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Public concerns are increasing regarding the prevalence and transmission of antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs), especially ARG persistence and dissemination in activated sludge (AS). However, the temporal dynamics of ARGs in the AS of WWTPs over a long period of time and their transfer potential after the treatment process upgrade (e.g., total nitrogen reduction from 20 to 15 mg/L in effluent) remain poorly explored. Here, metagenomic sequencing was performed to quantify the ARGs in AS samples from two WWTPs with different treatment processes over a 2-year period. A total of 368 and 426 ARG subtypes affiliated with 20 ARG types were identified separately in the two WWTPs and the similar core ARGs were shared by all 54 samples. There were significant differences in ARG composition in different treatment processes, yet the abundance and diversity of ARGs in the AS samples demonstrated no distinct seasonal patterns. Notably, after the treatment process upgrade, the relative abundance of sulfonamide, beta-lactam, and aminoglycoside resistance genes was reduced by more than 10%, and the transfer potential of ARGs in bacterial pathogens decreased greatly, which suggested that an upgrade could limit the prevalence and transmission of ARGs. Variation partitioning analysis showed that metal resistance genes rather than bacterial community represented the significantly influential factor in shaping ARGs, and some key genera correlated with ARGs were identified through network analysis. These results will deepen our understanding of the dynamic changes in ARG profiles in AS systems and guide wastewater treatment plant upgrades. KEY POINTS: • The potential transfer of ARGs decreased after the treatment process upgrade • Metal resistance genes were the most influential factor in shaping ARG composition • Co-occurrence networks displayed potential hosts of beta-lactam resistance genes.

In this paper, we propose a two-level adaptive resource allocation (TARA) framework to support vehicular safety message transmissions. In particular, three types of safety messages are considered in urban vehicular networks, i.e., event-triggered messages for urgent condition warnings, periodic messages for vehicular status notifications, and messages for environmental perception. Roadside units are deployed for network management, and thus messages can be transmitted through either vehicle-to-infrastructure or vehicle-to-vehicle connections. To satisfy the requirements of different message transmissions, TARA framework consists of a group-level resource reservation module and a vehicle-level resource allocation module. Particularly, the resource reservation module is designed to allocate resources to support different types of message transmissions for each vehicle group at the first level. To learn the implicit relationship between the resource demand and message transmission requests, a supervised learning model is devised in the resource reservation module, where to obtain the training data we further propose a sequential resource allocation (SRA) scheme. Based on historical network information, SRA scheme offline optimizes the allocation of sensing resources, i.e., choosing vehicles to provide perception data, and communication resources. With resources reserved for each group, the vehicle-level resource allocation module is then devised to distribute specific resources for each vehicle to satisfy the differential requirements in real-time. Extensive simulation results demonstrate the effectiveness of TARA framework in terms of the high packet delivery ratio and low latency for message transmissions, and the high quality of collective environmental perception.

Exploring efficient and economical electrocatalysts and understanding the mechanism for alkaline hydrogen oxidation reaction (HOR) are crucial to facilitate the development of alkaline polymer elec...

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts. However, the hydrogen oxidation reaction (HOR) kinetics is significantly slower in alkaline media than in acidic media. Understanding these phenomena requires applying theoretical and experimental methods to unravel molecular-level thermodynamics and kinetics of hydrogen and oxygen electrocatalysis and, particularly, the proton-coupled electron transfer (PCET) process that takes place in a proton-deficient alkaline media. Extensive electrochemical and spectroscopic studies, on single-crystal Pt and metal oxides, have contributed to the development of activity descriptors, as well as the identification of the nature of active sites, and the rate-determining steps of the HOR and ORR. Among these, the structure and reactivity of interfacial water serve as key potential and pH-dependent kinetic factors that are helping elucidate the origins of the HOR and ORR activity differences in acids and bases. Additionally, deliberately modulating and controlling catalyst–support interactions have provided valuable insights for enhancing catalyst accessibility and durability during operation. The design and synthesis of highly conductive and durable alkaline membranes/ionomers have enabled AEMFCs to reach initial performance metrics equal to or higher than those of PEMFCs. We emphasize the importance of using membrane electrode assemblies (MEAs) to integrate the often separately pursued/optimized electrocatalyst/support and membranes/ionomer components. Operando/in situ methods, at multiscales, and ab initio simulations provide a mechanistic understanding of electron, ion, and mass transport at catalyst/ionomer/membrane interfaces and the necessary guidance to achieve fuel cell operation in air over thousands of hours. We hope that this Review will serve as a roadmap for advancing the scientific understanding of the fundamental factors governing electrochemical energy conversion in alkaline media with the ultimate goal of achieving ultralow Pt or precious-metal-free high-performance and durable alkaline fuel cells and related technologies. This work was supported by the Center for Alkaline-Based Energy Solutions, an Energy Frontier Research Center program supported by the U.S. Department of Energy, under Grant DE-SC0019445. This work acknowledges the long-term support of TEM facilities at the Cornell Center for Materials Research (CCMR) which are supported through the National Science Foundation Materials Research Science and Engineering Center (NSF MRSEC) program (DMR1719875), and Cornell high-energy synchrotron sources (CHESS), which is supported by the National Science Foundation under Award DMR-1332208.

Plastisphere (the biofilm on microplastics) in wastewater treatment plants (WWTPs) may enrich pathogens and antibiotic resistance genes (ARGs) which can cause risks to the ecological environment by discharging into receiving waters. However, the microbiome and resistome of plastisphere in activated sludge (AS) systems remain inconclusive. Here, metagenome was applied to investigate the microbial composition, functions and ARGs of the Polyvinyl chloride (PVC) plastisphere in lab-scale reactors, and revealed the effects of tetracycline (TC) and/or Cu(II) pressures on them. The results indicated that the plastisphere provided a new niche for microbiota showing unique functions distinct from the AS. Particularly, various potentially pathogenic bacteria tended to enrich in PVC plastisphere. Moreover, various ARGs were detected in plastisphere and AS, but the plastisphere had more potential ARGs hosts and a stronger correlation with ARGs. The ARGs abundances increased after exposure to TC and/or Cu(II) pressures, especially tetracycline resistance genes (TRGs), and the results further showed that TRGs with different resistance mechanisms were separately enriched in plastisphere and AS. Furthermore, the exogenous pressures from Cu(II) or/and TC also enhanced the association of potential pathogens with TRGs in PVC plastisphere. The findings contribute to assessing the potential risks of spreading pathogens and ARGs through microplastics in WWTPs.

Hydrogen fuel cells operated in alkaline media enable the use of abundant nonprecious 3d metal oxides to replace Pt to catalyze the sluggish oxygen reduction reaction (ORR). Herein, we describe Co–...

Pulmonary fibrosis (PF) is a progressive respiratory disease. Phycocyanin derived eicosapeptide (PP20) is a novel peptide derived from active protein C-phycocyanin in Cyanobacteria. The aim of our study was to explore the anti-fibrotic activity of the PP20 and its underlying mechanism. Characteristic features of pulmonary fibrosis in oleic acid (OA)-induced mice and epithelial-mesenchymal transition (EMT) in TGF-β1-exposed A549 and HFL-1 cells with or without PP20 and the change of TGF-β/Smad and MAPK signaling pathways were examined. Smad and MAPK agonists were used to explore the role of TGF-β/Smad and MAPK signaling in TGF-β1- induced collagen I expression in A549 cells and α-SMA expression in HFL-1 cells when treated with PP20. Our results showed that PP20 significantly alleviated the inflammatory response and tissue destruction, inhibited EMT, restored the imbalance of TIMP-1/MMP-9 and reduced collagen fiber deposition. Moreover, PP20 inhibited TGF-β1-induced EMT and collagen I expression in A549 cells. PP20 could also inhibit the proliferation, and decrease TGF-β1-induced the expression of collagen I and transformation of fibroblasts into myofibroblasts in HFL-1 cells. Additionally, animal experiments and cell experiments combined with pathway agonists have shown that PP20 can negatively regulate TGF-β/Smad and MAPK pathways and show anti-fibrotic properties. PP20 may be a promising drug candidate for protection against pulmonary fibrosis.

Objective Active antibody-mediated rejection (aABMR), particularly late aABMR, remains a major challenge for long-term renal allograft survival. This single-center retrospective study aimed to compare clinical features between early vs late aABMR and to identify risk factors for allograft failure among patients with aABMR. Method Forty-one patients diagnosed with aABMR at our hospital were included and were divided into 2 groups: early aABMR (≤6 months; n = 10) vs late aABMR (>6 months; n = 31) based on the time from transplant to diagnosis. Their clinical and pathologic data were compared. This study was performed in compliance with the Helsinki Congress and the Declaration of Istanbul. Results Of 10 patients with early aABMR, none had allograft failure, whereas 8 of 31 patients with late aABMR had developed allograft failure at the time of follow-up (25.8%). At the time of biopsy, patients with early aABMR had higher positive grade in urine occult blood test than patients with late aABMR (P = .01); however, the late aABMR group displayed more intensive interstitial fibrosis and tubular atrophy (P = .03) and more frequent HLA-DQ-type donor-specific antibodies. Interestingly, donor-specific antibody conversion from positive to negative was not associated with C4d grade but was correlated with time from transplant to biopsy. Multivariate Cox regression analysis indicated that high levels of serum creatinine or proteinuria and concomitant T-cell-mediated rejection were independent risk factors for allograft failure in patients with aABMR. Conclusion These data not only confirm that early aABMR has better clinical outcomes than late aABMR but highlight the importance of early diagnostic biopsy and early therapeutic interventions in ABMR, particularly in patients with high levels of serum creatinine or proteinuria in the early posttransplant phase.

Aim: The purpose of this study was to predict and analyze the structure and function of 2019-novel Coronavirus (nCoV) key proteins. Materials & methods: We obtained the structure and sequence of proteins from related databases and studied them through multiple sequence alignment, homology modeling, sequence analysis, virtual screening, reverse mutation, protein structure overlap and surface property analysis. Results & conclusion: We found no significant changes in envelope protein, membrane protein, nucleocapsid protein and key proteases in open reading frame 1ab, and predicted results of proteins and performed molecular dynamics simulations. Based on the surface properties of spike protein and docking results with angiotensin-converting enzyme 2, we believe that the binding ability of spike protein to angiotensin-converting enzyme 2 may be similar to SARS. These studies will help us in fighting 2019-nCoV.