Source Tracing Research Articles

Department-specific patterns of bacterial communities and antibiotic resistance in hospital indoor environments

The hospital indoor environment has a crucial impact on the microbial exposures that humans encounter. Resistance to antibiotics is a mechanism used by bacteria to develop resilience in indoor environments, and the widespread use of antibiotics has led to changes in the ecological function of resistance genes and their acquisition by pathogens. By integrating the 16S rRNA Illumina sequencing and high-throughput-quantitative PCR approaches with water and air dust samples across seven departments in Peking University Shenzhen Hospital, China, this study yields intriguing findings regarding the department-specific variations, correlations and source tracing of bacteria, antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) within the hospital indoor environment. A notable observation was the pivotal role played by seasonal variations in shaping the bacterial composition across the entire hospital indoor environment. Another department-specific finding was the correlation between ARGs and MGEs abundance, which was evident in the overall hospital indoor environment, but not found in the blood test room, ophthalmology, and gynecology departments. Notably, as an important source of bacteria and ARGs/MGEs for the blood test room, the gynecology department also presented a close link between bacterial communities and the presence of ARGs/MGEs. Additionally, the results reiterate the importance of surveillance and monitoring of antibiotic resistance, specifically in Legionella spp. in man-made water systems, and highlight the significance of understanding genetic elements like Tp614 involved in gene transfer and recombination, and their impact on antimicrobial treatment efficacy. Key points•The department-specific variations, correlations and source tracing of bacteria, ARGs, and MGEs were uncovered in the hospital’s indoor environment.•Although each department exhibited consistent seasonal impacts on bacterial compositions, the co-occurrence between the presence of ARGs and MGEs was exclusively evident in the emergency, surgery, pneumology and otolaryngology departments.•The gynecology department emerged as a crucial source of bacteria, ARGs and MGEs within the hospital. Additionally, it was found to exhibit a significant correlation between bacterial communities and the presence of ARGs and MGEs.

Isotopic signature of N2O produced during sulfur‐ and thiosulfate‐driven chemoautotrophic denitrification in freshwaters

AbstractChemoautotrophic denitrification plays an important role in nitrogen removal and the formation of a greenhouse gas (N2O) in aquatic environments. Natural stable isotopes support the tracing of nitrogen sources and the identification of biogeochemical processes in field research. However, the isotopic characteristics of N2O produced during chemoautotrophic denitrification have not been investigated so far. In this study, we analyzed isotopic signatures of nitrate and N2O in sulfur‐ and thiosulfate‐dependent denitrifying enrichments obtained from freshwater lakes. Chemoautotrophic denitrification exhibited a nitrate isotope pattern similar to heterotrophic denitrification: the 18ε/15ε‐nitrate followed a ratio close to 1. However, chemoautotrophic denitrification produced N2O with lower δ15N, δ18O, and higher site preference (SP = δ15Nα‐δ15Nβ) values, compared to heterotrophic denitrification. The SP value, approximately 5.1‰, was characteristic in detecting chemoautotrophic denitrification driven by different sulfur forms. δ18O varied with specific electron donors, around 20‰ and 40‰ during sulfur‐ and thiosulfate‐dependent denitrification, respectively. The unique N2O isotope characteristics were likely regulated by nitric oxide reductases of Burkholderiaceae populations during sulfur‐dependent denitrification and Sulfurovum during thiosulfate‐dependent denitrification. These findings improve our understanding of N2O production processes and have important implications for predicting N2O emissions at a greater spatial and temporal resolution.

Using the check dam deposit for an individual event to document the sources and erosional loss of sediment-associated organic carbon from a small catchment on the Chinese Loess Plateau

Information on the sources and fate of organic carbon mobilized by soil erosion is crucial for understanding the impact of erosion on carbon (C) cycling. However, few studies have evaluated this in low-order stream systems. In this study, we adopted a novel approach, that used the sediment deposited behind a check dam constructed at the outlet of the Fengzigou catchment (0.91 km2) on the Chinese Loess Plateau by a single high magnitude storm event, to simplify the field sampling requirements. The total sediment-associated organic carbon (TOC) was fractionated into particulate organic carbon (POC) and mineral associated organic carbon (MOC). These results were combined with those from a sediment source tracing exercise. This made it possible to explore further the source and loss of the sediment-associated organic carbon. The results showed that the inter-gully areas contributed the most eroded TOC (52.3 ± 7.6 %) and, together with the gully walls, represented the main TOC source. The primary contributor of the POC fraction in the deposited sediment was the inter-gully areas (80.5 ± 12.6 %), whereas the gully walls were the main contributor of the MOC fraction (54.9 ± 10.2 %). The total output of sediment produced by the event was 1304 ± 48 t and the equivalent value for sediment-associated TOC was 2.94 ± 0.26 t, of which the POC fraction accounted for 27.6 ± 3.6 % and the MOC fraction 72.4 ± 9.8 %. The TOC lost (0.3 ± 0.02 t) through the mobilization and delivery processes was 10.2 ± 1.2 % of the TOC mobilized by erosion, and the lost carbon was dominated by the POC fraction (86.7 ± 8.8 %). The specific TOC output from the catchment associated with the event documented was 0.3 t km−2. This work demonstrates the potential for erosion-induced carbon redistribution to provide a source for atmospheric CO2 in the study area.

Machine learning-assisted source tracing in domestic-industrial wastewater: A fluorescence information-based approach

An emergency water pollution incident poses a significant risk to the proper functioning of wastewater treatment plants, particularly in domestic-industrial integrated facilities. Source tracing is recognized as an effective method to mitigate ongoing impacts. Machine learning-assisted traceability is emerging as a more efficient and faster method compared to traditional methods. In this study, a total of 712 sets of characterization wastewater information from effluent samples from14 discharge enterprises across 6 different sectors, as well as domestic wastewater was collected using 3-dimensional fluorescence spectroscopy. After data cleaning and augmentation, a feature fingerprint database of wastewater was constructed to train a traceability model. Several machine learning algorithms, including Back Propagation neural network (BP), Random Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB) and K-Nearest Neighbors (KNN), were selected for constructing the traceability framework. Subsequently, an advanced Particle Swarm Optimization Random Forest model (PSO-RF), capable of automatically optimizing model parameters, was proposed and applied to trace the sources of wastewater in integrated wastewater treatment plant. The PSO-RF achieved and accuracy of 96.55 % in sector identification and 94.25 % in manufacturer identification. As part of the validation process, laboratory simulations were conducted using blended wastewater with different volume ratios of domestic and industrial wastewater to evaluated the potential application of PSO-RF. The results consistently demonstrated PSO-RF's effectiveness, particularly in tracing pharmaceutical wastewater sources, maintaining an accuracy of over 85 %. This work presents a novel strategy for tracing abnormal sources during emergency pollutant incidents, providing essential support for integrating artificial intelligence (AI) into meticulous wastewater management.

Selecting Endogenous Promoters for Improving Biosynthesis of Squalene in Schizochytrium sp.

Squalene (C30H50) is an acyclic triterpenoid compound renowned for its myriad physiological functions, such as anticancer and antioxidative properties, rendering it invaluable in both the food and pharmaceutical sectors. Due to the natural resource constraints, microbial fermentation has emerged as a prominent trend. Schizochytrium sp., known to harbor the intact mevalonate acid (MVA) pathway, possesses the inherent capability to biosynthesize squalene. However, there is a dearth of reported key genes in both the MVA and the squalene synthesis pathways, along with the associated promoter elements for their modification. This study commenced by cloning and characterizing 13 endogenous promoters derived from transcriptome sequencing data. Subsequently, five promoters exhibiting varying expression intensities were chosen from the aforementioned pool to facilitate the overexpression of the squalene synthase gene squalene synthetase (SQS), pivotal in the MVA pathway. Ultimately, a transformed strain designated as SQS-3626, exhibiting squalene production 2.8 times greater than that of the wild-type strain, was identified. Finally, the optimization of nitrogen source concentrations and trace element contents in the fermentation medium was conducted. Following 120 h of fed-batch fermentation, the accumulated final squalene yield in the transformed strain SQS-3626 reached 2.2g/L.

NICER Observes the Full Z-track in GX 13+1

We present the temporal analysis of the persistent neutron star low-mass X-ray binary GX 13+1 using NICER data. Classification of this source has been ambiguous so far. We investigate the evolution of the source in its hardness–intensity diagram (HID) and power density spectra (PDS) of the 0.5–10 keV NICER archival data. For the first time, we detect the source tracing out the entire Z-track, distinctly identifying the horizontal branch (HB), normal branch (NB) and flaring branch (FB). We also detect a peaked noise component in the PDS at ∼5.4 Hz, which appears to be present when the source is either in the NB or FB. We note a positive slope of the HB in the HID which could be due to either the high intrinsic absorption of the source or the stronger contribution of the soft spectral components in the soft energy domain.

Sediment source tracing in a Brazilian subtropical catchment using diffuse reflectance: Effect of spectral ranges, pre-processing techniques, and multivariate model

ABSTRACT Agriculture intensification in Southern Brazil’s subtropical regions combined with the frequent occurrence of erosive rainfall has rendered the area a global water erosion hotspot. In this scenario, understanding and regulating erosion processes at the river catchment scale is critical for mitigating soil and water resource degradation. Traditional methods for tracing sediment sources are expensive and time-consuming and justify the development of alternative approaches. Therefore, in this study, we employed diffuse reflectance spectroscopy analyses in the ultraviolet-visible (UV-VIS), near-infrared (NIR), and mid-infrared (MIR) ranges, combined with multivariate models and spectral pre-processing techniques to estimate sediment source contributions in a homogeneous subtropical catchment (Conceição River, 804 km²). Soil samples (n = 181) were collected to characterize the four potential sediment sources, including: cropland (n = 78), stream bank (n = 36), unpaved road (n = 40) and pasture (n = 27). Moreover, 44 sediment samples were collected, including suspended sediment (n = 8), fine sediment deposited on the riverbed (n = 15), and suspended sediment samples collected in the water column during storm events (n = 21). Vector machine (SVM) model outperformed the others, with better accuracy and reliability. While UV-VIS spectra proved less effective due to soil homogeneity across the catchment, NIR and MIR spectra provided valuable information for discriminating sediment sources. Furthermore, reducing the number of potential sources (from four to three or two) improved model predictions, especially when distinguishing between surface sources (cropland and pasture) and subsurface sources (unpaved roads and stream banks). The study’s findings shed light on the power of efficient and cost-effective alternative methods for assessing sediment sources, which are vital for promoting effective erosion control and sustainable land management in similar regions.

Comprehensive Study on the Electrical Characteristics and Full-Spectrum Tracing of Water Sources in Water-Rich Coal Mines

Comprehensive Study on the Electrical Characteristics and Full-Spectrum Tracing of Water Sources in Water-Rich Coal Mines

Quaternary provenance changes in the loess deposits of the western Chinese Loess Plateau: Insights from U-Pb age spectra of detrital zircon

The western region of the Chinese Loess Plateau (CLP) on the western side of the Liupan Mountains connects the Tibetan Plateau with the deserts of the northern arid zones. This region is key for understanding of the coupled relationship between tectonic uplift and surface processes (erosion and climate) on the Tibetan Plateau; however, the variation of Quaternary wind-dust sources in the region remains uncertain, confounding analysis. In this paper, we conduct a source tracing investigation using detrital zircon U-Pb dating of 12 loess layers from the Huining aeolian sedimentary sequence of the western CLP, reconstruct the history of provenance changes during the Quaternary Period, and further explore driving mechanisms. Results show that aeolian dust from the western CLP is mainly from the northeastern margin of the Tibetan Plateau (NTP). At 1.8–1.66 Ma, the main source region was the NTP, which corresponds to the Episode C uplift event of the Tibetan Plateau. The dominant source area transitioned to the Gobi Altay Mountains (GAMs) around 1.5–1.4 Ma. This shift suggests that the tectonic uplift of the Tibetan Plateau had entered a period of stasis following the conclusion of Episode C, leading to increased transport of detrital material from the GAMs by the East Asian Winter Monsoon. After 1.24 Ma, the dominant source region abruptly changed from the GAMs to the NTP and lasted until 0.04 Ma. The topographic fluctuations caused by the Kunhuang Movement appears to have been the main reason for the sudden source change. Based on our results and evidence from previous studies, the source changes that occurred during the Quaternary Period were in response to a combination of tectonic events and climate change. Comparison of zircon age spectra between the eastern and western CLP further support the idea that the Plateau Winter Monsoon was the main transport system for aeolian dust in the western CLP.

Multi-evidences investigation into spatiotemporal variety, sources tracing, and health risk assessment of surface water nitrogen contamination in China

A comprehensive understanding of nitrogen pollution status, especially the identification of sources and fate of nitrate is essential for effective water quality management at the local scale. However, the nitrogen contamination of surface water across China was poorly understood at the national scale. A dataset related to nitrogen was established based on 111 pieces of literature from 2000 to 2020 in this study. The spatiotemporal variability, source tracing, health risk assessment, and drivers of China's surface water nitrogen pollution were analyzed by integrating multiple methods. These results revealed a significant spatiotemporal heterogeneity in the nitrogen concentration of surface water across China. Spatially, the Haihe River Basin and Yellow River Basin were the basins where surface water was seriously contaminated by nitrogen in China, while the surface water of Southwest Basin was less affected. Temporally, significant differences were observed in the nitrogen content of surface water in the Songhua and Liaohe River Basin, Pearl River Basin, Southeast Basin, and Yellow River Basin. There were 1%, 1%, 12%, and 46% probability exceeding the unacceptable risk level (HI＞1) for children in the Songhua and Liaohe River Basin, Pearl River Basin, Haihe River Basin, and Yellow River Basin, respectively. The primary sources of surface water nitrate in China were found to be domestic sewage and manure (37.7%), soil nitrogen (31.7%), and chemical fertilizer (26.9%), with a limited contribution from atmospheric precipitation (3.7%). Human activities determined the current spatiotemporal distribution of nitrogen contamination in China as well as the future development trend. This research could provide scientifically reasonable recommendations for the containment of surface water nitrogen contamination in China and even globally.

Genomic and Spatial Analysis on the Recent Transmission of Mycobacterium tuberculosis in Eastern China: A 10-Year Retrospective Population-Based Study.

Understanding the mode of Mycobacterium tuberculosis (M. tuberculosis) transmission is crucial for disease prevention and control. Compared to traditional genotyping methods, whole genome sequencing (WGS) provides higher resolution and comprehensive genetic information, enabling the tracing of infection sources and determining of transmission routes to resolve extensive tuberculosis (TB) outbreaks. We conducted a ten-year study on the transmission of M. tuberculosis in a population in eastern China. We selected Lianyungang, an eastern city in China, as the study site. Patients diagnosed with active pulmonary TB from 2011 to 2020 were enrolled as the study subjects. We isolated and sequenced 2252 M. tuberculosis. Strains with pairwise genetic distances of less than 12 single nucleotide polymorphisms were defined as genomic clusters and which were considered recent transmissions. Kernel density estimation and K-function analysis were applied to explore the spatial distribution of recently transmitted strains. After excluding non-tuberculous mycobacteria and duplicated samples, 2114 strains were included in the final analysis. These strains comprised lineage 2 (1593, 75.35%) and 4 (521, 24.65%). There were 672 clustered strains, with a recent transmission rate of 31.79%. The logistic regression model showed that the risk of recent transmission was high in students [adjusted odds ratio (aOR): 2.68, 95% confidence interval (CI): 1.63-4.49, P<0.001] and people infected with L2.2.1 strains (aOR: 1.59, 95% CI: 1.20-2.12). Higher spatial aggregation of TB transmission has been concentrated in Haizhou, Donghai, and Guanyun for the past 10 years. Three outbreaks affecting 46 patients were spatially spaced, with 11 to 23 persons each. Different groups exhibited varying geographic distances between the initial and later cases. There are areas with a high risk of transmission for M. tuberculosis in the research site, and the risk varies among different populations. Accurate prevention strategies targeted at specific regions and key populations can help curb the prevalence of TB.

Intrasample osmium isotope disequilibrium in young volcanic rocks: Insights from a new progressive digestion procedure

Some young volcanic rocks have been found to possess intrasample Os-isotope heterogeneity. This has important implications for source tracing and dating. Here, we use a new procedure through which it is possible to sequentially extract, from a single aliquot, the 187Os/188Os ratio of: i) the surface contaminant(s) (hydrobromic acid leachate); ii) the residual bulk rock powder (Step I) and iii) the Os-bearing phases entrapped within silicates (Step II). We applied this technique to two young basaltic reference materials (RMs), USGS BHVO-2 and EN026 10D-3. The former samples the 1919 lava from the Kīlauea summit crater (Hawaii) and the latter is a basalt sample dredged from Mohns Ridge (Greenland Sea). Both rock standards have previously been shown to display large intrasample Os isotope heterogeneity. In addition to analyzing these RMs, we also analyzed the RM USGS BHVO-1 for comparison, as well as another sample from the Kīlauea 1919 summit eruption (Kil 1919-6) along with a picritic tholeiite from the Kīlauea Iki 1959 eruption.Our leaching results show that BHVO-2 is contaminated with a highly radiogenic and labile contaminant with 187Os/188Os ratio of 0.525 ± 0.021. Without leaching, the Step I 187Os/188Os ratios varied from 0.1399 ± 0.0013 to 0.1568 ± 0.0014 while those for Step II were uniform (average = 0.1286 ± 0.0006, N = 5). A comparison of Re, Mo concentrations and 187Os/188Os ratio of the leachates of BHVO-2 and its predecessor (BHVO-1) indicates that BHVO-2 was contaminated during preparation. After leaching, the Step I and Step II 187Os/188Os ratios of BHVO-1 and another sample (Kīlauea 1919-6) from the same lava flow are identical within error to that of the Step II ratio of BHVO-2. A picrite from the 1959 Kīlauea Iki eruption also analyzed using the new technique gives homogenous results for both the steps with an average 187Os/188Os ratio of 0.1302 ± 0.0005. The 187Os/188Os ratio of recent Kīlauea lavas is identical within error to that of the primitive upper mantle (=0.1296). The Kīlauea Os-isotope composition could represent a “common component” that occurs globally in many plumes. The Step I 187Os/188Os ratio of EN026 10D-3 is 0.136 with Step II ratio being 0.131 (N = 2). The Step II 187Os/188Os ratios are more radiogenic than the nearby Jan Mayen lavas (187Os/188Os = 0.124–0.129) that have been argued to influence the chemistry of the Western section of the Mohns Ridge basalt but fall within the range of the Primitive Upper Mantle. We also discovered that BHVO-1, KIL 1919-6, 1959 Kīlauea Iki picrite, and EN026 10D-3 show Os-isotope disequilibrium between the leachate and Step I, suggesting wall rock assimilation during magma ascent. The data set presented here indicates a need for re-evaluating the extent to which mantle heterogeneities influence the Os isotope composition of ocean basalts.

Mechanisms of evolution and pollution source identification in groundwater quality of the Fen River Basin driven by precipitation

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as “excellent” or “good” in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO3−, and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO3− increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO3− and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau.

Adaptive Path Planning for Subsurface Plume Tracing with an Autonomous Underwater Vehicle

Autonomous underwater vehicles (AUVs) have been increasingly applied in marine environmental monitoring. Their outstanding capability of performing tasks without human intervention makes them a popular tool for environmental data collection, especially in unknown and remote regions. This paper addresses the path planning problem when AUVs are used to perform plume source tracing in an unknown environment. The goal of path planning is to locate the plume source efficiently. The path planning approach is developed using the Double Deep Q-Network (DDQN) algorithm in the deep reinforcement learning (DRL) framework. The AUV gains knowledge by interacting with the environment, and the optimal direction is extracted from the mapping obtained by a deep neural network. The proposed approach was tested by numerical simulation and on a real ground vehicle. In the numerical simulation, several initial sampling strategies were compared on the basis of survey efficiency. The results show that direct learning based on the interaction with the environment could be an appropriate survey strategy for plume source tracing problems. The comparison with the canonical lawnmower path used in practice showed that path planning using DRL algorithms could be potentially promising for large-scale environment exploration.

Particle swarm optimization inverse tracing method for mine tunnel fire based on quasi-steady-state heat transfer mechanism

Rapidly locating and assessing fires in coal mines is essential for effective response and minimizing damage. Traditional methods often struggle to swiftly and accurately pinpoint fire locations and statuses. Hence, this study introduces a particle swarm inverse tracing approach based on the quasi-steady-state heat transfer between high-temperature flue gases and mine tunnel walls. This method aims to remotely monitor smoke flow temperatures and gas concentrations to determine fire locations and combustion trends. Validation of the fire source tracing model was conducted through comprehensive tunnel fire experiments and numerical simulations. The particle swarm optimization inverse tracing method yielded a maximum 7.65 % error in fire location determination compared to actual measurements, while accurately matching the measured fire source heat release rate curve. These findings underscore the method’s high precision and reliability, particularly evident during the developmental and stable stages of fire burning.

The Inversion Location of Microleakage Source and Diffusion Backward Tracing Method Based on 3D Visual Information Model of Salt-Cavern Gas Storage

Summary The safe and stable operation of underground gas storage makes a positive contribution to national energy security. To improve the efficiency of real-time monitoring and early warning of gas leakage accidents at the wellsite of salt-cavern gas storage, an inversion location of the gas microleakage source and a backward tracing method of leakage diffusion are proposed. Through building a 3D visual information model of the salt-cavern gas storage based on building information modeling (BIM) technology and combining it with the advantages of the gas sensors, the real-time inversion location of the microleakage source and diffusion backward tracing in the wellsite can be realized. First, multiple point-type laser methane sensors were used to monitor the leakage of some key zones in real time, and a pan/tilt/zoom (PTZ) scanning laser methane telemeter was used to realize the real-time multidimensional space monitoring on-site from horizontal 360° to vertical 180°. Second, a 3D integrated monitoring platform is established to analyze the gas leakage source by combining the monitoring data and improving the mesh interpolation points. Finally, the whole data and wellsite information are imported into the 3D integrated monitoring platform to realize the inversion location of the microleakage source and the real-time monitoring of the leakage and diffusion state in the whole region. The monitoring precision of gas leakage concentration can be up to 1.0 ppm, and the location distance is within 0.1 m based on the numerical simulation of the 3D model and actual detected data from sensors in the platform. Compared with the technical means of manual assisted leak location, this method effectively solves the difficult problem of leakage monitoring and location accurately in the gas storage and can timely reduce the expansion and impact of leakage accidents.

Riverine seasonal rainfall event tracing of organic pollution sources using fluorescence fingerprint difference spectrum

Elucidating the dynamics of dissolved organic matter (DOM) transport and transformation under seasonal rainfall events is essential for the conservation of riverine ecosystems, for mitigating the effects of climate change, and for crafting informed water management strategies. Therefore, this study aimed to investigate the evolutionary characteristics of organic pollution sources during consecutive rainfall events in early spring and to quantify their relative contributions to the process of surface water pollution. The results showed seasonal rainfall induces water quality exceedances in rivers due to the combined impacts of terrestrial inputs and endogenous releases. Humic acid (HA) (region V) and fulvic acid (FA) (region III) emerged as the predominant organic matter in the water column, with their fluorescence intensity altering as rainwater flushed the riverbed. Sources of pollution include agricultural and urban domestic sources (AS + DS) (72.29 %), industrial and urban domestic and microbial sources (IS + DS + MS) (37.71 %), and agricultural and industrial sources (AS + IS) (63.32 %), indicating that agricultural surface pollution discharges contribute significantly. The gas–chromatography–mass spectrometry (GC–MS) further confirmed that exogenous inputs were predominantly comprised of particulate pollutants. This study underscores the efficacy of fluorescence difference spectrometry in delineating the migration and transformation of river pollution sources during seasonal rainfall and facilitating the implementation of targeted management strategies for river ecosystems.

Listeria monocytogenes in Food Production and Food Safety: A Review

In the current world of global food distribution and marketing, the outbreak of a particular foodborne disease in a region may eventually occur in another part of the world at the same time. Foodborne diseases are estimated to cause over 600 million illnesses and 420,000 deaths each year. Listeriosis, a zoonotic bacterial disease caused by Listeria spp. has been reported in various parts of the world’s disease outbreak and incidence. The highest number of diseases and outbreaks is caused by Listeria monocytogenes and is highly predominant among elderly persons, immunocompromised individuals, pregnant women, and infants. This bacterium possesses the ability to survive and multiply under refrigeration temperature, a wide range of pH (4.1 - 9.6), and high salt (≤ 10%). The disease can be minimal (non-invasive/febrile gastroenteritis) and the pathogen possesses the ability to cross the epithelium and infect sterile organs (invasive). Outside food contamination, resistance to antibiotics by Listeria monocytogenes poses major public health concerns as this bacterium has developed resistance to various antibiotics in use. In addition to food, Listeria species have been isolated from the soil, water, plants, fruits, and vegetables coupled with the long incubation period (11 - 70 days), which poses a challenge to infection source identification and trace back principle. Controlling Listeria in foods can be achieved by practicing a Hazard Analysis and Critical Control Point (HACCP) strategy in the food industry, improving hygiene measures, and avoiding the consumption of contaminated foods. Also, susceptible individuals should be educated on the risks associated with the consumption of contaminated foods.

Multiple locus variable number tandem repeat analysis genotype polymorphism of Bacillus anthracis in China

Objective: To analyze the multiple locus variable number tandem repeat analysis (MLVA) genotype polymorphism of Bacillus (B.) anthracis and establish a MLVA genotype database of B. anthracis in China. Methods: B. anthracis strains isolated from different sources in China since 1947 were collected. Genotype identification was carried out using the MLVA15 genotyping protocol based on 15 variable number tandem repeat loci. The genotypes were uniformly numbered and named. The distribution characteristics of the MLVA genotypes of strains were analyzed. Software Bionumerics was used to construct clustering diagrams to analyze the genetic relationships. Results: The MLVA15 clustering analysis subdivided the isolates into 4 major groups and 91 genotypes, 54 of which were unique to China. The genotypes from MLVA15-CHN1 to MLVA15-CHN6 were widely distributed throughout China and in all eras, while other genotypes were restricted to certain regions or eras. Conclusions: This study established a MLVA genotype database of B. anthracis, which provides basis for the understanding of MLVA genetic polymorphisms and the control and molecular source tracing of the anthrax outbreaks in China.

Source Tracing of PM2.5 in a Metropolitan Area Using a Low-Cost Air Quality Monitoring Network: Case Study of Denver, Colorado, USA

Air quality assessments often require source apportioning of the air pollutants observed at the receptor site. Conventional source apportionment models are subject to high uncertainties due to the lack of accurate emission profiles of all the contributing sources and a limited number of measurements at the receptor sites. Recent advances in the development and application of low-cost PM2.5 sensors have facilitated the formation of a more robust database with greater numbers of measurements per location and time. The main objective of this study is to combine a large database of PM2.5 concentration records to records from low-cost sensors in Denver, Colorado, during January 2021. Using wind speed and wind direction at the receptors, we developed a visualization tool for source tracing of PM2.5 with resulting statistical analyses and back-trajectory modeling. For this purpose, a combination of in-house and existing packages of R scripts along with National Oceanic and Atmospheric Administration (NOAA)’s trajectory model and climate and weather toolkits were used. In general, the results show that the PM2.5 measurements obtained from such a network of PM2.5 sensors incorporated with hourly wind field data, which are publicly available, can provide a powerful screening tool to discover the transport pathways of PM2.5 before requiring costly source apportionment approaches. The fraction of PM2.5 concentration detected by each sensor in regard to wind direction and speed bins were quantified using this method. The results of cluster analysis identified the area groups in respect to wind speed and wind direction bins, which shines a light on how far and in which direction polluting sources are. Finally, the back-trajectory modeling outputs illustrated the exact travel path of the PM2.5-laden air parcels of each day to each sensor.