This study evaluated the efficacy of anaerobic membrane bioreactors (AnMBRs) in treating pharmaceutical wastewater containing abundant protein particles, which can adversely affect the performance of UASBs under high organic loading rates (OLRs). Two parallel submerged hollow-fiber AnMBRs were constructed to treat the authentic oxytetracycline production wastewater containing protein particles at 1024 f 67 mg/L under increasing OLR from 1.5 to 13 g COD/L/d. After 207 days of operation, AnMBRs maintained stable performances under an OLR of 10 g COD/L/d. The removal efficiencies for total COD and protein particles were 65.0 % f 1.0 %-69.5 % f 0.7 % and 100 %, respectively. When the OLR increased to 13 g COD/L/d, the total COD removal efficiency decreased to 54.4 % f 1.3 % and volatile fatty acids (mainly acetic acid) surged from 399 f 34 mg/L to 1849 f 37 mg/L. During the experiment, suspended solids were not detected in the effluent, the methane yield ranged 0.322-0.340 L center dot CH4/g center dot CODre, and the transmembrane pressures of the two AnMBRs exhibited slight fluctuations, ranging between -1.24 and -1.03 kPa and between -3.21 and -3.10 kPa, respectively. Meanwhile, protein particles did not accumulate inside the AnMBRs, with 87.6 % f 1.0 % being hydrolyzed and converted to methane. Microbial analysis showed increased abundance of protein-degrading bacteria (DMER64, Christensenellaceae_R-7_group, Proteiniphilum, Fastidiosipila, Fermentimonas) and methanogens (Methanobacterium, Methanosaeta) with higher OLRs. Furthermore, by combining enhanced hydrolysis pretreatment with AnMBR, the relative abundance of antibiotic resistance genes (ARGs) in the digested sludge was just 0.62 f 0.04 copies/ 16S rRNA gene, and ARGs were not detected in effluent under the sampling/concentration and metagenomic protocol used. This research provides a foundation for next-generation pharmaceutical wastewater treatment systems.

This study aims to develop an economical, facile, and efficient approach for the recovery and reuse of Fenton sludge (FS) by proposing an in-situ reutilisation strategy that integrates acid leaching with micron-sized zero-valent iron (mZVI) reduction. Given the high iron content of FS (50.68%), single-factor experiments were performed to investigate the influence of critical parameters in acid leaching (liquid-to-solid ratio, sulfuric acid concentration, and acid leaching time) and mZVI reduction (mZVI/Fe3+ (mol/mol), reaction time, and stirring speed). Furthermore, response surface methodology was applied to optimise the process parameters. The optimisation results showed that the optimal acid leaching conditions were a liquid-to-solid ratio of 2.1, a sulfuric acid concentration of 6.2 mol/L, and an acid leaching time of 32 min, achieving a total iron leaching efficiency of 94.24%. For mZVI reduction, the optimal conditions were an mZVI/Fe3+ of 2.15, a reaction time of 134.4 min, and a stirring speed of 156.7 r/min, resulting in an Fe3+ reduction efficiency of 99.32%. Comparative experiments confirmed that the TOC removal efficiency of the FS-derived reduction solution was comparable to that of commercial FeSO4 in treating aniline-containing wastewater, achieving 44.11% and 44.36%, respectively. Economic analysis showed that the treatment cost using FS decreased from 0.63 $/kg-FS to 0.32 $/kg-FS. This study provides a feasible pathway for energy conservation and emission reduction in the Fenton process by minimising FS generation and enabling its in-situ resource recovery.

The early hydration of cementitious materials can be improved by using concrete slurry waste (CSW) to form biobased CaCO3. The yield of CO32-produced by carbon and nitrogen metabolism was investigated. Compared with septic liquid, glucose and sodium acetate, the highest conversion rate of arginine was 3.98. Arginine maintains a pH of 9, which facilitates the sequestration of CO2 in water. In contrast, the nitrogen metabolism of NaNO3 is weak, and the pH of urea was reduced to 3.9 after nitrification. Compared with other nitrogen utilization, arginine addition is beneficial to the synthesis and secretion of tryptophan-like proteins rather than nitrification. Arginine mainly results in less humification and encourages dissolved organic matter (DOM) degradation, shown by humification index (HIX) dropping by 0.02 and freshness index (FrI) by 0.11. Arginine also decreases Nitrospira populations and reduces nitrite oxidoreductase subunits A and B (NxrAB) abundance by 0.9 parts per thousand, limiting NO2-to NO3-conversion.. In conclusion, the production of bio-based CaCO3 can be regulated by arginine, with field applications depending on the protein content in carbon and nitrogen sources to maintain a pH close to 9 and delay the biological nitrification process.

Efficient separation of ferric flocs is a critical challenge in iron-based homogeneous Fenton treatment due to the poor settleability and shear sensitivity of the generated flocs. In this study, a hydrocyclone-based separation strategy was systematically optimized to provide an intensified alternative to conventional gravity-driven sedimentation. Among the investigated hydrocyclone outlines, a wide-angle design exhibited superior separation performance and was further optimized by integrating single-factor experiments, response surface modeling, and NSGA-II optimization. The optimized hydrocyclone achieved a suspended solids removal efficiency of 96.09% and a concentration factor of 5.62. Mechanistic analysis based on floc morphology revealed that coordinated structural modifications, including elimination of vortex finder insertion, enlargement of the cylindrical diameter, extension of the cylindrical length, and increase of underflow pipe diameter, effectively alleviated shear-induced floc breakage and enhanced separation efficiency. The optimized hydrocyclone demonstrated robust performance within the recommended operating conditions, which are a feed flow rate below 15 L/h, a split ratio of 14%, and a FeSO4 concentration below 7 mM. The effectiveness of the optimized hydrocyclone was successfully validated using real refractory industrial wastewaters without inducing organic matter release. Economic evaluation showed that, compared with typical gravity-driven sedimentation, the optimized hydrocyclone reduced footprint by 50%similar to 88.6%, capital costs by 51.28%similar to 80.65%, and operation costs by 40.99%similar to 83.11%. Overall, this study presents a compact, cost-effective, and environmentally sustainable solution for Fenton ferric floc separation, with strong potential for practical engineering application.

It has been demonstrated that antibiotic resistance genes (ARGs) exhibit seasonal variations in municipal wastewater treatment plants (MWTPs), but their relationship to bacterial phylogeny structure remains unclear. Using advanced metagenomic techniques and machine learning approach, the current study conducted a year-long investigation to explore the relationship between ARGs and the bacterial community of activated sludge in a full-scale MWTP in Beijing, where seasonal dynamics are remarkable. High abundance of ARGs, notably the clinically relevant high-risk ARGs, was observed in winter and spring, the cold season in Beijing. Seasonal patterns were also observed in the diversity of ARGs and the overall bacterial community. Machine learning-based random forest classification models were utilized to identify biomarkers for ARGs and bacterial genera as indicators of seasonal differences. Subsequent analysis of the relationship between ARGs and bacterial biomarkers was examined using random forest regression models. Results showed that the enrichment of potential pathogens such as Mycobacterium, Clostridium and Pseudomonas was high in winter and spring, strongly contributing to the abundance of high-risk ARGs (ermB, aac(6')-I, tetM, blaTEM, and mefA) during cold season. Conversely, functional taxa associated with activated sludge, such as Thauera, displayed seasonal fluctuations and a preference for ARGs with minor clinical implications. Metagenomic binning further illustrated the contribution of Mycobacterium to ARG enrichment in cold season. Our findings highlight the collective impact of human-derived clinically relevant taxa and functional bacterial taxa in activated sludge on the seasonal dynamics of ARGs in MWTPs. Additionally, this study offers valuable insights into the safe disposal of the excess sludge from MWTPs.

Bacteriophages are pivotal in shaping microbial communities, but their structural and functional responses to antibiotic stress in aerobic biofilms remain underexplored. This study aims to fill this void by providing a comprehensive understanding of how viral communities in aerobic biofilms adapt to increasing antibiotic pressures through interactions with their bacterial hosts. Three lab-scale aerobic biofilm systems were established and operated for 577 days, two of those were exposed to increasing influent concentrations of oxytetracycline (OTC) and streptomycin (STM), respectively. The dynamics of the biofilm virome under antibiotic stress was revealed by metagenomic sequencing. Results showed that the virome in aerobic biofilms displayed a high percentage (98.7 %) of unknown bacteriophages, indicating considerable viral diversity. As for the hosts of phages, a total of 1741 bacteriophage contigs were associated with 660 distinct bacterial hosts. In antibiotic-treated systems, broad-host-range generalist bacteriophages accounted for over 17.95 % (STM) and 17.90 % (OTC), compared to 14.32 % in the control. Furthermore, viral community did not carry diverse antibiotic resistance genes, which only accounted for 0.34 % of the resistome. Additionally, it did not regulate the number of resistant bacteria by activating the lytic and lysogenic cycles in this study. This indicated that the contribution of transduction to the horizontal spread of resistant determinants is very limited in the aerobic biofilm. Under antibiotic stress, viral auxiliary metabolic genes compensated for incomplete metabolic pathways in host cells, particularly those related to carbohydrate, amino acid, and cofactor metabolism. These genes likely offer dual benefits to bacterial hosts by repairing antibiotic-induced cellular damage and supporting energy generation, thereby providing adaptive advantages for bacterial survival and proliferation under antibiotic selection pressure. This study uncovers the complex interactions between bacteriophages, their hosts, and environmental pressures. It suggests that viral communities in these environments compensate for functional metabolism rather than promote resistance development under antibiotic stress, providing new insights into the potential roles of bacteriophages in the regulation of microbial-driven processes.

Sanitation of antibiotics production wastewater using a recognized alternative for disinfection is extremely critical for subsequent use and environmental protection as well. In this study, ozonation was used to treat a real oxytetracycline production wastewater. The experiments were conducted in laboratory scale using an ozonation reactor, which was operated in semi-batch mode. Antibiotics were efficiently degraded from 928 +/- 23 to 3.3 +/- 0.2 mu g/L, corresponding to the removal efficiency of 99.6 % at ozone consumption of 250.7 mg/L. Ozone consumptions of 82.6, 166.4, and 250.7 mg/L significantly (p < 0.01) inactivated bacterial growth by 63.9 %, 94.5 %, and 99.99 %, respectively. Further, the absolute abundances of antibiotic resistance genes (ARGs) were significantly (p < 0.01) decreased and some of the tet genes such as tetC, tetQ, and tetX lied below the detection limit after ozonation. The bacterial community showed various responses to ozone consumptions. Pseudomonas was the most dominant genus in all treatments that gradually decreased (34.07 % to 27.35 %) with the increase of ozone consumption. Overall, the results of this study highlighted that ozonation is an efficient process for treatment of oxytetracycline production wastewater in terms of degradation of antibiotics, removal of ARGs, and inactivation of microorganisms.

Resilience to increasing organic loading rates (OLRs) is the key to maintaining stable performance in treating industrial wastewater. First, this study compared the stability, particularly the nitrification performance, of two lab-scale moving bed biofilm reactors (MBBRs) filled with porous polyurethane biocarriers with two conventional activated sludge reactors (ASRs) in the treatment of synthetic coking wastewater under OLRs increasing from 0.3 kg to 1.5 kg COD m-3 day-1. In comparison with the ASRs, which could only achieve complete nitrification (99.31 % f 0.43 %) at an OLR of 0.7 kg COD m-3 day-1, the MBBRs could achieve efficient NH4+-N removal (99.45 % f 0.21 %) at an OLR as high as 1.3 kg COD m-3 day-1. Even at an OLR of 1.5 kg COD m-3 day-1 where nitrification was inhibited, the porous polyurethane biocarriers in the MBBRs still maintained a highly diversified bacterial community (Shannon index, 4.34 f 0.31) by retaining the slow-growing nitrifying bacteria and phenol-degrading bacteria, including Methyloversatilis and Acinetobacter, whose phenol degradation functions were confirmed by metagenome-assembled genome extraction and analysis, while the ASRs lost diversity (Shannon index, 1.41 f 0.45) due to the sequential occurrence of filamentous and viscous sludge bulking. The advantage of the MBBR was further verified in a full-scale coking wastewater treatment system, where a reactor series filled with 4.35 % porous polyurethane biocarriers exhibited better NH4+-N removal of 99.57 % f 0.34 % compared to 96.85 % f 2.56 % for a conventional one under an OLR of 0.54 f 0.12 kg COD m-3 day-1. The results could contribute to the development of more effective and resilient treatment systems for industrial wastewater.

As the discharge standards for wastewater from chemical industrial parks becomes more stringent, the secondary effluent from these facilities necessitates further advanced treatment. This study explores the impact of four key factors-pH, reaction time, H2O2:Fe2+ molar ratio, and reagent dosage-on the treatment performance Synchronized Oxidation-Adsorption (SOA) technology and traditional Fenton technology when treating secondary effluent from chemical industrial parks. The results showed that under the conditions of pH = 5, a reaction time of 30 minutes, an H2O2:Fe2+ molar ratio of 1, and an Fe2+ dosage of 1 mM, the SOA process achieved an organic matter removal efficiency of over 50 %, surpassing that of the traditional Fenton process. BET, LC-OCD-OND, and FTIR analyses revealed that, compared with the traditional Fenton process, the SOA process produced sludge with a larger specific surface area. Moreover, under the conditions of a higher pH (pH = 5) and a lower H2O2: Fe2+ molar ratio (H2O2:Fe2+ = 1:1), the SOA process enhanced the adsorption of hydrophobic organic compounds by Fe hydrolysis products through & sdot;OH oxidation modification of organic matter. When the effluent COD met the discharge standard (with a TOC removal efficiency of 35 %), the SOA process can achieve a 53 % reduction in total treatment costs compared with the traditional Fenton process, highlighting its higher economic benefits in practical engineering applications.

Microbial Source Tracking (MST) uses molecular markers targeting host-associated gut microorganisms to identify fecal pollution. However, MST faces significant challenges in fecal source identification, particularly due to the markers’ poor specificity and shared genomic areas among microorganisms from different host sources. This study addresses these challenges by using host-specific Escherichia coli genetic markers, originally developed through a novel, library-independent approach, to detect sources of fecal pollution. A total of 563 E.coli isolates from chicken, cow, and pig feces were isolated and assessed by nine reported host-associated E. coli genetic markers (Chicken: CH7, CH9, CH12, CH13; Cow: CO2, CO3; Pig: P1, P3, P4) through PCR. Marker possession patterns, sensitivity, specificity, and accuracy were calculated. The NCBI Microbial Genome database was searched for sequences homologous to genome regions of studied genetic markers and evaluated by finding the percentage of host sources and sequence location in the genome. Homology evaluation with binary PCR results was used to predict the best-performing marker. PCR results exhibited that the most effective markers were chicken CH7 (67% sensitivity, 77.9% specificity, 74.4% accuracy) and CH9 (55% sensitivity, 99.4% specificity, 84.7% accuracy). However, a homology search in the database narrowed the selection of the top-performing marker to CH7, which showed homology with E.coli from chicken hosts, while other markers exhibited higher homology with E.coli from Humans. Furthermore, sequences from the database homologous to the CH9 and CO2 markers were found on a plasmid, while those for CH12, CO3, P1, and P4 were on the chromosome, and CH7, CH13, and P3 were on both. This study highlights the critical need for integrated approaches to assess molecular markers in MST assays, emphasizing their significance in advancing research within the field.

This study aims to elucidate the impact of population immunity on the regional evolution of SARS-CoV-2. A total of 3701 wastewater SARS-CoV-2 concentration values and 168 wastewater whole genomes of SARS-CoV-2 were obtained in Beijing over 11 months following the implementation of the "dynamic zero-COVID" policy adjustments in December 2022. The findings indicate that the number of variant strains identified through wastewater surveillance was 2.46 times greater than that detected by clinical monitoring, with single nucleotide polymorphisms showing an increase of up to 7.14 times. This enhanced surveillance facilitates a more comprehensive analysis of regional virus evolution patterns. Following the adjustment of epidemic measure, Beijing experienced three distinct waves of epidemics, and the dominant variant transitioned directly from BA.5 in the first wave to XBB after six months in the second one. During this period, strong population immunity formed by centralized infection in over 90 % of the population blocked the outbreak of internationally prevalent and concerning variants BQ.1 and CH.1.1, resulting in a 12.5 % faster regional evolution of SARS-CoV-2 strains in Beijing compared to the international context. Subsequently, in August 2023, EG.5 became the dominant variant in the third wave, aligning with international trends. The epidemics in Beijing have caused significant positive selection pressure on SARS-CoV-2 strains, favoring those with enhanced antigenic escape mutations in spike gene. These results underscore that the extensive infection after the adjustment of epidemic prevention policies has accelerated the evolution of SARS-CoV-2 in Beijing and been conducive to antigenic escape evolution, which can effectively inform decision making for epidemic control and preemptive vaccine design.

BACKGROUND:Disability Weights (DWs) are crucial for assessing disease burden guiding public health decision-making. For emerging health threats such as COVID-19, the absence of relevant survey data from China has led to reliance on established DW values for specific symptoms in calculating the COVID-19 disease burden. However, these values have not been updated in real-time to reflect the ongoing mutations of the virus, potentially skewing the longitudinal estimation of COVID-19's burden and compromising the accuracy of public health interventions. METHODS:This study developed a real-time estimation framework using longitudinal internet survey data to track changes in DW distributions across different populations over time. These distributions were integrated into Monte Carlo simulations to model real-time disease burden, offering robust data to support evidence-based policy decisions and optimize resource allocation. RESULTS:Our analysis revealed substantial variation in DW distributions across symptoms. As populations experience multiple infections and the virus evolves, the COVID-19 disease burden has converged with, and in some cases fallen below, that of influenza's. Survey data suggested an average immunity interval of approximately five months between infections. Moreover, COVID-19 has profoundly reshaped healthcare-seeking behavior and consumption patterns, with individual lifestyle factors and pre-existing health conditions contributing significantly to infection severity. CONCLUSION:The real-time DW estimation method proposed in this study effectively and accurately reflects the dynamic changes in the COVID-19 disease burden amidst ongoing virus mutations, providing crucial reference data for the evaluation and formulation of public health policies. Furthermore, the study provides insights into the transmission interval of COVID-19 and behavioral changes during the pandemic, offering valuable insights for the potential outbreak of future "Disease X."

Wastewater-based epidemiology (WBE) based on viral surveillance has proven effective in combating COVID-19. More recently, symptom-based drug monitoring has gained traction with the expansion of wastewater monitoring systems worldwide. However, its integration into predictive models to support public health management and its comparative value relative to viral surveillance remain underexplored. Here, we monitored ibuprofen and acetaminophen in wastewater in Beijing, China, during the COVID-19 surge and postpandemic phases. By combining antipyretic concentrations with known human excretion rates, we estimated the number of individuals with fever and incorporated this into the SEIR model (Ip-Is-Ia) that includes asymptomatic infections. Notably, there is a systematic lead of the antipyretic-based incidence compared to the SARS-CoV-2-derived incidence, indicating that the antipyretic signal leads throughout the surge period. In the postpandemic scenario with alternating prevalence of COVID-19 and influenza, the antipyretic levels reflected the population-wide infection dynamics for both diseases. As fever is an important physiological response to infection, discrepancies between antipyretic usage and molecular biosurveillance data may serve as early signals of emerging fever-inducing "Disease X". This study highlights the potential of integrating antipyretic biomarkers into WBE to improve the early detection of outbreaks and support public health preparedness.

During the COVID-19 pandemic, healthcare systems worldwide faced severe strain. This study, utilizing wastewater virus surveillance, identified that periodic spontaneous avoidance behaviours significantly impacted infectious disease transmission during rapid and intense outbreaks. To incorporate these behaviours into disease transmission analysis, we introduced the Su-SEIQR model and validated it using COVID-19 wastewater data from Beijing and Hong Kong. The results demonstrated that the Su-SEIQR model accurately reflected trends in susceptible populations and confirmed cases during the COVID-19 pandemic, highlighting the role of spontaneous collective avoidance behaviours in generating periodic fluctuations. These fluctuations helped reduce infection peaks, thereby alleviating pressure on healthcare systems. However, the effect of these spontaneous behaviours on mitigating healthcare overload was limited. Consequently, we incorporated healthcare capacity constraints into the model, adjusting parameters to further guide population behaviours during the pandemic, aiming to keep the outbreak within manageable limits and reduce strain on healthcare resources. This study provides robust support for the development of environmental and public health policies during pandemics by constructing an innovative transmission model, which effectively prevents healthcare overload. Additionally, this approach can be applied to managing future outbreaks of unknown viruses or "Disease X".

The objective of this study is to quantitatively reveal the main genetic carrier of antibiotic resistance genes (ARGs) for blocking their environmental dissemination. The distribution of ARGs in chromosomes, plasmids, and phages for understanding their respective contributions to the development of antimicrobial resistance in aerobic biofilm consortium under increasing stresses of oxytetracycline, streptomycin, and tigecycline were revealed based on metagenomics analysis. Results showed that the plasmids harbored 49.2 %-83.9 % of resistomes, which was higher ( p < 0.001) than chromosomes (2.0 %-35.6 %), and no ARGs were detected in phage contigs under the strict alignment standard of over 80 % identity used in this study. Plasmids and chromosomes tended to encode different types of ARGs, whose abundances all increased with the hike of antibiotic concentrations, and the variety of ARGs encoded by plasmids (14 types and 64 subtypes) was higher than that (11 types and 27 subtypes) of chromosomes. The dosing of the three antibiotics facilitated the transposition and recombination of ARGs on plasmids, mediated by transposable and integrable transfer elements, which increased the co-occurrence of associated and unassociated ARGs. The results quantitatively proved that plasmids dominate the proliferation of ARGs in aerobic biofilm driven by antibiotic selection, which should be a key target for blocking ARG dissemination. (c) 2025 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

This study tried to reveal how the implementation and cancellation of the dynamic zero-COVID policy could affect the development of the epidemic through wastewater surveillance of SARS-CoV-2 in Beijing during its first COVID-19 surge. A total of 443 24 h composite wastewater samples were taken from seven manholes and 10 wastewater treatment plants immediately on December 7, 2022, when the new COVID-19 policy was implemented, for the detection of SARS-CoV-2. The results showed that the first COVID-19 surge in Beijing was characterized by a rapid outbreak, short duration (one month), and extremely high infection rate (92.8%). Wastewater tiling amplicon sequencing showed that the main subvariant for this surge was BF.7.14 (65%), which has never caused an outbreak in other countries in the world. The variant BF.7.14 appeared in Beijing on August 15, 2022, as an imported case and then managed to retain and become a dominant variant as the strict dynamic zero policy had blocked the entry of other more infectious SARS-CoV-2 variants. This is the first study to capture the unique picture of the epidemic development in Beijing during its first COVID-19 surge, demonstrating that the strict dynamic zero-COVID strategy could shape the infection patterns greatly.

Removal of refractory organics from the biological effluent of coking wastewater has been a challenge. In this study, synchronized oxidation-adsorption (SOA), which developed previously based on the Fenton reaction, was combined with powdered activated carbon (PAC) to remove the refractory chemical oxygen demand (COD) from a real bio-treated coking wastewater. Mesopore volume was found to be the most important factor affecting COD loading, and SOA (Fe2+ dose: 4 mM, H2O2 dose: 2 mM) + mesopore-rich PAC W1 (wood-based) could remove 57.2 %-79.3 % of COD with 100-1000 mg/L of PAC dosage, leading to the reduction of 90 % PAC addition comparing with PAC adsorption alone. Analysis revealed that SOA pretreatment could prevent pore blockage of PAC by removing the high molecular weight organics, including biopolymers and humics. The SOA + mesopore-rich PAC adsorption was applied in a full-scale coking wastewater treatment plant to stably decrease the COD from 222 +/- 38 mg/L to 60 +/- 10 mg/L over six months, and the treatment cost was reduced from over 3.1 US dollar/m(3) to 1.1-1.2 US dollar/m(3). This study demonstrated that SOA + mesopore-rich PAC is a promising approach for the deep removal of refractory COD from coking wastewater.

The start-up and stable operation of partial nitritation-anammox (PN/A) treatment of mature landfill leachate (MLL) still face challenges. This study developed an innovative staged pilot-scale PN/A system to enhance nitrogen removal from MLL. The staged process included a PN unit, an anammox upflow enhanced internal circulation biofilm (UEICB) reactor, and a post-biofilm unit. Rapid start-up of the continuous flow PN process (full-concentration MLL) was achieved within 35 days by controlling dissolved oxygen and leveraging free ammonia and free nitrous acid to selectively suppress nitrite-oxidizing bacteria (NOB). The UEICB was equipped with an annular flow agitator combined with the enhanced internal circulation device of the guide tube, which achieved an efficient enrichment of Candidatus Kuenenia in the biofilm (relative abundance of 33.4 %). The nitrogen removal alliance formed by the salt-tolerant anammox bacterium (Candidatus Kuenenia) and denitrifying bacteria (unclassified SBR1031 and Denitratisoma) achieved efficient nitrogen removal of UEICB (total nitrogen removal percentage: 90.8 %) and at the same time effective treatment of the refractory organic matter (ROM). The dual membrane process of UEICB fixed biofilm combined with post-biofilm is effective in sludge retention, and can stably control the effluent suspended solids (SS) at a level of less than 5 mg/L. The post-biofilm unit ensured that effluent total nitrogen (TN) remained below the 40 mg/L discharge standard (98.5 % removal efficiency). Compared with conventional nitrification-denitrification systems, the staged PN/A process substantially reduced oxygen consumption, sludge production, CO2 emissions and carbon consumption by 22.8 %, 67.1 %, 87.1 % and 87.1 %, respectively. The 195-day stable operation marks the effective implementation of the innovative pilot-scale PN/A process in treating actual MLL. This study provides insights into strategies for rapid start-up, robust NOB suppression, and anammox biomass retention to advance the application of PN/A in high-ammonia low-carbon wastewater.

Phytophthora sojae, one of the most devastating Oomycete pathogens, causes severe diseases that lead to economic loss in the soybean industry. The production of zoospores play a crucial role during the development of Phytophthora disease. In this work, CRISPR/Cas9 genome editing technology were used to obtain protein kinase A regulatory subunit (PsPkaR) knockout mutants. The role of PsPkaR in the production of zoospores and pathogenicity of P. sojae was analyzed. The overall findings indicate that PsPkaR is involved in regulating the growth process of P. sojae, primarily affecting the hyphal morphology and growth rate. Additionally, PsPkaR participates in the regulation of the release process of zoospores. Specifically, knocking-out PsPkaR resulted in incomplete cytoplasmic differentiation and uneven protoplast division, leading to abnormal release of zoospores. Furthermore, when the PsPkaR knockout mutants were inoculated on soybean leaves, the pathogenicity was significantly reduced compared to that of the wild-type and control strains. These findings of this study provide important clues and evidence regarding the role of the cAMP-PKA signaling pathway in the interaction between P. sojae and its host. This work contributes to a better understanding of the pathogenic mechanism of P. sojae and the development of corresponding prevention and control strategies.

Objective To test the ability of the 2015 modified version of the European Network for the Study of Adrenal Tumors staging system (mENSAT) in predicting cancer-specific mortality (CSM), as well as overall mortality (OM) in adrenocortical carcinoma (ACC) patients of all stages, in a large-scale, and contemporary United States cohort.Methods We relied on the Surveillance, Epidemiology, and End Results (SEER) database (2004-2020) to test the accuracy and calibration of the mENSAT and subsequently compared it to the 8th edition of the American Joint Committee on Cancer staging system (AJCC).Results In 858 ACC patients, mENSAT accuracy was 74.7% for 3-year CSM predictions and 73.8% for 3-year OM predictions. The maximum departures from ideal predictions in mENSAT were +17.2% for CSM and +11.8% for OM. Conversely, AJCC accuracy was 74.5% for 3-year CSM predictions and 73.5% for 3-year OM predictions. The maximum departures from ideal predictions in AJCC were -6.7% for CSM and -7.1% for OM.Conclusion The accuracy of mENSAT is virtually the same as that of AJCC in predicting CSM (74.7% vs 74.5%) and OM (73.7% vs 73.5%). However, calibration is lower for mENSAT than for AJCC. In consequence, no obvious benefit appears to be associated with the use of mENSAT relative to AJCC in US ACC patients.