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Understanding the composition of complex Escherichia coli populations from the environment is necessary for identifying strategies to reduce the impacts of fecal contamination and protect public health. Metabarcoding targeting the hypervariable gene gnd was used to reveal the complex population diversity of E. coli and phenotypically indistinct Escherichia species in water, soil, sediment, aquatic biofilm, and fecal samples from native forest and pastoral sites. The resulting amplicons were cross-referenced against a database containing over 700 different partial gnd sequences from E. coli/non-E. coli Escherichia species. Alpha and beta measures of diversity of Escherichia populations were lowest in feces, soil and sediment compared to water and aquatic biofilm samples. Escherichia populations recovered from extensive freshwater catchments dominated by sheep, beef and dairy farming were extremely diverse but well-separated from a wetland dairy site. In contrast, Escherichia populations from the low-impact native forest site with fewer fecal sources were less diverse. Metabarcoding distinguished E. coli populations important to fecal contamination monitoring from non-E. coli Escherichia environmental populations. These data represent in-depth analysis and geographic stability of Escherichia populations from environmental samples with extensive heterogeneity, and reveal links with diverse fecal sources, land-use and the overall burden of fecal contamination at sample sites. [ABSTRACT FROM AUTHOR]

To evaluate the efficacy of laparoscopic-assisted Soave procedure of Hirschsprung's Disease (HSCR) in neonates and infants within 3 months of age. Patients with HSCR who were admitted to the Department of Fetal and Neonatal Surgery of Hunan Children's Hospital from June 2012 to July 2020 and underwent laparoscopic-assisted Soave procedure were selected. The clinical manifestations, surgical procedures, postoperative fecal contamination, constipation, enterocolitis, and defecation function were analyzed. A total of 267 children were included, 230 males and 37 females. Vaginal delivery occurred in 138 cases (51.7%) and cesarean delivery in 129 cases (48.3%). There were 217 cases (81.3%) of delayed excretion of meconium, preoperative HAEC (Hirschsprung's Disease Associated enterocolitis) 116 cases (43.4%), postoperative HAEC 54 cases (20.2%), 1 cases of postoperative death, 266 cases (99.6%) were cured. There were 37 cases (13.9%) of long-segment type, 226 cases (84.6%) of common type, and 4 cases (1.5%) of short-segment type. Of the 267 cases, 214 cases were followed up (80.1%), 60 cases with fecal contamination, the incidence rate was 28.0%, and 5 cases were tertiary fecal contamination. The overall incidence of constipation was 3.7% (8 cases), and 2 cases were third-degree constipation. Evaluation of defecation function: The excellent rate was 94.4%. Laparoscopic-assisted Soave procedure in neonates and infants within 3 months of age is generally safe and feasible, most infants have good postoperative defecation function, and the incidence of postoperative fecal contamination, constipation, and enterocolitis is relatively low. [ABSTRACT FROM AUTHOR]

This work aimed to determine the level of some toxic elements (As, Cr, Cd, and Pb) in the water of the Rupsha River, Bangladesh, concerning their potential dangers to human exposure. The elemental concentrations (mg/L) were determined using Atomic Absorption Spectrometer and found to decrease in the order of Cr (0.041) > Pb (0.029) > As (0.004) > Cd (0.002). The level of elements in this river water surpasses various international limits, making it unfit for human consumption. Furthermore, the metal pollution index and contamination index indicated that the water was also unsuitable for this purpose. The elements chosen were persuasive to discern the hazard quotient of non-carcinogenic risk. Moreover, total targeted hazard quotient (TTHQ) values were found for adults and children within acceptable limits (TTHQ <1). The value of carcinogenic risk did not surpass the range (10−6 to 10−4) of the threshold limit. Due to their high-water consumption per unit of body-weight and physiological development, children were found to be more sensitive than adults. Multivariate analyses demonstrated that human activities were the primary origin of toxic elements in river water. According to the findings, urban and industrial effluents should be treated before being released into rivers. Development along the river bank must be carefully controlled to safeguard the river environment. In the end, this will improve the quality of the water and lower the chance that people will be exposed to metals. [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionEnvironmental contamination with Opisthorchis viverrini eggs significantly impacts on opisthorchiasis transmission and disease control. This study assessed O. viverrini egg contamination in underwater sediments from canals and aimed to reduce O. viverrini transmission in egg–positive and downstream communities by controlling human opisthorchiasis in endemic area of Northeast Thailand.Sediment samples from 14 sites in UdonThani municipality were determined for O. viverrini eggs. Human fecal samples and fish were examined for opisthorchiasis and metacercaria infection, respectively. Water samples were analysed for faecal coliforms bacteria. From 2017 to 2023, transmission control efforts were evaluated by monitoring changes in human and fish infection rates.In 2017 and 2018, O. viverrini eggs were found in canal sediments at 153 and 86 eggs/liter, respectively. Human opisthorchiasis prevalence was 5.3%, with cyprinoid fish showing a 25.0% infection rate (11.6 cysts/infected fish) and significant fecal contamination (>5,500 CFU/100 ml). Conversely, egg–negative sites showed a 0.5% human infection rate and no metacercariae were found. After health interventions (2019 to 2023), O. viverrini eggs were not detected in sediments from canals, resulting in a significant reduction in human opisthorchiasis prevalence to 0.9% at the previously egg–positive site and from 12.2% to 1.7% in downstream communities (p < 0.001). Additionally, the prevalence of metacercariae in cyprinoid fish decreased from 11.4% (7.6 cysts/infected fish) to 4.5% (2.4 cysts/infected fish), indicating reduced transmission.The presence of O. viverrini eggs in sediment was associated to human opisthorchiasis transmission and demonstrated the significant effectiveness of health interventions in controlling the disease. [ABSTRACT FROM AUTHOR]

This cross-sectional study aimed to assess the drinking water parameters in primary and secondary schools. A questionnaire encompassing the schools’ general characteristics and information about drinking water was administered to school administrators. Drinking water samples were taken from 60 schools to evaluate drinking water parameters. The data were analyzed using Chi-Square, Mann–Whitney U, and Kruskall–Wallis tests, T-test, and SPSS 22.0 software. Non-compliance with national legislation was observed in 16.7% of schools during drinking water analysis. The microbiological parameters exceeded the threshold values in 90% of the schools where the analysis results of the drinking water were deemed inadequate. The analysis yielded no discernible variations based on school district or type. Mains water was the primary drinking water source in 91.7% of schools. The rate was lower in rural schools compared to urban schools, with a difference of 85 and 95%, respectively. It was found that 41.7% of schools lacked canteens or the sale of packaged water. Consequently, the availability of tap water in schools falls short of the desired standard. It is imperative to investigate the factors leading to microbiological contamination in school drinking water and formulate short-, medium-, and long-term strategies to enhance its safety. [ABSTRACT FROM AUTHOR]

Olive mill wastewater, a byproduct of olive oil production, poses a major environmental challenge for Mediterranean countries like Morocco. These residues are rich in polyphenols with notable antimicrobial properties. This study aimed to investigate the impact of anthropogenic factors on the quality of certain wells in the Oued Amlil region of the Taza province, Morocco. It was carried out during two distinct periods by sampling water from six wells: P1, P2, P3, P4, P5 and P6. The first period occurred during the winter season of December 2022, when olive crushing operations for oil production were at their peak. The second period took place in the summer (August 2022), when the activities of the oil mills were stopped. The objective is to assess microbiological quality by determining the microbial load in total germs at 37°C (TG), Fecal Coliforms (FC), Total Coliforms (TC), and Fecal Streptococci (FS), as well as performing a polyphenol assay. The analysis results showed high concentrations of TG (Maximum value = 3100/100ml), FC (Maximum value = 910/100ml), TC (Maximum value = 7120/100ml), and FS (Maximum value = 7000/100ml) in wells P1, P2, and P5, although they are not located on the flow path of groundwater contaminated by the Innaouene River and the local olive oil mills. However, despite their location along this axis, wells P3, P4, and P6 show lower contamination levels. In order to identify similarities between different water sources and/or different points of contamination acquisition, principal component analysis (PCA) was applied to the collected data and showed a significant negative correlation between polyphenols and bacteriological parameters, confirming the hypothesis of polyphenols' bactericidal effect on fecal bacteria. In addition, the degree of contamination varies from one well to another depending on their location with the direction of flow of water in the groundwater and the proximity of sources of pollution. [ABSTRACT FROM AUTHOR]

The Silway River has historically failed to meet safe fecal coliform levels due to improper waste disposal. The river mouth is located in General Santos City, the tuna capital of the Philippines and a leading producer of hogs, cattle, and poultry. The buildup of contaminants due to direct discharge of waste from chicken farms and existing water quality conditions has led to higher fecal matter in the Silway River. While there were technical reports in the early 2000s about poultry farming, this is the first study where fecal coliform from poultry farming was detected in the Silway River using highly sensitive protocols like qPCR. This study characterized the effect of flow velocity and physicochemical water quality parameters on chicken fecal contamination. Gene markers such as Ckmito and ND5-CD were used to detect and quantify poultry manure contamination through microbial source tracking (MST) and environmental DNA (eDNA) profiling. The results of this study showed the presence of chicken fecal bacteria in all stations along the Silway River. The results revealed that normal levels of water quality parameters such as temperature, pH, and high TSS concentrations create favorable conditions for chicken fecal coliforms to thrive. Multiple regression analysis showed that flow velocity and DO significantly affect chicken fecal contamination. A lower cycle threshold (Ct) value indicated higher concentration of the marker ND5-CD, which means higher fecal contamination. It was found that there was an inverse relationship between the Ct value and both velocity (R2 = 0.55, p = 0.01) and DO (R2 = 0.98, p = 0.2), suggesting that low flow velocity and low DO can lead to higher fecal contamination. Findings of fecal contamination could negatively impact water resources, the health of nearby residents, and surrounding farms and industries, as well as the health and growth of fish. [ABSTRACT FROM AUTHOR]

We recently have shown that the gut microbiota composition in female and male runners positively correlates with sports, and female runners show similar gut microbiome diversity to male runners. However, gut microbiota composition has not yet been fully investigated in other endurance athletes, such as cyclists. Therefore, in the current study, we investigated the gut microbiome profiles in competitive, non-professional female and male cyclists compared to what we have shown in runners. We aim to understand (1) whether the gut microbiome signature is sport-specific; (2) whether there is a microbiome difference between female and male cyclists and runners; and (3) whether the gut bacteria expressed in cyclists and runners correlates with exercise performance. Our study included 58 subjects: 18 cyclists (9 males), 22 runners (13 males), and 18 control subjects (9 males). Fecal samples were obtained and subjected to taxonomic analysis to assess the relative abundances of species across subjects based on 16S rRNA sequencing results. Both alpha and beta diversity of the bacterial communities were evaluated to identify compositional variations between the groups. Each participant completed a maximal oxygen consumption test and a time-to-exhaustion test at 85% of the measured VO2max. Cyclists performed the test on an SRM ergometer, while runners used a motorized treadmill. Blood lactate levels were measured at 5 min intervals throughout the time-to-exhaustion trials. Alpha diversity demonstrated a significant difference (p-adj < 0.001) between cyclists and runners. Male cyclists showed significantly lower alpha diversity than runners (p-adj < 0.001). The taxonomic analysis of gut microbiota composition between cyclists, runners, and controls showed a lower or higher abundance of fifteen different bacteria. In cyclists, there was a significant positive correlation between six bacteria, and in runners, there was a significant positive correlation between eight bacteria, with weekly training volume, time-to-exhaustion, VO2max, and blood lactate levels. This study suggests potential sport-specific characteristics in long-distance cyclists' and runners' gut microbiome signatures. These findings emphasize the differences in gut microbiota between cyclists and runners, probably due to the difference in physiological and biomechanical conditions related to the activity mode during each sport. [ABSTRACT FROM AUTHOR]

A conventional, group-specific PCR method was developed to identify each of the four previously defined major taxa (Myoviridae, Siphoviridae, Podoviridae and Microviridae) of somatic coliphages and used to classify isolates from sewage. Somatic coliphage infectivity detection, occurrence and survival in primary human sewage effluent was observed over time to further understand the presence and behavior of the groups of somatic coliphages at two environmental temperatures (4 and 25 °C). Over time, the taxonomic composition of the somatic coliphage population in sewage changed, with the Microviridae family becoming the most prevalent family in the sewage population after several weeks. Based on their persistence and prevalence in environmental waters, phages belonging to the Microviridae family provide supporting information on sewage contamination and possibly of human enteric viruses in sewage-contaminated water. [ABSTRACT FROM AUTHOR]

Groundwater is an essential drinking water source for humans. However, improper groundwater management leads to fecal contamination and waterborne diseases caused by viral pathogens. Therefore, this study aimed to investigate norovirus (NoV) contamination by conducting nationwide monitoring over five years (2019–2023). Groundwater samples were analyzed for water quality parameters, indicator microorganisms, NoV prevalence, and viral genotypes. Water quality was assessed for temperature, turbidity, and residual chlorine, whereas microorganisms were analyzed for total coliforms, Escherichia coli, and NoV genotypes. Of the 600 sites, 11 (1.8%) were NoV-positive, irrespective of season or location. Low residual chlorine levels (0.02–0.75 mg/L) were observed, possibly limiting viral inactivation. Total coliforms were detected in only three NoV-positive samples, and E. coli was absent. NoV genotypes were identified as GI.1 and GII.4, with GII.4 being the most frequently detected genotype. The present study demonstrated that periodic monitoring and expanded nationwide efforts are required for effective groundwater management and public health protection. [ABSTRACT FROM AUTHOR]

Simple Summary: Wild bird species are known to be readily infected with and carry Salmonella enterica. This has two main consequences. Firstly, they may act as reservoirs in the transmission of infection to livestock species or zoonotic transmission to humans. Secondly, birds themselves may develop systemic infection, leading to high mortality disease. Recent studies have shown that specific genotypes adapted to and capable of causing disease in a range of bird species have recently evolved. Salmonella enterica is an important bacterial pathogen in humans and warm-blooded animals. Wild bird species represent both a potential reservoir for zoonotic infection and as a susceptible host to infection by host-adapted variants. Historically, wild birds were considered to be a major source of Salmonella infection in livestock, but in recent years, it has been more apparent that birds are more likely to act as a reservoir for recycling infection on farms rather than as the primary source of infection. Birds may also transmit infection to humans directly from feces or indirectly through fecal contamination of foods, including peanut butter. While many bird species can be infected with Salmonella, the rates of infection are variable, and most cases lead to intestinal carriage rather than disease. In this case, fecal shedding of Salmonella bacteria from birds can represent a risk for transmission to humans. As such, care is needed when in contact with fecal material such as that found on bird tables or feeders. In recent years, there have been emergences of Salmonella Typhimurium genotypes associated with high mortality in songbirds or passerine birds, resulting in 'die offs' in Europe, Israel, New Zealand and the US. Additionally, S. typhimurium DT2 and other variant Copenhagen genotypes are associated with high mortality disease in pigeons. These genotypes show evidence of evolution towards adaptation to specific hosts, with pseudogenes leading to loss of functional metabolic pathways and specific virulence factors. These 'signatures of adaptation' are common in host-adapted Salmonella serovars and suggest these S. typhimurium isolates are evolving to adapt to specific avian hosts. [ABSTRACT FROM AUTHOR]

Escherichia coli harbors various virulence factors responsible for diarrhea and other diseases in neonatal calves. The antimicrobial resistance (AMR) among the diarrheagenic and non-diarrheagenic E. coli may impose a potential health hazard among the calves and make the antibacterial therapy ineffective. The virulence gene expression among AMR strains plays a crucial role in establishing diarrheal disease with therapeutic complications. This study investigates the diversity of E. coli isolates from neonatal calves. E. coli isolated from the fecal samples were subsequently subjected to pathotyping and virulotyping using the PCR technique. AMR profiling was done by phenotypic and genotypic methods. The ERIC pattern of E. coli pathotypes was compared and correlated with the pattern of AMR and virulence traits. 179 isolates were obtained from 158 fecal samples collected from neonatal calves. Forty-two isolates were pathotypable; predominated by shigatoxigenic E. coli. Seventy-four isolates were ESBL producers. Nineteen isolates were carbapenem resistant and 68 isolates exhibited quinolone resistance. blaAmpC, blaVIM and qnrS were the predominant genes detected among ESBL, carbapenem and quinolone resistance genes, respectively. The present study indicated diverse virulence profiles and the presence of significant ESBL, carbapenem and fluoroquinolone resistance among E. coli pathotypes from calves. The analysis of resistance profiling indicates the risks associated with the indiscriminate antibiotic use among farm animals, which may pose a potential health hazard to livestock owners. [ABSTRACT FROM AUTHOR]

Based on a systematic review of convolutional neural networks (CNN), this study explores the efficacy of small imaging sensors in monitoring the real-time presence of cyanotoxins and hazardous contaminants in urban ecosystems. To develop a machine learning-based CNN, this study first investigated the relationships between the prevalence of hazardous algal blooms (HABs) and faecal indicator bacteria (FIB) in waterways and aquifers of certain semi-arid zones of Sri Lanka, Sweden and New York (United States). By incorporating a popularly known AbspectroscoPY framework to effectively process the spectrophotometric data of the obtained samples, the formulation subsequently reveals strong positive correlations between FIB coliforms and nutrient loads (particularly nitrate and phosphate). A corroborative association with the incidence of chronic kidney disease of uncertain aetiology (CKDu) among the residents of the studied regions further affirms the reliability of the methodology. These findings underline the need for policymakers to consider the geographical and land-use traits of urban habitats in strategies aimed at reducing water-borne health hazards. [ABSTRACT FROM AUTHOR]

Background: Current methods for obtaining fecal egg counts in horses are often inaccurate and variable depending on the analyst's skill and experience. Automated digital scanning of fecal sample slides integrated with analysis by an artificial intelligence (AI) algorithm is a viable, emerging alternative that can mitigate operator variation compared to conventional methods in companion animal fecal parasite diagnostics. Vetscan Imagyst is a novel fecal parasite detection system that uploads the scanned image to the cloud where proprietary software analyzes captured images for diagnostic recognition by a deep learning, object detection AI algorithm. The study describes the use and validation of Vetscan Imagyst in equine parasitology. Methods: The primary objective of the study was to evaluate the performance of the Vetscan Imagyst system in terms of diagnostic sensitivity and specificity in testing equine fecal samples (n = 108) for ova from two parasites that commonly infect horses, strongyles and Parascaris spp., compared to reference assays performed by expert parasitologists using a Mini-FLOTAC technique. Two different fecal flotation solutions were used to prepare the sample slides, NaNO3 and Sheather's sugar solution. Results: Diagnostic sensitivity of the Vetscan Imagyst algorithm for strongyles versus the manual reference test was 99.2% for samples prepared with NaNO3 solution and 100.0% for samples prepared with Sheather's sugar solution. Sensitivity for Parascaris spp. was 88.9% and 99.9%, respectively, for samples prepared with NaNO3 and Sheather's sugar solutions. Diagnostic specificity for strongyles was 91.4% and 99.9%, respectively, for samples prepared with NaNO3 and Sheather's sugar solutions. Specificity for Parascaris spp. was 93.6% and 99.9%, respectively, for samples prepared with NaNO3 and Sheather's sugar solutions. Lin's concordance correlation coefficients for VETSCAN IMAGYST eggs per gram counts versus those determined by the expert parasitologist were 0.924–0.978 for strongyles and 0.944–0.955 for Parascaris spp., depending on the flotation solution. Conclusions: Sensitivity and specificity results for detecting strongyles and Parascaris spp. in equine fecal samples showed that Vetscan Imagyst can consistently provide diagnostic accuracy equivalent to manual evaluations by skilled parasitologists. As an automated method driven by a deep learning AI algorithm, VETSCAN IMAGYST has the potential to avoid variations in analyst characteristics, thus providing more consistent results in a timely manner, in either clinical or laboratory settings. [ABSTRACT FROM AUTHOR]

Gut microbial dysbiosis, especially bacteriome, has been implicated in Alzheimer's disease (AD). However, nonbacterial members of the gut microbiome in AD, such as the mycobiome, archaeome, and virome, are unexplored. Here, we perform higher-resolution shotgun metagenomic sequencing on fecal samples collected longitudinally from a mouse model of AD to investigate longitudinal and multi-kingdom gut microbiome profiling. Shotgun metagenomic sequencing of fecal samples from AD mice and healthy mice returns 41,222 bacterial, 414 fungal, 1836 archaeal, and 1916 viral species across all time points. The ecological network pattern of the gut microbiome in AD mice is characterized by more complex bacterial–bacterial interactions and fungal–fungal interactions, as well as simpler archaeal–archaeal interactions and viral–viral interactions. The development of AD is accompanied by multi-kingdom shifts in the gut microbiome composition, as evidenced by the identification of 1177 differential bacterial, 84 differential fungal, 59 differential archaeal, and 10 differential viral species between healthy and AD mice across all time points. In addition, the functional potential of the gut microbiome is partially altered in the development of AD. Collectively, our findings uncover longitudinal and multi-kingdom gut microbiome alterations in AD and provide a motivation for considering microbiome-based therapeutics during the prevention and treatment of AD. [ABSTRACT FROM AUTHOR]

Access to safe drinking water sources and appropriate sanitation facilities remains a dream in low and middle-income countries including South Africa. This study identified the origin of faecal pollution by using quantitative polymerase chain reaction (qPCR) targeting host-specific Bacteroidales genetic markers to track the distribution of human-specific (BacHum) and animal-specific (cattle—BacCow, chicken—Cytb, pig—Pig-2-Bac, dog—BacCan) markers in water sources used by rural communities of the Vhembe District Municipality (VDM). Results revealed the prevalence of BacHum, BacCow, and BacCan in all surface water sources in Thulamela Local Municipality (TLM) and Collins Chabane Local Municipality (CLM) during wet (100%) and dry seasons (50–75%). Cytb was not detected in untreated spring water in TLM and CLM, and Pig-2-Bac was not detected in untreated hand-dug well water in TLM during both seasons. Household-level analysis detected Cytb (28.8% wet, 17.5% dry), BacHum (34.4% wet, 25% dry for Pig-2-Bac) in stored untreated spring water in CLM, and Cytb (42.9% wet, 28.5% dry) in untreated hand-dug well water in TLM. Despite differences in detection frequencies of host-specific Bacteroidales, the study highlights the public health concern of faecal pollution in rural VDM households. [ABSTRACT FROM AUTHOR]

Accurate taxonomic species identification is essential to the study of mammals. Despite this necessity, rapid and accurate identification of cryptic, understudied, and elusive mammals remains challenging. Traditional barcoding of mitochondrial genes is standard for molecular identification but requires time-consuming wet-lab methodologies. Recent bioinformatic advancements for nanopore sequencing data offer exciting opportunities for noninvasive and field-based identification of mammals. Nanopore adaptive sampling (NAS), a polymerase chain reaction (PCR)-free method, selectively sequences regions of DNA according to user-specified reference databases. Here, we utilized NAS to enrich mammalian mitochondrial genome sequencing to identify species. Fecal DNA extractions were sequenced from 9 mammals, several collected in collaboration with Minnesota Tribal Nations, to demonstrate utility for NAS barcoding of noninvasive samples. By mapping to the entire National Center for Biotechnology Information mammalian mitochondrial reference genome database and bioinformatically analyzing highly similar matches, we successfully produced species identifications for all fecal samples. Eight of 9 species identifications matched previous PCR or animal/fecal appearance-based identifications. For the ninth species, our genetic data indicate a misidentification stemming from the original study. Our approach has a range of applications—particularly in field-based wildlife research, conservation, disease surveillance, and monitoring of wildlife trade. Of importance to Minnesota tribes is invasive species monitoring, detections, and confirmation as climate impacts cause changes in biodiversity and shifts in species distributions. The rapid assessment techniques described here will be useful as new introductions and range expansions of native and invasive species may first be detected by the presence of signs such as scat rather than direct observations and will be helpful for chronically understaffed tribal natural resources agencies. [ABSTRACT FROM AUTHOR]

Background: Ensuring the availability of safe drinking water remains a critical challenge in developing countries, including Ethiopia. Therefore, this paper aimed to investigate the prevalence of fecal coliform and E. coli bacteria and, geographical, children availability, and seasonal exposure assessment through a meta-analysis. Methods: Two independent review groups extensively searched internet databases for English-language research articles published between 2013 and 2023. This systematic review and meta-analysis followed PRISMA guidelines. The methodological quality of each included study was evaluated using the STROBE guidelines. Publication bias was assessed by visual inspection of a funnel plot and then tested by the Egger regression test, and meta-analysis was performed using DerSimonian and Laird random-effects models with inverse variance weighting. Subgroup analyses were also conducted to explore heterogeneity. Results: Out of 48 potentially relevant studies, only 21 fulfilled the inclusion criteria and were considered for meta-analysis. The pooled prevalence of fecal coliform and E. coli was 64% (95% CI: 56.0–71.0%, I2 = 95.8%) and 54% (95% CI: 45.7–62.3%, I2 = 94.2%), respectively. Subgroup analysis revealed that the prevalence of fecal coliform bacteria increased during the wet season (70%) compared to the dry season (60%), particularly in households with under-five children (74%) compared to all households (61%), in rural (68%) versus urban (66%) areas, and in regions with high prevalence such as Amhara (71%), Gambela (71%), and Oromia (70%). Similarly, the prevalence of E. coli was higher in households with under-five children (66%) than in all households (46%). Conclusions: The analysis highlights the higher prevalence of fecal coliform and E. coli within households drinking water, indicating that these bacteria are a significant public health concern. Moreover, these findings emphasize the critical need for targeted interventions aimed at improving drinking water quality to reduce the risk of fecal contamination and enhance public health outcomes for susceptible groups, including households with under-five children, in particular geographical areas such as the Amhara, Gambela, and Oromia regions, as well as rural areas, at point-of-use, and during the rainy season. Registration: This review was registered on PROSPERO (registration ID - CRD42023448812). [ABSTRACT FROM AUTHOR]

Background and purpose: Early detection, diagnosis, and treatment of colorectal cancer and its precancerous lesions can significantly improve patients' survival rates. The purpose of this research is to identify methylation markers specific to colorectal cancer tissues and validate their diagnostic capability in colorectal cancer and precancerous changes by measuring the level of DNA methylation in stool samples. Method: We analyzed samples from six cancer tissues and adjacent normal tissues and fecal samples from 758 participants, including 62 patients with interfering diseases. Bioinformatics databases were used to screen for candidate biomarkers for CRC, and quantitative methylation-specific PCR methods were applied for identification. The methylation levels of the candidate biomarkers in fecal and tissue samples were measured. Logistic regression and random forest models were built and validated using fecal sample data from one of the centers, and the independent or combined diagnostic value of the candidate biomarkers in fecal samples for CRC and precancerous lesions was analyzed. Finally, the diagnostic capability and stability of the model were validated at another medical center. Results: This study identified two colorectal cancer CpG sites with tissue specificity. These two biomarkers have certain diagnostic power when used individually, but their diagnostic value for colorectal cancer and colorectal adenoma is more significant when they are used in combination. Conclusion: The results indicate that a DNA methylation biomarker combined diagnostic model based on two CpG sites, cg13096260 and cg12587766, has the potential for screening and diagnosing precancerous lesions and colorectal cancer. Additionally, compared to traditional diagnostic models, machine learning algorithms perform better but may yield more false-positive results, necessitating further investigation. [ABSTRACT FROM AUTHOR]

Porcine Teschoviruses (PTVs) are ubiquitous enteric viral pathogens that infect pigs and wild boars worldwide. PTVs have been responsible for causing the severe clinical disease (Teschen disease) to asymptomatic infections. However, to date, limited information is available on large-scale epidemiological data and molecular characterization of PTVs in several countries. In this study, we report epidemiological data on PTVs based on screening of 534 porcine fecal samples from different states of India and a RT-PCR based detection of PTVs shows a percent positivity of 8.24% (44/534). The PTV prevalence varied among different regions of the country with the highest detection rates observed in the state of Karnataka (38.1%). Phylogenetic analysis based on VP1 gene reveals the presence of PTV genotype 6 and 13 along with some unassigned novel genotypes which did not cluster with any of the established PTV genotypes (PTV 1–PTV 13). Indian PTV 6 strains are genetically closest to the Spanish strains (85.7–94.4%) whereas PTV 13 and novel genotype strains were found to be more similar to the Chinese strains (88.1–99.1%). Using recombination detection software, no Indian PTVs found to be recombinant on VP1 gene and selection pressure analysis revealed the purifying selection in the several sites of the VP1 gene of PTVs. The Bayesian analysis of Indian PTVs shows 1.16 × 10–4 substitution/site/year as the mean evolutionary rate. Further, isolation of the novel PTV strains from India and more detailed investigation much needed to know the evolutionary history of PTV strains circulating in porcine populations in India. [ABSTRACT FROM AUTHOR]

Access to safe drinking water sources and appropriate sanitation facilities remains a dream in low and middle-income countries including South Africa. This study identified the origin of faecal pollution by using quantitative polymerase chain reaction (qPCR) targeting host-specific Bacteroidales genetic markers to track the distribution of human-specific (BacHum) and animal-specific (cattle—BacCow, chicken—Cytb, pig—Pig-2-Bac, dog—BacCan) markers in water sources used by rural communities of the Vhembe District Municipality (VDM). Results revealed the prevalence of BacHum, BacCow, and BacCan in all surface water sources in Thulamela Local Municipality (TLM) and Collins Chabane Local Municipality (CLM) during wet (100%) and dry seasons (50–75%). Cytb was not detected in untreated spring water in TLM and CLM, and Pig-2-Bac was not detected in untreated hand-dug well water in TLM during both seasons. Household-level analysis detected Cytb (28.8% wet, 17.5% dry), BacHum (34.4% wet, 25% dry for Pig-2-Bac) in stored untreated spring water in CLM, and Cytb (42.9% wet, 28.5% dry) in untreated hand-dug well water in TLM. Despite differences in detection frequencies of host-specific Bacteroidales, the study highlights the public health concern of faecal pollution in rural VDM households. [ABSTRACT FROM AUTHOR]

Safe drinking water access is a human right, but data on safely managed drinking water services (SMDWS) is lacking for more than half of the global population. We estimate SMDWS use in 135 low- and middle-income countries (LMICs) at subnational levels with a geospatial modeling approach, combining existing household survey data with available global geospatial datasets. We estimate that only one in three people used SMDWS in LMICs in 2020 and identified fecal contamination as the primary limiting factor affecting almost half of the population of LMICs. Our results are relevant for raising awareness about the challenges and limitations of current global monitoring approaches and demonstrating how globally available geospatial data can be leveraged to fill data gaps and identify priority areas in LMICs. [ABSTRACT FROM AUTHOR]

This study aims to analyze the relationship between handler hygiene and the content of coliform bacteria in drinking water depots in the former Maospati District, Magetan Regency in 2024. Coliform bacteria are used as an indicator of fecal contamination in drinking water, which can pose serious health risks for consumers. The research method used is analytical observational with a cross-sectional approach. Sampling was carried out at simple random from 52 drinking water depots, with a total of 19 samples analyzed using the Most Probable Number (MPN) method to determine the concentration of coliform bacteria. The research results showed that the majority of drinking water depots (59%) had poor handler hygiene, while the remaining 41% had good hygiene. Microbiologically, 51.3% of water samples did not meet the requirements because they contained coliform bacteria, while 48.7% met the requirements. Statistical analysis showed a significant relationship between poor handler hygiene and high levels of coliform content (p = 0.001), with a relative risk 12.2 times higher. This study makes an important contribution to knowledge about drinking water safety in the region, highlighting the importance of sanitation and hygiene monitoring in drinking water depots to reduce public health risks. Recommendations from this research include increased supervision and training for drinking water depot managers, as well as the need to strengthen regulations and implement stricter sanitation hygiene standards. [ABSTRACT FROM AUTHOR]

Intestinal infections caused by non-typhoidal Salmonella spp. along with antimicrobial resistance spread are a major food safety concern worldwide. Here, we evaluate the potential of competitive exclusion products developed by anaerobic or aerobic conditions to control systemic infection, cecal colonization, fecal excretion, and improve the intestinal health in broilers challenged by Salmonella Heidelberg (SH). A total of 105 day-old chickens were randomly distributed into three experimental groups: A (untreated control), B (treated with anaerobic culture), and C (treated with aerobic culture). During 21 days, morphometric parameters of the small intestine were analyzed using microscopy, fecal excretions by cloacal swabs, systemic infection, and cecal colonization by colony-forming unit counts (CFU/g). The results indicated the lowest number of positive swabs (45.33%) recovered from Group C, followed by Group B (71.8%) and Group A (85.33%). The bacterial enumeration revealed the lowest amounts in Group C at the necropsy realized in 5-, 7-, and 14-days post-infection (DPI) (P  = 0.0010, P  = 0.0048, and P  = 0.0094, respectively). Statistical differences between intestinal morphometrics were observed in the Group C at 21 DPI. Our results suggest that the product developed under aerobic conditions can improve intestinal health, protecting birds against SH. [ABSTRACT FROM AUTHOR]

A four-week trial was conducted to compare the effects of a conventional flow-through system diet (FTS) and an experimental RAS diet (ERAS) on fish performance, water quality and general system implication in a replicated recirculation aquaculture system (RAS). Six identical RAS, each with a total system water volume of 1500 L and cylindrical rearing tanks of 1000 L were stocked with Atlantic salmon (Salmo salar) post-smolts with an average weight of 199.7 ± 28 g, to an average stocking density of 30 kg/m3 and reaching approximately 49 kg/m3 at the trial end. The ERAS diet were composed to inhabit typical RAS feed characteristics compared with the FTS diet, such as a higher fecal stability and reduced protein levels (−12%), but at the same time increased fat content (+8%) to secure similar gross energy levels (22–23 MJ kg−1) between the two diets. Water quality parameters were measured individually. The total accumulation of minerals and metals was analyzed in water from different parts of the system at the start and end of the trial period for both diets. No differences in growth, condition factor, feed conversion rate (FCR), or survival of fish fed the two dietary adaptations were observed. The system using the ERAS diet showed significantly higher pH (+1.2%) and alkalinity (+17%) and lower total ammonia nitrogen (TAN) (−18%) and NO2− (−46%) compared with the FTS diet. The count of drum filter activations was also significantly lower (−13%) with the ERAS diet. Compared with the FTS diet, the ERAS diet had a lower probability (−4%) of generating particles smaller than 50 μm, and that the RAS was also more effective in removing particles from the drum filter, prompting a lower daily activation of the filter of 22.1 ± 3.0 counts compared with 25.5 ± 3.5 for the FTS diet. Mineral analysis showed a significantly lower accumulation of total phosphorus (TP) (−90%) and dissolved phosphorus (DP) (−92%) in the RAS units using the ERAS diet compared with those using the FTS diet. Compared with a traditional flow-through diet, these results highlight the benefits of using an RAS-adapted diet that matches the energy requirement of flow-through diets regarding water quality, system performance, satisfactory growth, and condition. [ABSTRACT FROM AUTHOR]

The New Mexico Jumping Mouse (Zapus luteus) is a federally endangered granivore active for only 3 to 5 months annually. Knowledge of diet can help guide habitat recovery and yet despite calls for restoration of its riparian habitat, the diet of Z. luteus remains largely unknown. To date, only 8 plant species have been described in the diet—whereas insectivory, mycophagy, and dietary shifts have only been hypothesized. In the late summer, Z. luteus rapidly accumulates fat for a 9-month hibernation and restoration may fail if seasonal variation in the diet is overlooked. We used DNA metabarcoding on fecal DNA (n = 165) to resolve dietary taxa within multiple trophic levels of the diet and investigate monthly patterns of consumption. Seldom studied in metabarcoding frameworks, we also investigated exogenous contamination in Sherman live-capture traps. Potential contamination among feces, pelage, and trap surfaces was detectable but low (median = 0% to 2%), with fecal communities distinct from exogenous sources. The diet of Z. luteus was varied and most frequently (frequency of occurrence) of graminoids, forbs, lepidopterans, dipterids, and false-truffles. For plant foods, dietary diversity increased throughout their season of activity, shifting from sedges and woody vegetation in the early season (June to July) to forbs and grasses in the late season (August to September). Insect consumption was consistently detected throughout the season, whereas mycophagy was more frequently detected in August, when hypogeous fungi are typically more abundant. The breadth of dietary taxa suggests plasticity in resource use, potentially accommodating diverse patterns of seed availability throughout their active period. Shifts in plant consumption may reflect a dietary adaptation to the phenological patterns of their plant communities, a synchrony that might benefit both pre- and post-hibernation survival. Our work substantially improves our understanding of the diet of Z. luteus (241 dietary taxa) and will be useful for guiding habitat recovery. It also offers scalable methods to further investigate the diet under disturbance contexts (e.g. grazing, wildfire, drought). [ABSTRACT FROM AUTHOR]

During adaptive laboratory evolution experiments, any unexpected interruption in data monitoring or control could lead to the loss of valuable experimental data and compromise the integrity of the entire experiment. Most homemade mini-bioreactors are built employing microcontrollers such as Arduino. Although affordable, these platforms lack the robustness of the programmable logic controller (PLC), which enhances the safety and robustness of the control process. Here, we describe the design and validation of a PLC-controlled morbidostat, an innovative automated continuous-culture mini-bioreactor specifically created to study the evolutionary pathways to drug resistance in microorganisms. This morbidostat includes several improvements, both at the hardware and software level, for better online monitoring and a more robust operation. The device was validated employing Escherichia coli, exploring its adaptive evolution in the presence of didecyldimethylammonium chloride (DDAC), a quaternary ammonium compound widely used for its antimicrobial properties. E. coli was subjected to increasing concentrations of DDAC over 3 days. Our results demonstrated a significant increase in DDAC susceptibility, with evolved populations exhibiting substantial changes in their growth after exposure. [ABSTRACT FROM AUTHOR]

In the poultry industry, the evisceration stage often sees the highest microbial load on chicken carcasses. While manual trimming has traditionally been employed to remove gastrointestinal contamination, Brazilian legislation allows the use of a carcass washing system as an alternative. This study aimed to establish and validate a protocol for the use of a chicken carcass washing system as a replacement for manual trimming in a major poultry processing facility in southern Brazil. The methodology followed international standards for microbial analysis such as total mesophilic counts and Enterobacteriaceae. Comparing contamination levels before and after treatments, significant reductions are seen. Manual trimming reduced contamination by 39.43% (gastric), 53% (fecal), and 50% (biliary). Washing achieved greater reductions, with a 96.37% drop in gastric contamination and complete elimination (100%) of fecal contamination. These results met statistical significance. Both procedures reduced contamination levels. Manual trimming maintained 50% of samples below the mean value without exceeding upper control limits (UCL). Washing increased the percentage of samples below the mean value from 46% to 54%, demonstrating its superior efficiency. For Enterobacteriaceae, trimming maintained 44% of samples below the mean value, and washing increased it from 46% to 48%. In conclusion, the carcass washing system effectively removes visible gastrointestinal contents, meeting regulatory standards and receiving authorization from the Federal Inspection Service for use in the facility. [ABSTRACT FROM AUTHOR]

Exhaustive exercise is known to induce muscle damage characterized by inflammation and oxidative stress. Although "regular" and "weekend warrior" exercise regimens have been shown to confer comparable health benefits in human studies, such as reduced risks of all-cause, cardiovascular disease (CVD), and cancer mortality, their differential impacts on muscle damage post-exhaustive exercise remain unclear. This study aimed to compare the effects of long-term, moderate-intensity (LTMI) and short-term, high-intensity (STHI) training modalities, matched for total exercise volume, on gut microbiota, short-chain fatty acids (SCFAs), and exhaustive exercise-induced muscle damage in mice, as well as to evaluate the correlation between these factors. LTMI is considered a regular exercise regimen, while STHI shares some similarities with the "weekend warrior" pattern, such as promoting exercise intensity and condensing training sessions into a short period. Our findings indicate that LTMI training significantly enhanced the abundance of SCFA-producing bacteria, including Akkermansia, Prevotellaceae_NK3B31_group, Odoribacter, Alistipes, and Lactobacillus, thereby increasing SCFA levels and attenuating muscle damage following exhaustive swimming. In contrast, STHI training increased the abundance of opportunistic pathogens such as Staphylococcus and Bilophila, without altering SCFA levels, and was associated with exacerbated muscle damage. Moreover, we observed a significant negative correlation between the abundance of SCFA-producing bacteria and SCFA levels with the expression of inflammatory cytokines in the muscle of mice post-exhaustive exercise. Conversely, the abundance of Staphylococcus and Bilophila showed a notable positive correlation with these cytokines. Additionally, the effects of LTMI and STHI on exhaustive exercise-induced muscle damage were transmissible to untrained mice via fecal microbiota transplantation, suggesting that gut microbiota changes induced by these training modalities may contribute to their contrasting impacts on muscle damage. These results underscore the significance of selecting an appropriate training modality prior to engaging in exhaustive exercise, with implications for athletic training and injury prevention. [ABSTRACT FROM AUTHOR]

The article discusses the increasing importance of rainwater harvesting pump systems as a solution to the global water shortage. It highlights the water shortages experienced by billions of people worldwide and the worsening situation in cities. The article emphasizes the need to harness rainwater as a sustainable option and calls for the installation of rainwater harvesting systems in new buildings and commercial developments. It also provides insights from experts in Australia, where rainwater harvesting has become ingrained due to government mandates, incentives, and water shortages. The article discusses the benefits and challenges of rainwater harvesting systems, including the need for strong foundations, proper maintenance, and addressing potential issues such as pump failures and mosquito infestation. It also mentions the potential for using rainwater for indoor purposes, such as toilets and washing machines, to save even more mains water. The article concludes by emphasizing the importance of learning from the experiences of countries like Australia and ensuring that rainwater harvesting systems meet the expectations of consumers. [Extracted from the article]

Karst groundwater, which is one of most important drinking water sources, is vulnerable to be polluted as its closed hydraulic relation with surface water. Thus, it is very important to identify the groundwater source to control groundwater pollution. The Pearson correlation coefficient among major ions (Na + K+, Ca2+, Mg2+, HCO3−, SO42−, and Cl−) was employed to deduce the groundwater types in Zhong Liang Mountain, Southwest China. Then, the combined method of principal component analysis and cluster analysis were employed to identify the groundwater sources in a typical karst region of southwest China. The results shown that (1) the high positive correlation between cations and anions indicated the water–rock reaction of Ca‐HCO3, Ca‐SO4, (Na + K)‐Cl, and Mg‐SO4. (2) The major two principal components that would represent water–rock reaction of CaSO4 and Ca‐HCO3 would, respectively, explain 60.41% and 31.80% of groundwater information. (3) Based on the two principal components, 33 groundwater samples were clustered into eight groups through hierarchical clustering, each group has similar water–rock reaction. The findings would be employed to forecast the surge water, that was an important work for tunnel construction and operation. Practitioner Points: The components of groundwater was highly correlated with water–rock reaction.The principal component analysis screens the types of groundwater.The cluster analysis identifies the groundwater sources. [ABSTRACT FROM AUTHOR]

Climate change is altering rainfall patterns resulting in increasing variability and intensity of rainfall events worldwide. Increases to short duration, intense rainfall (i.e., convective rainfall), will lead to increases in sewage overflow and run‐off from agricultural land. Such events generate spikes in micro‐organisms from feces and manure, especially Escherichia coli and intestinal enterococci, that temporarily end up in bathing waters posing serious health risks to bathers. Forecasting of bathing water quality associated with convective rainfall presents a distinctive forecasting challenge due to high uncertainties associated with predicting the timing, location, and impact of such events. In this article, we review examples of bathing water quality forecasting practices, with a focus on the United Kingdom where convective rainfall in the summer bathing water season is a particular concern, and question whether the current approach is robust in a changing climate. We discuss potential upgrades in bathing water forecasting and identify the main challenges that must be addressed before an improved framework for bathing water forecasting can be achieved. Although developments in meteorological and hydrological short‐range forecasting capabilities are promising, convective rainfall forecasting has significant predictability limits. We suggest taking full advantage of short‐range forecasts to provide sub‐daily bathing water forecasts, focusing on targeted bathing water monitoring regimes to improve model accuracy with the ultimate goal of providing improved information and guidance for beach users. This article is categorized under:Science of Water > Water and Environmental ChangeHuman Water > Water GovernanceScience of Water > Water Quality [ABSTRACT FROM AUTHOR]

Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the Escherichia coli genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of E. coli transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including emrKY-evgAS, ibsB-(mdtABCD-baeSR), ompC-rcsDB, and yedS-yedR, that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water E. coli isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus--thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts. [ABSTRACT FROM AUTHOR]

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]

Urban reservoirs contribute significantly to human survival and ecological balance. Machine learning-based remote sensing techniques for monitoring water quality parameters (WQPs) have gained increasing prominence in recent years. However, these techniques still face challenges such as inadequate band selection, weak machine learning model performance, and the limited retrieval of non-optical active parameters (NOAPs). This study focuses on an urban reservoir, utilizing unmanned aerial vehicle (UAV) multispectral remote sensing and ensemble machine learning (EML) methods to monitor optically active parameters (OAPs, including Chla and SD) and non-optically active parameters (including CODMn, TN, and TP), exploring spatial and temporal variations of WQPs. A framework of Feature Combination and Genetic Algorithm (FC-GA) is developed for feature band selection, along with two frameworks of EML models for WQP estimation. Results indicate FC-GA's superiority over popular methods such as the Pearson correlation coefficient and recursive feature elimination, achieving higher performance with no multicollinearity between bands. The EML model demonstrates superior estimation capabilities for WQPs like Chla, SD, CODMn, and TP, with an R2 of 0.72–0.86 and an MRE of 7.57–42.06%. Notably, the EML model exhibits greater accuracy in estimating OAPs (MRE ≤ 19.35%) compared to NOAPs (MRE ≤ 42.06%). Furthermore, spatial and temporal distributions of WQPs reveal nitrogen and phosphorus nutrient pollution in the upstream head and downstream tail of the reservoir due to human activities. TP, TN, and Chla are lower in the dry season than in the rainy season, while clarity and CODMn are higher in the dry season than in the rainy season. This study proposes a novel approach to water quality monitoring, aiding in the identification of potential pollution sources and ecological management. [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]

Climate change, unpredictable weather patterns, and droughts are depleting water resources in some parts of the globe, where recycling and reusing wastewater is a strategy for different purposes. To counteract this, the EU regulation for water reuse sets minimum requirements for the use of reclaimed water for agricultural irrigation, including a reduction in human enteric viruses. In the present study, the occurrence of several human enteric viruses, including the human norovirus genogroup I (HuNoV GI), HuNoV GII, and rotavirus (RV), along with viral fecal contamination indicator crAssphage was monitored by using (RT)-qPCR methods on influent wastewater and reclaimed water samples. Moreover, the level of somatic coliphages was also determined as a culturable viral indicator. To assess the potential viral infectivity, an optimization of a capsid integrity PMAxx-RT-qPCR method was performed on sewage samples. Somatic coliphages were present in 60% of the reclaimed water samples, indicating inefficient virus inactivation. Following PMAxx-RT-qPCR optimization, 66% of the samples tested positive for at least one of the analyzed enteric viruses, with concentrations ranging from 2.79 to 7.30 Log10 genome copies (gc)/L. Overall, most of the analyzed reclaimed water samples did not comply with current EU legislation and contained potential infectious viral particles. [ABSTRACT FROM AUTHOR]

Current methods for testing water for faecal contamination rely on the culture of faecal indicator bacteria (FIB; Escherichia coli and Enterococci) that take 24-48 h, which leads to delays in taking proactive measures and poses a risk to public health. More rapid methods are therefore required. Here, we have tested a rapid, portable assay (Bacterisk) that detects the bacterial biomarker endotoxin in 30 min to quantify the bacterial biomass present, to evaluate 159 coastal water samples and to compare the results with the traditional culture of FIB. There was a significant correlation between the Bacterisk data given in endotoxin risk (ER) units and FIB culture that could accurately distinguish between poor and sufficient or good quality bathing water using the EU bathing directive values. Receiver operating characteristic analysis was used to determine the optimal ER threshold for coastal water samples, and the area under the curve was 0.9176 with a p-value of,0.0001. The optimal threshold was 7,300 ER units with a sensitivity of 95.45% and a specificity of 83.48%. In conclusion, we have shown that the Bacterisk assay provides a rapid and easy-to-use in situ method to assess bathing water quality. [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]

Purpose: When examining the underlying processes of obesity, evaluation of gut flora and energy homeostasis can be crucial since disruption of the normal gut microbiota community and energy imbalances are significant factors in the development of obesity. Therefore, this study aimed to compare the relative abundance of important obesity modulator gut microbiota (including Firmicutes, Bacteroidetes, Bifidobactrium spp., Lactobacillus spp., Bacteroides fragilis, Faecalibacterium prausnitzii, Akkermansia muciniphila, and Escherichia coli) in fecal samples of normometabilic and hypometabolic overweight/obese individuals. Methods: This matched case–control study conducted on 36 healthy women aged 18–50 years old. An indirect calorimeter and impedance body analyzer were used to assess resting metabolic rate (RMR) and body composition, respectively. Dietary intake and physical activity were assessed using questionnaires. To determine the abundance of the abovementioned gut microbiota, quantitative polymerase chain reaction (qPCR) method was performed. Moreover, ELISA kits were used to assess leptin, ghrelin, and insulin hormones. Results: The results highlighted higher load of Firmicutes (p = 0.02), F. prausnitzii (p < 0.001), and B. fragilis (p = 0.02) in the normometabolic individuals compared to the hypometabolic ones. Besides, the positive correlation between the abundance of Firmicutes (β = 7.76 × 10–1, p = 0.01), F. prausnitzii (β = 1.29 × 10–5, p = 0.01), and B. fragilis (β = 4.13 × 10–6, p = 0.04) with the RMR have been shown. Whereas the abundance of Bacteroidetes, A. muciniphila, Lactobacillus spp., Bifidobactrium spp., and E. coli showed no significant difference (p > 0.05) and no significant correlation with the RMR except Lactobacillus spp. (β = 1.73 × 10–4, p = 0.01). Conclusion: It seems that gut microbiota can be a potential target for refining host energy homeostasis and treating obesity and its consequences. [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]