Dual-Emission Single Sensing Element-Assembled Fluorescent Sensor Arrays for the Rapid Discrimination of Multiple Surfactants in Environments.

Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal-organic frameworks (UiO-66-NH2@Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH2@Au NCs were fabricated by integrating UiO-66-NH2 (2-aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dual-emission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH2@Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH2@Au NCs, producing diverse fluorescent "fingerprints", which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.

Measuring HBV pregenomic RNA may be a potential biomarker to determine HBV functional cure in HIV/HBV-co-infected patients with HBsAg loss.

Functional cure of hepatitis B virus (HBV) is an optimal treatment goal for chronic hepatitis B, with the loss of hepatitis B surface antigen (HBsAg) being a crucial indicator. However, the adequacy of HBsAg loss for evaluating functional cure of HBV in patients co-infected with HBV/human immunodeficiency virus (HIV) remains controversial. In this study, we measured HBV pregenomic RNA (pgRNA), a potential biomarker that correlates with covalently closed circular DNA, in the frozen plasma of 98 patients with HBsAg loss from a large HIV/HBV co-infection cohort in Guangzhou, China. HBV pgRNA was still detected in 43.9% (44/98) of the patients, suggesting active HBV replication in individuals with HBsAg loss. Our observations imply that HBsAg loss may not be a reliable predictor of HBV functional cure in cases of HIV/HBV co-infection.

Improved Catalytic Activity of Spherical Nucleic Acid Enzymes by Hybridization Chain Reaction and Its Application for Sensitive Analysis of Aflatoxin B1.

Conventional spherical nucleic acid enzymes (SNAzymes), made with gold nanoparticle (AuNPs) cores and DNA shells, are widely applied in bioanalysis owing to their excellent physicochemical properties. Albeit important, the crowded catalytic units (such as G-quadruplex, G4) on the limited AuNPs surface inevitably influence their catalytic activities. Herin, a hybridization chain reaction (HCR) is employed as a means to expand the quantity and spaces of G4 enzymes for their catalytic ability enhancement. Through systematic investigations, we found that when an incomplete G4 sequence was linked at the sticky ends of the hairpins with split modes (3:1 and 2:2), this would significantly decrease the HCR hybridization capability due to increased steric hindrance. In contrast, the HCR hybridization capability was remarkably enhanced after the complete G4 sequence was directly modified at the non-sticky end of the hairpins, ascribed to the steric hindrance avoided. Accordingly, the improved SNAzymes using HCR were applied for the determination of AFB1 in food samples as a proof-of-concept, which exhibited outstanding performance (detection limit, 0.08 ng/mL). Importantly, our strategy provided a new insight for the catalytic activity improvement in SNAzymes using G4 as a signaling molecule.

Insight into the Sensing Behavior of DNA Probes Based on MOF-Nucleic Acid Interaction for Bioanalysis.

Adsorption of DNA probes onto nanomaterials is a promising strategy for bioassay establishment typically using fluorescence or catalytic activities to generate signals. Albeit important, there is currently a lack of systematic understanding of the sensing behaviors building on nanomaterial-DNA interactions, which greatly limits the rational method design and their subsequent applications. Herein, the issue was investigated by employing multifunctional metal-organic frameworks (MOFs) (FeTCPP⊂UiO-66) as a model that was synthesized via integrating heme-like ligand FeTCPP into commonly used MOFs (UiO-66). Our results demonstrated that the fluorescently labeled DNA adsorbed onto FeTCPP⊂UiO-66 was quenched through photoinduced electron transfer, fluorescence resonance energy transfer, and the internal filtration effect. Among different DNA structures, double-stranded DNA and hybridization chain reaction products largely retained their fluorescence due to desorption and conformational variation, respectively. In addition, ssDNA could maximally inhibit the peroxidase activity of FeTCPP⊂UiO-66, and this inhibition was strongly dependent on the strand length but independent of base composition. On the basis of these discoveries, a fluorescence/colorimetric dual-modal detection was designed against aflatoxin B1 with satisfactory performances obtained to further verify our results. This study provided some new insights into the sensing behaviors based on MOF-DNA interactions, indicating promising applications for rational bioassay design and its performance improvement.

Function and distribution of nitrogen-cycling microbial communities in the Napahai plateau wetland.

Nitrogen is an essential component of living organisms and a major nutrient that limits life on Earth. Until now, freely available nitrogen mainly comes from atmospheric nitrogen, but most organisms rely on bioavailable forms of nitrogen, which depends on the complex network of microorganisms with a wide variety of metabolic functions. Microbial-mediated nitrogen cycling contributes to the biogeochemical cycling of wetlands, but its specific microbial abundance, composition, and distribution need to be studied. Based on the metagenomic data, we described the composition and functional characteristics of microbial nitrogen cycle-related genes in the Napahai plateau wetland. Six nitrogen cycling pathways existed, such as dissimilatory nitrate reduction, denitrification, nitrogen fixation, nitrification, anammox, and nitrate assimilation. Most genes related to the nitrogen cycling in this region come from bacteria, mainly from Proteobacteria and Acidobacteria. Habitat types and nitrogen cycle-related genes largely explained the relative abundance of total nitrogen pathways. Phylogenetic trees were constructed based on nitrogen cycle-related genes from different habitats and sources, combined with PCoA analysis, most of them clustered separately, indicating richness and uniqueness. Some microbial groups seemed to be special or general in the nitrogen cycling. In conclusion, it suggested that microorganisms regulated the N cycling process, and may lead to N loss throughout the wetland, thus providing a basis for further elucidation of the microbial regulation of N cycling processes and the Earth's elemental cycles.

Inhibition of USP10 induces myeloma cell apoptosis by promoting cyclin D3 degradation.

The cell cycle regulator cyclin D3 (CCND3) is highly expressed in multiple myeloma (MM) and it promotes MM cell proliferation. After a certain phase of cell cycle, CCND3 is rapidly degraded, which is essential for the strict control of MM cell cycle progress and proliferation. In the present study, we investigated the molecular mechanisms regulating CCND3 degradation in MM cells. By utilizing affinity purification-coupled tandem mass spectrometry, we identified the deubiquitinase USP10 interacting with CCND3 in human MM OPM2 and KMS11 cell lines. Furthermore, USP10 specifically prevented CCND3 from K48-linked polyubiquitination and proteasomal degradation, therefore enhancing its activity. We demonstrated that the N-terminal domain (aa. 1-205) of USP10 was dispensable for binding to and deubiquitinating CCND3. Although Thr283 was important for CCND3 activity, it was dispensable for CCND3 ubiquitination and stability modulated by USP10. By stabilizing CCND3, USP10 activated the CCND3/CDK4/6 signaling pathway, phosphorylated Rb, and upregulated CDK4, CDK6 and E2F-1 in OPM2 and KMS11 cells. Consistent with these findings, inhibition of USP10 by Spautin-1 resulted in accumulation of CCND3 with K48-linked polyubiquitination and degradation that synergized with Palbociclib, a CDK4/6 inhibitor, to induce MM cell apoptosis. In nude mice bearing myeloma xenografts with OPM2 and KMS11 cells, combined administration of Spautin-l and Palbociclib almost suppressed tumor growth within 30 days. This study thus identifies USP10 as the first deubiquitinase of CCND3 and also finds that targeting the USP10/CCND3/CDK4/6 axis may be a novel modality for the treatment of myeloma.

Revealing viral diversity in the Napahai plateau wetland based on metagenomics.

We focused on exploring the diversity of viruses in the Napahai plateau wetland, a unique ecosystem located in Yunnan, China. While viruses in marine environments have been extensively studied for their influence on microbial metabolism and biogeochemical cycles, little is known about their composition and function in plateau wetlands. Metagenomic analysis was employed to investigate the viral diversity and biogeochemical impacts in the Napahai wetland. It revealed that the Caudoviricetes and Malgrandaviricetes class level was the most abundant viral category based on phylogenetic analysis. Additionally, a gene-sharing network highlighted the presence of numerous unexplored viruses and demonstrated their unique characteristics and significant variation within the viral community of the Napahai wetland. Furthermore, the study identified the auxiliary metabolic genes (AMGs). AMGs provide phages with additional functions, such as protection against host degradation and involvement in metabolic pathways, such as the pentose phosphate pathway and DNA biosynthesis. The viruses in the Napahai wetland were found to influence carbon, nitrogen, sulfur, and amino acid metabolism, indirectly contributing to biogeochemical cycling through these AMGs. Overall, the research sheds light on the diverse and unique viral communities in the Napahai plateau wetland and emphasizes the significant roles of viruses in microbial ecology. The findings contribute to a deeper understanding of the characteristics and ecological functions of viral communities in plateau wetland ecosystems.

Microbial-driven carbon fixation in natural wetland.

With the development of global industrialization, carbon neutrality has become an issue that we must be paid attention to. Microorganisms not only have an important impact on the carbon chemical cycle between the Earth's biosphere and biogeography but also play a key role in maintaining the global organic carbon balance. Wetlands are the main reservoir of organic carbon in the mainland of China, and wetland carbon sinks are indispensable for China to achieve the goal of "dual carbon," and China has taken the consolidation and improvement of wetland carbon sink capacity as an important part of the carbon peaking action plan. As a unique low-latitude, high-altitude seasonal plateau wetland in China, Napahai shows high research value. However, the role of microbes in maintaining dissolved organic carbon balance in this area has not been reported. In the study, six carbon fixation genes, accA, aclB, acsA, acsB, cbbL, and rbcL, were analyzed based on metagenomics to elucidate the rich genetic diversity, uniqueness and differences in the Napahai plateau wetland. It was found that the microbial diversity in the Napahai plateau wetland was different from other habitats. In addition, the aclB gene, a rare taxon with high genetic diversity and rich species in the Napahai plateau wetland, played a key role in the microbial metabolic pathway. Finally, the construction of a metabolic pathway through the Kyoto encyclopedia for genes and genomes revealed the contribution of microbes to carbon fixation and the role of microbes in maintaining the organic carbon balance of the Napahai plateau wetland.

Chemiluminescence microarray immunoassay for multiple aminoglycoside antibiotics based on carbon nanotube-assisted signal amplification.

The simultaneous determination of multiple analytes has been an urgent demand in screening of antibiotic residues in food products of animal origin due to its higher analysis efficiency. Five aminoglycoside antibiotics (AGAs) have been monitored in milk, including gentamicin (GEN), kanamycin (KAN), neomycin (NEO), and streptomycin/dihydrostreptomycin (STR/diSTR). A chemiluminescence microarray immunoassay (CLMIA) based on nitrocellulose membrane had been developed for the detection of multiple AGAs, which the LODs for STR, KAN, NEO, and GEN were 4.74 ng/mL, 4.97 ng/mL, 2.99 ng/mL, and 4.42 ng/mL respectively. To improve the sensitivity of immunoassay, single-well carbon tubes (SWCNTs) were utilized as solid support for loading horseradish peroxidase-labelled goat anti-mouse antibody to obtain the multi-enzyme particles. After the optimization of usage of multi-enzyme particles and antibodies, the enhanced CLMIA was established and evaluated. The LODs were 1.25 ng/mL for STR, 0.64 ng/mL for KAN, 0.38 ng/mL for GEN, and 0.39 ng/mL for NEO, which was improved by threefold, sevenfold, 11-fold, and sevenfold compared with the conventional CLMIA developed. These methods presented higher specificity and repeatability. Finally, the enhanced CLMIA based on CNT-assisted multi-enzyme particles was utilized to analyze twenty-five milk samples from local market and dairy farm, which all the results were below the LOD. The enhanced CLMIA showed the great application potential for the detection of multiple targets simultaneously and provided efficient tool for the screening of pollutants in food.

A Bi-level representation learning model for medical visual question answering.

Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to learn a fine-grained multimodal semantic representation from relatively small volume of data resources for answer prediction. Moreover, the long-tailed distribution labels of medical VQA data frequently result in poor performance of models. To this end, we propose a novel bi-level representation learning model with two reasoning modules to learn bi-level representations for the medical VQA task. One is sentence-level reasoning to learn sentence-level semantic representations from multimodal input. The other is token-level reasoning that employs an attention mechanism to generate a multimodal contextual vector by fusing image features and word embeddings. The contextual vector is used to filter irrelevant semantic representations from sentence-level reasoning to generate a fine-grained multimodal representation. Furthermore, a label-distribution-smooth margin loss is proposed to minimize generalization error bound of long-tailed distribution datasets by modifying margin bound of different labels in training set. Based on standard VQA-Rad dataset and PathVQA dataset, the proposed model achieves 0.7605 and 0.5434 on accuracy, 0.7741 and 0.5288 on F1-score, respectively, outperforming a set of state-of-the-art baseline models.

Comparison of Repeatability and Stability of Residual Magnetic Field for Stress Characterization in Elastic and Plastic Ranges of Silicon Steels.

Deep insights into microstructures and domain wall behaviors in the evaluation of different material statuses under elastic and plastic stress ranges have essential implications for magnetic sensing and nondestructive testing and evaluation (NDT&E). This paper investigates the repeatability and stability of residual magnetic field (RMF) signals using a magneto-optical Kerr effect microscope for the stress characterization of silicon steel sheets beyond their elastic limit. Real-time domain motion is used for RMF characterization, while both the repeatability under plastic ranges after the cyclic stress rounds and stability during relaxation time are studied in detail. The distinction between elastic and plastic materials is discussed in terms of their spatio-temporal properties for further residual stress measurement since both ranges are mixed. During the relaxation time, the RMF of the plastic material shows a two-stage change with apparent recovery, which is contrasted with the one-stage change in the elastic material. Results show that the grain boundary affects the temporal recovery of the RMF. These findings concerning the spatio-temporal properties of different RMFs in plastic and elastic materials can be applied to the design and development of magnetic NDT&E for (residual) stress measurement and material status estimation.

Study on In-Service Inspection of Nuclear Fuel Assembly Failure Using Ultrasonic Plate Wave.

As protection for nuclear power plants is quite necessary, the nuclear fuel is sealed in zirconium alloy thin wall cladding. During service, fuel rods might be damaged caused by wall-thickness thinning, cladding corrosion and cracking, etc. This will cause the coolant to enter into the fuel rod, which may lead to the failure of the fuel assembly. However, current diagnostic methods have limitations due to the special structure of the fuel assembly and the underwater and radioactive environment. In this paper, a novel inspection method is proposed to recognize the failure of a fuel rod. The fuel rod failure can be detected based on the presence or absence of coolant inside the fuel rod by using an ultrasonic plate wave. The inspection model and process algorithm are proposed for in-service inspection. The relationship between signal and scanning position is established and analyzed. Both ultrasound field simulation and experiment have been carried out for validation. The corresponding results illustrate that the failed nuclear fuel rod of the whole fuel assembly (including the internal rods) can be effectively detected without the influence of the near-field region by using the proposed method.

Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning.

BACKGROUND: Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficiency to reduce the cost of clinical research. However, existing methods suffer from poor classification performance due to the complexity and imbalance of eligibility criteria text data. METHODS: An ensemble learning-based model with metric learning is proposed for eligibility criteria classification. The model integrates a set of pre-trained models including Bidirectional Encoder Representations from Transformers (BERT), A Robustly Optimized BERT Pretraining Approach (RoBERTa), XLNet, Pre-training Text Encoders as Discriminators Rather Than Generators (ELECTRA), and Enhanced Representation through Knowledge Integration (ERNIE). Focal Loss is used as a loss function to address the data imbalance problem. Metric learning is employed to train the embedding of each base model for feature distinguish. Soft Voting is applied to achieve final classification of the ensemble model. The dataset is from the standard evaluation task 3 of 5th China Health Information Processing Conference containing 38,341 eligibility criteria text in 44 categories. RESULTS: Our ensemble method had an accuracy of 0.8497, a precision of 0.8229, and a recall of 0.8216 on the dataset. The macro F1-score was 0.8169, outperforming state-of-the-art baseline methods by 0.84% improvement on average. In addition, the performance improvement had a p-value of 2.152e-07 with a standard t-test, indicating that our model achieved a significant improvement. CONCLUSIONS: A model for classifying eligibility criteria text of clinical trials based on multi-model ensemble learning and metric learning was proposed. The experiments demonstrated that the classification performance was improved by our ensemble model significantly. In addition, metric learning was able to improve word embedding representation and the focal loss reduced the impact of data imbalance to model performance.

Time-Response-Histogram-Based Feature of Magnetic Barkhausen Noise for Material Characterization Considering Influences of Grain and Grain Boundary under In Situ Tensile Test.

Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties' inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet's inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress.

Magnetic Barkhausen Noise Transient Analysis for Microstructure Evolution Characterization with Tensile Stress in Elastic and Plastic Status.

Stress affects the microstructure of the material to influence the durability and service life of the components. However, the previous work of stress measurement lacks quantification of the different variations in time and spatial features of micromagnetic properties affected by stress in elastic and plastic ranges, as well as the evolution of microstructure. In this paper, microstructure evolution under stress in elastic and plastic ranges is evaluated by magnetic Barkhausen noise (MBN) transient analysis. Based on a J-A model, the duration and the intensity are the eigenvalues for MBN transient analysis to quantify transient size and number of Barkhausen events under stress. With the observation of domain wall (DW) distribution and microstructure, the correlation between material microstructure and MBN transient eigenvalues is investigated to verify the ability of material status evaluation on the microscopic scale of the method. The results show that the duration and the intensity have different change trends in elastic and plastic ranges. The eigenvalue fusion of the duration and intensity distinguishes the change in microstructure under the stress in elastic and plastic deformation. The appearance of grain boundary (GB) migration and dislocation under the stress in the plastic range makes the duration and the intensity higher on the GB than those inside the grain. Besides, the reproducibility of the proposed method is investigated by evaluating microstructure evolution for silicon steel sheet and Q235 steel sheet. The proposed method investigates the correlation between the microstructure and transient micromagnetic properties, which has the potential for stress evaluation in elastic and plastic ranges for industrial materials.

Pipeline In-Line Inspection Method, Instrumentation and Data Management.

Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline's integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed.

Efficacy of Huoxiang Zhengqi dropping pills and Lianhua Qingwen granules in treatment of COVID-19: A randomized controlled trial.

BACKGROUND: With the global epidemic of coronavirus disease (COVID-19), China has made progress in the prevention and control of the epidemic, and traditional Chinese medicine (TCM) has played a key role in dealing with the disease's effects on the respiratory system. This randomized controlled clinical trial evaluated the clinical efficacy and prognosis of Huoxiang Zhengqi dropping pills and Lianhua Qingwen granules in patients with COVID-19. METHODS: A total of 283 patients participated in this clinical trial, and participants were randomly assigned to receive either 1) Huoxiang Zhengqi dropping pills and Lianhua Qingwen granules or 2) Linahua granules, both combined with western medicine, or 3) western medicine alone for 14 days. At the end of the trial, the improvement and resolution rates of clinical symptoms and the rate of patients who progressed to severe disease status were evaluated. RESULTS: After 14 days of treatment, there was no significant difference in the improvement rate of clinical symptoms among the three groups (P > 0.05). Huoxiang Zhengqi dropping pills combined with Lianhua Qingwen granules has advantages in the treatment of nausea, vomiting and limb soreness. During treatment, all participants were treated with western medicine, and there was a significant difference in the use of macrolides among the three groups (P < 0.05). Specifically, the utilization rate of antibiotics in the western medicine group was significantly greater than that of the other two groups. Among the 182 diagnosed patients who completed this clinical trial, 13 patients progressed to severe disease, including one case in the Huoxiang + Lianhua group (1.6 %), five cases in the Lianhua group (8.6 %), and seven cases in the western medicine group (11.1 %). There was no statistical differences in this rate among the three groups (P > 0.05). However, the proportion of patients who progressed to severe disease in the Huoxiang + Lianhua group was the lowest, suggesting that the combination of TCM with western medicine has a potential advantage in improving the prognosis of patients with COVID-19. CONCLUSION: The use of Huoxiang Zhengqi dropping pills and Lianhua Qingwen granules combined with western medicine may have clinical advantages for COVID-19 patients in improving clinical symptoms, reducing utilization rate of anti-infective drugs, and improving patient prognosis, which could pave the way for the use of complementary medicine in treating this infection.

Chemiluminescence imaging immunoassay for simultaneous determination of TBBPA-DHEE and TBBPA-MHEE in aquatic environments.

The environmental concentration of tetrabromobisphenol A bis(2-hydroxyethyl) ether (TBBPA-DHEE) and tetrabromobisphenol A mono(hydroxyethyl) ether (TBBPA-MHEE), as some of the main derivatives and byproducts of tetrabromobisphenol A (TBBPA), are obscure due to lacking available analytical methods. In the present study, a multiplexed competitive chemiluminescent imaging immunoassay (CLIIA) based on specific monoclonal antibody respectively against TBBPA-MHEE and TBBPA-DHEE has been developed for the simultaneous detection of the two targets. To improve the sensitivity of immunoassay, Au nanoparticles (AuNPs) were utilized as solid support for loading horseradish peroxidase, labeled to obtain the multi-enzyme particles. Under the optimized conditions, the limits of detection (LODs) for TBBPA-MHEE and TBBPA-DHEE were 1.85 ng/mL and 2.05 ng/mL, respectively. After estimating its accuracy and precision, the established method was applied for investigation of the contaminants at the inner rivers in Zhenjiang, Jiangsu Province. Our results indicated that no TBBPA-MHEE was found in all 11 water samples and two samples of TBBPA-DHEE were detected up to 6.34 ng/mL, possibly ascribed to the dense population and slow flow rate around the sampling site. Graphical abstract.

High Rates of Human Fecal Carriage of mcr-1-Positive Multidrug-Resistant Enterobacteriaceae Emerge in China in Association With Successful Plasmid Families.

Background: mcr-1-mediated colistin resistance in Enterobacteriaceae is concerning, as colistin is used in treating multidrug-resistant Enterobacteriaceae infections. We identified trends in human fecal mcr-1-positivity rates and colonization with mcr-1-positive, third-generation cephalosporin-resistant (3GC-R) Enterobacteriaceae in Guangzhou, China, and investigated the genetic contexts of mcr-1 in mcr-1-positive 3GC-R strains. Methods: Fecal samples were collected from in-/out-patients submitting specimens to 3 hospitals (2011-2016). mcr-1 carriage trends were assessed using iterative sequential regression. A subset of mcr-1-positive isolates was sequenced (whole-genome sequencing [WGS], Illumina), and genetic contexts (flanking regions, plasmids) of mcr-1 were characterized. Results: Of 8022 fecal samples collected, 497 (6.2%) were mcr-1 positive, and 182 (2.3%) harbored mcr-1-positive 3GC-R Enterobacteriaceae. We observed marked increases in mcr-1 (0% [April 2011] to 31% [March 2016]) and more recent (since January 2014; 0% [April 2011] to 15% [March 2016]) increases in human colonization with mcr-1-positive 3GC-R Enterobacteriaceae (P < .001). mcr-1-positive 3GC-R isolates were commonly multidrug resistant. WGS of mcr-1-positive 3GC-R isolates (70 Escherichia coli, 3 Klebsiella pneumoniae) demonstrated bacterial strain diversity; mcr-1 in association with common plasmid backbones (IncI, IncHI2/HI2A, IncX4) and sometimes in multiple plasmids; frequent mcr-1 chromosomal integration; and high mobility of the mcr-1-associated insertion sequence ISApl1. Sequence data were consistent with plasmid spread among animal/human reservoirs. Conclusions: The high prevalence of mcr-1 in multidrug-resistant E. coli colonizing humans is a clinical threat; diverse genetic mechanisms (strains/plasmids/insertion sequences) have contributed to the dissemination of mcr-1, and will facilitate its persistence.

Diverse Secondary Metabolites from the Marine-Derived Fungus Dichotomomyces cejpii F31-1.

By adding l-tryptophan and l-phenylalanine to GPY medium, twenty-eight compounds, including amides, polyketides, a sesquiterpenoid, a diterpenoid, a meroterpenoid, diketopiperazines, ß-carbolines, fumiquinazolines, and indole alkaloids, were discovered from the marine-derived fungus Dichotomomyces cejpii F31-1, demonstrating the tremendous biosynthetic potential of this fungal strain. Among these compounds, four amides dichotomocejs A-D (1-4), one polyketide dichocetide A (5), and two diketopiperazines dichocerazines A-B (15 and 16) are new. The structures of these new compounds were determined by interpreting detailed spectroscopic data as well as calculating optical rotation values and ECD spectra. Obviously, Dichotomomyces cejpii can effectively use an amino acid-directed strategy to enhance the production of nitrogen-containing compounds. Dichotomocej A (1) displayed moderate cytotoxicity against the human rhabdomyosarcoma cell line RD with an IC50 value of 39.1 µM, and pityriacitrin (22) showed moderate cytotoxicity against the human colon carcinoma cell line HCT116 with an IC50 value of 35.1 µM.