likelihood of virus detection and, when combined with TES, can provide a deeper understanding of virus prevalence in this important water compartment. This approach is expected to streamline long-term monitoring efforts and enable small communities or water managers with limited resources to effectively manage their groundwater reservoirs. [Display omitted] [ABSTRACT FROM AUTHOR]

Plastic pollution in the marine ecosystem and their sources have been widely investigated, however some parts of the world remain under studied. Herein, we report on plastic pollution in the Namibian marine ecosystem, based on data collected by fisheries observers between 2003 and 2020 during commercial fishing activities. A total of 79 plastic pollution incidents were reported between 2003 and 2020, which consisted of unspecified non-biodegradable objects (55.7%), unspecified plastic items (25.3%), fishing gear (8.9%), plastic bottles (5.0%), plastic gloves (1.3%) and single-use plastic bags (3.8%). We found no significant Pearson correlation between the number of disposal incidents and the fisheries observer coverage (r = 0.3254, df = 14, p = 0.2187). The spatial analysis in the disposal of non-biodegradable objects show a fair distribution along the Namibian coast with more concentrations around latitude 18⁰S, 22⁰S, and 26⁰S. We conclude that fishing vessels are important marine-based sources of plastic pollution, highlighting a continuous need to raise awareness over the fishing industry, in particular seafarers, on plastic use and management. The study expands the plastic pollution knowledge by quantifying incidents of plastic pollution, plastic litter composition, and identifying spatial distribution in the Namibian waters, thus, to the best of our knowledge, represents a baseline for studies on marine plastic pollution in this oceanic region. Identifying sources of marine plastic litter and providing a spatial picture is a step closer to develop and implement specific regulatory tools to combat marine pollution. [ABSTRACT FROM AUTHOR]

Cryptosporidium and Giardia genus negatively impact the production of small ruminants. This study aimed to determine the prevalence of infection by Cryptosporidium spp. and Giardia spp. and to assess associated risk factors in sheep from Brazil. We collected fecal samples (n = 459) from animals aged up to twelve months old. Samples were processed using formalin-ether centrifuge-sedimentation techniques with modified Ziehl-Neelsen staining for Cryptosporidium spp. and zinc sulfate centrifuge-flotation for Giardia spp. We calculated the Odds Ratio (OR) to determine associations between different variables and positivity. In total, 27.45 % (n = 126/459; 95 % CI = 23.57 – 31.71) of the animals were infected by Cryptosporidium spp., 13.29 % (n = 61/459; 95 % CI = 10.49 – 16.70) by Giardia spp., and in 3.05 % (n = 14/459; 95 % CI = 1.83 – 5.05) both parasites were detected. Cryptosporidium spp. (χ2 = 28.373; p < 0.0001) predominated in the sheep population. Intensive farming (OR = 3.87; p < 0.0001), herds with 51–80 animals (OR = 3.60; p < 0.0001), no chloride water (OR = 2.0; p = 0.0167), no manure removal (OR = 3.2; p < 0.0001), dirt floors (OR = 6.8; p < 0.0001), and the presence of flies (OR = 2.0; p = 0.0096) were considered risk factors for Cryptosporidium spp. infection. The presence of cohabitating species (OR = 2.1; p = 0.0358) and the presence of dogs or cats (OR = 4.5; p < 0.0001) were risk factors for Giardia spp. infections. Our data demonstrate the need to implement prophylactic actions on the evaluated properties to minimize economic losses and the impact on overall health resulting from infections by Cryptosporidium spp. and Giardia spp. • Cryptosporidium and Giardia genus negatively impact the production of small ruminants. • This study detected a high prevalence of infection by Cryptosporidium and Giardia parasites. • Fecal contamination of water and food were risk factors for both infections. • It is necessary to implement prophylactic actions on the evaluated municipalities. [ABSTRACT FROM AUTHOR]

Water quality monitoring plays an essential role in environmental management and the protection of water resources. However, the increasing risks of pollution make the process of monitoring using conventional methods more complex and costly. Currently, the use of automated processes based on artificial intelligence and machine learning techniques has become necessary in the field of water quality control to achieve quality control and reduce operating costs. This paper presents a comparative study of three machine learning techniques, namely K-nearest neighbors (KNN), decision tree (DT), and support vector machine (SVM), for the water quality classification of Tilesdit Dam (Algeria). Furthermore, the kernel principal component analysis (KPCA) technique was utilized to choose the important variables for water quality classification. The models were trained and tested based on historical data collected from the dam monitoring station for 3 y (2016-2018). The results of the study indicated that a combination of KPCA and DT techniques gave the best performance, with a classification accuracy of 99.68%. [ABSTRACT FROM AUTHOR]

Background: Herbs and spices are rich in polyphenolic compounds that may influence gut bacterial composition. The effect of culinary doses of herbs and spices consumed as part of a well-defined dietary pattern on gut bacterial composition has not been previously studied.Objectives: The aim of this pre-specified exploratory analysis was to examine gut bacterial composition following an average American diet (carbohydrate: 50% kcal; protein: 17%; total fat: 33%; saturated fat: 11%) containing herbs and spices at 0.5 (Low Spice Diet; LSD), 3.3 (Moderate Spice Diet; MSD) and 6.6 (High Spice Diet; HSD) g.d-1.2100 kcal-1 in adults at-risk for cardiovascular disease (CVD).Design: Fifty-four adults (57% female; mean ± SD age 45 ± 11 years, BMI 29.8 ± 2.9 kg/m2; waist circumference 102.8 ± 7.1 cm) were included in this three-period, randomized, crossover, controlled-feeding study. Each diet was provided for 4-weeks with a minimum 2-week wash-out period. At baseline and the end of each diet period participants provided a fecal sample for 16S rRNA gene (V4 region) sequencing. QIIME2 was used for data filtration, sequence clustering, taxonomy assignment and statistical analysis.Results: Alpha diversity assessed by the Observed Features metric (p = 0.046) was significantly greater following the MSD vs. the LSD; no other between diet differences in alpha diversity were detected. Differences in beta-diversity were not observed between the diets (p = 0.45). Compared to baseline, beta-diversity differed following all diets (p < 0.02). Enrichment of the Ruminococcaceae family was observed following the HSD vs. the MSD (relative abundance (RA) = 22.14%; LDA = 4.22; p = 0.03) and the LSD (RA = 24.90%; LDA = 4.47; p = 0.004).Conclusions: The addition of herbs and spices to an average American diet induced shifts in gut bacterial composition after 4-weeks in adults at risk for CVD. The metabolic implications of these changes merits further investigation. Clinical Trial Registry: NCT03064932. [ABSTRACT FROM AUTHOR]

The increasing occurrence of pharmaceuticals in the ecosystem is considered a global concern. These substances easily reach water and wastewater treatment systems and water bodies through the industrial, hospital, and residential effluent discharges, human and animal urine and feces, fertilizers, and disposal of medicines in common garbage or sinks. These drugs, even at low concentrations, when present in the environment, can cause changes in the endocrine, immune, and reproductive systems of living things there. In this context, this article presented an overview of where drugs such as caffeine, paracetamol, and diclofenac were found worldwide. In addition, this review set out to discuss how these drugs affect the quality of the water and all the beings around it. Therefore, this review aims to provide a deeper and more critical systematic approach to non-conventional processes such as adsorption, advanced oxidative processes, and membranes that can be employed to remove caffeine, paracetamol, and/or diclofenac from water. To this end, theoretical concepts were expounded, and scientific articles published in the literature on these advanced treatments between 2010 and 2022 were analyzed. This review will be valuable for researchers studying advanced processes to remove emerging contaminants. [Display omitted] [ABSTRACT FROM AUTHOR]

• Fallow age and cattle grazing affect plant functional traits. • In early succession, functional traits are associated with water conservation. • In late succession, functional traits are linked to sunlight acquisition. • In cattle present, plants showed functional traits related to defense against herbivory. • Soil nutrients increase with fallow age driving changes in plant functional traits. Evaluating plant functional traits helps to understand how plants respond to changing environmental conditions and resource availability associated with disturbance events. Livestock production is one of the primary drivers of tropical forest loss and degradation. Livestock alter environmental conditions within the forest by grazing, trampling and nutrient inputs, which in turn can influence species composition and functional traits of species. Understanding how livestock influence functional traits along a successional gradient is poorly understood. Here, we studied the effect of cattle grazing and fallow age on plant functional traits and soil nutrients in secondary and old-growth tropical dry forests. We analyzed plant functional traits of the most important species in successional and old-growth forest communities in both cattle present and cattle excluded plots. Our results showed the effects of cattle grazing and fallow age on plant functional traits, with fallow age explaining more variation than cattle grazing. In early succession, functional traits were associated with water conservation (thicker leaves, lower specific leaf area), and in later successional they were linked with sunlight conservation (larger height, higher specific leaf area). The presence of large fruits and seeds in advanced successional sites suggests high resource availability, which may help plants to successfully reproduce. Moreover, under cattle grazing some functional traits are associated with herbivory defense (high foliar dry weight and thick leaves). Even though N and C increased as succession advanced, the sites with cattle grazing had higher NH4 and NO3 concentrations as a result of fecal deposition. Plant functional traits responded to fallow age than to cattle grazing. Our study showed that cattle exclusion, as a management and biodiversity conservation strategy, contributes positively to soil nutrition. Thus, fallow age and cattle exclusion facilitate soil recovery and allows establishing species with suitable functional attributes for overcoming environmental filters in abandoned cattle fields. [ABSTRACT FROM AUTHOR]

In order to investigate the main factors that caused the Nitrate increasement in Huixian Wetland, 15N- NO3 and 18O- NO3 analysis were conducted. SIAR model was applied to quantitatively test the contribution proportions of kinds of pollutants. Health risk assessment (HRA) was taken to study ten heavy metals of 96 groups samples in the four main waters in Huixian Wetland: Surface River, Subterranean Stream, Blue Hole and Well Water. The main sources of Nitrate were domestic sewage and animal feces, chemical fertilizer, and soil, with the contribution proportions of 39.1%, 32.2%, and 28.5%, respectively. The heavy metals concentration order is that of Mn > Al > Cr > Zn > As > Pb > Cu > Fe > Cd > Hg. The HRA showed that the average annual total health risks-through drinking and skin penetration-order was: Well Water > Blue Hole > Subterranean Stream > Surface River. The drinking water from Well and Blue Hole can cause the cancer risks in children of 7.08 × 10−5 a−1 and 7.01 × 10−5 a−1, respectively. Both were higher than the recommendation standard (5.0 × 10−5 a−1) from ICRP. As the main element contributed to the health risk of adults and children, the Cr in all the four waters were also over the standard (1 × 10−6 a−1) recommended by the Swedish Environmenta1 Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The health risk levels of non-carcinogenic metals were 1 × 10−16–1 × 10−10, which were 5–11 order of magnitude lower than the acceptable level. [ABSTRACT FROM AUTHOR]

This paper reports on major outcomes of the ERA-PLANET (The European network for observing our changing planet) project, which was funded under Horizon 2020 ERA-net co-funding scheme. ERA-PLANET strengthened the European Research Area in the domain of Earth Observation (EO) in coherence with the European participation to Group on Earth Observation and the Copernicus European Union's Earth Observation programme. ERA-PLANET was implemented through four projects focused on smart cities and resilient societies (SMURBS), resource efficiency and environmental management (GEOEssential), global changes and environmental treaties (iGOSP) and polar areas and natural resources (iCUPE). These projects developed specific science-policy workflows and interfaces to address selected environmental policy issues and design cost-effective strategies aiming to achieve targeted objectives. Key Enabling Technologies were implemented to enhancing 'data to knowledge' transition for supporting environmental policy making. Data cube technologies, the Virtual Earth Laboratory, Earth Observation ontologies and Knowledge Platforms were developed and used for such applications. SMURBS brought a substantial contribution to resilient cities and human settlements topics that were adopted by GEO as its 4th engagement priority, bringing the urban resilience topic in the GEO agenda on par with climate change, sustainable development and disaster risk reduction linked to environmental policies. GEOEssential is contributing to the development of Essential Variables (EVs) concept, which is encouraging and should allow the EO community to complete the description of the Earth System with EVs in a close future. This will clearly improve our capacity to address intertwined environmental and development policies as a Nexus. iGOSP supports the implementation of the GEO Flagship on Mercury (GOS4M) and the GEO Initiative on POPs (GOS4POPs) by developing a new integrated approach for global real-time monitoring of environmental quality with respect to air, water and human matrices contamination by toxic substances, like mercury and persistent organic pollutants. iGOSP developed end-user-oriented Knowledge Hubs that provide data repository systems integrated with data management consoles and knowledge information systems. The main outcomes from iCUPE are the novel and comprehensive data sets and a modelling activity that contributed to delivering science-based insights for the Arctic region. Applications enable defining and monitoring of Arctic Essential Variables and sets up processes towards UN2030 SDGs that include health (SDG 3), clean water resources and sanitation (SDGs 6 and 14). • Earth Observation can support an efficient science-policy interaction by trusted information. • Policy targets are inherently multidisciplinary, posing challenges on integrating knowledge from different scientific domains. • Specific science-policy workflows and implemented applications were demonstrated through ERA-PLANET. • A comprehensive approach to generate and delivery knowledge from EO and Earth Sciences to policy-makers was developed. [ABSTRACT FROM AUTHOR]

Background Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. Objectives We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. Methods Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70–180 mg/dL), above range (>180 mg/dL), and below range (54–69 mg/dL)] and glycated hemoglobin (i.e. HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. Results Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus , Eubacterium ventriosum , and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). Conclusions Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D. This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622). [ABSTRACT FROM AUTHOR]

Escherichia coli is a very well-known microorganism typically selected as indicator of fecal contamination in foods and water. The reference method for the quantification of E. coli in live mollusks relies on Most Probable Number (MPN) followed by tube confirmation on a chromogenic medium, TBX, ISO 16649-3. Even though reliable, this approach needs a minimum of two days to be completed, making it not ideal for short shelve life foods such as seafood. In the current study the conventional TBX confirmation was replaced by a novel, colorimetric Loop-mediated isothermal amplification (LAMP) assay. The MPN-LAMP method allowed to reduce by half the turnaround time of the method, 24 vs 48 h, when compared to the standard MPN-TBX. In addition to this, given the robustness of this technique to conventional inhibitory compounds, it was possible to directly add the presumptive positive tube suspension of the tube to the reaction vessel, without DNA extraction, and interpret the results in 30–35 min, after the MPN step. This approach allowed to simplify the workflow, reduce hands-on work, and costs associated to the assay. By analyzing a total of 39 mussel samples spiked with concentration ranges from <0.42–76.82 MPN/ g, minor differences in the results were observed among both confirmatory approaches, not being these statistically significant. • Real-time, and end-point colorimetric, LAMP assays to detect E. coli were developed. • Colorimetric LAMP was compatible with MPN ISO standard method. • MPN-LAMP performed satisfactory without prior DNA extraction. • MPN quantification results by ISO and LAMP were comparable. • MPN-LAMP allowed to reduce by half the turnaround time of the ISO method. [ABSTRACT FROM AUTHOR]

Human-specific faecal contamination has been affecting surface water and is a threat to both the environment and public health due to its potential co-occurrence with pathogens. Extended studies were conducted to detect and quantify faecal contamination using microbial source tracking (MST) markers targeting bacteria and viruses. The prototypical crAssphage, a presumed Bacteroides -infecting phage discovered in 2014, showed superior specificity to human faeces and high abundance in untreated sewage water. This study evaluated the applicability of crAssphage markers, CPQ_056 and CPQ_064, as MST tools for detecting domestic sewage contamination in surface water in China. Validation tests based on domestic sewage and animal faecal samples demonstrated high sensitivity/specificity of 100%/96.7% for CPQ_056 and 100%/100% for CPQ_064 within the scope of this study, surpassing the performance of traditional Bacteroidales markers such as HF183 (100%/80.4% against sewage). MST markers targeting different hosts and validated in the Taihu watershed (CPQ_056, CPQ_064, BacUni, HF183 TaqMan, Pig-2-Bac, and GFD) were quantified in water samples collected from the inflow rivers of Taihu Lake in summer and winter 2020. The results showed the dominance of sewage/wastewater as the source of contamination in all faecal pollution. Spatial analysis revealed higher contamination levels in northwest rivers, which were those most impacted by human activities. There was also a diluting pattern downstream of some rivers. Correlations with water quality parameters indicated the co-occurrence of nutrient-related pollution and faecal contamination, particularly in areas with industrial, low-density residential, green space, and municipal service land uses. The findings established the efficacy of crAssphage markers in enhancing precision and accuracy in monitoring faecal contamination, offering valuable tools for policymakers and environmental managers. [Display omitted] • CrAssphage MST markers validated in China as human faecal contamination indicators. • CrAssphage markers showed higher specificity as compared to Bacteroidales markers. • Seasonal/spatial change in crAssphage markers were observed in the inflow rivers. • Nutrients and faecal pollution were also observed in inflow rivers of Taihu lake. • Higher human faecal contamination was found near some of the land uses. [ABSTRACT FROM AUTHOR]

• cLAMP was less analytically sensitive than qPCR by two orders of magnitude. • Both qPCR and cLAMP assays had a host sensitivity value of 1.00 in untreated sewage. • LAMP's host specificity was higher than qPCR, with values of 0.81 and 0.64 respectively. • Both methods detected HF183 in environmental water samples with moderate agreement. • LAMP could be a rapid, sensitive method for detecting sewage pollution in environmental waters. Surface waters are vulnerable to contamination by human and animal feces, posing risks to human health due to potential exposure to enteric pathogens. This research developed a colorimetric loop-mediated isothermal amplification (cLAMP) assay to detect sewage associated Bacteroides dorei HF183/BacR287 (HF183) marker in wastewater and environmental water samples. The host sensitivity and host specificity of the assay were evaluated, and their performance was compared to the Bacteroides HF183 qPCR assay using control materials (gBlocks), environmental water samples seeded with untreated sewage, and ambient environmental water samples. In serial dilutions of control materials, qPCR produced quantifiable data across all dilutions, while cLAMP detected the marker down to 0.001 pg/µL of control materials, which was two orders of magnitude less sensitive than qPCR. All untreated sewage samples (n = 12) tested positive for HF183 by both the qPCR and cLAMP assays, demonstrating a host sensitivity value of 1.00 (maximum value of 1.00). The host specificity by analysing 70 non-human fecal nucleic acid samples revealed cLAMP's specificity value of 0.81 compared to qPCR's 0.64. When testing sewage-seeded environmental water samples, both methods detected HF183 for the lowest amount of sewage, indicating similar detection sensitivity. The application of cLAMP for tracking sewage pollution in environmental waters showed promising results, with moderate agreement between cLAMP and qPCR (κ = 0.510). However, cLAMP occasionally missed detections compared to qPCR, particularly in low-concentration samples. Overall, the cLAMP HF183 assay demonstrated promising potential as a rapid and sensitive method for detecting sewage pollution, offering a viable alternative to qPCR in certain environmental monitoring scenarios. [Display omitted] [ABSTRACT FROM AUTHOR]

Antibiotic resistance genes (ARGs) have been extensively observed in bacterial DNA, and more recently, in phage particles from various water sources and food items. The pivotal role played by ARG transmission in the proliferation of antibiotic resistance and emergence of new resistant strains calls for a thorough understanding of the underlying mechanisms. The aim of this study was to assess the suitability of the prototypical p-crAssphage, a proposed indicator of human fecal contamination, and the recently isolated crAssBcn phages, both belonging to the Crassvirales group, as potential indicators of ARGs. These crAss-like phages were evaluated alongside specific ARGs (bla TEM , bla CTX-M-1 , bla CTX-M-9 , bla VIM , bla OXA-48 , qnrA , qnrS , tetW and sul1) within the total DNA and phage DNA fractions in water and food samples containing different levels of fecal pollution. In samples with high fecal load (>103 CFU/g or ml of E. coli or somatic coliphages), such as wastewater and sludge, positive correlations were found between both types of crAss-like phages and ARGs in both DNA fractions. The strongest correlation was observed between sul1 and crAssBcn phages (rho = 0.90) in sludge samples, followed by bla CTX-M-9 and p-crAssphage (rho = 0.86) in sewage samples, both in the phage DNA fraction. The use of crAssphage and crAssBcn as indicators of ARGs, considered to be emerging environmental contaminants of anthropogenic origin, is supported by their close association with the human gut. Monitoring ARGs can help to mitigate their dissemination and prevent the emergence of new resistant bacterial strains, thus safeguarding public health. [Display omitted] • p-crAssphage and a new crAss-like phage, crAssBcn, were assessed. • CrAss-like phages correlate with ARGs in fecally polluted samples. • Correlations with ARGs differed between total and phage DNA fractions. • CrAss-like phages may be used as indicators of abundant ARGs. [ABSTRACT FROM AUTHOR]

Enterococci are common indicators of fecal contamination and are used to assess the quality of fresh and marine water, sand, soil, and sediment. However, samples collected from these environments contain various cells and other factors that can interfere with the assays used to detect enterococci. We developed a novel assay for the sensitive and specific detection of enterococci that is resistant to interference from other cells and environmental factors. Our interference-resistant assay used 30-nm gold nanoparticles (AuNPs), streptavidin, and a biotinylated Enterococcus antibody. Enterococci inhibited the interaction between streptavidin and biotin and led to the disaggregation of AuNPs. The absence of enterococci led to the aggregation of AuNPs, and this difference was easily detected by spectrophotometry. This interference-resistant AuNP assay was able to detect whole cells of Enterococcus in the range of 10 to 107 CFU/mL within 3 h, had high specificity for enterococci, and was unaffected by the presence of other intestinal bacteria, such as Escherichia coli. Our examination of fresh and marine water samples demonstrated no interference from other cells or environmental factors. The interference-resistant AuNP assay described here has the potential to be used as a rapid, simple, and effective method for monitoring enterococci in diverse environmental samples. [Display omitted] • Developed an interference-resistant AuNP assay for detecting enterococci in water. • Assay detects enterococci in 10-107 CFU/mL within 3 h with high specificity. • No interference by other cells or environmental factors in actual water samples. • Assay uses whole cells, avoiding steps of culturing and nucleic acid extraction. • Potential for simple, effective monitoring of enterococci in diverse environments. [ABSTRACT FROM AUTHOR]

Despite the growing emphasis on aquatic disease monitoring via environmental DNA (eDNA) in water samples, detecting low concentrations of viruses in aquatic environments remains challenging. Prior studies demonstrated that plankton act as mechanical vectors for several aquatic viral pathogens but not for the viral hemorrhagic septicemia virus (VHSV). In this study, we aimed to identify the potential interaction between VHSV and microplankton and further assess the effectiveness of the water concentration method using a plankton net for VHSV detection in water. Briefly, VHSV was co-cultured with Chlorella , rotifer, and microcosms generated using plankton nets with sieve sizes of 20, 40, and 70 μm. A close interaction between VHSV and rotifer and microplankton collected with the 70 μm-plankton net with an abundant zooplankton population was found, likely influenced by the filter-feeding behaviors of zooplankton. We also found that VHSV could adsorb to fish feces at concentrations 25–88 times higher than that in the equivalent volume of seawater. Subsequently, we evaluated the efficiency of a 70 μm-plankton net for VHSV concentration in rearing water containing infected fish compared to the iron flocculation method. Notably, the plankton net outperformed the iron flocculation method in terms of sensitivity (∼10 to 20-fold), possibly due to its ability to capture fish-derived organic materials, such as feces, shed from infected fish. Our overall findings advocate for the plankton net concentration approach, not only for its pronounced sensitivity but also its operational simplicity, identifying it as a promising avenue for efficient VHSV detection in aquaculture water monitoring. • This study demonstrates an association between VHSV and microplankton. • Concentration of rearing water using a plankton net outperformed iron-flocculation in terms of viral detection. • The plankton net method, with its operational simplicity, can be an effective eDNA tool for monitoring aquatic diseases. [ABSTRACT FROM AUTHOR]

• Faecal pollution data from the past 11 years in the Adriatic sea were analysed. • FIB contamination changed over space and time. • A general reduction of structural zeros over time was found. River discharge and rainfall did not explain faecal pollution • CSOs events were highly correlated with peaks in FIB. Faecal contamination of the coastal sea poses widespread hazard to human and environmental health and is predicted to rise in response to global change and human pressure. For better management and risk reduction it is thus imperative to clarify and predict trends of faecal pollution over spatial and temporal scales, and to assess links with climate and other variables. Here, we investigated the spatio-temporal variation in the Faecal Indicator Bacteria (FIB) Escherichia coli and enterococci, over a time frame spanning 11 years (2011–2021) along a coastal area covering approximately 40 km and 59 bathing sites in the Marche region (Adriatic Sea, Italy), characterized by intense beach tourism, high riverine inputs, resident population, maritime traffic and industrial activities. Our analysis, that considers 5,183 measurements during the bathing season (April to October), shows that FIB abundance varied significantly among years. A general, although not significant, increase over time of both FIB was observed, mainly due to a general reduction of structural zeros (i.e., zeros originated from the actual absence of the response variable) over the examined time period. FIB abundances displayed their maxima and minima in different years according to the municipality, with overall peaks recorded in different months (May-June or September), whereas the lowest values were always observed in October. FIB levels were not significantly related neither to rainfalls nor to river discharge, but the activation of combined sewer overflows (CSOs), typically occurring after intense rainfall events, appeared as a necessary condition for the high faecal contamination levels. Considering climate change scenarios predicting significant increases in extreme weather events, our findings support the usefulness of analysing long-term trends to identify pollution sources, and the prioritization of control strategies to better manage the release of microbial pollutants from combined sewer overflows in coastal waters to reduce human risks. [Display omitted] [ABSTRACT FROM AUTHOR]

We investigated the dynamics of feces-associated microorganisms in areas with wrack accumulation in the southeastern part of the Baltic Sea. Our study covered single-day (2021) and multi-day (2022) observations during the recreational season. We collected water, sand, and wrack samples and assessed the abundance of fecal indicator bacteria (FIB), as well metagenomic analysis was conducted to monitor changes in microbial composition. Based on metagenomic data we identified taxa associated with feces, sewage, and ruminant sources. Human-related fecal pollution based on genetic markers correlated with the presence of Lachnospiraceae, Prevotellaceae and Rickenellacea abundance. Higher abundance and diversity of feces-associated and ruminant-associated taxa and the presence of enteric pathogens were observed when wrack accumulated near the river outflow in 2021, suggesting a potential link with fecal pollution from the river. As a preventive measure, it is recommended to remove the wrack to reduce the risk of exposure to potential enteric pathogens if it is accumulated next to the river outflow. [Display omitted] • Fecal pollution levels and sources were studied in wrack-affected environment. • Fecal pollution levels were estimated by cultivation. • Host-specific genetic markers and metagenomics were used to determine the source. • Humans, birds, ruminants and sewage were identified as sources of fecal pollution. • Feces-associated taxa and enteric pathogens were more abundant near river outflow. [ABSTRACT FROM AUTHOR]

Numerical health risk assessment models have been developed to describe faecal contamination of water using Escherichia coli as an indicator bacterium. Although many previously established numerical models for E. coli in aquatic environments have only considered the effects of one or two water quality parameters such as temperature and sunlight, it is difficult to simulate E. coli survival with only one or two parameters because the aquatic environment is a complex system. This study conducted a series of comparative experiments to select water quality parameters that should be preferentially considered in a numerical model for E. coli survival in lakes. The parameters considered were temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), suspended solids (SS), coexisting microbes, and light intensity. In the laboratory experiments, the survival of E. coli was observed by controlling two of these seven parameters, and the effects of these parameters on the rate of E. coli population change were statistically compared. Consequently, light intensity affected the survival of E. coli most significantly, followed by the presence of coexisting microbes, temperature, pH, and TDS. However, DO and SS had smaller effects on survival than other parameters. High-impact interactions on E. coli survival were observed between temperature and TDS and temperature and coexisting microbes. These results suggest that existing numerical models for simulating E. coli survival in lakes should be modified to consider the independent and interactive effects of multiple parameters such as sunlight, coexisting microbes, temperature, pH, and TDS. [Display omitted] • To refine models, we determined parameters that highly impact E. coli survival. • Light affected E. coli survival most significantly followed by coexisting microbes. • Temperature, pH, and total dissolved solids also affected E. coli survival. • Dissolved oxygen and suspended solids affected E. coli survival less. • Temperature and total dissolved solids/coexisting microbes strongly interacted. [ABSTRACT FROM AUTHOR]

In this work, copper nanoclusters (CuNCs) with tiny particle sizes were successfully obtained by a template-assisted synthesis approach. The interfacial interaction energies of cysteine (Cys) and CuNCs were simulated and calculated by molecular dynamics using the Materials Studio program package, and the anchoring sites of Cys on CuNCs surface in aqueous solution were investigated in detail by adsorption modeling. Chitosan (CS), a natural polymer, was used as a confining agent to enhance the excellent peroxidase (POD)-like activity of CuNCs. Therefore, the composite can catalyze the decomposition of hydrogen peroxide (H 2 O 2) to generate hydroxyl radical (·OH) and possess higher antibacterial activity. A broad-spectrum antibacterial system based on CS@CuNCs was established for E. coli and S. aureus , avoiding the harmful effects of high concentration of H 2 O 2 on organisms. In addition, a cascade reaction with glucose oxidase (GOx) was established for the specific consumption of glucose by bacteria, and a method for the visual colorimetric detection of bacterial viability within 30 min was established. Finally, based on the polymer properties of CS, a cling wrap with antibacterial properties was also prepared for food preservation. In summary, this study provides innovative proposals for the application of CS/nanocluster composite in food packaging, food safety, and even bioengineering. [Display omitted] • Copper nanoclusters were synthesized and modified with chitosan. • The composite with POD-like activity was used in detecting bacterial viability. • The composite could produce antibacterial properties. • The composite could be used for fruit preservation. [ABSTRACT FROM AUTHOR]

Laboratory-based nucleic acid amplification tests (NAATs) are highly sensitive and specific, but they require the transportation of samples to centralized testing facilities and have long turnaround times. During the Coronavirus Disease 2019 (COVID-19) pandemic, substantial advancement has been achieved with the development of paper-based point-of-care (POC) NAATs, offering features such as low cost, being easy to use, and providing rapid sample-to-answer times. Although most of the POC NAATs innovations are towards clinical settings, we have developed a portable, paper-based loop-mediated isothermal amplification (LAMP) testing platform for on-farm applications, capable of detecting Bacteroidales as a fecal contamination biomarker. Our integrated platform includes a drop generator, a heating and imaging unit, and paper-based biosensors, providing sensitive results (limit of detection 3 copies of Bacteroidales per cm2) within an hour of sample collection. We evaluated this integrated platform on a commercial lettuce farm with a concordance of 100% when compared to lab-based tests. Our integrated paper-based LAMP testing platform holds great promise as a reliable and convenient tool for on-site NAATs. We expect that this innovation will encourage the fresh produce industry to adopt NAATs as a complementary tool for decision-making in growing and harvesting. We also hope that our work can stimulate further research in the development of on-farm diagnostic tools for other agricultural applications, leading to improved food safety and technology innovation. [Display omitted] [ABSTRACT FROM AUTHOR]

With the rapid development of monitoring systems, extensive amount of water quality high-resolution measurements are accumulated, which make it unrealistic to manually extract the water quality anomaly features from the huge river environment information. In this study, a hybrid anomaly detection framework is developed by the combination of prediction-based and classification-based data-driven methods to provide a scientific indication for river pollution identification. A Variational Mode Decomposition-Back Propagation Neural Network (VMD-BPNN) model is used to analyze the real-time water quality variation tendencies in the first stage. Additionally, a Support Vector Data Description (SVDD) algorithm is adopted to capture the multi-dimensional water quality anomaly characteristics in the second stage. The developed hybrid framework is then applied to the Kansas River in America, to verify its river pollution identification performance in comparison to different anomaly detection methods and in various anomaly-level scenarios. The developed hybrid framework can achieve a maximum Area Under the Curve (AUC) value of 0.932 under a two-dimensional anomaly detection pattern with the True Positive Rate (TPR) and False Positive Rate (FPR) values of 0.861 and 0.142, respectively. The results indicate that the developed hybrid framework can provide an effective river pollution identification performance with dynamically determined warning thresholds. Meanwhile, a vigorous anomaly detection pattern can improve the pollution identification performance by considering the cumulative interactions among the multi-dimensional water quality parameters. [Display omitted] • A hybrid anomaly detection algorithm is established for pollution identification. • A prediction-based method is used for real-time anomaly feature extraction. • A classification-based method is adopted for multivariate anomaly feature fusion. • The framework can provide an indicator by a series of evolving warning thresholds. [ABSTRACT FROM AUTHOR]

• The demosaiced RGB imagery can improve the estimation of E. coli spatial patterns. • The quantile-based data splitting improved modeling of Imbalanced E. coli datasets. • The visible blue intensity and air temperature were the most influential inputs. The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. The application of these approaches, however, is challenged by limited sample availability and unbalanced water quality datasets. In this study, we estimated the E. coli concentration in an irrigation pond in Maryland, USA, during the summer season using demosaiced natural color (red, green, and blue: RGB) imagery in the visible and infrared spectral ranges, and a set of 14 water quality parameters. We did this by deploying four machine learning models – Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), and K-nearest Neighbor (KNN) – under three data utilization scenarios: water quality parameters only, combined water quality and small unmanned aircraft system (sUAS)-based RGB data, and RGB data only. To select the training and test datasets, we applied two data-splitting methods: ordinary and quantile data splitting. These methods provided a constant splitting ratio in each decile of the E. coli concentration distribution. Quantile data splitting resulted in better model performance metrics and smaller differences between the metrics for both the training and testing datasets. When trained with quantile data splitting after hyperparameter optimization, models RF, GBM, and XGB had R 2 values above 0.847 for the training dataset and above 0.689 for the test dataset. The combination of water quality and RGB imagery data resulted in a higher R 2 value (>0.896) for the test dataset. Shapley additive explanations (SHAP) of the relative importance of variables revealed that the visible blue spectrum intensity and water temperature were the most influential parameters in the RF model. Demosaiced RGB imagery served as a useful predictor of E. coli concentration in the studied irrigation pond [Display omitted] [ABSTRACT FROM AUTHOR]

Environmental viruses in wastewater and sludge are widely recognized for their roles in waterborne diseases. However, previous studies mainly focused on RNA viruses, and little is known about the diversity of DNA viral communities and their driving factors in municipal wastewater treatment environments. Herein, we conducted a pilot study to explore DNA virus profiles in municipal wastewater and recycled sludge by metagenomics method, and track their temporal changes in northern China. Results showed that 467 viral species were co-shared among all the samples. We identified six families of human viruses with a prevalence of 0.1%, which were rare but relatively stable in wastewater and sludge for six months. Adenoviridae , Parvoviridae , and Herpersviridae were the most dominant human viral families in municipal wastewater and recycled sludge. A time series of samples revealed that the dynamic changes of human DNA viruses were stable based on qPCR results, particularly for high-risk fecal-oral transmission viruses of adenovirus, bocavirus, polyomavirus, human gamma herpesvirus, human papillomavirus, and hepatitis B virus. Concentrations of Adenovirus (5.39–7.48 log 10 copies/L) and bocavirus (4.36–7.48 log 10 copies/L) were observed to be the highest in these samples compared to other viruses. Our findings demonstrated the DNA viruses' high prevalence and persistence in municipal wastewater treatment environments, highlighting the value of enhancing public health responses based on wastewater-based epidemiology. [Display omitted] • The first study on DNA virus profile in Tianjin Municipal Wastewater Treatment Plant. • Herpersvirus, adenovirus, and bocavirus were the dominant viral pathogens in WWTP. • DNA virus composition in municipal wastewater was differ from recycled sludge. • Human viruses were highly prevalent and stable in municipal wastewater and recycled sludge. [ABSTRACT FROM AUTHOR]

[Display omitted] • Livestock restriction successfully reduces riverine antibiotic resistance at a watershed scale. • Animal waste reduction is key to decreasing ARG abundance in river. • Long-term surveillance is crucial for environmental monitoring. • The necessity of an integrated framework to effectively mitigate ARG spread. Natural environments play a crucial role in transmission of antimicrobial resistance (AMR). Development of methods to manage antibiotic resistance genes (ARGs) in natural environments are usually limited to the laboratory or field scale, partially due to the complex dynamics of transmission between different environmental compartments. Here, we conducted a nine-year longitudinal profiling of ARGs at a watershed scale, and provide evidence that restrictions on livestock farms near water bodies significantly reduced riverine ARG abundance. Substantial reductions were revealed in the relative abundance of genes conferring resistance to aminoglycosides (42%), MLSB (36%), multidrug (55%), tetracyclines (53%), and other gene categories (59%). Additionally, improvements in water quality were observed, with distinct changes in concentrations of dissolved reactive phosphorus, ammonium, nitrite, pH, and dissolved oxygen. Antibiotic residues and other pharmaceuticals and personal care products (PPCPs) maintain at a similarly low level. Microbial source tracking demonstrates a significant decrease in swine fecal indicators, while human fecal pollution remains unchanged. These results suggest that the reduction in ARGs was due to a substantial reduction in input of antibiotic resistant bacteria and genes from animal excreta. Our findings highlight the watershed as a living laboratory for understanding the dynamics of AMR, and for evaluating the efficacy of environmental regulations, with implications for reducing environmental risks associated with AMR on a global scale. [ABSTRACT FROM AUTHOR]

[Display omitted] • Successful partial nitritation was conducted under 40 g-NaCL/L. • T-RFLP indicators were developed based on the 16S rRNA gene database. • AOB was discriminated from total bacteria via Tai I and Fnu DII restriction enzymes. • T-RFLP signals improved the R2 of ACR prediction using machine learning by 0.9459. • SHAP proved the contribution of T-RFLP for the ACR prediction in addition to ALR. This study introduces the smart development of a cost-effective biomolecular indicator using terminal restriction fragment length polymorphism (T-RFLP) based on the 16S rRNA gene database obtained from operating the partial nitritation (PN) process under saline conditions. As a result of next-generation sequencing (NGS) on the 16S rRNA gene, ammonia-oxidizing bacteria (AOB) of Nitrosomonas sp. OTU0 (N. OTU0) favored higher salinity of 20–35 g-NaCl/L, while Nitrosomonas sp. OTU8 (N. OTU8) and Nitrosomonas sp. OTU11 (N. OTU11) were predominant under 20 g-NaCl/L. The T-RFLP system with the restriction enzymes of Tai I and Fnu DII, which was thoroughly simulated based on the NGS data of the 16S rRNA gene, effectively differentiates N. OTU0 against N. OTU8 and N. OTU11. In addition, together with AOB's signals, the signals of nitrite-oxidizing and heterotrophic bacteria were obtained as biomolecular indicators of successful PN under saline conditions. These findings suggest that T-RFLP can serve as an economically viable monitoring approach for the sensitive PN process under saline conditions to achieve more sustainable nitrogen removal. For further application, the designated T-RFLP signals of this study were applied to the regression of ammonia conversion rate through machine learning modeling. The regression showed R2 values of 0.9446 and 0.9458 for the training and test sets, respectively. The contribution of T-RFLP for the regression was quantified by a shapley additive explanation (SHAP). [ABSTRACT FROM AUTHOR]

• Watershed-scale green infrastructure did not alter microbiome or resistome. • Stormwater microbiome and resistome shift with season and rainfall characteristics. • Fecal contamination is associated with stormwater microbiome and resistome shifts. • Stormwater carries potentially clinically relevant, antibiotic-resistant bacteria • Molecular methods and Escherichia coli results were not well correlated. Since stormwater conveys a variety of contaminants into water bodies, green infrastructure (GI) is increasingly being adopted as an on-site treatment solution in addition to controlling peak flows. The purpose of this study was to identify differences in microbial water quality of stormwater in watersheds retrofitted with GI vs. those without GI. Considering stormwater is recently recognized as a contributor to the antibiotic resistance (AR) threat, another goal of this study was to characterize changes in the microbiome and collection of AR genes (resistome) of urban stormwater with season, rainfall characteristics, and fecal contamination. MinION long-read sequencing was used to analyze stormwater microbiome and resistome from watersheds with and without GI in Columbus, Ohio, United States, over 18 months. We characterized fecal contamination in stormwater via culturing Escherichia coli and with molecular microbial source tracking (MST) to identify sources of fecal contamination. Overall, season and storm event (rainfall) characteristics had the strongest relationships with changes in the stormwater microbiome and resistome. We found no significant differences in microbial water quality or the microbiome of stormwater in watersheds with and without GI implemented. However, there were differences between the communities of microorganisms hosting antibiotic resistance genes (ARGs) in stormwater from watersheds with and without GI, indicating the potential sensitivity of AR bacteria to treatment. Stormwater was contaminated with high concentrations of human-associated fecal bacterial genes, and the ARG host bacterial community had considerable similarities to human feces/wastewater. We also identified 15 potential pathogens hosting ARGs in these stormwater resistome, including vancomycin-resistant Enterococcus faecium (VRE) and multidrug-resistant Pseudomonas aeruginosa. In summary, urban stormwater is highly contaminated and has a great potential to spread AR and microbial hazards to nearby environments. This study presents the most comprehensive analysis of stormwater microbiome and resistome to date, which is crucial to understanding the potential microbial risk from this matrix. This information can be used to guide future public health policy, stormwater reuse programs, and urban runoff treatment initiatives. [Display omitted] [ABSTRACT FROM AUTHOR]

• A validated RT-PCR method targeting 16S ribosomal RNA to qualitatively E. coli in drinking water at a sensitivity of 1 CFU/100 ml. • The method is as sensitive as the reference culture method. • The E. coli RT-PCR showed high interlaboratory reproducibility. • An extensive comparison on practical samples showed good agreement between RT-PCR and the culture method. • Application of the RT-PCR will improve the safety of drinking water consumers. Escherichia coli (E. coli) plays a central role as an indicator for fecal contamination to predict the possible presence of microbial pathogens in drinking water. Current detection methods for E. coli are based on time-consuming culture-based techniques. There is a strong need for methods to detect fecal contamination rapidly in distributed drinking water to prevent outbreaks of waterborne disease and support water utilities to efficiently manage their operations like actions to repair or maintain distribution pipes, to minimize impact on consumers. This study describes the validation and application of a qualitative real time reverse transcription PCR (RT-PCR) method targeting 16S ribosomal RNA (rRNA) for rapid detection of E. coli in distributed drinking water. The RT-PCR assay targets 16S rRNA, a highly abundant RNA in viable cells, enabling robust detection at the required sensitivity of 1 CFU/100 ml. The validation was performed by comparing the RT-PCR method with the culture-based chromogenic reference method (CCA) using the protocol and criteria described in ISO 16,140–2:2016. The validation demonstrated that this RT-PCR method can be used to specifically detect E. coli in a broad range of drinking water samples with at least the same limit of detection as the culture method (Relative Limit Of Detection = 0.75, range 0.43–1.43). The inclusivity study showed that the RT-PCR method was able to detect a broad range of E. coli strains derived from different sources and geographic areas, including pathogenic serotype O157 strains that are not detected with the culture method. The exclusivity study determined that other bacterial genera are not detected with this RT-PCR. However, Escherichia fergusonii was detected and, based on " in silico " analysis, it is expected that also E. albertii and E. marmotae and Shigella species will be detectable using this RT-PCR. An interlaboratory study confirmed that the RT-PCR and culture method have comparable sensitivities when tested by different participants at different laboratories. The application of RT-PCR to confirm the hygienic quality of distributed drinking water after actions to repair or maintain distribution pipes was compared with the culture method on 8076 routine samples, analyzed by the drinking water laboratories in the Netherlands. This comparison study showed a 96.4 % agreement between RT-PCR and culture. In 3.3 % of the samples E. coli was detected with RT-PCR and not with the culture method and in 0.1 % of the samples E. coli was only detected by culture confirming either a higher sensitivity for RT-PCR or the detection of RNA from uncultivable cells. Finally, the application of RT-PCR was highlighted during a contamination event in Belgium where we demonstrate the potency of RT-PCR as a tool to rapidly monitor the spread of microbial contamination and to monitor the effect of measures to remove the contamination This is the first fully validated rapid nucleic based method for detection of E. coli in distributed drinking water. These results demonstrate that this RT-PCR method can be used as a rapid alternative to the culture method to monitor E. coli in distributed drinking water. However, it should be emphasized that nucleic acid based detection methods rely on highly different detection principles (detection of captured nucleic acids present in a sample) than culture base methods (presence of cells cultivable on a selective medium) resulting in occasional different analysis results. Varying treatment and disinfection steps (UV, chlorine, monochloramine, Ozone) or environmental factors (decay) can influence the results and cause differences between RT-PCR and culture methods. [Display omitted] [ABSTRACT FROM AUTHOR]

• Manure-borne ARGs and bacR removal assessed in experimental streams.. • The rate at which bacR was removed from the water column differed from tetW removal. • A stochastic model showed that streambed interactions govern ARG removal in streams. • The type of ARG and stream geomorphology alters the downstream transport of ARGs. Antibiotic resistance is a serious global health issue, resulting in at least 1.2 million deaths in 2019. The environment is a potentially important reservoir of antibiotic resistance; however, the fate of Antibiotic Resistance Genes (ARGs) in the environment remains poorly characterized. One important environmental source of ARGs is manure used as a soil amendment. ARGs from manure may then enter nearby flowing waterbodies, where the factors governing their downstream transport remain unknown. To address this, we conducted experiments by spiking cattle manure in an artificial stream to estimate removal rates (k ; m−1) for three ARGs (mefA, tetQ , and tetW) and a ruminant fecal marker (bacR). We then used a Stochastic Mobile-Immobile Model (SMIM) to separate the overall removal into two components , r s , and r h , corresponding to immobilizations in the surface (i.e., water column) and subsurface (i.e., streambed), respectively. Finally, we applied the SMIM across four model streams to predict the downstream travel distance of ARGs and bacR. Our results showed measurable removal for all targets in all experimental replicates (n = 3) and no differences were found in the removal rates among replicates for any target (ANCOVA; p > 0.05). We found that the removal of bacR was significantly lower than tetW (p < 0.05) and slightly lower than mefA (p = 0.088), while tetQ removal was slightly different from tetW 's (p = 0.072). We also found that r h values were orders of magnitude larger than r s for ARGs and bacR (t -test; p < 0.05). These findings suggest that ARGs and bacR are being removed from the water column through immobilization reactions occurring in the streambed. Additionally, we predicted that the 90 % removal (or D90) of targets occurs within the first 500 m in all model streams except in a slow-flow pastoral stream, which required 1400 m of downstream transport for 90 % removal. Our findings and model stand out as promising tools to predict the fate of ARGs in streams and will contribute to improving and managing agricultural practices that employ animal manure. [Display omitted] [ABSTRACT FROM AUTHOR]

• Urban stormwater reflects anthropogenic contamination. • Bioretention cell treatment of stormwater does not increase microbial hazards. • Biofiltered stormwater microbiome indices correlate with rainfall and water quality. • Beta diversity community structure of stormwater changes after biofiltration. • Bioretention technology sustains microbial and improves physical water quality. Bioretention cells (BRCs) control stormwater flow on-site during precipitation, reducing runoff and improving water quality through chemical, physical, and biological processes. While BRCs are effective in these aspects, they provide habitats for wildlife and may face microbial hazards from fecal shedding, posing a potential threat to human health and the nearby environment. However, limited knowledge exists regarding the ability to control microbial hazards (e.g., beyond using typical indicator bacteria) through stormwater biofiltration. Therefore, the purpose of this study is to characterize changes in the bacterial community of urban stormwater undergoing bioretention treatment, with the goal of assessing the public health implications of these green infrastructure solutions. Samples from BRC inflow and outflow in Columbus, Ohio, were collected post-heavy storms from October 2021 to March 2022. Conventional culture-based E. coli monitoring and microbial source tracking (MST) were conducted to identify major fecal contamination extent and its sources (i.e., human, canine, avian, and ruminant). Droplet digital polymerase chain reaction (ddPCR) was utilized to quantify the level of host-associated fecal contamination in addition to three antibiotic resistant genes (ARGs): tetracycline resistance gene (tetQ), sulfonamide resistance gene (sul 1), and Klebsiella pneumoniae carbapenemase resistance gene (bla KPC). Subsequently, 16S rRNA gene sequencing was conducted to characterize bacterial community differences between stormwater BRC inflow and outflow. Untreated urban stormwater reflects anthropogenic contamination, suggesting it as a potential source of contamination to waterbodies and urban environments. When comparing inlet and outlet BRC samples, urban stormwater treated via biofiltration did not increase microbial hazards, and changes in bacterial taxa and alpha diversity were negligible. Beta diversity results reveal a significant shift in bacterial community structure, while simultaneously enhancing the water quality (i.e., reduction of metals, total suspended solids, total nitrogen) of urban stormwater. Significant correlations were found between the bacterial community diversity of urban stormwater with fecal contamination (e.g. dog) and ARG (sul 1), rainfall intensity, and water quality (hardness, total phosphorous). The study concludes that bioretention technology can sustainably maintain urban microbial water quality without posing additional public health risks, making it a viable green infrastructure solution for heavy rainfall events exacerbated by climate change. This is special type of abstract that is so short and could be inserted after main abstract of article, as a blurb or inserted as annotations into a Table of contents [Display omitted] [ABSTRACT FROM AUTHOR]

• A liquid crystal (LC)-based aptasensor was designed for E. coli detection. • A textile grid was used to anchor the LCs and create a substrate free platform. • CTAB was used to adsorb the aptamers on the LC surface, creating a bright signal. • The presence of target bacteria dissociates the aptamer and creates a dark signal. • Image analysis and machine learning were implemented for precise data analysis. We have developed a rapid, facile liquid crystal (LC)-based aptasensor for E. coli detection in water and juice samples. A textile grid-anchored LC platform was used with specific aptamers adsorbed via a cationic surfactant, cetyltrimethylammonium bromide (CTAB), on the LC surface. The presence of E. coli dissociates the aptamers from CTAB and restores the dark signal induced by the surfactant. Using polarized microscopy, the images of the LCs in the presence of various concentrations of E. coli were captured and analyzed using image analysis and machine learning (ML). The artificial neural networks (ANN) and extreme gradient boosting (XGBoost) rendered the best results for water samples (R2 = 0.986 and RMSE = 0.209) and juice samples (R2 = 0.976 and RMSE = 0.262), respectively. The platform was able to detect E. coli with a detection limit (LOD) of 6 CFU mL−1. [ABSTRACT FROM AUTHOR]