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Background: Predictive markers for fecal microbiota transplantation (FMT) outcomes in patients with active ulcerative colitis (UC) are poorly defined. We aimed to investigate changes in gut microbiota pre- and post-FMT and to assess the potential value in determining the total copy number of fecal bacterial siderophore genes in predicting FMT responsiveness. Methods: Patients with active UC (Mayo score ≥ 3) who had undergone two FMT procedures were enrolled. Fecal samples were collected before and 8 weeks after each FMT session. Patients were classified into clinical response and non-response groups, based on their Mayo scores. The fecal microbiota profile was accessed using metagenomic sequencing, and the total siderophore genes copy number via quantitative real-time polymerase chain reaction. Additionally, we examined the association between the total siderophore genes copy number and FMT efficacy. Results: Seventy patients with UC had undergone FMT. The clinical response and remission rates were 50% and 10% after the first FMT procedure, increasing to 72.41% and 27.59% after the second FMT. The cumulative clinical response and clinical remission rates were 72.86% and 25.71%. Compared with baseline, the response group showed a significant increase in Faecalibacterium, and decrease in Enterobacteriaceae, consisted with the changes of the total bacterial siderophore genes copy number after the second FMT (1889.14 vs. 98.73 copies/ng, P < 0.01). Virulence factor analysis showed an enriched iron uptake system, especially bacterial siderophores, in the pre-FMT response group, with a greater contribution from Escherichia coli. The total baseline copy number was significantly higher in the response group than non-response group (1889.14 vs. 94.86 copies/ng, P < 0.01). A total baseline copy number cutoff value of 755.88 copies/ng showed 94.7% specificity and 72.5% sensitivity in predicting FMT responsiveness. Conclusions: A significant increase in Faecalibacterium, and decrease in Enterobacteriaceae and the total fecal siderophore genes copy number were observed in responders after FMT. The siderophore genes and its encoding bacteria may be of predictive value for the clinical responsiveness of FMT to active ulcerative colitis. [ABSTRACT FROM AUTHOR]

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]

Background: Colorectal cancer (CRC) arises from complex interactions between host and environment, which include the gut and tissue microbiome. It is hypothesized that epigenetic regulation by gut microbiota is a fundamental interface by which commensal microbes dynamically influence intestinal biology. The aim of this study is to explore the interplay between gut and tissue microbiota and host DNA methylation in CRC. Methods: Metagenomic sequencing of fecal samples was performed on matched CRC patients (n = 18) and healthy controls (n = 18). Additionally, tissue microbiome was profiled with 16S rRNA gene sequencing on tumor (n = 24) and tumor-adjacent normal (n = 24) tissues of CRC patients, while host DNA methylation was assessed through whole-genome bisulfite sequencing (WGBS) in a subset of 13 individuals. Results: Our analysis revealed substantial alterations in the DNA methylome of CRC tissues compared to adjacent normal tissues. An extensive meta-analysis, incorporating publicly available and in-house data, identified significant shifts in microbial-derived methyl donor-related pathways between tumor and adjacent normal tissues. Of note, we observed a pronounced enrichment of microbial-associated CpGs within the promoter regions of genes in adjacent normal tissues, a phenomenon notably absent in tumor tissues. Furthermore, we established consistent and recurring associations between methylation patterns of tumor-related genes and specific bacterial taxa. Conclusions: This study emphasizes the pivotal role of the gut microbiota and pathogenic bacteria in dynamically shaping DNA methylation patterns, impacting physiological homeostasis, and contributing to CRC tumorigenesis. These findings provide valuable insights into the intricate host-environment interactions in CRC development and offer potential avenues for therapeutic interventions in this disease. [ABSTRACT FROM AUTHOR]

Canine parvovirus 2 (CPV-2) is a highly contagious enteric virus that causes high morbidity and mortality, especially in dogs under six months of age. Recovery from this illness is dependent on several factors, including the patient's prognosis for adequate therapy. The aim of this study was to evaluate the risk factors associated with the death outcome in CPV-2 positive dogs in a case-control study conducted at the Veterinary Hospital of the Universidade Federal de Lavras (HV-UFLA) in Lavras, Minas Gerais, Brazil. Twenty-six dogs with CPV-2 symptoms that arrived at the HV-UFLA between 2017 and 2018 were evaluated for inclusion in the study. Data on medical history, clinical signs, blood count and rapid test of parvovirus and faecal test for polymerase chain reaction (PCR) were collected for all the animals. All the dogs received treatment at the HV-UFLA, and the overall fatality rate due to canine parvovirus was 30.77%. Descriptive analysis and univariate and multivariate statistical analyses (logistic regression) were performed to assess the variables that were possibly associated with an unfavourable prognosis (death). In the univariate and multivariate analyses, Systemic Inflammatory Response Syndrome (SIRS) was observed to be a significant risk factor for an unfavourable prognosis in canine parvovirus, as it increased the risk of death by 12.96 times (95% CI 1.85-133.70; P < 0.01) compared with patients who did not exhibit SIRS. Thus, SIRS was strongly associated with an unfavourable prognosis, suggesting that it can be used as a prognostic indicator for canine parvovirus in veterinary practice. [ABSTRACT FROM AUTHOR]

Urban surface water is increasingly used for contact recreation. Predicting Escherichia coli (E. coli) concentrations in these waters can support early warning of bathers and explain the dynamics of this faecal pollution indicator. This study provides the first overview of the scientific knowledge on E. coli prediction models for freshwater in cities. Modelling techniques for urban waters are comparable to those for other freshwater environments, with multiple linear regression being the most frequently used approach. While previously reviewed E. coli prediction models for freshwater beaches predominantly target lakes, urban models mainly target rivers. We found indications that model performance for urban rivers is lower than for recreational beach water in rivers in general. Reported performance metrics indicate that not all relevant sources are captured by the models. Future research should solve the lack of insight into model performance for specific applications and verify the suggested directions to improve models' accuracy. [ABSTRACT FROM AUTHOR]

Background: The study aims to analyze the epidemiology of preservation fluid (PF) contamination and investigate the impact of PF contamination and possible donor-derived infections(p-DDI) on early postoperative prognosis in kidney transplant (KT) recipients. Methods: A total of 256 PF samples were collected for microbiological evaluation from all KT recipients who received deceased donor donations in our hospital from June 2018 to August 2022. Data on the baseline and clinical characteristics of these PF corresponding to recipients and donors were extracted from the electronic medical record. It mainly included the early postoperative complications and prognosis of KT recipients. Results: From June 2018 to August 2022, 597 kidney transplants were performed in our center, with 260 recipients receiving kidney transplantation from donation after citizens' death. A total of 256 samples of PF were collected, of which 64.5% (165/256) were culture positive, and 24.6% (63/165) of the culture-positive PF were polymicrobial contamination. A total of 238 strains were isolated, of which coagulase-negative staphylococci (CoNS) had the highest proportion of 34.0% (81/238), followed by Klebsiella pneumoniae with 20.6% (49/238) and Escherichia coli with 8.8% (21/238). Recipients with culture-positive PF had a significantly higher incidence of postoperative infection (55.8% vs. 20.9%, P < 0.001) and DGF (38.2% vs. 24.2%, P = 0.023). In addition, the incidence of p-DDI was 12.9% (33/256). CRKP was the most common pathogen causing p-DDI. The recipients who developed p-DDI had a higher rate of graft loss (9.1% vs. 0.4%, P < 0.001), mortality (12.1% vs. 3.1%, P = 0.018), and longer postoperative hospital stay (30 days (19.5–73.5) vs. (22 days (18–32), P < 0.05) compared with recipients who did not develop p-DDI. Conclusions: Culture-positive PF is potentially significant for KT recipients, and p-DDI may increase the risk of poor prognosis for recipients. Prophylactic anti-infective treatment should be actively performed for highly virulent or multidrug-resistant (MDR) pathogens (especially Carbapenem-resistant Klebsiella pneumoniae, CRKP) in PF to avoid the occurrence of p-DDI. [ABSTRACT FROM AUTHOR]

Wastewater discharge into the environment in resource-poor countries poses a threat to public health. Studies in this area within these countries are limited, and the use of high-throughput whole-genome sequencing technologies is lacking. Therefore, understanding of environmental impacts is inadequate. The present study investigated the antibiotic resistance profiles and diversity of beta-lactamases in Escherichia coli strains isolated from environmental water sources in Accra, Ghana. Microbiological analyses were conducted on wastewater samples from three hospitals, a sewage and wastewater treatment plant, and water samples from two urban surface water bodies. Confirmed isolates (N = 57) were selected for phenotypic antibiotic resistance profiles. Multi-drug-resistant isolates (n = 25) were genome sequenced using Illumina MiSeq sequencing technology and screened for sequence types, antibiotic resistance, virulence and beta-lactamase genes, and mobile genetic elements. Isolates were frequently resistant to ampicillin (63%), meropenem (47%), azithromycin (46%), and sulfamethoxazole-trimethoprim (42%). Twenty different sequence types (STs) were identified, including clinically relevant ones such as ST167 and ST21. Five isolates were assigned to novel STs: ST14531 (n = 2), ST14536, ST14537, and ST14538. The isolates belonged to phylogroups A (52%), B1 (44%), and B2 (4%) and carried β-lactamase (TEM-1B, TEM-1C, CTX-M-15, and blaDHA-1) and carbapenemase (OXA-1, OXA-181) resistance genes. Dominant plasmid replicons included Col440I (10.2%) and IncFIB (AP001918) (6.8%). Polluted urban environments in Accra are reservoirs for antibiotic-resistant bacteria, posing a substantial public health risk. The findings underscore the need for targeted public health interventions to mitigate the spread of antibiotic-resistant bacteria and protect public health. [ABSTRACT FROM AUTHOR]

In vivo experiments are increasingly using clinical score sheets to ensure minimal distress to the animals. A score sheet is a document that includes a list of specific symptoms, behaviours and intervention guidelines, all balanced to for an objective clinical assessment of experimental animals. Artificial Intelligence (AI) technologies are increasingly being applied in the field of preclinical research, not only in analysis but also in documentation processes, reflecting a significant shift towards more technologically advanced research methodologies. The present study explores the application of Large Language Models (LLM) in generating score sheets for an animal welfare assessment in a preclinical research setting. Focusing on a mouse model of inflammatory bowel disease, the study evaluates the performance of three LLM – ChatGPT-4, ChatGPT-3.5, and Google Bard – in creating clinical score sheets based on specified criteria such as weight loss, stool consistency, and visible fecal blood. Key parameters evaluated include the consistency of structure, accuracy in representing severity levels, and appropriateness of intervention thresholds. The findings reveal a duality in LLM-generated score sheets: while some LLM consistently structure their outputs effectively, all models exhibit notable variations in assigning numerical values to symptoms and defining intervention thresholds accurately. This emphasizes the dual nature of AI performance in this field—its potential to create useful foundational drafts and the critical need for professional review to ensure precision and reliability. The results highlight the significance of balancing AI-generated tools with expert oversight in preclinical research. [ABSTRACT FROM AUTHOR]

Water constitutes an indispensable resource crucial for the sustenance of humanity, as it plays an integral role in various sectors such as agriculture, industrial processes, and domestic consumption. Even though water covers 71% of the global land surface, governments have been grappling with the challenge of ensuring the provision of safe water for domestic use. A contributing factor to this situation is the persistent contamination of available water sources rendering them unfit for human consumption. A common contaminant, pesticides are not frequently tested for despite their serious effects on biodiversity. Pesticide determination in water quality assessment is a challenging task because the procedures involved in the extraction and detection are complex. This reduces their popularity in many monitoring campaigns despite their harmful effects. If the existing methods of pesticide analysis are adapted by leveraging new technologies, then information concerning their presence in water ecosystems can be exposed. Furthermore, beyond the advantages conferred by the integration of wireless sensor networks (WSNs), the Internet of Things (IoT), Machine Learning (ML), and big data analytics, a notable outcome is the attainment of a heightened degree of granularity in the information of water ecosystems. This paper discusses methods of pesticide detection in water, emphasizing the possible use of electrochemical sensors, biosensors, and paper-based sensors in wireless sensing. It also explores the application of WSNs in water, the IoT, computing models, ML, and big data analytics, and their potential for integration as technologies useful for pesticide monitoring in water. [ABSTRACT FROM AUTHOR]

Wastewater surveillance represents an alternative approach to regulating contamination and the early detection of infectious agents and outbreaks of diseases of public health importance. This study evaluated domestic wastewater effects on recreational waters in estuarine and seawater bodies in Guayas and Santa Elena provinces in Ecuador, South America. Fecal indicator bacteria (thermotolerant coliforms) served as key indicators for evaluation. Physical, chemical, and microbiological quality markers following the Ecuadorian environmental quality standard and the discharge of effluents to the water resource were analyzed. Samples were collected from 44 coastal sites and 2 oxidation lagoons during the dry and rainy seasons of 2020 and 2021, respectively. SARS-CoV-2 RNA was detected in samples with higher E. coli concentrations using reverse transcription quantitative PCR to detect the genes N and ORF1ab. All samples analyzed for SARS-CoV-2 showed Ct ˂ 40 for at least one gene. Four samples showed at least 20 genome copies of gene N per reaction. These were at an artisanal fishing port, an estuarine area (Palmar), a recreational bay, and an oxidation lagoon. A moderate correlation was found between SARS-CoV-2 RNA, thermotolerant coliform and E. coli (p-value ≤ 0.0037), and a strong and positive correlation between thermotolerant coliform and E. coli. (p-value ≤ 0.00001), highlighting the utility of these established parameters as a proxy of the virus. Significant differences were found in the concentrations of thermotolerant coliforms between seasons (p-value = 0.016) and sites (p-value = 0.005). The highest levels of coliforms were found in the dry season (63000 MPN/100 mL) in Anconcito and during the rainy season (14000 MPN/100 mL) at Esterillo in Playas County. It is recommended that the decentralized autonomous governments of the surveyed provinces in Ecuador implement urgent corrective actions and establish medium-term mechanisms to minimize a potential contamination route. Additional parameters must be included in the monitoring, such as Enterococcus and intestinal parasites, due to their public health implications. In the oxidation lagoons, maintenance actions must be carried out, including the dissolution of sediments, an increase in water retention times, and in situ treatment of the sludge, to improve the system's performance. [ABSTRACT FROM AUTHOR]

This editorial from the Journal of Water & Health emphasizes the importance of ensuring safe drinking water and converting commitment into action. It discusses the history of guidelines for drinking water quality and the shift towards a preventive risk management approach. The document highlights the development and implementation of Water Safety Plans (WSPs) as a means to achieve health-based targets. It includes insights from various countries on the implementation of WSPs, the importance of an enabling environment, continual improvement, risk assessment, and addressing natural hazardous events. The text provides valuable case studies and perspectives from different countries and settings, offering insights into the challenges and successes of implementing WSPs. [Extracted from the article]

We hypothesized that lactic acid bacteria (LAB) present in sediments at aquaculture sites can be employed as an indicator for the early prediction of deterioration, as the concentration of organic acids controls hydrogen sulfide production via sulfate-reducing bacteria. We selected two aquaculture sites with different acid volatile sulfide (AVS-S) values, St. OJ (average AVS-S = 0.24 mg S/g dry mud) and St. UM (average AVS-S = 1.16 mg S/g dry mud), which were less and critically deteriorated, respectively, and examined our hypothesis by performing a 3-year-long survey in Tanabe Bay, Wakayama Prefecture, Japan. In St. UM, the bacterial community showed positive correlations with AVS-S values and water contents. With AVS-S accumulation at the site, the abundances of LAB decreased below the detection limit, suggesting that LAB viable counts may be unsuitable for predicting early deterioration at sites with severe AVS-S accumulation. In St. OJ, the LAB viable counts, organic acid content, and AVS-S values increased after the beginning of sea bream aquaculture, and the bacterial community showed high correlations with the LAB counts, succinic and total organic acid concentrations, and the abundance of the class Bacilli. These on-site experiments indicated that LAB counts can be a reasonable indicator for evaluating deterioration in aquaculture sites. [ABSTRACT FROM AUTHOR]

Escherichia coli is a promising subject for globally coordinated surveillance of antimicrobial resistance (AMR) in water environments due to its clinical relevance and widespread use as an indicator of fecal contamination. Cefotaxime-resistant E. coli was recently evaluated favorably for this purpose by the World Health Organization TriCycle Protocol, which specifies tryptone bile x-glucuronide (TBX) medium and incubation at 35°C. We assessed comparability with the U.S. Environmental Protection Agency-approved method for E. coli quantification, which uses membrane-thermotolerant E. coli (mTEC) agar and incubation at 44.5°C, in terms of recovery of E. coli and cefotaxime-resistant E. coli from wastewater influent and surface waters. Total E. coli concentrations in wastewater influent were 106-108 CFU/100 mL, while cefotaxime-resistant E. coli were ~100-fold lower. Total E. coli in surface waters were ~10² CFU/100 mL, and cefotaxime-resistant isolates were near the limit of detection (0.4 CFU/100 mL). Total and putative cefotaxime-resistant E. coli concentrations did not differ significant ly between media or by incubation method; however, colonies isolated on mTEC were more frequently confirmed to species (97.1%) compared to those from TBX (92.5%). Incubation in a water bath at 44.5°C significantly decreased non-specific background growth and improved confirmation frequency on both media (97.4%) compared to incubation at 35°C (92.3%). This study helps to advance globally coordinated AMR in water environments and suggests that the TriCycle Protocol is adaptable to other standard methods that may be required in different locales, while also offering a means to improve specificity by decreasing the frequency of false-positive identification of cefotaxime-resistant E. coli by modifying incubation conditions. [ABSTRACT FROM AUTHOR]

The consumption of contaminated poultry meat is a significant threat for public health, as it implicates in foodborne pathogen infections, such as those caused by Arcobacter. The mitigation of clinical cases requires the understanding of contamination pathways in each food process and the characterization of resident microbiota in the productive environments, so that targeted sanitizing procedures can be effective ly implemented. Nowadays these investigations can benefit from the complementary and thoughtful use of culture- and omics-based analyses, although their application in situ is still limited. Therefore, the 16S-rRNA gene-based sequencing of total DNA and the targeted isolation of Arcobacter spp. through enrichment were performed to reconstruct the environmental contamination pathways within a poultry abattoir, as well as the dynamics and distribution of this emerging pathogen. To that scope, broiler's neck skin and caeca have been sampled during processing, while environmental swabs were collected from surfaces after cleaning and sanitizing. Metataxonomic survey highlighted a negligible impact of fecal contamination and a major role of broiler's skin in determining the composition of the resident abattoir microbiota. The introduction of Arcobacter spp. in the environment was mainly conveyed by this source rather than the intestinal content. Arcobacter butzleri represented one of the most abundant species and was extensively detected in the abattoir by both metataxonomic and enrichment methods, showing higher prevalence than other more thermophilic Campylobacterota. In particular, Arcobacter spp. was recovered viable in the plucking sector with high frequency, despite the adequacy of the sanitizing procedure. [ABSTRACT FROM AUTHOR]

Traditional laboratory-based water quality monitoring and testing approaches are soon to be outdated, mainly because of the need for real-time feedback and immediate responses to emergencies. The more recent wireless sensor network (WSN)-based techniques are evolving to alleviate the problems of monitoring, coverage, and energy management, among others. The inclusion of the Internet of Things (IoT) in WSN techniques can further lead to their improvement in delivering, in real time, effective and efficient water-monitoring systems, reaping from the benefits of IoT wireless systems. However, they still suffer from the inability to deliver accurate real-time data, a lack of reconfigurability, the need to be deployed in ad hoc harsh environments, and their limited acceptability within industry. Electronic sensors are required for them to be effectively incorporated into the IoT WSN water-quality-monitoring system. Very few electronic sensors exist for parameter measurement. This necessitates the incorporation of artificial intelligence (AI) sensory techniques for smart water-quality-monitoring systems for indicators without actual electronic sensors by relating with available sensor data. This approach is in its infancy and is still not yet accepted nor standardized by the industry. This work presents a smart water-quality-monitoring framework featuring an intelligent IoT WSN monitoring system. The system uses AI sensors for indicators without electronic sensors, as the design of electronic sensors is lagging behind monitoring systems. In particular, machine learning algorithms are used to predict E. coli concentrations in water. Six different machine learning models (ridge regression, random forest regressor, stochastic gradient boosting, support vector machine, k-nearest neighbors, and AdaBoost regressor) are used on a sourced dataset. From the results, the best-performing model on average during testing was the AdaBoost regressor (a M A E ¯ of 14.37 counts/100 mL), and the worst-performing model was stochastic gradient boosting (a M A E ¯ of 42.27 counts/100 mL). The development and application of such a system is not trivial. The best-performing water parameter set (Set A) contained pH, conductivity, chloride, turbidity, nitrates, and chlorophyll. [ABSTRACT FROM AUTHOR]

Background: Broiler chickens are frequently colonized with Extended-Spectrum Beta-Lactamase- (ESBL-) and plasmid mediated AmpC Beta-Lactamase- (pAmpC-) producing Enterobacterales, and we are confronted with the potential spread of these resistant bacteria in the food chain, in the environment, and to humans. Research focused on identifying of transmission routes and investigating potential intervention measures against ESBL- and pAmpC- producing bacteria in the broiler production chain. However, few data are available on the effects of cleaning and disinfection (C&D) procedures in broiler stables on ESBL- and pAmpC- producing bacteria. Results: We systematically investigated five broiler stables before and after C&D and identified potential ESBL- and pAmpC- colonization sites after C&D in the broiler stables, including the anteroom and the nearby surrounding environment of the broiler stables. Phenotypically resistant E. coli isolates grown on MacConkey agar with cefotaxime were further analyzed for their beta-lactam resistance genes and phylogenetic groups, as well as the relation of isolates from the investigated stables before and after C&D by whole genome sequencing. Survival of ESBL- and pAmpC- producing E. coli is highly likely at sites where C&D was not performed or where insufficient cleaning was performed prior to disinfection. For the first time, we showed highly related ESBL-/pAmpC- producing E. coli isolates detected before and after C&D in four of five broiler stables examined with cgMLST. Survival of resistant isolates in investigated broiler stables as well as transmission of resistant isolates from broiler stables to the anteroom and surrounding environment and between broiler farms was shown. In addition, enterococci (frequently utilized to detect fecal contamination and for C&D control) can be used as an indicator bacterium for the detection of ESBL-/pAmpC- E. coli after C&D. Conclusion: We conclude that C&D can reduce ESBL-/pAmpC- producing E. coli in conventional broiler stables, but complete ESBL- and pAmpC- elimination does not seem to be possible in practice as several factors influence the C&D outcome (e.g. broiler stable condition, ESBL-/pAmpC- status prior to C&D, C&D procedures used, and biosecurity measures on the farm). A multifactorial approach, combining various hygiene- and management measures, is needed to reduce ESBL-/pAmpC- E. coli in broiler farms. [ABSTRACT FROM AUTHOR]

Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure. [ABSTRACT FROM AUTHOR]

Background Environmental surveillance (ES) for Salmonella Typhi potentially offers a low-cost tool to identify communities with a high burden of typhoid fever. Methods We developed standardized protocols for typhoid ES, including sampling site selection, validation, characterization; grab or trap sample collection, concentration; and quantitative PCR targeting Salmonella genes (ttr , staG, and tviB) and a marker of human fecal contamination (HF183). ES was implemented over 12 months in a historically high typhoid fever incidence setting (Vellore, India) and a lower incidence setting (Blantyre, Malawi) during 2021–2022. Results S. Typhi prevalence in ES samples was higher in Vellore compared with Blantyre; 39/520 (7.5%; 95% confidence interval [CI], 4.4%–12.4%) vs 11/533 (2.1%; 95% CI, 1.1%–4.0%) in grab and 79/517 (15.3%; 95% CI, 9.8%–23.0%) vs 23/594 (3.9%; 95% CI, 1.9%–7.9%) in trap samples. Detection was clustered by ES site and correlated with site catchment population in Vellore but not Blantyre. Incidence of culture-confirmed typhoid in local hospitals was low during the study and zero some months in Vellore despite S. Typhi detection in ES. Conclusions ES describes the prevalence and distribution of S. Typhi even in the absence of typhoid cases and could inform vaccine introduction. Expanded implementation and comparison with clinical and serological surveillance will further establish its public health utility. [ABSTRACT FROM AUTHOR]

Understanding the dynamic change in abundance of both fecal and opportunistic waterborne pathogens in urban surface water under different abiotic and biotic factors helps the prediction of microbiological water quality and protection of public health during recreational activities, such as swimming. However, a comprehensive understanding of the interaction among various factors on pathogen behavior in surface water is missing. In this study, the effect of salinity, light, and temperature and the presence of indigenous microbiota, on the decay/persistence of Escherichia coli and Pseudomonas aeruginosa in Rhine River water were tested during 7 days of incubation with varying salinity (0.4, 5.4, 9.4, and 15.4 ppt), with light under a light/dark regime (light/dark) and without light (dark), temperature (3, 12, and 20 °C), and presence/absence of indigenous microbiota. The results demonstrated that light, indigenous microbiota, and temperature significantly impacted the decay of E. coli. Moreover, a significant (p<0.01) four-factor interactive impact of these four environmental conditions on E. coli decay was observed. However, for P. aeruginosa, temperature and indigenous microbiota were two determinate factors on the decay or growth. A significant three-factor interactive impact between indigenous microbiota, temperature, and salinity (p<0.01); indigenous microbiota, light, and temperature (p<0.01); and light, temperature, and salinity (p<0.05) on the decay of P. aeruginosa was found. Due to these interactive effects, caution should be taken when predicting decay/persistence of E. coli and P. aeruginosa in surface water based on a single environmental condition. In addition, the different response of E. coli and P. aeruginosa to the environmental conditions highlights that E. coli monitoring alone underestimates health risks of surface water by non-fecal opportunistic pathogens, such as P. aeruginosa. Key points: Abiotic and biotic factors interactively affect decay of E. coli and P. aeruginosa E.coli and P.aeruginosa behave significantly different under the given conditions Only E. coli as an indicator underestimates the microbiological water quality [ABSTRACT FROM AUTHOR]

Background: Numerous recent studies have found a strong correlation between intestinal flora and the occurrence of hypertension. However, it remains unclear whether fecal microbiota transfer might affect the blood pressure of the host. This study aimed to quantify both associations. Methods: An electronic search was conducted in PubMed, EMBASE, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), WanFang database, Weipu, Embase, and SinoMed to retrieve relevant studies. The final search was completed on August 22, 2022. Two authors independently applied the inclusion criteria, extracted data, and assessed the risk of bias assessment. All data were analyzed using RevMan 5.4. Results: A total of 5 articles were selected for final inclusion. All studies were assessed as having a high risk of bias according to the SYRCLE risk of bias tool. The meta-analysis results showed that transplantation of fecal bacteria from the hypertensive model can significantly improve the host's systolic pressure (MD = 18.37, 95%CI: 9.74~26.99, P<0.001), and diastolic pressure (MD = 17.65, 95%CI: 12.37~22.93, P<0.001). Subgroup analyses revealed that the increase in systolic pressure in the hypertension model subgroup (MD = 29.56, 95%CI = 23.55–35.58, P<0.001) was more pronounced than that in the normotensive model subgroup (MD = 12.48, 95%CI = 3.51–21.45, P<0.001). Conclusion: This meta-analysis suggests a relationship between gut microbiota dysbiosis and increased blood pressure, where transplantation of fecal bacteria from the hypertensive model can cause a significant increase in systolic pressure and diastolic pressure in animal models. [ABSTRACT FROM AUTHOR]

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics. [ABSTRACT FROM AUTHOR]

Simple Summary: Non-alcoholic fatty liver disease (NAFLD) is a type of metabolic stress liver injury closely related to insulin resistance (IR) and genetic susceptibility without alcohol consumption, which encompasses a spectrum of liver disorders ranging from simple hepatic lipid accumulation, known as steatosis, to the more severe form of steatohepatitis (NASH). In this narrative review, we summarize the roles of gut barrier dysfunction and gut microbiota in NAFLD, including their physiological functions, assessment methods, related mechanisms, and therapeutic approaches for the prevention and treatment of NAFLD. Non-alcoholic fatty liver disease (NAFLD) is a type of metabolic stress liver injury closely related to insulin resistance (IR) and genetic susceptibility without alcohol consumption, which encompasses a spectrum of liver disorders ranging from simple hepatic lipid accumulation, known as steatosis, to the more severe form of steatohepatitis (NASH). NASH can progress to cirrhosis and hepatocellular carcinoma (HCC), posing significant health risks. As a multisystem disease, NAFLD is closely associated with systemic insulin resistance, central obesity, and metabolic disorders, which contribute to its pathogenesis and the development of extrahepatic complications, such as cardiovascular disease (CVD), type 2 diabetes mellitus, chronic kidney disease, and certain extrahepatic cancers. Recent evidence highlights the indispensable roles of intestinal barrier dysfunction and gut microbiota in the onset and progression of NAFLD/NASH. This review provides a comprehensive insight into the role of intestinal barrier dysfunction and gut microbiota in NAFLD, including intestinal barrier function and assessment, inflammatory factors, TLR4 signaling, and the gut–liver axis. Finally, we conclude with a discussion on the potential therapeutic strategies targeting gut permeability and gut microbiota in individuals with NAFLD/NASH, such as interventions with medications/probiotics, fecal transplantation (FMT), and modifications in lifestyle, including exercise and diet. [ABSTRACT FROM AUTHOR]

When combined with conducive atmospheric conditions, air pollution caused by fossil fuel consumption associated with transportation, industry and electricity production for households, create and sustain continuous pollution over the megalopolis of Tehran, Iran. In conjunction with daily meteorological forecasts, remote sensing can be used to identify and predict days with hazardous levels of air pollution, providing an opportunity for air quality alert systems to be triggered and warnings circulated to reduce health risks to citizens of Tehran province. Combining remotely sensed ozone column density (OCD) data from the Sentinel-5 TROPOMI sensor with NASA Giovanni data concerning meteorological parameters (temperature (T), wind speed (WS) and specific humidity (SH)), geographical parameters and population data, this study considers the drivers and effects of ozone pollution on the urban climate and vegetation condition (normalized difference vegetation index (NDVI)) of 16 counties in Tehran province, Iran during 12 months (i.e., January 2021 to December 2021). Future monthly forecasts of the OCD, climatic and terrestrial factors in 2022 are also presented. Google Earth Engine and the NASA Giovanni platforms were employed for the processing and analysis of data using an interpolation technique. Additionally, a Box–Jenkins ARIMA and Exponential Smoothing (ETS) models were compared and tailored to generate monthly forecasts of OCD, T, WS, SH and NDVI. The highest and lowest OCD was obtained in June and December 2021, with a concentration of 0.14277 mol/m2 and 0.12383 mol/m2, respectively. However, the annual average OCD was higher in the cities of Shahriar and Pakdasht in March, with values of 0.13237 mol/m2 and 0.13244 mol/m2, respectively. The lowest OCD recorded was 0.13105 mol/m2, in Shemiranat city, in the north of Tehran. The results indicate a positive correlation between OCD and NDVI, and a negative correlation between OCD, SH, WS and T. A strong seasonal trend in OCD was identified for all cities, but across the entire province, altitude and population size were the most significant explanatory variables for spatial variations in OCD. This research demonstrates that an effective OCD monitoring and forecasting model may be generated from remote sensing and meteorological variables. The implementation and utilization of these models are of paramount importance as they offer vital information to authorities for continuous air quality monitoring and strategic planning, particularly for days with hazardous air pollution. By effectively implementing the OCD model, it has the potential to directly contribute to improved health outcomes in major cities across Iran. [ABSTRACT FROM AUTHOR]

Overweight and obesity are closely linked to gut dysbiosis/dysmetabolism and disrupted De‐Ritis ratio [aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio], which may contribute to chronic noncommunicable diseases onset. Concurrently, extensive research explores nutraceuticals, and health‐enhancing supplements, for disease prevention or treatment. Thus, sedentary overweight volunteers were double‐blind randomized into two groups: Novel Nutraceutical_(S) (without silymarin) and Novel Nutraceutical (with silymarin). Experimental formulations were orally administered twice daily over 180 consecutive days. We evaluated fecal gut microbiota, based on partial 16S rRNA sequences, biochemistry and endocrine markers, steatosis biomarker (AST/ALT ratio), and anthropometric parameters. Post‐supplementation, only the Novel Nutraceutical group reduced Clostridium clostridioforme (Firmicutes), Firmicutes/Bacteroidetes ratio (F/B ratio), and De‐Ritis ratio, while elevating Bacteroides caccae and Bacteroides uniformis (Bacteroidetes) in Brazilian sedentary overweight volunteers after 180 days. In summary, the results presented here allow us to suggest the gut microbiota as the action mechanism of the Novel Nutraceutical promoting metabolic hepatic recovery in obesity/overweight non‐drug interventions. [ABSTRACT FROM AUTHOR]

The traditional monitoring method of water resources environment mainly relies on manual sampling and laboratory analysis, which is limited in time and space and can not realize the comprehensive monitoring of water resources environment. With the continuous development of computer technology and network communication technology, real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis has gradually become a new solution. This paper aims to propose a real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis, in order to achieve accurate and efficient monitoring of water resources environment, timely acquisition and analysis of key data of water resources environment, and provide scientific basis for relevant decisions. In this paper, the key parameters of water quality, water quantity and water ecology are collected by using computer remote data acquisition and image analysis. Using computer image analysis technology, the collected image data are processed and analyzed, and the related characteristics and indicators of water resources environment are extracted. The results show that the real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis can monitor the data changes of water resources environment accurately and efficiently. Through the analysis and processing of the real-time data, the problems in the water resources environment can be found and warned in time, and the corresponding measures can be taken to regulate and manage. [ABSTRACT FROM AUTHOR]

Background: Escherichia coli, a ubiquitous inhabitant of the gut microbiota, has been recognized as an indicator of fecal contamination and a potential reservoir for antibiotic resistance genes. Its prevalence in drinking water sources raises concerns about the potential dissemination of antibiotic resistance within aquatic ecosystems and the subsequent impact on public health. The ability of E. coli to acquire and transfer resistance genes, coupled with the constant exposure to low levels of antibiotics in the environment, underscores the need for comprehensive surveillance and rigorous antimicrobial stewardship strategies to safeguard the quality and safety of drinking water supplies, ultimately mitigating the escalation of antibiotic resistance and its implications for human well-being. Methods: WG5D strain, isolated from a drinking water distribution source in North-West Province, South Africa, underwent genomic analysis following isolation on nutrient agar, anaerobic cultivation, and DNA extraction. Paired-end Illumina sequencing with a Nextera XT Library Preparation kit was performed. The assembly, annotation, and subsequent genomic analyses, including phylogenetic analysis using TYGS, pairwise comparisons, and determination of genes related to antimicrobial resistance and virulence, were carried out following standard protocols and tools, ensuring comprehensive insights into the strain's genomic features. Results: This study explores the notable characteristics of E. coli strain WG5D. This strain stands out because it possesses multiple antibiotic resistance genes, encompassing tetracycline, cephalosporin, vancomycin, and aminoglycoside resistances. Additionally, virulence-associated genes indicate potential heightened pathogenicity, complemented by the identification of mobile genetic elements that underscore its adaptability. The intriguing possibility of bacteriophage involvement and factors contributing to pathogenicity further enriches our understanding. We identified E. coli WG5D as a potential human pathogen associated with a drinking water source in South Africa. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. It further identified WG5D as a potential human pathogen. The occurrence of E. coli WG5D raised the awareness of the potential pathogens and the carrying of antibiotic resistance in drinking water. Conclusions: The findings of this study have highlighted the advantages of the genomic approach in identifying the bacterial species and antibiotic resistance genes of E. coli and its potential as a human pathogen. [ABSTRACT FROM AUTHOR]

Background and Aim: Milk contamination for human consumption is one of the biggest concerns worldwide. To prevent milk contamination, it is important to implement sustainable production practices that ensure animal health and guarantee veterinary drugs have been used properly. This study aimed to detect antibiotic residues and microbial contamination in commercially available pasteurized whole milk intended for human consumption. Materials and Methods: We conducted a cross-sectional study on all brands of pasteurized milk (n = 17) for human consumption in Medellín, Colombia, from February 30 to April 30, 2022. Six milk samples of each brand were collected every 15 days, resulting in 102 samples. IDEXX SNAPduo™ ST Plus test (IDEXX Laboratories Inc, Maine, USA) was used to detect cephalosporins residues to detect beta-lactam and tetracyclines. We detected mesophilic aerobic bacteria and coliforms using Chromocult Coliform Agar® (Merck KGaA, Darmstadt, Germany) and Plate-Count Agar® (Merck KGaA), respectively. Results: Beta-lactam residues were found in 24.4% of the brands. No tetracyclines or cephalosporins were detected. Mesophilic aerobic bacteria and coliform contamination were detected in 42.6% and 12.8% of the brands, respectively. No fecal coliform contamination was detected. Conclusion: This study demonstrated the presence of antibiotic residues and microbial contamination in commercially available pasteurized whole milk intended for human consumption in the study area, highlighting its potential public health implications. [ABSTRACT FROM AUTHOR]

Onsite wastewater treatment systems (OWTSs) and private wells are commonly used in Eastern North Carolina, USA. Water from private wells is not required to be tested after the initial startup, and thus persons using these wells may experience negative health outcomes if their water is contaminated with waste-related pollutants including bacteria, nitrate or synthetic chemicals such as hexafluoropropylne oxide dimer acid and its ammonium salt (GenX). Water samples from 18 sites with OWTSs and groundwater wells were collected for nitrate, Escherichia coli (E. coli), total coliform, and GenX concentration analyses. Results showed that none of the 18 water supplies were positive for E. coli, nitrate concentrations were all below the maximum contaminant level of 10 mg L-1, and one well had 1 MPN 100 mL-1 of total coliform. However, GenX was detected in wastewater collected from all 18 septic tanks and 22% of the water supplies tested had concentrations that exceeded the health advisory levels for GenX. Water supplies with low concentrations of traditionally tested for pollutants (nitrate, E. coli) may still pose health risks due to elevated concentrations of emerging contaminants like GenX and thus more comprehensive and routine water testing is suggested for this and similar persistent compounds. [ABSTRACT FROM AUTHOR]

Anecdotal evidence and available literature indicated that contaminated water played a major role in spreading the prolonged cholera epidemic in Malawi from 2022 to 2023. This study assessed drinking water quality in 17 cholera-affected Malawi districts from February to April 2023. Six hundred and thirty-three records were analysed. The median counts/100 ml for thermotolerant coliform was 98 (interquartile range (IQR): 4-100) and that for Escherichia coli was 0 (IQR: 0-9). The drinking water in all (except one) districts was contaminated by thermotolerant coliform, while six districts had their drinking water sources contaminated by E. coli. The percentage of contaminated drinking water sources was significantly higher in shallow unprotected wells (80.0% for E. coli and 95.0% for thermotolerant coliform) and in households (55.8% for E. coli and 86.0% for thermotolerant coliform). Logistic regression showed that household water has three times more risk of being contaminated by E. coli and two and a half times more risk of being contaminated by thermotolerant coliform compared to other water sources. This study demonstrated widespread contamination of drinking water sources during a cholera epidemic in Malawi, which may be the plausible reason for the protracted nature of the epidemic. [ABSTRACT FROM AUTHOR]

Computer vision (CV) technologies have been applied extensively in turbid water assessment. However, the accuracies of CV to detect turbidity is limited by several factors such as inferior image quality and adoptation of traditional machine learning (MsL). Several past studies have shown that the accuracy of CV to detect turbidity can be enhanced by employing image pre-processing and artificial intelligence (AI). Therefore, this study proposes a combined CV and convolution neural network (CNN) approach for turbid water classification in accordance with national water quality standards. A total of 71 turbid water samples in the range of 0–100 nephelometry turbidity units (NTU) were prepared from a mixture of 1000 NTU stock Formazine solution and distilled water. Digital images of water samples were acquired with the Asus Zenfone Go smartphone and nephelometry principle. Synthetic minority oversampling technique (SMOTE) was employed for image pre-processing, synthesis, and augmentation. Classification models were developed with Keras CNN architecture and TensorFlow framework. Two national water standards referred to were Malaysia National Water Quality Standard Class I (NWQS-C1) and France Système D'évaluation de la Qualité des cours d'EAU bleu aptitude (SEQ-EAU-b). The proposed CV-CNN approach was successfully implemented with 94.34–98.42% accuracy. The accuracy of CNN was slightly higher when trained with color images (98.42%) than with grayscale images (94.34%). This study demonstrated that CV and CNN are excellent tools for water quality assessment, especially for classifying water turbidity. [ABSTRACT FROM AUTHOR]

Sponges from the Clathria genus, especially those from Derawan Island, Indonesia, are renowned repositories of microbial symbionts enriched with potent bioactive compounds. Our study delved into these sponges, extracting and examining their bacterial symbionts for their antimicrobial, antioxidant, and enzymatic activities. Using dilution and streak methods, 23 distinct bacterial types were isolated and identified based on cellular morphology. Among these, the SC-06 isolate demonstrated significant antibacterial capabilities against Staphylococcus aureus and Escherichia coli. Further, isolates SC-01, SC-03, SC-11, SC-13, and SC-15 exhibited powerful antioxidant properties, neutralizing over 50% of radicals. Additionally, strains SC-08, SC-02, SC-05, and SC-22 displayed remarkable enzymatic activities, suggesting their potential industrial applications. The Clathria sp. sponges from Derawan offer a promising biotechnological frontier, with their bacterial symbionts poised to redefine marine biotech innovations. [ABSTRACT FROM AUTHOR]

Many empirical studies on large municipalities, ranging from thousands to millions of inhabitants, have helped shape the knowledge of sustainability management in developed countries. However, issues and approaches specific to micro‐municipalities with fewer than 1,000 inhabitants have been relatively less covered. In this context, this study presents an empirical content analysis of sustainability‐related instruments used in the 487 smallest municipalities of Quebec. A total of 1,962 instrumental documents were identified, and their characteristics (e.g., accountability‐based vs. informative‐based approach) and scope (e.g., land‐use planning and pollution reduction) were assessed. The results are threefold. First, informative‐based instruments (e.g., flyers and project presentations) are generally preferred to those with accountability mechanisms (e.g., policies and plans). Second, 90% of the municipalities address sustainability issues, but in pieces and parsimoniously rather than comprehensively; hence, initiatives vary significantly from one municipality to another. Third, because of their mandatory nature, initiatives such as sorted waste collection and pro‐environmental zoning are common among municipalities. In contrast, non‐mandatory services such as transportation planning have only a few adopters. These findings have policy implications for urban sustainability management in micro‐municipal organizations. Key messages: A broader approach, beyond dedicated policy or action plans, is needed to research small municipalities' approaches to sustainability.Micro‐municipalities tend to adopt a parsimonious approach to sustainability issues, rather than addressing them comprehensively.Unlike large municipalities, whose challenges are similar to one another, small municipalities' sustainability initiatives differ widely because of their unique circumstances. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is an ever-present threat to the treatment of infectious diseases. However, the potential relevance of this phenomenon in environmental reservoirs still raises many questions. Detection of antimicrobial-resistant bacteria in the environment is a critical aspect for understanding the prevalence of resistance outside of clinical settings, as detection in the environment indicates that resistance is likely already widespread. We isolated antimicrobial-resistant Escherichia coli from three urban waterbodies over a 15-month time series, determined their antimicrobial susceptibilities, investigated their population structure, and ident ified genetic determinants of resistance. We found that E. coli populations at each site were composed of different dominant phylotypes and showed distinct patterns of antimicrobial and multidrug resistance, despite close geographic proximity. Many strains that were genome-sequenced belonged to sequence types of international concern, particularly the ST131 clonal complex. We found widespread resistance to clinically important antimicrobials such as amoxicillin, cefotaxime, and ciprofloxacin, but found that all strains were susceptible to amikacin and the last-line antimicrobials meropenem and fosfomycin. Resistance was most often due to acquirable antimicrobial resistance genes, while chromosomal mutations in gyrA, parC, and parE conferred resistance to quinolones. Whole-genome analysis of a subset of strains further revealed the diversity of the population of E. coli present, with a wide array of AMR and virulence genes identified, many of which were present on the chromosome, including blaCTX-M. Finally, we determined that environmental persistence, transmission between sites, most likely mediated by wild birds, and transfer of mobile genetic elements likely contributed significantly to the patterns observed. IMPORTANCE A One Health perspective is crucial to understand the extent of antimicrobial resistance (AMR) globally, and investigation of AMR in the environment has been increasing in recent years. However, most studies have focused on waterways that are directly polluted by sewage, industrial manufacturing, or agricultural activities. Therefore, there remains a lack of knowledge about more natural, less overtly impacted environments. Through phenotypic and genotypic investigation of AMR in Escherichia coli, this study adds to our understanding of the extent and patterns of resistance in these types of environments, including over a time series, and showed that complex biotic and abiotic factors contribute to the patterns observed. Our study further emphasizes the importance of incorporating the surveillance of microbes in freshwater environments in order to better comprehend potential risks for both human and animal health and how the environment may serve as a sentinel for potential future clinical infections. [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]

This study aimed to investigate the effects of different dosages of adenine on intestinal microorganisms and enzyme activities, laying the experimental groundwork for subsequent exploration of the microbial mechanisms underlying diarrhea with kidney yang deficiency syndrome. Twenty-four mice were assigned to the following four groups: the control (NC) group, low-dosage adenine (NML) group, middle-dosage adenine (NMM) group, and high-dosage adenine (NMH) group. Mice in the NML, NMM, and NMH groups received 25 mg/(kg·d), 50 mg/(kg·d), and 100 mg/(kg·d) of adenine, respectively, 0.4 mL/each, once a day for 14 days. The NC group received 0.4 mL sterile water. Parameters including body weight, rectal temperature, intestinal microorganisms, enzyme activities, and microbial activity were measured. Results indicated that mice in the experimental group displayed signs of a poor mental state, curled up with their backs arched, and felt sleepy and lazy, with sparse fur that was easily shed, and damp bedding. Some mice showed fecal adhesion contamination in the perianal and tail areas. Dosage-dependent effects were observed, with decreased food intake, body weight, rectal temperature, and microbial activity and increased water intake and fecal water content. Enzyme activity analyses revealed significantly higher activities of protease, sucrase, amylase, and cellulase in intestinal contents and lactase, sucrase, amylase, and cellulase in the mucosa of the NMM group compared to those of other groups. Ultimately, the higher adenine dosage was associated with more pronounced symptoms of kidney yang deficiency syndrome, with 50 mg/kg adenine exhibiting the most substantial impact on the number of intestinal microbial colonies and enzyme activities. [ABSTRACT FROM AUTHOR]

In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the Internet of Things (IoT) in developing a monitoring system, particularly for water quality, to reduce the risk of contracting diseases. Water quality components data, such as water temperature, alkalinity or acidity, and contaminants, were obtained through a series of linked sensors. An Arduino microcontroller board acquired all the data and the Narrow Band-IoT (NB-IoT) transmitted them to the web server. Due to limited human resources to observe the water quality physically, the monitoring was complemented by real-time notifications alerts via a telephone text messaging application. The water quality data were monitored using Grafana in web mode, and the binary classifiers of machine learning techniques were applied to predict whether the water was drinkable or not based on the data collected, which were stored in a database. The non-decision tree, as well as the decision tree, were evaluated based on the improvements of the artificial intelligence framework. With a ratio of 60% for data training: at 20% for data validation, and 10% for data testing, the performance of the decision tree (DT) model was more prominent in comparison with the Gradient Boosting (GB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) modeling approaches. Through the monitoring and prediction of results, the authorities can sample the water sources every two weeks. [ABSTRACT FROM AUTHOR]

Background: Exocrine pancreatic insufficiency (EPI) can be associated with all types of diabetes. Pancreatic enzyme replacement therapy (PERT) has short and long-term benefits in subjects with EPI, but its effects on diabetes control are uncertain. We aimed to study the effects of PERT initiation on glycemic control in subjects with diabetes and EPI from any cause. Methods: In this retrospective study, we compared subjects with EPI and diabetes who were prescribed PERT with subjects with diabetes who had a fecal elastase-1 concentration dosage, but did not receive PERT. The primary outcome was the effect of PERT on hypoglycemia frequency and severity. The secondary outcomes were the effects of PERT on gastro-intestinal disorders, HbA1c and body mass index (BMI). Results: 48 subjects were included in each group. Overall, PERT did not have any significant effect on hypoglycemia frequency or severity, but hypoglycemia frequency tended to decrease in subjects with chronic pancreatitis. While 19% of subjects experienced mild hyperglycemia after PERT initiation, we did not report any keto-acidosis or any other severe adverse event. Gastro-intestinal disorders improved in 80% of subjects treated with PERT, versus in 20% of control subjects (p = 0.02). Gastro-intestinal disorders improved in 87% of subjects with recommended dosage of PERT, versus in 50% of subjects with underdosage (NS). HbA1c and BMI evolution did not differ between the groups. Conclusions: PERT initiation is safe in subjects with diabetes and EPI. It does not globally decrease hypoglycemia severity of frequency, but is associated with a decrease in gastro-intestinal disorders. Trial registration Retrospectively registered. The database was registered with the Commission Nationale Informatique et Libertés (CNIL), registration number: 2203351v0. The study was approved by the local ethics committee CLEP, registration number: AAA-2023-09047 [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) and its composition in aquatic ecosystems is a key indicator of ecosystem function and an important component of the global carbon cycle. Tropical rainforest headwaters play an important role in global carbon cycling. However, there is a large uncertainty on how DOM sources interact during mobilisation and the potential fate of associated carbon and nutrients. Using field techniques to measure dissolved organic carbon (DOC) concentration and composition, changes in DOM source from headwaters to larger downstream rivers were observed. This study shows that the hydrological connectivity, developed during the transition from dry to wet seasons, changes the DOM supply and transport across a tropical river catchment. The observed variability in the DOC-river discharge relationship provides further evidence of the changes in the DOM supply in a small headwater. This novel insight into the seasonal changes of the dynamics of DOM supply to the river helps understanding the mobilization of terrestrial DOM to tropical headwaters and its export from smaller to larger rivers. It also highlights the data gap in the study of smaller headwaters which may account for uncertainty in estimating the terrestrial carbon transported by inland waters. [ABSTRACT FROM AUTHOR]

This study aimed to investigate and compare the proportion of AMR Escherichia coli (E. coli) between urban (Dompe in the Western province) and rural (Dambana in the Sabaragamuwa province) areas in Sri Lanka. The overall hypothesis of the study is that there is a difference in the proportion of AMR E. coli between the urban and the rural areas. Faecal samples were collected from healthy humans (n = 109), dairy animals (n = 103), poultry (n = 35), wild mammals (n = 81), wild birds (n = 76), soil (n = 80) and water (n = 80) from both areas. A total of 908 E. coli isolates were tested for susceptibility to 12 antimicrobials. Overall, E. coli isolated from urban area was significantly more likely to be resistant than those isolated from rural area. The human domain of the area had a significantly higher prevalence of AMR E. coli, but it was not significantly different in urban (98%) and rural (97%) areas. AMR E. coli isolated from dairy animals, wild animals and water was significantly higher in the urban area compared with the rural area. There was no significant difference in the proportion of multidrug resistance (MDR) E. coli isolated from humans, wild animals and water between the two study sites. Resistant isolates found from water and wild animals suggest contamination of the environment. A multi‐sectorial One Health approach is urgently needed to control the spread of AMR and prevent the occurrences of AMR in Sri Lanka. [ABSTRACT FROM AUTHOR]

The purification and densification of wastewater play an important role in water recycling, especially if the materials used in water recycling are other types of recycled waste. Therefore, considering this view in this study, the biosynthesis of silver-decorated chromium oxide nanoparticles utilizing a wasted Allium sativum (garlic) peel extract is investigated. The aqueous extract of garlic peel (GPE) was treated with silver nitrate, chromium nitrate, and a mixture of silver nitrate and chromium nitrate to synthesize silver nanoparticles (Ag-garlic), chromium oxide nanoparticles (Cr2O3-garlic), and silver-decorated chromium oxide nanoparticles (Ag@Cr2O3-garlic), respectively. The synthesized nanoparticles were elucidated via thermal gravimetric analysis (TGA), infrared spectra (FT-IR), absorption spectra (UV-Vis), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). Antimicrobial activity studies were conducted against waterborne germs, bacterial strains (Bacillus subtilis, Enterococcus faecium, Escherichia coli, and Pseudomonas aeruginosa), and fungal strains (Alternaria porri, Aspergillus flavus, Aspergillus niger, Fuserium oxysporum, and Trichoderma longibrachiatum) and showed significant levels of antimicrobial activity. The results revealed that Ag@Cr2O3 significantly improved antimicrobial activity due to their synergistic effect. The photocatalytic activity of nanoparticles was assessed using Rhodamine B dye (5 ppm) under solar irradiation. Cr2O3-garlic exhibited the best activity as a photocatalyst among the studied nanoparticles, with 97.5% degradation efficiency under optimal conditions. [ABSTRACT FROM AUTHOR]

Water parameter estimation based on remote sensing is one of the common water quality evaluation methods. However, it is difficult to describe the relationship between the reflectance and the concentration of non-optically active substances due to their weak optical characteristics, and machine learning has become a viable solution for this problem. Therefore, based on machine learning methods, this study estimated four non-optically active water quality parameters including the permanganate index (CODMn), dissolved oxygen (DO), total nitrogen (TN), and total phosphorus (TP). Specifically, four machine learning models including Support Vector Machine Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and K-Nearest Neighbor (KNN) were constructed for each parameter and their performances were assessed. The results showed that the optimal models of CODMn, DO, TN, and TP were RF (R2 = 0.52), SVR (R2 = 0.36), XGBoost (R2 = 0.45), and RF (R2 = 0.39), respectively. The seasonal 10 m water quality over the Zhejiang Province was measured using these optimal models based on Sentinel-2 images, and the spatiotemporal distribution was analyzed. The results indicated that the annual mean values of CODMn, DO, TN, and TP in 2022 were 2.3 mg/L, 6.6 mg/L, 1.85 mg/L, and 0.063 mg/L, respectively, and the water quality in the western Zhejiang region was better than that in the northeastern Zhejiang region. The seasonal variations in water quality and possible causes were further discussed with some regions as examples. It was found that DO would decrease and CODMn would increase in summer due to the higher temperature and other factors. The results of this study helped understand the water quality in Zhejiang Province and can also be applied to the integrated management of the water environment. The models constructed in this study can also provide references for related research. [ABSTRACT FROM AUTHOR]

Lakes play a crucial role in the global biogeochemical cycles through the transport, storage, and transformation of different biogeochemical compounds. Their regulatory service appears to be disproportionately important relative to their small areal extent, necessitating continuous monitoring. This study leverages the potential of optical remote sensing sensors, specifically Sentinel-2 Multispectral Imagery (MSI), to monitor and predict water quality parameters in lakes. Optically active parameters, such as chlorophyll a (CHL), total suspended matter (TSM), and colored dissolved matter (CDOM), can be directly detected using optical remote sensing sensors. However, the challenge lies in detecting non-optically active substances, which lack direct spectral characteristics. The capabilities of artificial intelligence applications can be used in the identification of optically non-active compounds from remote sensing data. This study aims to employ a machine learning approach (combining the Genetic Algorithm (GA) and Extreme Gradient Boost (XGBoost)) and in situ and Sentinel-2 Multispectral Imagery data to construct inversion models for 16 physical and biogeochemical water quality parameters including CHL, CDOM, TSM, total nitrogen (TN), total phosphorus (TP), phosphate (PO4), sulphate, ammonium nitrogen, 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and the biomasses of phytoplankton and cyanobacteria, pH, dissolved oxygen (O2), water temperature (WT) and transparency (SD). GA_XGBoost exhibited strong predictive capabilities and it was able to accurately predict 10 biogeochemical and 2 physical water quality parameters. Additionally, this study provides a practical demonstration of the developed inversion models, illustrating their applicability in estimating various water quality parameters simultaneously across multiple lakes on five different dates. The study highlights the need for ongoing research and refinement of machine learning methodologies in environmental monitoring, particularly in remote sensing applications for water quality assessment. Results emphasize the need for broader temporal scopes, longer-term datasets, and enhanced model selection strategies to improve the robustness and generalizability of these models. In general, the outcomes of this study provide the basis for a better understanding of the role of lakes in the biogeochemical cycle and will allow the formulation of reliable recommendations for various applications used in the studies of ecology, water quality, the climate, and the carbon cycle. [ABSTRACT FROM AUTHOR]

Faecal contamination across the lettuce value chain was assessed in Maputo, Mozambique. Escherichia coli was used as an indicator of faecal contamination, with concentrations ranging from 3.4 to 5.7 log units/100 ml in groundwater, river water and partially treated wastewater. Municipal tap water used to wash lettuce heads in the markets had lower than 1 log unit/100 ml. Irrespective of the source of irrigation water, the lettuce heads were contaminated throughout the value chain, with concentrations ranging between 6.5 and 7.8 log units/100 g. Interventions and awareness raising should be applied at every stage of the value chain. [ABSTRACT FROM AUTHOR]

Discharge of untreated wastewater into water bodies pollutes the receiving waters. This study assessed the impact of abattoir and Kampala designers' effluent discharge on the water quality of the Yemoja River in Abeokuta, Nigeria. Twenty-seven water samples collected at three points, covering 180 m length, for 6 months were assessed for physicochemical parameters and metals and compared with the World Health Organization (WHO) and Standard Organization of Nigeria (SON) permissible standards. Most discharge point levels were found to be higher than their corresponding upstream and downstream values. Temperature, turbidity, magnesium, alkalinity, DO, TSS, phosphate, lead, BOD and potassium were found to be higher than normal levels for river water as prescribed by the WHO and SON while parameters like TDS, TS, calcium, chloride, nitrate, sulphate, iron and COD were lower than the standards. The total coliform values were higher than both national and international permissible limits, indicating contamination by human sewage or animal droppings. The water quality index indicated polluted water that is unfit for consumption. Findings from this research indicate that butchering and tie-and-dye activities have impacted river Yemoja water quality. Therefore, wastewater from the abattoir and textile industries be treated before discharge into water bodies. [ABSTRACT FROM AUTHOR]

The present study explores the suitability of groundwater for drinking purpose and evaluates non-carcinogenic health risks for children, women, and men. For this purpose, 47 groundwater samples were collected and analyzed for physicochemical parameters, including nitrate concentration. The results revealed that nitrate concentration varied from 15 to 85 mg/L and that 48.93% of the groundwater samples exceeded the Bureau of Indian Standards' limits of 45 mg/L. The spatial map of the pollution index of groundwater specifies that most of the study area lies in moderate to high pollution zones. Principal component analysis was also applied, and five principal components achieving eigenvalues more than 1 with a cumulative variance of 77.36% were found to be sufficient. The findings of non-carcinogenic risk rates range from 0.628 to 3.559 (average of 2.069) for children, 0.427 to 2.421 (average of 1.408) for women, and 0.362 to 2.049 (average of 1.191) for men, and approximately 80% of the population in the study region is exposed to high health risks. The health risk assessment specified that children in the study area are more susceptible than women and men. The findings of this study suggest that groundwater quality in the region has deteriorated, emphasizing the need for treatment before drinking. [ABSTRACT FROM AUTHOR]

The antimicrobial resistance (AMR) problem is one that demands urgent interventions to minimize the rapid spread in humans, animals and the environment. Extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-Ec) could spread from livestock farms to environment or circulate in farms via wastewater. This study aimed to quantify and characterize ESBL-Ec in swine feces and wastewater samples collected from 2 conventional swine farms with wastewater treatment systems. Microbiological analysis was performed on fecal and wastewater samples, and the concentration of cefotaxime (CTX)-resistant bacteria, indicative of ESBL-Ec, was determined across different stages of wastewater treatment. Additionally, ESBL-Ec was isolated and identified from fresh feces, swine house wastewater, and treated wastewater from covered lagoons and photosynthetic ponds. Results indicated a higher concentration of CTX-resistant bacteria in the wastewater in the early process of wastewater treatment. However, CTXresistant bacteria were not detected in the final photosynthetic pond in one of the 2 farms. ESBL-Ec was identified in fresh feces from swine houses and wastewater treatment plants in both farms. Further antimicrobial susceptibility testing revealed diverse resistance patterns among the ESBL-Ec isolates, with tetracycline and gentamicin demonstrated the highest resistance rates. The ESBL genes identified belonged to the CTX-M-14, CTX-M-17 and CTX-M-55. This study demonstrated the presence of ESBL-Ec in swine feces and wastewater, emphasizing the importance of effective wastewater treatment before discharging to limit the spread of AMR bacteria. [ABSTRACT FROM AUTHOR]

The bull shark (Carcharhinus leucas) is an apex predator with a wide distribution in tropical and warm temperate waters. This species is known to utilise freshwater systems and estuaries as nursery grounds. During a wider bull shark tagging survey in the Rewa River, Fiji, in 2017 and 2018, 27 neonate bull sharks with red eye pupils were recorded. This opportunistic observation prompted an examination of water quality parameters in the Rewa River to collect preliminary data on the potential cause of pollution. Water samples were analysed for faecal indicator bacteria (Escherichia coli), ammonia, total nitrogen, and various metals. Results indicated high levels of E. coli contamination, as well as elevated ammonia and total nitrogen concentrations. However, due to the limited sample size and the likelihood of additional underlying causes, a definitive causal relationship could not be established. Hence, this finding stands as an opportunistic observation, detailed here for documentation and stimulation of discourse. Field observations of 27 neonate bull sharks with red eyes in the Rewa River, Fiji, raised concerns about water quality. Analysis indicated high levels of Escherichia coli contamination, ammonia, and total nitrogen. However, the definitive causal relationship is yet to be investigated. [ABSTRACT FROM AUTHOR]

The study aims to assess variations in spatio-temporal characteristics of water quality parameters from three tropical estuaries, namely Muri-Ganga, Saptamukhi, and Hooghly, in the western portion of the Indian Sundarbans. Reliable retrieval of near-surface concentration of water quality parameters such as Chlorophyll-a, SST & TSM from diverse aquatic ecosystems with broad ranges of tropical requirements has always remained a complex issue. In this study, application of Case 2 Regional Colour Correction (C2RCC) processor has been tested for its accuracy across different bio-optical regimes in both inland and coastal waters. Satellite images for the same period were also collected and analysed using the C2RCC processing sequence to retrieve parameters like the depth of water, surface reflectance, water temperature, inherent optical properties (IOPs), chlorophyll-a, salinity, total suspended matter (TSM), etc., using the SNAP software. In situ sampling from specific locations within these estuaries and water quality analysis were conducted for the period 2017–2019. The OLCI retrieved datasets were compared and corroborated with field survey datasets. It was observed that the highest amount of TSM was recorded at Diamond Harbour during the 2018 pre-monsoon season (301.40 mg/L field-based value and 308.54 mg/L estimated value). Similarly, chlorophyll-a had higher concentrations throughout the monsoon season (3.03 mg m−3, (field survey), and 2.96 mg m−3, (estimated) at Fraserganj and Sagar south points. A very good correlation was observed for all seasons for Chl-a (r = 0.829) and TSM (r = 0.924) between the OLCI data and in situ measurements. Higher correlation and significant 'r' values highlight the importance of having both field-based as well as remotely-sensed information in understanding any dynamic system in a sustained manner. Results also confirm that the water quality model using OLCI Chl-a and TSM products outperforms conventional techniques. The study demonstrates the efficacy of using Sentinel 3 OCLI data for shallow marine and estuarine remote sensing applications, especially for monitoring TSM and Chl-a concentrations. [ABSTRACT FROM AUTHOR]

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform metaanalyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quant ified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological difference s between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies. [ABSTRACT FROM AUTHOR]