Artificial olfactory memory system based on conductive metal-organic frameworks.

The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

Trends in cancer imaging.

Molecular imaging of cancer is a collaborative endeavor, uniting scientists and physicians from diverse fields. Such collaboration is actively developing and translating cutting-edge molecular imaging approaches to enhance the diagnostic landscape of human malignancies. The advent of positron emission tomography (PET) and PET imaging tracers has realized non-invasive target annotation and tumor characterization at the molecular level. In surgical procedures, novel imaging techniques, such as fluorescence or Cherenkov luminescence, help identify tumors and enhance surgical precision. Simultaneously, progress in imaging equipment, innovative algorithms, and artificial intelligence has opened avenues for next-generation cancer screening and imaging, augmenting the efficiency and accuracy of cancer diagnosis. In this review, we provide a panorama of molecular cancer imaging and ongoing developments in the field.

Development and Validation of a Nomogram Model for Accurately Predicting Depression in Maintenance Hemodialysis Patients: A Multicenter Cross-Sectional Study in China.

Purpose: Depression is a major concern in maintenance hemodialysis. However, given the elusive nature of its risk factors and the redundant nature of existing assessment forms for judging depression, further research is necessary. Therefore, this study was devoted to exploring the risk factors for depression in maintenance hemodialysis patients and to developing and validating a predictive model for assessing depression in maintenance hemodialysis patients. Patients and Methods: This cross-sectional study was conducted from May 2022 to December 2022, and we recruited maintenance hemodialysis patients from a multicentre hemodialysis centre. Risk factors were identified by Lasso regression analysis and a Nomogram model was developed to predict depressed patients on maintenance hemodialysis. The predictive accuracy of the model was assessed by ROC curves, area under the ROC (AUC), consistency index (C-index), and calibration curves, and its applicability in clinical practice was evaluated using decision curves (DCA). Results: A total of 175 maintenance hemodialysis patients were included in this study, and cases were randomised into a training set of 148 and a validation set of 27 (split ratio 8.5:1.5), with a depression prevalence of 29.1%. Based on age, employment, albumin, and blood uric acid, a predictive map of depression was created, and in the training set, the nomogram had an AUC of 0.7918, a sensitivity of 61.9%, and a specificity of 89.2%. In the validation set, the nomogram had an AUC of 0.810, a sensitivity of 100%, and a specificity of 61.1%. The bootstrap-based internal validation showed a c-index of 0.792, while the calibration curve showed a strong correlation between actual and predicted depression risk. Decision curve analysis (DCA) results indicated that the predictive model was clinically useful. Conclusion: The nomogram constructed in this study can be used to identify depression conditions in vulnerable groups quickly, practically and reliably.

A novel vesicular stomatitis virus armed with IL-2 mimic for oncolytic therapy.

Oncolytic virus (OV) is increasingly being recognized as a novel vector in cancer immunotherapy. Increasing evidence suggests that OV has the ability to change the immune status of tumor microenvironment, so called transformation of 'cold' tumors into 'hot' tumors. The improved anti-tumor immunity can be induced by OV and further enhanced through the combination of various immunomodulators. The Neo-2/15 is a newly de novo synthesized cytokine that functions as both IL-2 and IL-15. However, it specifically lacks the binding site of IL-2 receptor α subunit (CD25), therefore unable to induce the Treg proliferation. In present study, a recombinant vesicular stomatitis virus expressing the Neo-2/15 (VSVM51R-Neo-2/15) was generated. Intratumoral delivery of VSVM51R-Neo-2/15 efficiently inhibited tumor growth in mice without causing the IL-2-related toxicity previously observed in clinic. Moreover, treatment with VSVM51R-Neo-2/15 increased the number of activated CD8+ T cells but not Treg cells in tumors. More tumor-bearing mice were survival with VSVM51R-Neo-2/15 treatment, and the surviving mice displayed enhanced protection against tumor cell rechallenge due to the induced anti-tumor immunity. In addition, combination therapy of OV and anti-PD-L1 immune checkpoint inhibitors further enhanced the anti-tumor immune response. These findings suggest that our novel VSVM51R-Neo-2/15 can effectively inhibit the tumor growth and enhance the sensitivity to immune checkpoint inhibitors, providing promising attempts for further clinical trials.

T cell-related circRNA pairs to predict prognosis of patients with esophageal squamous cell carcinoma.

The prognosis for esophageal squamous cell carcinoma (ESCC), a prevalent and aggressive form of cancer, remains poor despite advancements in treatment options. Addressing the gap in comprehensive prognostic information derived from circRNA expression profiles for ESCC, our study aimed to establish a linkage between circRNA expressions and ESCC prognosis. To achieve this, we first developed an optimized prognostic model named T cell-related risk score (TRRS), which integrates T cell-associated features with machine learning algorithms. In parallel, we re-analyzed existing RNA-seq datasets to redefine the expression profiles of circRNAs and mRNAs. Utilizing the TRRS as a foundational "bridge," we identified circRNAs correlated with TRRS, leading to the development of a novel circRNA pair-based prognostic model, the TCRS, which is independent of specific expression levels. Further investigations uncovered two circRNAs, circNLK(5,6,7).1 and circRC3H1(2).1, with potential functional significance. These findings underscore the utility of these risk scores as tools for predicting overall survival and identifying potential therapeutic targets for ESCC patients.

Volatile organic compounds in cancer and exhaled breath detection technology.

The detection of volatile organic compounds (VOCs) in breath has become a potential method for early cancer screening. Although this approach has attracted increasing attention from the both scientific and medical communities, it has not received appreciable traction in the clinical setting. There are two main obstacles. One involves the identification of specific biomarkers or combinations thereof especially in early cancer. The other is the lack the specialized equipment for breath analysis having the appropriate sensitivity and specificity. Using metabolomics, this chapter examines the research strategies involving gas biomarkers in cancer patient breath, cancer cell gas metabolites and synthetic biomarkers. We briefly explore gas biomarkers of seven cancers and introduce principles of detection and clinical application. Large analytical instruments and small sensor technology are highlighted. Challenges to VOC analysis are presented including clinical use, extraction and detection, miniaturization efforts and examination of metabolic VOC pathways. Finally, VOCs in cancer and in exhaled breath detection technology are summarized and future prospects explored.

Fluorescent Polylactic acid composite incorporating lignin-based carbon quantum dots for sustainable 4D printing applications.

Fluorescent 4D printing materials, as innovative materials that combine fluorescent characteristics with 4D printing technology, have attracted widespread interest and research. In this study, green lignin-derived carbon quantum dots (CQDs) were used as the fluorescent module, and renewable poly(propylene carbonate) polyurethane (PPCU) was used for toughening. A new low-cost fluorescent polylactic acid (PLA) composite filament for 4D printing was developed using a simple melt extrusion method. The strength of the prepared composite was maintained at 32 MPa, while the elongation at break increased 8-fold (34 % increase), demonstrating excellent shape fixed ratio (∼99 %), recovery ratio (∼92 %), and rapid shape memory recovery speed. The presence of PPCU prevented fluorescence quenching of the CQDs in the PLA matrix, allowing the composite to emit bright green fluorescence under 365 nm ultraviolet light. The composite exhibited shear thinning behavior and had an ideal melt viscosity for 3D printing. The results obtained demonstrated the versatility of these easy-to-manufacture and low-cost filaments, opening up a novel and convenient method for the preparation of strong, tough, and multifunctional PLA materials, increasing their potential application value.

A seasonal study on the microbiomes of Diploid vs. Triploid eastern oysters and their denitrification potential.

Oyster reefs are hotspots of denitrification mediated removal of dissolved nitrogen (N), however, information on their denitrifier microbiota is scarce. Furthermore, in oyster aquaculture, triploids are often preferred over diploids, yet again, microbiome differences between oyster ploidies are unknown. To address these knowledge gaps, farmed diploid and triploid oysters were collected over an annual growth cycle and analyzed using shotgun metagenomics and quantitative microbial elemental cycling (QMEC) techniques. Regardless of ploidy, Psychrobacter genus was abundant, with positive correlations found for genes of central metabolism, DNA metabolism, and carbohydrate metabolism. MAGs (metagenome-assembled genomes) yielded multiple Psychrobacter genomes harboring norB, narH, narI, and nirK denitrification genes, indicating their functional relevance within the eastern oysters. QMEC analysis indicated the predominance of carbon (C) and nitrogen (N) cycling genes, with no discernable patterns between ploidies. Among the N-cycling genes, the nosZII clade was overrepresented, suggesting its role in the eastern oyster's N removal processes.

Moderate/severe biatrial dilation predicts adverse events after ablation in atrial fibrillation with heart failure.

AIMS: To retrospectively compare the long-term outcomes following atrial fibrillation (AF) ablation between heart failure (HF) with preserved ejection fraction (EF) (HFpEF) and reduced/mildly reduced EF (HFr-mrEF) patients, and to identify novel predictors of adverse clinical events. METHODS: In total, 1402 AF patients with HF who underwent successful ablation were consecutively enrolled. Adverse clinical events including all-cause death, HF hospitalization, and stroke were followed up. Cox proportional hazards models were used to assess the associations between clinical factors and events. Kaplan-Meier analysis was performed to estimate the cumulative incidences of these events. A receiver operating characteristic curve was used to test the ability of these predictors. RESULTS: During a follow-up period of 42 ± 15 months, 265 (18.9%) patients experienced adverse clinical events after ablation. The cumulative incidence of adverse clinical events was significantly higher in HFr-mrEF than in HFpEF (25.4% vs. 15.7%, P < 0.001), the similar tendency was observed on all-cause death (10.5% vs. 6.5%, P = 0.011) and HF hospitalization (17.2% vs. 10.1%, P < 0.001). After multivariate adjustment, non-paroxysmal AF [hazard ratio (HR) 1.922, 95% confidence interval (CI) 1.130-3.268, P = 0.016], LAD ≥ 45 mm (HR 2.197, 95% CI 1.206-4.003, P < 0.001), LVEF (HR 0.959, 95% CI 0.946-0.981, P < 0.001), and RAD ≥ 45 mm (HR 2.044, 95% CI 1.362-3.238, P < 0.001) remained the independent predictors for developing adverse clinical events. A predictive model performed with non-paroxysmal AF, LAD ≥ 45 mm and RAD ≥ 45 mm yielded an area under curve of 0.728 (95% CI 0.696-0.760, P < 0.001). CONCLUSIONS: AF patients with HFpEF had better long-term outcomes than those with HFr-mrEF, and moderate/severe biatrial dilation could predict adverse clinical events following catheter ablation in AF and HF patients.

Reduction in antimicrobial resistance in a watershed after closure of livestock farms.

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

Combined analysis of the effects of hypoxia and oxidative stress on DNA methylation and the transcriptome in HTR-8/SVneo trophoblast cells.

The alterations in DNA methylation and transcriptome in trophoblast cells under conditions of low oxygen and oxidative stress have major implications for pregnancy-related disorders. However, the exact mechanism is still not fully understood. In this study, we established models of hypoxia (H group) and oxidative stress (HR group) using HTR-8/SVneo trophoblast cells and performed combined analysis of genome-wide DNA methylation changes using reduced representation bisulphite sequencing and transcriptome expression changes using RNA sequencing. Our findings revealed that the H group exhibited a higher number of differentially methylated genes and differentially expressed genes than the HR group. In the H group, only 0.90% of all differentially expressed genes displayed simultaneous changes in DNA methylation and transcriptome expression. After the threshold was expanded, this number increased to 6.29% in the HR group. Notably, both the H group and HR group exhibited concurrent alterations in DNA methylation and transcriptome expression within Axon guidance and MAPK signalling pathway. Among the top 25 differentially methylated KEGG pathways in the promoter region, 11 pathways were commonly enriched in H group and HR group, accounting for 44.00%. Among the top 25 KEGG pathways in transcriptome with significant differences between the H group and HR group, 10 pathways were consistent, accounting for 40.00%. By integrating our previous data on DNA methylation from preeclamptic placental tissues, we identified that the ANKRD37 and PFKFB3 genes may contribute to the pathogenesis of preeclampsia through DNA methylation-mediated transcriptome expression under hypoxic conditions.

TFTG: A comprehensive database for human transcription factors and their targets.

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

ImmunoPET imaging of Trop2 in patients with solid tumours.

Accurately predicting and selecting patients who can benefit from targeted or immunotherapy is crucial for precision therapy. Trophoblast cell surface antigen 2 (Trop2) has been extensively investigated as a pan-cancer biomarker expressed in various tumours and plays a crucial role in tumorigenesis through multiple signalling pathways. Our laboratory successfully developed two 68Ga-labelled nanobody tracers that can rapidly and specifically target Trop2. Of the two tracers, [68Ga]Ga-NOTA-T4, demonstrated excellent pharmacokinetics in preclinical mouse models and a beagle dog. Moreover, [68Ga]Ga-NOTA-T4 immuno-positron emission tomography (immunoPET) allowed noninvasive visualisation of Trop2 heterogeneous and differential expression in preclinical solid tumour models and ten patients with solid tumours. [68Ga]Ga-NOTA-T4 immunoPET could facilitate clinical decision-making through patient stratification and response monitoring during Trop2-targeted therapies.

Cellular Trojan Horse initiates bimetallic Fe-Cu MOF-mediated synergistic cuproptosis and ferroptosis against malignancies.

Disruptions in metal balance can trigger a synergistic interplay of cuproptosis and ferroptosis, offering promising solutions to enduring challenges in oncology. Here, we have engineered a Cellular Trojan Horse, named MetaCell, which uses live neutrophils to stably internalize thermosensitive liposomal bimetallic Fe-Cu MOFs (Lip@Fe-Cu-MOFs). MetaCell can instigate cuproptosis and ferroptosis, thereby enhancing treatment efficacy. Mirroring the characteristics of neutrophils, MetaCell can evade the immune system and not only infiltrate tumors but also respond to inflammation by releasing therapeutic components, thereby surmounting traditional treatment barriers. Notably, Lip@Fe-Cu-MOFs demonstrate notable photothermal effects, inciting a targeted release of Fe-Cu-MOFs within cancer cells and amplifying the synergistic action of cuproptosis and ferroptosis. MetaCell has demonstrated promising treatment outcomes in tumor-bearing mice, effectively eliminating solid tumors and forestalling recurrence, leading to extended survival. This research provides great insights into the complex interplay between copper and iron homeostasis in malignancies, potentially paving the way for innovative approaches in cancer treatment.

Formation and Application of Polymer Spherulite-like Patterns of Halloysite Nanotubes by Evaporation-Induced Self-Assembly.

Halloysite nanotubes (HNTs) are one-dimensional clay nanomaterials featuring distinct tubular structures and unique surface charges. HNTs can readily form ordered assembly structures under specific conditions, which shows significant potential applications in optical and biological fields. In this study, sodium hexametaphosphate (SHMP) was employed as a stabilizer to prepare polymer spherulite-like patterns via the evaporation-induced self-assembly (EISA) technique. The incorporation of SHMP enhanced the repulsion force among the nanotubes and the surface potential, which facilitated the orderly deposition of HNTs. The influence of HNT concentration, SHMP concentration, drying temperature, and substrate on the polymer spherulites-like pattern has been investigated in detail. The optimal conditions were 10 wt % HNT dispersion, 0.6 wt % SHMP concentration, 30 °C as drying temperature, and glass substrates. In addition, by changing the droplet volume and shape of the three-phase contact line, patterns of different sizes and shapes can be achieved. Bovine serum albumin or metal salt compounds were incorporated into the dispersion of SHMP-modified HNTs, which altered the charge and the self-assembled patterns with different area ratios. Thus, this technology can be utilized for the analysis and comparison of protein and metal ion concentration accurately. This study creates the correlation between the structural parameters and the preparation process involved in creating polymer spherulite-like patterns of modified HNTs and offers fresh insights into potential applications for the self-assembly of HNT droplets in the realms of anticounterfeiting and solution concentration analysis.

Development and validation of a nomogram model for accurately predicting severe fatigue in maintenance hemodialysis patients: A multicenter cross-sectional study in China.

INTRODUCTION: This study aims to analyze the risk factors for severe fatigue in maintenance hemodialysis (MHD) patients and develop a clinical prediction model to help doctors and patients prevent severe fatigue. METHODS: Multicentre MHD patients were included in this study. The objective was to investigate the risk factors for severe fatigue in MHD patients and develop a prediction model. RESULTS: A total of 243 MHD patients were included in the study, and the incidence of severe fatigue was found to be 20.99%. Using age, body mass index, total cholesterol, and albumin levels, a predictive nomogram for fatigue was constructed. In the training set, the nomogram had an area under the curve of 0.851, sensitivity of 82.86%, specificity of 81.76%, and c-index of 0.851. The nomogram was accurate in calibration and proved to be clinically useful. CONCLUSION: The nomogram developed in this study is a practical and reliable tool for quickly identifying severe fatigue in MHD patients.

A living neutrophil Biorobot synergistically blocks multifaceted inflammatory pathways in macrophages to effectively neutralize cytokine storm.

Cytokine storm is a potentially life-threatening immune response typically correlated with lung injury, particularly in people with underlying disease states, such as pneumonia. Therefore, the prompt treatment of cytokine storm is essential for successful recovery from a potentially fatal condition. Herein, a living anti-inflammatory Biorobot (firefighter), composed of neutrophils encapsulating mannose-decorated liposomes of the NF-κB inhibitor TPCA-1 and STING inhibitor H-151 (M-Lip@TH, inflammatory retardant), is developed for alleviating hyperinflammatory cytokine storm through targeting multiple inflammatory pathways in macrophages. Biorobot fully inherits the chemotaxis characteristics of neutrophils, and efficiently delivers and releases therapeutic M-Lip@TH at the inflammatory site. Subsequently, M-Lip@TH selectively targets macrophages and simultaneously blocks the transcription factor NF-κB pathway and STING pathway, thereby preventing the overproduction of cytokines. Animal studies show that Biorobot selectively targets LPS-induced acute lung injury, and not only inhibits the NF-κB pathway to suppress the release of various pro-inflammatory cytokines and chemokines, but also blocks the STING pathway to prevent an overactive immune response, which helps to neutralize cytokine storms. Particularly, Biorobot reduces lung inflammation and injury, improves lung function, and increases the survival rates of pneumonia mice. Therefore, Biorobot represents a rational combination therapy against cytokine storm, and may provide insights into the treatment of diseases involving overactive immune responses.

Multiomics analyses of the effects of LED white light on the ripening of apricot fruits.

INTRODUCTION: Apricot (Prunus armeniaca L.) fruits are highly perishable and prone to quality deterioration during storage and transportation. OBJECTIVES: To investigate the effects of LED white light treatment on postharvest ripening of fruits using metabolomics, transcriptomics, and ATAC-Seq analysis. METHODS: Fruits were exposed to 5 µmol m-2 s-1 LED white light for 12 h followed by 12 h of darkness at 20 °C daily for 12 days. The effects of the treatments on the physiological and nutritional quality of the fruits were evaluated. These data were combined with transcriptomic, metabolomic, and ATAC-Seq data from fruits taken on 8 d of treatment to provide insight into the potential mechanism by which LED treatment delays ripening. RESULTS: LED treatment activated pathways involved in ascorbate and aldarate metabolism and flavonoid and phenylpropanoid biosynthesis. Specifically, LED treatment increased the expression of UDP-sugar pyrophosphorylase (USP), L-ascorbate peroxidase (AO), dihydroflavonol 4-reductase (DFR), chalcone synthase (CHS), and caffeoyl-CoA O-methyltransferase (CCOAOMT1), leading to the accumulation of caffeoyl quinic acid, epigallocatechin, and dihydroquercetin and the activation of anthocyanin biosynthesis. LED treatment also affected the expression of genes associated with plant hormone signal transduction, fruit texture and color transformation, and antioxidant activity. The notable genes affected by LED treatment included 1-aminocyclopropane-1-carboxylate synthase (ACS), 1-aminocyclopropane-1-carboxylate oxidase (ACO), hexokinase (HK), lipoxygenase (LOX), malate dehydrogenase (MDH), endoglucanase (CEL), various transcription factors (TCP, MYB, EFR), and peroxidase (POD). ATAC-Seq analysis further revealed that LED treatment primarily regulated phenylpropanoid biosynthesis. CONCLUSION: The results obtained in this study provide insights into the effects of LED light exposure on apricot fruits ripening. LEDs offer a promising approach for extending the shelf life of other fruits and vegetables.

[High-throughput qPCR and Amplicon Sequencing as Complementary Methods for Profiling Antibiotic Resistance Genes in Urban Wetland Parks].

Urban wetland parks are an important practice for urban wetland protection and utilization due to the vast ecosystem service value. As emerging contaminants, antibiotic resistance genes (ARGs) are great attractions for environmental research and public concerns. Based on high-throughput qPCR and high-throughput amplicon sequencing techniques, we investigated the occurrence, abundance, and distribution profiles of antibiotic resistance genes in the aquatic environment of Xiamen urban wetland parks (five sites). The influencing factors and driving mechanisms of antibiotic resistance genes were deciphered on the basis of microbial community structure and water quality. Diverse and abundant ARGs were observed and coexisted in urban wet parks. A total of 217 ARGs were detected in the water body of urban wetland parks, with an abundance up to 6.48×109 copies·L-1. Urban wetland parks were important hotspots and repositories of the antibiotic resistome. A total of nine bacterial genera, including Marivivens, NS5_marine_group, and Planktomarina, were identified as the potential carriers of diverse resistance genes (41 ARGs). The microbial communities could alone explain 51% of alterations in the antibiotic resistome in the aquatic environment of the urban wetland parks. Therefore, the microbial community was the key driving force for the occurrence and evolution of ARGs in urban wetland parks. Based on the results, with the presence of ARGs and antibiotic resistance bacteria, it is suggested that the water environments of urban wetland parks have potential risks of water ecological security and human health, and it is necessary to further enhance the research and control of microbial contaminants in the aquatic environment of urban wetland parks.

Mapping the profiles and underlying driving mechanisms of the antibiotic resistome and microbiome within a subtropical complex river watershed.

Antibiotic resistance is an escalating global concern, leading to millions of annual deaths worldwide. Human activities can impact antibiotic resistance gene (ARG) prevalence in aquatic ecosystems, but the intricate interplay between anthropogenic disturbances and river system resilience, and their respective contributions to the dynamics of different river segments, remains poorly understood. In this study, we investigate the antibiotic resistome and microbiome in water and sediment samples from two distinct sub-watersheds within a specific watershed. Results show a decrease in the number of core ARGs downstream in water, while sediments near densely populated areas exhibit an increase. PCoA ordination reveals clear geographic clustering of resistome and microbiome among samples from strong anthropogenic disturbed areas, reservoir areas, and estuary area. Co-occurrence networks highlight a higher connectivity of mobile genetic elements (MGEs) in disturbed areas compared to reservoir areas, presenting a threat to densely populated areas. Water quality parameters and antibiotics concentration were the key factors shaping the ARG profiles in sediment samples from urban regions. Overall, our study reveals distinct patterns of ARGs in sediment and water samples, emphasizing the importance of considering both anthropogenic and natural factors in comprehending and managing ARG distribution in river systems.