Cognitive behavioural therapy to improve social skills in children and adolescents with autism spectrum disorder: A meta-analysis of randomised controlled trials.

BACKGROUND: Cognitive behavioural therapy (CBT) is effective in treating various neurological and psychiatric diseases. It improves anxiety symptoms in children with autism spectrum disorder, gaining considerable empirical support. However, social skills results are mixed, leading to debate over its effectiveness, highlighting the need for further development. While the Social Responsiveness Scale (SRS) is a secondary indicator to measure anxiety symptoms, it primarily evaluates social skills, which are essential for rehabilitating children with autism. Therefore, evaluating social disorder improvement in children with autism is imperative. Social impairment is a core autism symptom. Therefore, we conducted a systematic review of randomised controlled trials assessing the effects of CBT on social skills in this population. METHODS: We reviewed articles published in several databases through October 2022 and relevant reference lists. We used the standardised mean difference (SMD) as the main effect size indicator and focused on SRS metrics from baseline to endpoint. We analysed subgroups, heterogeneity, bias risk, and publication bias. RESULTS: Our meta-analysis included 214 children from seven randomised controlled trials with nine datasets. Forest plot analysis shows CBT improved social skills in children with autism compared to controls. Subgroup analysis revealed parents' and teachers' SRS scores for children, SRS scores of CBT versus waitlist controls, and those of CBT versus non-waiting-list controls. LIMITATIONS: Most randomised controlled CBT trials for children with autism have explored anxiety symptom improvement. Further, social skill assessment was a secondary outcome or not assessed. Thus, social skills data are insufficient. CONCLUSIONS: CBT is effective in improving social impairment in children with autism. REGISTRATION: This meta-analysis was registered with the International Prospective Register of Systematic Reviews (CRD42022363423).

The Role of Mass Spectrometry in Hepatocellular Carcinoma Biomarker Discovery.

Hepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.

Identification and cultivation of anaerobic bacterial scavengers of dead cells.

The cycle of life and death and Earth's carbon cycle(s) are intimately linked, yet how bacterial cells, one of the largest pools of biomass on Earth, are recycled back into the carbon cycle remains enigmatic. In particular, no bacteria capable of scavenging dead cells in oxygen-depleted environments have been reported thus far. In this study, we discover the first anaerobes that scavenge dead cells and the two isolated strains use distinct strategies. Based on live-cell imaging, transmission electron microscopy, and hydrolytic enzyme assays, one strain (designated CYCD) relied on cell-to-cell contact and cell invagination for degrading dead food bacteria where as the other strain (MGCD) degraded dead food bacteria via excretion of lytic extracellular enzymes. Both strains could degrade dead cells of differing taxonomy (bacteria and archaea) and differing extents of cell damage, including those without artificially inflicted physical damage. In addition, both depended on symbiotic metabolic interactions for maximizing cell degradation, representing the first cultured syntrophic Bacteroidota. We collectively revealed multiple symbiotic bacterial decomposition routes of dead prokaryotic cells, providing novel insight into the last step of the carbon cycle.

Is the government's direct subsidy to COVID-19 effective?

With the outbreak of COVID-19, governments worldwide have provided direct subsidies to enterprises. This paper aims to identify the motivation behind these subsidies and evaluate their impact. Previous studies have overlooked the discussion of subsidy motivation, and there is still a wide divergence of views among scholars on whether subsidies have a positive effect on firm performance. To test the hypothesis, a fixed effect model is adopted. The study examines 228 Chinese A-share listed companies and confirms that subsidies are primarily attributable to the severity of the pandemic. Moreover, subsidies have a significant positive effect on social performance, particularly for small-scale enterprises. Contrary to the belief that subsidies have a positive effect on firm performance, this study disproves this viewpoint. The research findings provide a theoretical basis for subsidy policy-making during pandemics and outline the boundaries of government intervention in society and the economy.

The origin and evolution of methanogenesis and Archaea are intertwined.

Methanogenesis has been widely accepted as an ancient metabolism, but the precise evolutionary trajectory remains hotly debated. Disparate theories exist regarding its emergence time, ancestral form, and relationship with homologous metabolisms. Here, we report the phylogenies of anabolism-involved proteins responsible for cofactor biosynthesis, providing new evidence for the antiquity of methanogenesis. Revisiting the phylogenies of key catabolism-involved proteins further suggests that the last Archaea common ancestor (LACA) was capable of versatile H2-, CO2-, and methanol-utilizing methanogenesis. Based on phylogenetic analyses of the methyl/alkyl-S-CoM reductase family, we propose that, in contrast to current paradigms, substrate-specific functions emerged through parallel evolution traced back to a nonspecific ancestor, which likely originated from protein-free reactions as predicted from autocatalytic experiments using cofactor F430. After LACA, inheritance/loss/innovation centered around methanogenic lithoautotrophy coincided with ancient lifestyle divergence, which is clearly reflected by genomically predicted physiologies of extant archaea. Thus, methanogenesis is not only a hallmark metabolism of Archaea, but the key to resolve the enigmatic lifestyle that ancestral archaea took and the transition that led to physiologies prominent today.

Regional convergence analysis of sustainable innovation efficiency in European Union countries.

Sustainable innovation strategies have been taken very seriously by the European Union (EU), which aims to reduce energy consumption and environmental pollutants emissions. For the sake of testing the sustainable performance of EU countries empirically, this research evaluates the sustainable innovation efficiency (SIE) of EU countries through a DEA-SBM model and analyzes the convergence trends of the EU regions by convergence analysis. The results show that the EU has attached great importance to sustainable innovation efficiency, indicating that the EU makes a concerted effort in technological innovation, energy saving, and environmental protection. Significant differences exist in SIE among EU regions, even though the southern region has the highest efficiency. In addition, there are distinct convergence trends in regional sustainable innovation efficiency. Control variables have significant impacts on the convergence of SIE in the EU regions. Furthermore, policymakers are also provided with useful decision support for regional sustainable innovation, energy conservation, and emission reduction policies.

Children autism spectrum disorder and gut microbiota: A bibliometric and visual analysis from 2000 to 2023.

Autism spectrum disorder (ASD) has evolved from a narrow and rare childhood-onset disorder to a widely publicized and researched lifelong disease recognized as common and significantly heterogeneous. Researchers have suggested that gastrointestinal symptoms in ASD may be a manifestation of an underlying inflammatory process. However, there is a lack of bibliometric analysis of ASD and gut microbiota in children. Accordingly, this study conducts a bibliometric analysis of ASD and gut microbiota in children from 2000 to 2023, explores the current status and cutting-edge trends in the field of ASD and gut microbiota in children, and identifies new directions for future research. The literature on ASD and gut microbiota in children was screened using the Web of Science Core Collection from 2000 to 2023. Annual publications, countries, institutions, authors, journals, keywords, and references were visualized and analyzed using CiteSpace 5.8. R3 and VOSviewer1.6.18. This study included 1071 publications. Since the beginning of 2011, the overall number of articles shows an upward trend. The most productive country and institution are the United States and the University of California system, respectively. The most frequently cited author is Kang Dae-Wook, with 790 citations, who has contributed significantly to this field. Timothy Dinan is the most prolific author, with 34 articles. The journal with the most published articles on this topic is Nutrients, whereas PLOS One is the most cited journal. The most used keyword is "gut microbiota," and the reference for the highest outbreak intensity is Hsiao. The research hotspots and trends predicted in this study provide a reference for further in-depth research in this field.

Meta-Omics-Supervised Characterization of Respiration Activities Associated with Microbial Immigrants in Anaerobic Sludge Digesters.

Immigration has been recently recognized as an important ecological process that affects the microbial community structure in diverse ecosystems. However, the fate of microbial immigrants in the new environment and their involvement in the local biochemical network remain unclear. In this study, we performed meta-omics-supervised characterization of immigrants' activities in anaerobic sludge digesters. Metagenomic analyses revealed that immigrants from the feed sludge accounted for the majority of populations capable of anaerobic respiration in a digester. Electron acceptors that were predicted to be respired, including nitrate, nitrite, sulfate, and elemental sulfur, were added to digester sludge in batch tests. Consumption of up to 91% of the added electron acceptors was observed within the experiment period. 16S rRNA sequencing detected populations that were stimulated by the electron acceptors, largely overlapping with respiration-capable immigrants identified by metagenomic analysis. Metatranscriptomic analysis of the batch tests provided additional evidence for upregulated expression of respiration genes and concomitant suppressed expression of methanogenesis. Anaerobic respiration activity was further evaluated in full-scale digesters in nine wastewater treatment plants. Although nitrate and sulfate respiration were ubiquitous, the expression level of respiration genes was generally 2-3 orders of magnitude lower than the expression of methanogenesis in most digesters, suggesting marginal ecological roles by immigrants in full-scale digester ecosystems.

Optimized Systematic Review Tool: Application to Candidate Biomarkers for the Diagnosis of Hepatocellular Carcinoma.

This review aims to develop an appropriate review tool for systematically collating metabolites that are dysregulated in disease and applies the method to identify novel diagnostic biomarkers for hepatocellular carcinoma (HCC). Studies that analyzed metabolites in blood or urine samples where HCC was compared with comparison groups (healthy, precirrhotic liver disease, cirrhosis) were eligible. Tumor tissue was included to help differentiate primary and secondary biomarkers. Searches were conducted on Medline and EMBASE. A bespoke "risk of bias" tool for metabolomic studies was developed adjusting for analytic quality. Discriminant metabolites for each sample type were ranked using a weighted score accounting for the direction and extent of change and the risk of bias of the reporting publication. A total of 84 eligible studies were included in the review (54 blood, 9 urine, and 15 tissue), with six studying multiple sample types. High-ranking metabolites, based on their weighted score, comprised energy metabolites, bile acids, acylcarnitines, and lysophosphocholines. This new review tool addresses an unmet need for incorporating quality of study design and analysis to overcome the gaps in standardization of reporting of metabolomic data. Validation studies, standardized study designs, and publications meeting minimal reporting standards are crucial for advancing the field beyond exploratory studies.

Effects of Disease-Related Knowledge on Illness Perception and Psychological Status of Patients With COVID-19 in Hunan, China.

OBJECTIVE: The aim of this study was to assess the current status of disease-related knowledge and to analyze the relationship among the general condition, illness perception, and psychological status of patients with coronavirus disease 2019 (COVID-19). METHODS: A hospital-based cross-sectional study was conducted on 118 patients using convenience sampling. The general questionnaire, disease-related knowledge questionnaire of COVID-19, Illness Perception Questionnaire (IPQ), and Profile of Mood States (POMS) were used to measure the current status of participants. RESULTS: The overall average score of the disease-related knowledge of patients with COVID-19 was (79.19 ± 14.25), the self-care situation was positively correlated with knowledge of prevention and control (r = 0.265; P = 0.004) and total score of disease-related knowledge (r = 0.206; P = 0.025); the degree of anxiety was negatively correlated with the knowledge of diagnosis and treatment (r = -0.182; P = 0.049). The score of disease-related knowledge was negatively correlated with negative cognition (volatility, consequences, emotional statements) and negative emotions (tension, fatigue, depression) (P < 0.05); positively correlated with positive cognition (disease coherence) and positive emotion (self-esteem) (P < 0.05). CONCLUSIONS: It was recommended that we should pay more attention to the elderly and low-income groups, and increase the knowledge about diagnosis and treatment of COVID-19 and self-care in the future health education for patients.

Neuroendocrine Neoplasms: Identification of Novel Metabolic Circuits of Potential Diagnostic Utility.

The incidence of neuroendocrine neoplasms (NEN) is increasing, but established biomarkers have poor diagnostic and prognostic accuracy. Here, we aim to define the systemic metabolic consequences of NEN and to establish the diagnostic utility of proton nuclear magnetic resonance spectroscopy (1H-NMR) for NEN in a prospective cohort of patients through a single-centre, prospective controlled observational study. Urine samples of 34 treatment-naïve NEN patients (median age: 59.3 years, range: 36-85): 18 had pancreatic (Pan) NEN, of which seven were functioning; 16 had small bowel (SB) NEN; 20 age- and sex-matched healthy control individuals were analysed using a 600 MHz Bruker 1H-NMR spectrometer. Orthogonal partial-least-squares-discriminant analysis models were able to discriminate both PanNEN and SBNEN patients from healthy control (Healthy vs. PanNEN: AUC = 0.90, Healthy vs. SBNEN: AUC = 0.90). Secondary metabolites of tryptophan, such as trigonelline and a niacin-related metabolite were also identified to be universally decreased in NEN patients, while upstream metabolites, such as kynurenine, were elevated in SBNEN. Hippurate, a gut-derived metabolite, was reduced in all patients, whereas other gut microbial co-metabolites, trimethylamine-N-oxide, 4-hydroxyphenylacetate and phenylacetylglutamine, were elevated in those with SBNEN. These findings suggest the existence of a new systems-based neuroendocrine circuit, regulated in part by cancer metabolism, neuroendocrine signalling molecules and gut microbial co-metabolism. Metabonomic profiling of NEN has diagnostic potential and could be used for discovering biomarkers for these tumours. These preliminary data require confirmation in a larger cohort.

Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity.

Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.

Metagenomic and Metatranscriptomic Analyses Revealed Uncultured Bacteroidales Populations as the Dominant Proteolytic Amino Acid Degraders in Anaerobic Digesters.

Current understanding of amino acid (AA) degraders in anaerobic digesters is mainly based on cultured species, whereas microorganisms that play important roles in a complex microbial community remain poorly characterized. This study investigated short-term enrichments degrading single AAs using metagenomics and metatranscriptomics. Metagenomic analysis revealed that populations related to cultured AA degraders had an abundance <2.5% of the sequences. In contrast, metagenomic-assembled bins related to uncultured Bacteroidales collectively accounted for >35% of the sequences. Phylogenetic analyses suggested that these Bacteroidales populations represented a yet-to-be characterized family lineage, i.e., Bacteroidetes vadinHA17. The bins possessed the genetic capacity related to protein degradation, including surface adhesion (3-7 genes), secreted peptidase (52-77 genes), and polypeptide-specific transporters (2-5 genes). Furthermore, metatranscriptomics revealed that these Bacteroidales populations expressed the complete metabolic pathways for degrading 16 to 17 types of AAs in enrichments fed with respective substrates. These characteristics were distinct from cultured AA degraders including Acidaminobacter and Peptoclostridium, suggesting the uncultured Bacteroidales were the major protein-hydrolyzing and AA-degrading populations. These uncultured Bacteroidales were further found to be dominant and active in full-scale anaerobic digesters, indicating their important ecological roles in the native habitats. "Candidatus Aminobacteroidaceae" was proposed to represent the previously uncharted family Bacteroidetes vadinHA17.

Catabolism and interactions of uncultured organisms shaped by eco-thermodynamics in methanogenic bioprocesses.

BACKGROUND: Current understanding of the carbon cycle in methanogenic environments involves trophic interactions such as interspecies H2 transfer between organotrophs and methanogens. However, many metabolic processes are thermodynamically sensitive to H2 accumulation and can be inhibited by H2 produced from co-occurring metabolisms. Strategies for driving thermodynamically competing metabolisms in methanogenic environments remain unexplored. RESULTS: To uncover how anaerobes combat this H2 conflict in situ, we employ metagenomics and metatranscriptomics to revisit a model ecosystem that has inspired many foundational discoveries in anaerobic ecology-methanogenic bioreactors. Through analysis of 17 anaerobic digesters, we recovered 1343 high-quality metagenome-assembled genomes and corresponding gene expression profiles for uncultured lineages spanning 66 phyla and reconstructed their metabolic capacities. We discovered that diverse uncultured populations can drive H2-sensitive metabolisms through (i) metabolic coupling with concurrent H2-tolerant catabolism, (ii) forgoing H2 generation in favor of interspecies transfer of formate and electrons (cytochrome- and pili-mediated) to avoid thermodynamic conflict, and (iii) integration of low-concentration O2 metabolism as an ancillary thermodynamics-enhancing electron sink. Archaeal populations support these processes through unique methanogenic metabolisms-highly favorable H2 oxidation driven by methyl-reducing methanogenesis and tripartite uptake of formate, electrons, and acetate. CONCLUSION: Integration of omics and eco-thermodynamics revealed overlooked behavior and interactions of uncultured organisms, including coupling favorable and unfavorable metabolisms, shifting from H2 to formate transfer, respiring low-concentration O2, performing direct interspecies electron transfer, and interacting with high H2-affinity methanogenesis. These findings shed light on how microorganisms overcome a critical obstacle in methanogenic carbon cycles we had hitherto disregarded and provide foundational insight into anaerobic microbial ecology. Video Abstract.

Superior resolution characterisation of microbial diversity in anaerobic digesters using full-length 16S rRNA gene amplicon sequencing.

In the past decade, the characterisation of the microbial community in anaerobic digestion was primarily done by using high-throughput short-read amplicon sequencing. However, the short-read approach has inherent primer bias and low phylogenetic resolution. Our previous study using Illumina MiSeq suggested that the heterogeneity of AD microbiome was operation-driven. To advance our knowledge towards the complexity of the AD microbiome, we performed full-length 16S rRNA gene amplicon sequencing using PacBio Sequel for a more accurate phylogenetic identification. To this end, purified DNA samples from 19 global anaerobic digesters were sequenced. Sixteen methanogenic archaea were identified at the species level. Among them, Methanosarcina horonobensis and Methanosarcina flavescens had significant presence under specific operating conditions. Methanothrix concilii presented in all digesters sequenced. Unexpectedly, over 90% of the Smithella detected were closely related to alkane-degrading Smithella strains D17 and M82, not Smithella propionica. Using LEfSe and network analysis, the interspecies relationship between the fermentative and syntrophic bacteria was addressed. Comparison of the short- and long-read sequencing results were performed and discussed. From sample preparation to data analysis, this work characterised the digester microbiomes in a superior resolution.

Modified Voronoi Analysis of Spontaneous Formation of Interfacial Droplets on Immersed Oil-Solid Substrates.

The nucleation and growth of liquid droplets on solid substrates have received much attention because of the significant relevance of these multiphase processes to both nature and practical applications. There have been extensive studies on the condensation of water from the air phase on solid substrates. Here, we focus on water diffusion through the oil phase and subsequent settlement on solid substrates because such interfacial droplets are formed. Voronoi diagram analysis is proposed to statistically characterize the size distribution of the growing droplets. It is found that modification of the standard Voronoi diagram is required for systems of interfacial droplets which have a noncircular shape and/or whose centers change with time. The modified Voronoi analysis of the growing droplets provides an automatic quantification of the droplet distribution and reveals that (i) during the nucleation stage, the interfacial droplets do not nucleate at the same time because the nucleation of newly formed droplets competes with the growth of the existing ones; (ii) the growth of interfacial droplets comes from water diffusion from the bulk water layer, and/or from adjacent interfacial droplets, and/or from coalescence of interfacial droplets; and (iii) the sizes of interfacial droplets become more polydispersed on P-glass but more monodispersed on OTS-glass as time goes. This work opens a new perspective on the formation of interfacial droplets at the interface between oil and the solid substrate and demonstrates the capability of an automatic analysis method, which can be potentially applied to similar interfacial multiphase systems.

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene that may not truly represent in situ functions. RESULTS: Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs). We found that the AS MAGs have obvious plant-specific features and that few proteins are shared by different WWTPs, especially for WWTPs located in geographically distant areas. Further, we developed a novel machine learning approach that can distinguish between AS MAGs and MAGs from other environments based on the clusters of orthologous groups of proteins with an accuracy of 96%. With the aid of machine learning, we also identified some functional features (e.g., functions related to aerobic metabolism, nutrient sensing/acquisition, and biofilm formation) that are likely vital for AS bacteria to adapt themselves in wastewater treatment bioreactors. CONCLUSIONS: Our work reveals that, although the bacterial species in different municipal WWTPs could be different, they may have similar deterministic functional features that allow them to adapt to the AS systems. Also, we provide valuable genome resources and a novel approach for future investigation and better understanding of the microbiome of AS and other ecosystems. Video Abtract.

Identifying anaerobic amino acids degraders through the comparison of short-term and long-term enrichments.

Degradation of amino acids is an important process in methanogenic environments. Early studies in the 1980s focused on isolated clostridia species to study the degradation behaviours. However, it is now well-recognized that isolated species may not represent those with important roles in situ. This study conducted a continuous enrichment experiment with focus on the comparison of the microbial communities after short-term enrichment (SE) and long-term enrichment (LE). Individual amino acids were used as the substrate, and two different anaerobic digester sludge were used as the inoculum. Based on 16S rRNA and 16S rRNA gene, a clear community shift was observed during a time course of 18 months. The SE communities were dominated by microbial populations such as an uncultured Bacteroidales that was different from known fermenters. In the LE communities, known amino acids fermenters were consistently observed with high abundance, including Peptoclostridium acidaminophilum, Acidaminobacter hydrogenoformans and Propionivibrio pelophilus. The community structures could be classified into four types depending on the diversity of fermenters and syntrophs. A culturability index was developed to compare the SE and LE community and revealed that long-term enrichment tended to select microbial populations closely related to species that has been cultivated whereas larger fractions of the inoculum and SE communities remained uncultured.

Internet use and individuals' environmental quality evaluation: Evidence from China.

Identifying factors that influence the public's environmental quality perception is conducive to environmental protection and risk management. By employing data from the Chinese Social Survey (CGSS) and the ordinary least squares (OLS) method, the present study aims to explore the associations between Internet use and Chinese residents' environmental quality evaluation. The results show that, compared with non-netizens, netizens have a higher negative evaluation of environmental quality, which supports the negativity bias theory, namely, that netizens pay more attention to negative news related to environmental pollution on the Internet. Further study suggests that the impact of Internet use on environmental quality evaluation is heterogeneous across different categories of environmental issues and populations: Internet use has greater effects on risk perception of environmental issues that are closely related to residents' lives. In addition, Internet use has a greater negative impact on environmental quality evaluation for older people and rural residents. Finally, this paper utilizes a substitution variable method, propensity score matching (PSM) and quantile regression to conduct the robustness check.

Bacterial enrichment in highly-selective acetate-fed bioreactors and its application in rapid biofilm formation.

In this study, we systematically investigated the bacterial community dynamics in highly-selective (strong hydraulic selection pressure and high organic loading rate) bioreactors with acetate as the sole carbon source. 16S rRNA gene high-throughput sequencing and metagenomic sequencing results showed that phenolics-degrading bacteria (PDB), which were mainly Acinetobacter species, in the newly-formed aerobic granules could account for >70% of the total bacteria. Near full-length 16S rRNA gene sequences obtained by cloning suggest that the PDB are potentially novel species because they are distantly related to known Acinetobacter species. However, these PDB only temporarily appeared in the early stage of the granule formation and their abundance quickly decreased along the reactor operation. To retain these PDB, we demonstrated that the newly-formed aerobic granules could accelerate biofilm formation in moving bed biofilm reactors (MBBRs), and the biofilm carriers showed gradually-increased phenol degradation performance in the MBBRs. While, the bacterial community in biofilm significantly changed during the operation process of the MBBRs and the community structure became more complicated than that in the aerobic granules. Collectively, this study provides new insights into the microbial ecology of sludge granulation and biofilm formation process in the wastewater treatment systems for remediating phenolic matters.