Escherichia coli (E. coli) proliferation caused by H9N2 AIV, as well as to determine the regulatory effect of AL. It was found that H9N2 AIV infection led E. coli to become the dominant gut microbe and promoted E. coli translocation from the intestinal tract to the visceral tissue through the damaged intestinal barrier. H9N2 AIV infection induces inflammation in the intestinal mucosa and promotes the secretion and release of nitrate from the host intestinal epithelium. In addition, nitrate promoted E. coli proliferation in the inflamed intestinal tract following H9N2 AIV infection. Furthermore, Chinese herbal medicine AL can restore intestinal homeostasis, inhibit the production of nitrate in the intestinal epithelium and effectively prevent the proliferation and translocation of E. coli in the intestines. This is the first report on the mechanism of E. coli secondary infection induced by H9N2 AIV, where herbal medicine AL was shown to have a good preventive effect on the secondary infection.H9N2 avian influenza virus (AIV) infection in chickens is often accompanied by secondary bacterial infection, but the mechanism is unclear. The aim of the present study was to reveal that mechanism and explore non-antibiotic treatment. 16s rRNA sequencing and metabonomics were performed in the intestinal contents of chickens infected with H9N2 AIV or H9N2 AIV and fed with ageratum-liquid (AL) to reveal the metabolite that promote intestinal  Avian influenza virus (AIV) belongs to the influenza virus A genus of the Orthomyxoviridae family . The genEscherichia coli (E. coli) infection, which is associated with high mortality in poultry -α levels in enteric homogenates to improve the diarrhea caused by Salmonella typhimurium in mice . The experiments were performed in accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health.6TCID50/0.1 mL, and AL was administered at the same time as the viral infection, at a dose of 2.5 mL/kg/day for 3 days, and then put into a negative pressure isolator for routine feeding. At the same time of viral infection, 0.1 mL phosphate buffer saline (PBS) was dripped into nasal cavity of chickens in mock group and AL group.One-day-old specific pathogen free (SPF) chickens and SPF chicken embryos were purchased from the SPF Experimental Animal Center of Guangdong Dahuanong Co., Ltd. The H9N2 SH01 strain was isolated and preserved in our laboratory. A total of 32 9-day-old healthy SPF chickens with a uniform body weight were selected and divided into four groups: The mock, H9N2 AIV infection (H9N2), AL feeding (AL), and H9N2 AIV infection with feeding AL (H9N2-AL) groups. H9N2 AIV infection was carried out by nasal drip and the infection dose of the H9N2 virus was 3-fold 10The cloacal swab was frozen and thawed repeatedly 3 times, and the virus RNA in the sample was extracted, according to the instructions of the AxyPrep humoral virus DNA/RNA small extraction kit . A pair of identification primers were designed according to the HA gene of the H9N2 virus; the upstream sequence was 5′-CAAGATGGAAGTAGTATCACT-3′ and the downstream sequence was 5′-TTGCCAATTATATACAAATGT-3′. The extracted RNA was used as a template for the preparation of a one-step reverse transcription system and detected by RT-qPCR, as previous reported .The tissue samples (lung and ileum) of the same quality were collected, and the total RNA in the tissue was extracted by TRIzol  reagent method, according to the manufacturer’s instructions. The total RNA of the obtained tissue sample was reverse transcribed into cDNA, according to the instructions of the genome removal reverse transcription kit . Detection of the viral copy number in each tissue was assessed by quantitative RT-PCR (RT-qPCR). The primers used for constructing standard curves were as follows: 5′-ACTCGATGAGCATGACGCAA-3′ and 5’-GGTCCCGTTCCGAATTGTCT-3’. RT-qPCR quantification of the viral load of each organ was conducted using standard curves, as previously described .The DNA of the ileum contents was extracted using a genomic DNA extraction kit. The V3 and V4 regions of bacterial 16S rDNA were amplified by RT-qPCR. The primers used were as follows: 5′-CCTACGGRRBGCASCAGKVRVGAAT-3′ and 5′-GGACTACNVGGGTWTCTAATCC-3′; a connector with Index was simultaneously added to the end of the fragment, and then a sequencing library was constructed. After the library was qualified, 2 × 300 bp double-terminal sequencing was carried out according to the instructions of the Illumina MiSeq instrument. The forward and backward reads obtained by sequencing were spliced, the splicing sequences containing N were filtered out and the sequences of > 200 bp were retained. The retained sequences were qualitatively filtered and the chimeric sequences deleted; the sequence operational taxonomic unit (OTU) cluster analysis was then performed using VSEARCH . The representative sequence of OTU was then annotated and analyzed by RDP classifier Bayesian algorithm, and the species composition of each sample was calculated. Based on the results of OTU, the subsequent diversity difference analysis was carried out. Mothur (v.1.30) software was used for A index analysis . Princip2O; the primers of detecting the gene expression in ileal tissue were listed in CT–ΔΔ method , including 10 μL of 2 x SYBR Green qPCR Master Mix, 1 μL forward primer and 1 μL reversed primer, 1 μL RNA and 7 μL ddHT method .E. coli Nissle1917 (EcN) strain, E. coli NeonGreen strain , pSC101-BAD-gbaA-amp plasmid , pSC101-BAD-cre-tet plasmid  and pR6K-lox71-cm-lox66 plasmid were all donated by Professor Zhang Youming .The The aseptic isolated liver, lung and mesentery were homogenized. Homogenate (100 μL) was mixed on a Luria broth (LB) plate, and the bacterial solution was coated and cultured in a 37°C incubator for 12 h. When the bacterial growth was observed on the plate, the colony growth was judged to be positive, while the non-colony growth was judged to be negative.6 TCID50/0.1 mL, and AL was fed to the chickens at the same time as the viral infection at a dose of 2.5 mL/kg/day, which lasted 3 days. On day 3 after viral infection, all chickens were fed NeonGreen bacteria at a dose of 300 mL 1 × 109 CFU/mL per chicken, which was routinely raised in a negative pressure isolator.A total of 36 9-day-old healthy SPF chickens with a uniform body weight were purchased and divided into three groups: The mock, H9N2 AIV infection (H9N2) and H9N2 AIV infection with feeding AL (H9N2-AL) groups. At the age of 9 days, the infection dose of the H9N2 virus was 3-fold 10Samples were taken at 12, 24, 36 and 48 h after the administration of NeonGreen bacteria. The mixture containing ileum, liver, lung and mesentery inner wall and lumen tissues was aseptically collected and homogenized in a sterile homogenate tube filled with 1 mL saline. Homogenate mixture (100 μL) was applied to the LB&Amp plate, and the bacterial solution was coated in a 37°C incubator for 12 h. When the bacterial growth on the plate was observed, the colony growth was judged to be positive, while the non-colony growth was judged to be negative.E. coli bacteria. The total volume of DNA extracted was derived from enteric contents, mesentery, lung and liver. The DNA was adjusted to the same concentrations. DNA standards were prepared from E. coli strains carrying plasmids with E. coli fragment inserts, which was isolated from a poultry farm (GenBank No. MG602206). The abundance of the gene was evaluated by multiplying the number of copies per well by the total volume of DNA per well. The total reaction volume of 20 μL contained 1.0 μL DNA, 10.0 μL SYBR Green qPCR Mix , 0.5 μL of each primer and 8 μL H2O. Samples were amplified by the following conditions: Initial denaturation at 94°C for 2 min, 40 cycles of heat denaturation at 94°C for 10 s, primer annealing at 60°C for 40 s. Fluorescence signal acquisition was set at 60°C. The primers for E. coli amplification were as follows: 5′-GTTAATACCTTTGCTCATTGA-3′ and 5′-ACCAGGGTATCTTAATCCTGTT-3′.RT-qPCR was performed for the count of NeonGreen The collected ileum contents were sent to Shanghai Matt painting Biotechnology Co., Ltd., for non-targeted metabonomics. Gas chromatography time-of-flight mass spectrometry based on silanization derivation was used as the analytical chromatographic mass. A metabolite database, JIALIB, was established through the identification of high-purity chemical standards of metabolites. The statistical analysis of the data was performed based on conventional multivariate statistical methods, such as PCA, Partial Least Square Discriminant Analysis (PLS-DA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA). The metabolic pathway enrichment analysis used a specific hypergeometric algorithm to enrich the information of metabolites, weigh their contribution and identify key metabolic networks.In order to screen and count the strains in the later stage, the resistant high-copy plasmid was transformed into the target strain to carry the corresponding resistance function. In the present study, the pMD-19T (Control Insert) plasmid was electrotransformed to make EcN carry Amp resistance. The specific transfer steps of EcN were conducted as previously described .napA, narZ and narG in the nitrate metabolism were deleted  was added to the culture system in the treatment group, repeated 3 times in each treatment group, sealed in an anaerobic incubator and transferred to a 37°C incubator for culture. After 24 h, the number of EcN:Amp and EcN ΔmoaA strains in each culture bottle was counted. The viable bacterial count of 3 mutant strains  was determined, the bacterial liquid was diluted 10 times, the sample homogenate with suitable 3-5 continuous dilutions was selected, and the 1 mL was poured into the plate containing antibiotics ampicillin and chloramphenicol; 2 plates were made for each dilution, and the dilution was compared at the same time. Following incubation at 37°C for 18–24 h, the plate colony count was determined, and the plate record of colony numbers between 15–150 CFU was selected. Finally, the competitive index (CI) of EcN:Amp and EcN strain ΔmoaA with or without nitrate treatment was calculated. The competitive culture of EcN:Amp and EcN ΔAZG was carried out according to the above steps, and the CI of EcN:Amp and EcN strain ΔAZG was calculated with or without nitrate treatment.EcN:Amp and EcN strain ΔS-methyl-isothiourea (SMT) after H9N2 AIV infection, and feeding AL after H9N2 AIV infection groups. At the age of 9 days, the infection dose of the H9N2 virus was 3-fold 106 TCID50/0.1 mL, and the mixed bacterial solution of EcN:Amp and EcN ΔmoaA was administered at the same time as the viral infection at a dose of 100 μL/per chicken, 1 × 1010 CFU/mL; SMT and AL were fed to them on day 1 after viral infection. The dose of SMT was 10 mg/per/d and that of AL 2.5 mL/kg, lasting for 3 days, and put into the negative pressure isolator for routine feeding. The above animal experiments were repeated with EcN:Amp and EcN strain ΔAZG.A total of 16 9-day-old healthy SPF chickens with uniform body weight were divided into four groups: The mock, H9N2 AIV infection, feeding On day 5 after viral infection, the ileum tissue near the ileocecal junction was cut and sampled. Following rinsing with phosphate-buffered saline (PBS), the intestinal tissue was lysed using cell and tissue lysate reagent, and the nitrate content in the intestinal tissue was detected, according to the instructions of the total nitric oxide detection kit. In addition, the contents at the junction of the blind were collected in the aseptic environment and, following weighing, each sample was diluted with PBS, according to a fixed mass-volume ratio. The sample was then used as the original solution. Next, the number of bacteria was identified and the competition index was calculated.P < 0.01, P < 0.01 and P < 0.05, Cloacal swabs were collected on day 3 after viral infection for the RT-PCR detection of the HA gene of H9N2 AIV. Results showed that the cloacal swabs collected from SPF chickens infected with the virus can be amplified into HA fragments of H9N2 AIV, indicating that SPF chickens were infected successfully in this experiment . Lung anP > 0.05), indicating that H9N2 AIV infection did not cause the change of intestinal community species richness. The species richness of the AL group increased significantly compared with the mock group (P < 0.05), and that of the H9N2-AL group increased significantly compared to the H9N2 AIV infection group, indicating that AL could increase the intestinal community species richness (P < 0.01), indicating that H9N2 AIV infection can destroy intestinal flora diversity, while AL can restore it. OTU analysis-based dilution and grade abundance curves in different groups were shown in α diversity reflects the species richness and diversity of a single sample . The Charichness . Shannonrichness . As showβ diversity analysis, which included PCA, PCoA, NMDS and UPGMA analysis, showed that the samples of the same treatment group were concentrated in one area, while the sample distances of different groups were concentrated in different areas, with marked differences between the mock and H9N2 AIV infection groups at the 5 day time point, which indicated that the similarity of samples between the mock and H9N2 AIV infection groups was low. By contrast, the sample distance between the single feeding AL and H9N2 AIV infection with feeding AL groups were close to each other, indicating a high species similarity between the two groups . AccordiAccording to the sequencing results, sequences with a similarity of > 97% were defined as an OTU, with each OTU corresponding to a representative sequence. As shown in Firmicutes, with an average relative abundance of 96%. Secondly, the relative abundance of Proteobacteria reached 3%. Following infection with H9N2 AIV, the relative abundance of Proteobacteria became the dominant flora, with an average relative abundance of 85%, while that of Firmicutes decreased to 14%, indicating that H9N2 AIV could cause intestinal flora disorder and lead to the proliferation of Proteobacteria. In the AL group, the average relative abundance of the phylum Firmicutes accounted for 89%, followed by Actinobacteria, with an average relative abundance of 8%. In the H9N2-AL group, the phylum Firmicutes returned to the dominant flora, with an average relative abundance of 89%, followed by Actinobacteria with an average of 8%, and Proteobacteria with an average of 2%. The above results suggested that H9N2 AIV can induce intestinal flora disorder and cause a high proliferation of Proteobacteria, while AL can improve the intestinal microecological environment, inhibit the proliferation of Proteobacteria and promote the proliferation of Firmicutes and Actinobacteria into the dominant flora.By comparing the OTU sequences with the reference database, the composition of the flora at each classification level was obtained. As shown in Bacilli, Lactobacillaceae and Lactobacillus, respectively. The second dominant flora was Gammaproteobacteria, Enterobacteriaceae and Escherichia. The average relative abundance of Lactobacillus and Escherichia in the mock group was 90 and 2.5%, respectively , Veillonellaceae, Phaseolus acutifolius (tepary bean), Megamonas and Faecalibacterium. The biomarkers used for the H9N2-AL group were Bifidobacteriaceae, Bifidobacteriales, Aeriscardovia and Enterobacter on day 5 post infection. According to the biological classification of bacteria and LDA score, the biomarker for each treatment group was further screened. Lactobacillus, Escherichia, Candidatus-Arthromitus and Aeriscardovia were the biomarkers used for the mock, H9, AL and H9N2-AL groups, respectively.In order to further screen the biomarker in the changes of intestinal flora caused by different treatments, LefSe analysis was performed. With a linear discriminant analysis (LDA) score of > 4.0 as the threshold, the species were screened from the phylum to the genus level. As shown in Lactobacillus, Escherichia and Aeriscardovia. In combination, H9N2 AIV infection caused intestinal flora disorder, and the possible bacterial biomarkers for the mock and infection groups were Lactobacillus and Escherichia, respectively. After feeding the infection group with AL, the biomarker was Aeriscardovia.In order to more intuitively judge the changes in the microflora caused by different treatments, an evolutionary branching tree was made, and the circles radiated from inside to outside, representing the taxonomic level from the phylum to the genus, respectively. As shown in ZO-1, and transmembrane proteins Claudin 3 and Occludin was measured. As shown in ZO-1 and Occludin was significantly decreased , while that of Claudin 3 did not change significantly (P > 0.05), indicating that H9N2 AIV infection can cause the destruction of tight junction proteins in intestinal epithelial cells. There was no significant difference in the expression of intestinal epithelial tight junction proteins between the mock and AL groups (P > 0.05), while AL treatment in the infection group could upregulate the ZO-1 and Occludin, as compared with the infection group (P < 0.01 and P < 0.05), indicating that AL can protect the structure and function of the intestinal epithelial mucosa to a certain extent.In order to explore the barrier function of H9N2 AIV on intestinal mucosal epithelial cells, the mRNA expression of scaffold protein H9N2 AIV infection is often accompanied by secondary bacterial infection in visceral organs. The present results showed that bacteria were isolated from the lungs and mesentery at 5 dpi and were positive in all tissues at 12 dpi, while in the H9N2-AL group, bacteria were only isolated from the lungs at 5 dpi . These fE. coli bacteria count in different treatment groups was shown in E. coli from intestinal cavity in H9N2-NeonGreen group was significantly higher than that in NeonGreen group and H9N2-AL-NeonGreen group at 12 h, 24 h, 36 h and 48 h. The count of NeonGreen-tagged E. coli from mesentery in H9N2-NeonGreen group was gradually increasing from 24 h to 48 h, however, no NeonGreen-tagged E. coli was detected in NeonGreen and H9N2-AL-NeonGreen groups. Besides, the count of NeonGreen-tagged E. coli was gradually increasing from 24 h to 48 h in lung, however, no NeonGreen-tagged E. coli was detected in NeonGreen and H9N2-AL- NeonGreen groups at 12 h, 24 h and 48h, although the NeonGreen-tagged E. coli was detected in H9N2-AL-NeonGreen group at 36 h, while the count was significantly lower than that in the H9N2-NeonGreen group. Similarly, the count of NeonGreen-tagged E. coli in liver was gradually higher from 36 h to 48 h in H9N2-NeonGreen group, but no NeonGreen-tagged E. coli was detected in NeonGreen group and H9N2-AL- NeonGreen group from 12 h to 48 h, illustrating that H9N2 AIV infection causes NeonGreen-tagged E. coli translocation, leading to bacterial secondary infection, while AL could effectively inhibit E. coli translocation through the intestinal wall to mesentery, lung and liver.Following H9N2 AIV infection, bacteria can be isolated in the mesentery, lung and liver, indicating that there is a phenomenon of bacterial translocation . Our preIn combination, H9N2 AIV infection promotes bacterial translocation from the intestinal cavity to the mesentery, lung and liver and causes secondary bacterial infection. AL can effectively prevent bacterial translocation induced by H9N2 AIV.A multivariate model was used to construct a multivariate control chart to evaluate the validity of each sample data. Results showed that the biological variability of metabolic group samples was small and could be used for follow-up data analysis . By compLactobacillus from the mock group and Escherichia from the H9N2 AIV infection group were selected and screened according to the absolute value of a correlation coefficient of > 0.5. A total of 6 metabolites were found to be associated with Lactobacillus and Escherichia, in which the L-Glutamic acid/L-Glutamine ratio was positively correlated with Escherichia , while SMT could significantly reduce the H9N2 AIV-induced nitrate content (P < 0.01). AL could also significantly reduce the production of H9N2 AIV-induced nitrate   . Subsequriaceae) . In 2015ectively . Howeverectively , b,c. Inur group .E. coli in the intestinal tract caused by H9N2 AIV may translate to other organs. As expected, our results showed that bacteria could indeed be isolated from the liver and other visceral tissues following H9N2 AIV infection. In order to further confirm whether the microbiota in the viscera were translocated from the intestinal tract, NeonGreen-tagged bacteria were administrated into the gastrointestinal tract and used to trace the translocation of E. coli from the intestinal tract to the mesentery, lung and liver, in order to illustrate whether the bacterial secondary infection in SPF chickens infected with H9N2 was due to intestinal flora disorder and then result to the E. coli translocate to the visceral organs. Furthermore, the NeonGreen-tagged E. coli bacteria count in different treatment groups was detected by RT-qPCR to further illustrate that H9N2 AIV infection causes NeonGreen-tagged E. coli translocation, leading to bacterial secondary infection. This explains the causal relationship among H9N2 virus, intestinal microbial imbalance and bacterial secondary infection.The destruction of the intestinal barrier increases intestinal permeability, and intestinal bacteria are easy to translocate through the barrier to visceral organs . In addiE. coli and its translocation to other organs. Therefore, in-depth understanding of the causes of E. coli proliferation is key to exploring the mechanism of bacterial secondary infection. E. coli is a facultative anaerobic bacteria that belongs to the Proteobacteria of the Escherichia genus. E. coli is a conditional pathogen in the intestinal tract and has a symbiotic relationship with the body. Under normal circumstances, E. coli is harmless to the body; however, when a disease occurs in the host, E. coli proliferates to become harmful bacteria. Proteobacteria, as a feature of intestinal flora imbalance, is often associated with some inflammatory diseases, such as ulcerative colitis . Written informed consent was obtained from the owners for the participation of their animals in this study.XZ, HL, and WL conceived study, designed the experiments, and analyzed the data. QZ, CW, ZX, and XC performed the experiments and analyzed the data. XZ wrote the manuscript. HZ and QX supervised the experiments and edited the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer WR declared a shared affiliation, with no collaboration, with the authors to the handling editor at the time of review.


Emerging evidence implicates excess weight as a potential risk factor for hearing loss. However, this association remained inconclusive. Therefore, we aimed to systematically and quantitatively review the published observational study on the association between body mass index (BMI) or waist circumference (WC) and hearing loss.The odds ratios (ORs) or relative risks (RRs) with their 95% confidence intervals (CIs) were pooled under a random-effects model. Fourteen observational studies were eligible for the inclusion in the final analysis.2 increase in BMI, and 1.22 (95% CO 0.88. 1.68) for higher WC. In the meta-analysis of longitudinal studies, the RRs were 0.96  for underweight, 1.15  for overweight, 1.38  for obesity, 1.15  for each 5 kg/m2 increase in BMI, and 1.11  for higher WC.In the meta-analysis of cross-sectional studies, the ORs for prevalent hearing loss were 1.10  underweight, 1.14  for overweight, OR 1.40  for obesity, 1.14  for each 5 kg/mIn summary, our findings add weight to the evidence that elevated BMI and higher WC may be positively associated with the risk of hearing loss. Hearing loss is a growing important global public health concern. In 2018, the World Health Organization (WHO) estimated there were 466 million (6.1% of the world’s population) people living with disabling hearing loss worldwide. The number of people with hearing loss is projected to increase to 630 million by 2030 and to 900 million in 2050 –12. ConsEmerging evidence implicates excess weight  and its Given these considerations, we aimed to perform a systematic review and meta-analysis of observational studies to provide further clarification of the potential association between BMI and hearing loss (primary aim). In addition, we also investigated the potential association between marker of central adiposity, waist circumference (WC), and hearing loss (secondary aim).The present systematic review and meta-analysis followed the Meta-analysis Of Observational Studies in Epidemiology checklist . Two invThe PubMed and Web of Science databases were used to identify the relevant articles in any language that were published from inception to May 2019. We used the following search terms to identify the relevant articles: (hearing OR hearing loss OR hearing impairment OR deaf OR deafness) AND (adiposity OR body fatness OR body size OR anthropometric OR body mass index OR waist circumference OR underweight OR overweight OR obesity). The references cited in the included studies were also scrutinized to identify additional relevant articles.The observational studies of any design were selected for the final analysis only if they reported the risk estimates (relative risks (RRs), odds ratios (ORs), or hazard ratios (HRs)) with their corresponding 95% confidence intervals (CIs) of the association between BMI or WC and hearing loss in adults. Studies that specifically enrolled children or adolescents were excluded. If multiple articles reporting the data from the same population were identified, we included only those with the most up-to-date, complete, and relevant data.The following information were extracted from each included study: the first author’s last name, publication year, design, country, age of the participants, proportion of men, total sample and number of cases, exposure category, ascertainment of exposure, ascertainment of hearing loss, definition of hearing loss, and adjustment for confounders. The risk estimates from the maximally adjusted model were included whenever reported. The Newcastle-Ottawa Scale (NOS)  was usedThe ORs  or RRs  with their 95% CIs were used as the measures of effect size. In the longitudinal study by Barrenas et al. , the dat2, overweight as 25.0 to 29.9 kg/m2, and obesity as ≥ 30.0 kg/m2) as classified by the WHO [2 increase in BMI.In the analysis of BMI, we first investigated the influence of abnormal BMI status , 25–50% (moderate heterogeneity), > 50–75% (high heterogeneity), and > 75% (severe heterogeneity) [P values were two-sided, and the level of significance was set at < 0.05.The geneity) . Publicageneity) . If publgeneity) . All staThe flow chart of study selection and the reasons for exclusion is presented in Fig. Characteristics of the included studies are summarized in Additional file 2 increase in BMI [I2 ≥ 50.7). There was no evidence of publication bias in all analyses .Pooled cross-sectional studies revealed that obesity was positively associated with the odds of having hearing loss . There was no evidence of publication bias in all analyses .Pooled longitudinal studies showed that overweight , particularly in the obesity range, and higher WC were positively associated with hearing loss. The findings of the positive association between elevated BMI and hearing loss were further supported by the linear relationship between BMI and hearing loss.The underlying biological mechanisms by which excess weight may play a role in the development of hearing loss are poorly understood. Adipose tissue is an endocrine organ that secretes a number of pro-inflammatory and anti-inflammatory adipokines . Excess Study design did not appear to alter the association between BMI and hearing loss, as the positive linear relationship between BMI and hearing loss were evident in both cross-sectional and cohort studies. However, two , 29 of tAge is a well-established risk factor for hearing loss, as hearing tends to gradually worsen with age . Thus, iThe positive association between BMI and hearing loss could also be mediated or confounded by the cardiometabolic comorbidities related to excess weight. DM , 58, 59 2) and high WC (> 88 cm) were independently associated with an increased risk of hearing loss after mutual adjustment. Nonetheless, future studies need to investigate whether BMI and WC independently contribute to hearing loss.Adipose tissue may differently affect the health risk according to the site of deposition. It has been suggested that excessive accumulation of adipose tissue around the intra-abdominal organs, central adiposity, confers greater risk for cardiometabolic complications of obesity . There iIt is also possible that excess weight and its cardiometabolic comorbidities may be the consequences of exposure to poor lifestyle choices that could also contribute to hearing loss. In other words, excess weight might be a proxy of unhealthy lifestyle habits. It is known that excess consumption of certain foods, particularly those that contain high amounts of refined grains, sugars, and trans fat, is associated with increased risks of obesity, DM, and CVD . The BluThe present meta-analysis should be interpreted within the context of its limitations. First, the present meta-analysis pooled the data from the observational studies. Therefore, the unmeasured or residual confounders may also influence of the associations between BMI, WC, and the risk of hearing loss. For example, only few studies performed adjustment for important risk factors for hearing loss, such as longstanding noise exposure, medical conditions that may lead to hearing loss, and the use of ototoxic drugs. Moreover, we could not rule out the potential role of cardiometabolic comorbidities related to excess weight as mediators of the associations between BMI or WC and hearing loss. Second, we did not have enough data sets to investigate the associations between BMI or WC and hearing loss according to several important factors, such as type of hearing loss , frequency of hearing loss, and severity of hearing loss. The potential effect modification by these factors warrants further investigation. Third, slight variation in the cut-points (frequencies and threshold) used to define hearing loss among the included studies should also be considered. Finally, high heterogeneity observed across studies suggests that the findings should be treated with caution. Unfortunately, we were unable to pin-point the source of heterogeneity because subgroup analyses could not be performed. However, high heterogeneity appeared to be mainly caused by differences in the strength (significant vs. non-significant) of association across studies rather than differences in the direction (inverse vs positive) of association across studies as the vast majority of studies on elevated BMI (overweight and obesity) or higher WC showed a tendency toward positive associations, although some did not reach statistical significance.In summary, our findings add weight to the evidence that elevated BMI and higher WC may be positively associated with the risk of hearing loss. However, the nature of the observed positive associations remains unclear because we were unable to consider the type and severity of hearing loss, noise exposure, and other potential effect modifiers or mediators in our analyses. These issues need to be addressed by well-performed prospective studies.Additional file 1: Table S1. Characteristics of the included studies.Additional file 2: Table S2. The Newcastle Ottawa scale for cohort study.Additional file 3: Table S3. The Newcastle Ottawa scale for cross-sectional study.


No differences in RMR were seen under the different conditions of the SSt method, or of the filtering method. No differences were seen between the methods in terms of the variance in RMR explained by its classical determinants. In conclusion, the SSt and filtering methods return the lowest RMRs and intra-measurement coefficients of variation when using breath-by-breath metabolic carts.The method used to select representative gas exchange data from large datasets influences the resting metabolic rate (RMR) returned. This study determines which of three methods yields the lowest RMR , and in which method the greatest variance in RMR is explained by classical determinants of this variable. A total of 107 young and 74 middle-aged adults underwent a 30 min RMR examination using a breath-by-breath metabolic cart. Three gas exchange data selection methods were used: (i) steady state (SSt) for 3, 4, 5, or 10 min, (ii) a pre-defined time interval (TI), i.e., 6–10, 11–15, 16–20, 21–25, 26–30, 6–25, or 6–30 min, and (iii) “filtering”, setting thresholds depending on the mean RMR value obtained. In both cohorts, the RMRs yielded by the SSt and filtering methods were significantly lower ( It is widely assumed that the first 5 min of data recorded should be discarded ,9. A sho% for RQ ), (ii) t% for RQ , and  .Servicio Andaluz de Salud , while the FIT-AGEING was approved by the Human Research Ethics Committee of the Junta de Andalucía (0838-N-2017). Both studies were performed in accordance with the Declaration of Helsinki (2013 revision) and registered on the clinicaltrials.gov platform (IDs: NCT02365129 for the ACTIBATE study and NCT03334357 for the FIT-AGEING study). Oral and written informed consent was obtained from all the subjects before their enrolment.The participants of this retrospective study were 107 young adults (72 women) enrolled in the ACTIBATE study  and 74 mIn both the above studies, subjects underwent a 30 min indirect calorimetry assessment of RMR at rest, early in the morning, following an overnight fast. All subjects were instructed to refrain from moderate (24 h) and vigorous physical activity 48 h) before the test day. On the previous evening, all subjects consumed a standardized meal of an egg omelet, boiled rice, and tomato sauce (ad libitum amounts). They were also instructed to avoid physical activity after they woke up, and to come to the research center by car or bus early in the morning, having had no breakfast (ensuring a ~12 h fast). Upon arrival, and after confirming their compliance with these above conditions, body weight and height were measured using a Seca model 799 electronic column scale  with subjects barefoot and wearing light clothing. Thereafter, the subjects laid on a bed in the supine position for 20–30 min. Gas exchange data were then recorded by indirect calorimetry for 30 min in a quiet room with dim lighting, controlled at 22–24 °C and 35–45% relative humidity [ h before2 using a non-dispersive infrared analyzer, and both determine VO2 using a galvanic fuel cell [Gas exchange was recorded using either a CCM Express or a CPX Ultima CardiO2 (two different devices were used only in the middle-aged adults cohort) breath-by-breath metabolic cart . Both instruments require the use of a face mask equipped with a Directconnect™ flow sensor . Both determine VCOuel cell . The flouel cell .® Breeze Suite 8.1.0.54 SP7 software  to yield a data point for each variable for every minute  for each particular minute). The first 5 min of data were discarded [The collected gas exchange data were processed using MGCDiagnosticiscarded ; the rempMVD values for all variables available for these time periods calculated. These processed data were used to calculate the RMR and nutrient oxidation rate (see below for details).Short TIs of 6–10 min, 11–15 min, 16–20 min, 21–25 min, and 26–30 min, and long TIs of 6–25 min and 6–30 min were established [2, VCO2, VE, and RQ were calculated for every period of 3, 4, 5, and 10 min  and the mean CVs for each variable calculated for each time period. The periods selected for the final analyses were those with the lowest mean CV for each  [pMVD values for these time periods were then calculated. These processed data were used to calculate the RMR and nutrient oxidation rate (see below for details).The CVs of VO to 9th) . The meapMVD values for VO2 and VCO2 for the entire 25 min data collection period—i.e., with no division into SSt or TI periods—were used to calculate the mean25 min RMR (see below for details). Furthermore, pMVD RMR values were also calculated, discarding either (i) those values <85% or >115% of the mean25 min RMR (low filter), (ii) <90% or >110% of the mean25 min RMR (medium filter), or (iii) <95% or >105% of the mean25 min RMR (strong filter). For the minutes that passed these filters, the means were calculated for all pMVD values available.The pMVD for VO2 and VCO2 obtained with each gas exchange data selection method. The FATOx and CHOOx rates were calculated using Frayn’s stoichiometric equations [2, VCO2, FATOx, and CHOOx were calculated for all gas exchange data selection methods under each different condition.Weir’s equation (assuming zero urinary nitrogen excretion)  was usedquations , also asBody composition was determined by dual energy X-ray absorptiometry using a Discovery Wi device . Quality controls, the positioning of participants and analysis of the results were performed according to the manufacturer’s recommendations.p < 0.05. Repeated-measures analysis of variance (ANOVA) with a post-hoc Bonferroni test was used to detect differences in RMR, RQ, VO2, VCO2, FATOx, and CHOOx estimates across the methods for gas exchange data selection. The CVs for VO2, VCO2, RQ, and VE obtained via the different methods were also compared. Two different ANOVA models were used: one with four levels of fixed factors , and one with 14 levels .Results are presented as mean±SD unless otherwise stated. All analyses were conducted using the Statistical Package for the Social Sciences v.22.0 . Significance was set at The differences between the methods in terms of the variance in RMR explained by its classical determinants   were exap < 0.001; p < 0.001; p = 1.000; 2 and VCO2 estimates  and the “best” SSt achieved  in RMR estimation in young adults  in the young and the middle-aged adults are presented in g adults .p < 0.002; p = 0.038; p < 0.013; p = 1.000; The RQ estimates yielded by the short TI method were significantly higher than all others in the young adult cohort  was 36%, 36%, 34% and 38% for the short TI, long TI, SSt, and filtering methods respectively in young adults, and 50%, 51%, 52% and 51% respectively in the middle-aged adults. The most explained variance was obtained using the low-filter method (40%) in young adults and the TI 6–10 min method (54%) in the middle-aged adults.The variance explained increased to 34–45% and 54–68% in the young and middle-aged adults respectively after including subject sex in the model . The mosA further model including subject sex, lean, and fat masses increased the variance in RMR explained by ~5% in the young adults, but not in the middle-aged adults . The lowThe present results show that when using breath-by-breath metabolic carts, RMR, and RQ estimates yielded by the SSt and filtering methods are lower than those yielded by the TI method, while no differences were seen between the SSt and filtering methods. The variance in the RMR explained by its classical determinants  was similar in all methods. These findings largely concurred in the cohorts of young adults and middle-aged adults examined, which further reinforced the consistency of the results.Given that RMR is defined as the lowest energy expenditure of a person who is awake , the pre2 and VCO2 are <10% over a period of 5 consecutive min, (ii) RMR assessment should end when a steady respiratory state is achieved, and (iii) when a steady respiratory state cannot be reached, a more prolonged test (≥60 min) becomes necessary. Reeves et al. [The SSt method purportedly reflects the baseline physiological state , thus res et al.  showed ts et al. , but in s et al.  no diffes et al. . In addiTo our knowledge, no other study has compared the TI, SSt, and filtering methods, rendering further comparisons impossible. However, the present results suggest that those provided by the filtering method are similar to those provided by the SSt method. It might therefore be used as an alternative in subjects in whom a steady respiratory state is not achieved .Mean FATOx was higher and CHOOx lower, when determined via the SSt and filtering methods compared to the TI method, with no differences seen among the different SSt periods or among the different filtering conditions. In contrast, differences were observed among the TI periods in terms of both the RQ and nutrient oxidation rates, with an increase in the RQ seen over each test period , The present results should be considered with some caution. The assessment of RMR was performed using two different breath-by-breath metabolic carts indiscriminately, both of which were equipped with a face-mask. The use of other metabolic carts or other gas collection systems  might influence the RMR results obtained ,27. FurtThe present findings suggest that when using CCM Express and CPX Ultima CardiO2 breath-by-breath metabolic carts, both the SSt and filtering methods yield the lowest RMR and RQ estimates with the lowest amount of variability . Moreover, the filtering method might be a valid alternative for use with subjects who do not achieve a steady respiratory state.


Posttraumatic stress disorder (PTSD) and hearing loss are hallmark public health issues related to military service in Iraq and Afghanistan. Although both are significant individual contributors to disability among veterans, their co-occurrence has not been specifically explored.A total of 1179 male U.S. military personnel who sustained an injury between 2004 and 2012 during operations in Iraq or Afghanistan were identified from clinical records. Pre- and postinjury audiometric data were used to define new-onset hearing loss, which was categorized as unilateral or bilateral. Diagnosed PTSD was abstracted from electronic medical records. Logistic regression analysis examined the relationship between hearing loss and PTSD, while adjusting for age, year of injury, occupation, injury severity, injury mechanism, and presence of concussion.The majority of the study sample were aged 18–25 years (79.9%) and sustained mild-moderate injuries (94.6%). New-onset hearing loss was present in 14.4% of casualties . Rates of diagnosed PTSD were 9.1, 13.9, and 29.2% for those with no hearing loss, unilateral hearing loss, and bilateral hearing loss, respectively. After adjusting for covariates, those with bilateral hearing loss had nearly three-times higher odds of PTSD  compared to those with no hearing loss. Unilateral hearing loss was not associated with PTSD.Both PTSD and hearing loss are frequent consequences of modern warfare that adversely affect the overall health of the military. Bilateral, but not unilateral, hearing loss was associated with a greater burden of PTSD. This has implications for warfighter rehabilitation and should encourage collaboration between audiology and mental health professionals. Posttraumatic stress disorder (PTSD) is a frequent wartime problem –3. The dSimilar to PTSD, hearing loss is a significant public health problem in the military, as the Department of Veterans Affairs (VA) reported that the cost of hearing loss exceeds one billion dollars annually . In geneAlthough PTSD and hearing loss both contribute significantly to the overall health burden in the military, their co-occurrence has not been widely described in the literature . A VA stThe paucity of literature on hearing loss and PTSD, in addition to the combined public health impacts, warrants an investigation of their co-occurrence. The present study aimed to examine the relationship between new-onset hearing loss and PTSD, as measured using audiometric data, among a sample of U.S. military personnel with deployment-related injury. It was hypothesized that hearing loss would be positively associated with PTSD diagnosis.Military personnel injured during combat deployment in Iraq and Afghanistan between 2004 and 2012 were identified from the Expeditionary Medical Encounter Database (EMED), which contains clinical encounters across all levels of medical care . The EMEn = 1573). After excluding those with a previous PTSD diagnosis (n = 6) and those with preinjury hearing loss (n = 388), the final study sample consisted of 1179 individuals. This study received local Institutional Review Board approval.A subset of the EMED was used to create the Blast-Related Auditory Injury Database (BRAID), which includes injured military personnel, specifically Navy and Marine Corps, with valid audiometric information from the DoD Hearing Conservation Program . DetailsIncluded age at time of injury, which was calculated as the difference between date of injury and birth and categorized as 18–25 or 26 and older. Occupation was dichotomized per DoD Military Occupational Specialty code into infantry or non-infantry .no injury) to 75 (unsurvivable injury). In the present study, ISS was categorized as 1–8  or 9 and greater  [Were abstracted from the EMED clinical record. Year of injury was categorized as 2004–2006 or 2007–2012. Battle injury was categorized as battle or nonbattle, and blast injury as blast or nonblast. Injuries were distinguished by battle and blast injury in order to account for combat noise exposure. Injury severity was measured using the Injury Severity Score (ISS), which provides an overall measure of injury severity for individuals with multiple injuries , 30. Thed worse) –31. ConcWas measured using audiometric pure-tone hearing threshold levels for left and right ears at six test frequencies  that were abstracted from the BRAID. Postinjury hearing loss was defined as a response exceeding 25 dB at any test frequency . PostinjDiagnosis was obtained from outpatient medical information in the MDR. PTSD was defined as presence of an International Classification of Diseases, 9th Revision, Clinical Modification code of 309.81 within 2 years postinjury .Data management and statistical analyses were performed using SAS software, version 9.4 . Characteristics of the study sample were stratified by hearing loss status and chi-square statistics were used to test for differences. Tetrachoric correlation coefficients were calculated to highlight relationships between covariates. Univariate and multivariate logistic regression with backward selection was used to model the relationship between hearing loss and PTSD. The Hosmer-Lemeshow test was used to assess the model for goodness of fit with an alpha level of 0.10.n = 122) and 4.1% (n = 48) of study participants, respectively. Sample characteristics are shown in Table p = 0.003), and those with battle injury (p < 0.001), blast injury (p < 0.001), and concussion (p = 0.002). Hearing loss groups did not statistically differ by age or ISS (ps > 0.05). The overall rate of PTSD was 10.4%, and rates differed significantly across hearing loss groups (p < 0.001). Those with bilateral hearing loss had the highest PTSD rate at 29.2%, followed by unilateral hearing loss at 13.9%, and no hearing loss at 9.1%.Overall, unilateral and bilateral hearing loss was present in 10.3% (The tetrachoric correlation matrix for covariates is shown in Table ps < 0.01). In multivariate modeling with backward selection, however, only battle injury  and bilateral hearing loss  were significantly associated with PTSD. Unilateral hearing loss was not significantly associated with PTSD . The Hosmer Lemeshow test had a p-value greater than 0.10, indicating a good model fit.Table Hearing loss and PTSD are significant public health problems in the military. The present study suggests the two may be linked. In a large group of injured male military personnel, we found that the odds of PTSD are approximately three-times higher in individuals with postinjury bilateral hearing loss when compared to personnel without hearing loss. Hearing loss can affect listening performance and decrease quality of life, which may serve to exacerbate mental health problems such as PTSD .Physical injury during combat is an established predictor of PTSD . Koren eComorbidities of both PTSD and hearing loss may have played a role in the observed association. Depression has been frequently linked to PTSD and multiple studies have found increased rates of depression among those with hearing loss , 43, 44.The present study has several strengths. In comparison with the recent study by Swan et al. that identified a relationship between PTSD and hearing loss using strictly diagnosis codes, the present study used audiometric data collected under standardized medical surveillance protocols . The useThere are limitations that warrant mention. First, regarding the temporal relationship between hearing loss and PTSD, both were ascertained at different times postinjury. Using this methodology, it is possible that a diagnosis of PTSD might be recorded before or after the date of the audiogram and, as such, temporality could not be established. Using diagnosis codes to ascertain PTSD also excludes those individuals who may meet criteria for the disorder, but do not present for care. Moreover, a diagnosis of PTSD could be delayed by years, thus a diagnostic bias may occur with follow-up time restricted to two years. It is also possible that hearing loss could worsen between the blast injury and audiogram date, sometimes unrelated to the injury. A full assessment of combat experiences for each individual was not available for the present study. While it is arguable that a blast produced the hearing loss, it is likely that a collection of combat exposures caused the PTSD, the blast event being one. Though we accounted for injury-specific variables in our analysis, it may be difficult to fully adjust for the possible confounding effects of trauma severity on hearing loss. Additional controlled studies are needed to clarify these effects. Restricting the study sample to men precluded any examination of possible sex differences, and the findings may not generalize to military women. Lastly, potential comorbidities, such as tinnitus and depression, were not measured in the present study.To our knowledge, this is the first study to examine the association between PTSD and hearing loss in military personnel that have been injured during combat deployment. Taken together, both conditions are responsible for billions in health care costs for veterans. Delays in identification of these conditions may result in reduced quality of life for affected individuals, thus early provider diagnosis and intervention may be highly beneficial. Approximately 80% of primary care providers do not screen for hearing loss, and individuals with hearing loss often do not recognize a problem until they are examined and counseled . This fu


Increasing use of personal listening devices has been accompanied by increase in the prevalence of hearing loss (HL) among youth in Korea, as in other countries. Auditory processing disorder (APD) is one of the main factors affecting academic achievement at school. This study aimed to investigate the prevalence of HL in students attending general middle- and high schools and compare the findings with the APD survey results. From June 1 to December 31, 2016, Korean adolescents  in the first years of middle- and high school underwent audiometric testing and otologic examination and completed questionnaires on APD. The survey was sponsored by the Korean Society of Otolaryngology-Head and Neck Surgery and the Korean Otology Society. The prevalence of speech-frequency hearing loss (SFHL) and high-frequency hearing loss (HFHL) in the poorer ear was 11.6% and 10.3%, respectively, among Korean adolescents. We analysed data from the Scale of Auditory Behaviors, Fisher’s Auditory Problems Checklist, and KNISE-Auditory Behavioral Checklist and compared these with the results of hearing tests. We observed positive correlations among the APD questionnaire results and mean hearing levels. This study suggested that hearing loss, especially bilateral high-frequency hearing loss, may affect central auditory processing. Two nationwide studies have been conducted on adolescents in South Korea: Hong et al. reported unilateral and bilateral HFHLs > 20 dB in 5.0% and 1.9%, respectively, of 1,658 adolescents aged 13–18 years in South Korea2 and Rhee et al. reported that approximately 17% of Korean adolescents exhibited at least slight HL3.With the increasing use of personal listening devices, the prevalence of hearing loss (HL) among the current generation of adolescents has been predictably higher than that among the past generations of adolescents. A study from the USA reported that the prevalence of HL among US adolescents increased from 14.9% in 1988–1994 to 19.5% in 2005–2006. In addition, chronic noise exposure from using mobile devices may increase high-frequency hearing loss (HFHL)4. Because of masking effects from background noise or a hearing problem, the acoustic speech signal is easily degraded, making it difficult to understand. To overcome this difficulty and facilitate speech perception, one strategically adopts some auditory and language-based compensatory mechanisms5. Such language-based mechanisms include semantic and lexical expectations about words presented in context to facilitate speech perception in a noisy environment7. However, unlike adults who have normal language fluency, children in the process of learning a language lack the capacity to “fill in the blanks” for inaudible sounds. Moreover, it is often challenging for children to understand speech under various listening conditions, such as a noisy or a reverberant environment8.Understanding external auditory speech normally and naturally requires at least two stages: auditory processing of the signal and language-based processing of that information9, and approximately 2–5% of school-aged children are reported to be affected by hearing problems10. In addition, a 2017 New Zealand study of youth offenders aged 14–17 years reported that 27% suffered from APD and 64% showed language impairment compared to 18% and 10% of adolescents with normal hearing, respectively11. Children diagnosed with APD have listening difficulties, and many of those who present at audiology or other paediatric clinics have ‘normal’ audiograms. Most of these children have other complications such as speech/language or attention impairments and various learning disorders12.Auditory processing disorders (APDs) are defined as speech perception deficits that exist despite normal peripheral hearing14. Therefore, it must be diagnosed as early as possible. Several test batteries are available to diagnose APDs in patients with normal hearing16. However, several studies have shown that in patients with cochlear HL of up to approximately 45–50 dB, speech perception is mainly influenced by audibility18. In patients with more severe HL, poor discrimination of suprathreshold stimuli plays an important role in addition to the loss of audibility.Although the central hearing difficulty seems to be a single problem, it may be a cause of language disorder, reading disorder, learning disorder, attention deficit hyperactivity disorder, and other problems19. Therefore, having normal pure tone average does not mean that speech perception is normal.However, APD was found in children with normal pure tone average or mild high-frequency hearing lossThe purpose of this study was to analyse the relationship between different degree of HL and results of screening surveys of the central auditory processing ability of middle- and high-school students in South Korea.20.We performed a cross-sectional, complex sampling survey of first-year middle- and high-school students, except those attending special schools for disabled children. The sampling frame was the 2015 Yearbook of Educational Statistics prepared by the Korean Educational Statistics Services22. Details of the study design and research methods are presented in another study2.We sought to enrol 3,013 students from 124 middle schools and 124 high schools based on the prevalence of HL in Korean adolescents, the estimated association between noise and HL, and an expected 80% response rateThe survey was performed from June 1 to December 31, 2016. After providing written information about the study to students and parents, we selected and evaluated only those children who themselves and whose parents provided written informed consent. This study was approved by the Institutional Review Board of Seoul National University Hospital (No. 1604-086-755). All methods/experiments were performed in accordance with relevant guidelines and regulations (Declaration of Helsinki).2. Briefly, four experienced audiologists measured the hearing thresholds of adolescents using an AD229b diagnostic audiometer  in a soundproof booth inside a mobile vehicle. Prior to audiometry, otological examinations were performed to rule out factors affecting hearing, such as external ear anomalies, ear wax, retraction of the tympanic membrane, cholesteatoma, and middle ear effusion.The methods of audiological evaluation are superbly detailed in the previous studyThe tested frequencies were 0.5, 1, 2, 3, 4, 6, and 8 kHz. We started at 30 dB, adjusting with a 10 dB decrease or a 5 dB increase according to the participant’s response, until we decided that his or her frequency-specific hearing threshold was reached. If the hearing threshold was over 25 dB at any frequency, we measured the bone conduction threshold to determine whether conductive hearing loss was present.1. Speech-frequency hearing loss (SFHL) was the average of the HLs at 0.5, 1, and 2 kHz, while HFHL was the average of the HLs at 3, 4, 6, and 8 kHz.We defined HL as a hearing threshold ≥15 dB. The severity of HL was based on the poorer threshold for unilateral HL and better threshold for bilateral HL, as described previouslyThe students were asked to complete separate questionnaires to evaluate their everyday difficulties in areas such as listening, learning, and communication.24. The KNISE-ABC has 36 items rated on a 5-point scale and includes seven test areas, namely, listening, listening in background noise, communication, learning, auditory memory, auditory attention, and related behaviour.The KNISE-Auditory Behavioural Checklist (KNISE-ABC) is used for screening children with APDs and other related disorders to provide information necessary for establishing and implementing management and educational plans25. The questionnaire is easily administered because it has a small number  of questions and answer options that are easily understood. This questionnaire was developed to assess everyday behaviours associated with audition, listening and academic skills, attention, memory, and organisation.The Scale of Auditory Behaviours (SAB) questionnaire, chosen for this study, has a version that may be used by parents or professionals26 and comprises a list of 25 items rated on a 2-point scale. To collect information about the perceived auditory processing problems, this checklist includes questions on acuity, attention, attention span, figure ground, discrimination, short-term memory, long-term memory, sequential memory, comprehension, speech and language problems, auditory-visual integration, motivation, and performance.Fisher’s Auditory Problems Checklist (FAPC) was developed by Fisher Lp-value <0.05.All data in the study are summarised as means and standard deviations for continuous variables and as frequencies and percentages for categorical variables. Comparisons of general characteristics between HL and no HL were conducted using the chi-squared test or Fisher’s exact test. Prevalence rates of SFHL and HFHL were estimated with 95% confidence intervals. To evaluate the association between the degree of HL and mean scores of KNISE-ABC, SAB, and FAPC, we adopted Wilcoxon’s rank sum test. All statistical analyses were performed using SAS , and statistical significance was defined as a two-sided In total, 3,013 students from 109 middle- and high schools agreed to complete the questionnaires. Of these, 134 (4.4%) were excluded because of incomplete audiometric data. Additionally, 88 students were excluded because of incomplete survey tests. Finally, a total of 2,791 (90.0%) students participated in this study .Demographic characteristics of these 2,791 students are summarised in Table The prevalence of any-HL  was 12.8%. In addition, the prevalence of any-HFHL and any-SFHL was 7.9% and 8.3%, respectively; that of unilateral HL, HFHL, and SFHL was 8.7%, 5.8%, and 5.9%, respectively; and that of bilateral HL, HFHL, and SFHL was 4.1%, 2.1%, and 2.4%, respectively. Detailed data are presented in Table . FAPC analysis also revealed no significant difference was observed between students with and without hearing loss in the any hearing loss and unilateral hearing loss groups. However, students with bilateral hearing loss, irrespective of whether they had high-frequency hearing loss or speech-frequency hearing loss, showed significantly worse performance scores than those without hearing loss. Moreover, students with bilateral high-frequency hearing loss showed relatively larger differences than those with other bilateral hearing loss .The KNISE-ABC analysis revealed no significant differences between students with and without hearing loss in the any-HL and unilateral HL groups. However, students with bilateral HL, irrespective of whether they had HFHL or SFHL, showed significantly worse performance scores than those without HL. Moreover, students with bilateral HFHL showed relatively larger differences than those with other bilateral HL Fig. . The SABFig. . FAPC anoss Fig. .Figure 2In this study, the prevalence of SFHL and HFHL in the poorer ear was 11.6% and 10.3%, respectively, among Korean adolescents. There were no significant differences between the no-HL and any-HL groups in sex ratio, grade level of middle- vs. high school, household income, and family history, meaning that environmental factors such as noise exposure might be more influential on their hearing. In addition, when the three degrees of HL  and mean scores from KNISE-ABC, SAB, and FAPC were compared, Korean adolescents with bilateral HL showed significantly worse scores on all three screening tests for APD.27. One or more deficiencies in this ability are referred to as central APD or APD.Auditory behaviour is defined as behavioural characteristics associated with hearing that appear in relation to the process or outcome of receiving and perceiving auditory information in the peripheral and central auditory systems. Children’s hearing behaviour may vary according to the mechanism and function of the central nervous system (CNS). The ability to perceive and manipulate auditory information in the CNS can be used for sound localisation and lateralisation, auditory discrimination, determining the temporal aspects of audition , assessing auditory performance with competing sound signals and acoustic signals, and assessing auditory performance with degraded acoustic signals27. Children with hearing impairment may have problems with overall auditory behavioural characteristics and may exhibit sluggishness or difficulty in certain areas only.Auditory behavioural characteristics resulting from these central hearing processing problems can be caused by or related to difficulties in higher language, learning, and cognitive function. In addition, they may be associated with language disorders, reading disabilities, learning disabilities, and attention deficit hyperactivity disorder17, whereas a less clear distinction can be made using low-pass filtered speech17, binaural interaction, and localisation/lateralisation27. The usefulness of the dichotic test of binaural integration in children was also doubted28. Previous studies have reported these relationships between APD and hearing impairment. Miltenberger et al.29 reported that auditory processing tests must always be related to the basic audiological assessment. They insisted that if the test results do not correspond with expectations based on the peripheral audiological assessment, the presence of APDs is likely, in addition to peripheral auditory disorders. Moreover, in the case of symmetrical hearing thresholds, auditory processing test results should be symmetrical. If the hearing thresholds are asymmetrical and performance in the better ear is poorer than that in the other ear, then an APD could be present21. The problem in APD is a decrease of speech performance in children with normal or mild hearing loss or functional hearing loss31.However, distinguishing between APD and peripheral HL is sometimes difficult; moreover, both problems may sometimes coexist. Peripheral HL does not have uniform effects on the results of APD tests. Studies have shown that cochlear lesions can be clearly distinguished from cerebral lesions using the dichotic-digit test, dichotic sentence identification test, and frequency-pattern test32 or because the loss of the cortical auditory function and high frequency hearing loss occurred simultaneously for some reason. The latter case may be considered as having the same mechanism as loss of speech in noise processing and temporal processing from age-related hearing loss, leading to an increase in APD33. This idea requires further research.In this study, adolescents with bilateral mild hearing loss showed a higher risk of APD. This may be because hearing loss is causally related to functional loss of central auditory processing35, while Neijenhuis et al.16 reported that hearing-impaired patients did not show normal scores on these two tests. As with the results of Neijenhuis et al., in addition to the fact that peripheral sensorineural deafness affects the central hearing process, our results for bilateral HL are the most meaningful. We suggest that adolescents with bilateral sensorineural HL are more likely to have learning difficulties than those with normal or unilateral HL; therefore, more active hearing rehabilitation should be considered for such adolescents.In this study, we adopted three different survey tools—the KNISE-ABC, SAB, and FAPC—for evaluating the ability of central auditory processing among Korean adolescents. All three test results showed that students with bilateral HL, irrespective of whether they had HFHL or SFHL, had significantly worse performance scores than those without HL. Some authors have concluded that HL has only a slight influence on the dichotic-digit and pattern-recognition testsA limitation of this study is that the survey tests conducted to measure the capacity of the central auditory system were originally developed for evaluating children in the elementary school age group. The results of this study showed that only bilateral HL is related to disabilities in central auditory processing and learning; however, in reality, unilateral or various hearing impairments, such as SFHL or HFHL, may be related to learning disabilities in middle- and high-school students. These findings suggest the need for developing a survey to test central auditory processing in students of middle and high school age.Our findings suggest that hearing loss, especially bilateral high-frequency hearing loss, may affect central auditory processing. We should consider providing hearing aid, assistive listening devices, or enforcing educational programs to prevent further noise-induced hearing loss to improve the academic achievement of youth with bilateral hearing loss.


Lawsonia intracellularis, an obligately intracellular enteric bacterium, infects intestinal epithelial cells, but may also be found within macrophages in the intestinal lamina propria of affected pigs. Macrophages play an important role in host defense against infectious agents, but the role of this cell in L. intracellularis infection is not well understood. The aim of this study was to evaluate the permissibility of macrophages to L. intracellularis infection in vitro. Pure culture of L. intracellularis was added to swine peripheral blood monocyte-derived macrophages. Viability of intracytoplasmic L. intracellularis was evaluated at different time points by transmission electron microscopy (TEM). Potential replication of L. intracellularis in macrophages was also evaluated by qPCR. By TEM, phagocytosis L. intracellularis within of phagolysosomes were observed 1-hour post-infection (hpi) and bacterial structures in binary fission at 48 hpi. The number of intracellular bacteria was determined at 1, 4, 24, 48, and 72 hpi by qPCR in infected macrophages and compared to the number of intracellular bacteria from culture in McCoy cells. In both cell lines, the amount of L. intracellularis was decreased at 4 hpiand increased at 24 hpi. The number of intracellular bacteria continued to increase in McCoy cells over time. This is the first study showing interaction, survival and propagation of L. intracellularis in macrophages. These findings are critical to establish an experimental model for future studies of the pathogenesis of porcine proliferative enteropathy and the potential persistence of L. intracellularis in macrophages during chronic infections. Macrophages play an important role in innate and adaptive immune responses against invading pathogens. They contribute to the elimination of microorganisms and are capable of presenting antigens to T cells. In addition, macrophages may serve as an escape route for some bacterial species, as intracellular bacteria may remain viable and potentially proliferate and/or disseminate in the host , 2.Lawsonia intracellularis is a microaerophilic, obligately intracellular bacterium that causes porcine proliferative enteropathy (PPE)  findings, we hypothesized that L. intracellularis can survive and propagate in macrophages [L. intracellularis organisms within phagolysosomes in cultured macrophages, free in the macrophage cytoplasm, and in binary fission. These results indicate that L. intracellularis has the ability to survive and propagate inside macrophages. However, despite the capacity of L. intracellularis to survive within the macrophages as shown in the present study, only fortuitous cases of L. intracellularis infection are associated to extra intestinal lesions [L. intracellularis indicate that the survival of L. intracellularis in macrophages is not related to the dissemination of the bacterium to extra intestinal tissues, as already described for other intestinal gram-negative bacteria [L. intracellularis to survive intracellularly whether in epithelial cell or macrophages are as still required.nd birds . L. intr in 1993 . Due the in 1993 , researcprevious  e 23 finrophages . The preprevious  e 23 fin lesions . These rbacteria , 28. DirRhodococcus equi and Coxiella burnetii [R. equi survive and proliferate within intracellular environment by blocking the acidification of the phagolysosome [C. burnetii delays the fusion process between the phagosome and the lysosome [Listeria monocytogenes [Franscisella tularensis [Edwardsiella tarda [L. intracellularis pathogenesis.The survival of bacteria in phagolysosomal compartments has been observed in other species, such as burnetii , 29. R. lysosome . On anotlysosome . Binary lysosome . Howeverytogenes , Franscilarensis , and Edwla tarda , are knoL. intracellularis survival within the macrophages may also be related to the persistence of the microorganisms in the host, which results in the chronic presentation of the disease. Therefore, the elimination of L. intracellularis for long periods, as previously demonstrated by Guedes and Gebhart and Stege et al, may be a source of dissemination of the pathogen in the herd [the herd , 35.L. intracellularis has the capacity to proliferate at low levels within the macrophages, but other methods should be used in future studies to confirm this hypothesis. Our findings do not corroborate Lawson et al. [L. intracellularis needs mitotically active cells for its proliferation. L. intracellularis is a unique bacterial species, with several peculiarities obligately intracellular microorganism, requires specific microaerophilic atmosphere that make it difficult to grow and manipulate under laboratory conditions. Therefore, evaluation of L. intracellularis survival and its quantification inside the cells is not possible using conventional assays used for studying other bacterial species [L. intracellularis potential to survive and to replicate within macrophages, therefore, it represents the first step towards the understanding of the persistence of the organism in chronically-infected animals.To assess the bacterial numbers in the macrophage cultures over time, qPCR was performed. This technique detects DNA sequences with good sensitivity and specificity but lacks the ability to differentiate metabolically active and inactive microorganisms. In addition, the chronological evaluation was performed by using samples from different wells, which can result in numerical variations from well to well. Nevertheless, from the results obtained, we can hypothesize that n et al.  findings species , 37. TheL. intracellularis is able to internalize and survive within phagolysosomal environment of swine macrophages. In addition, this is the first study to report the binary fission of L. intracellularis free in the cytoplasm of swine macrophages. These findings are critical to establish an experimental model for future studies the pathogenesis of porcine proliferative enteropathy and the potential persistence of L. intracellularis in macrophages during chronic infections.In conclusion, our results showed that S1 FigL: lysosome; N: nucleus; rER: rough endoplasmic reticulum.(TIF)Click here for additional data file.


However, owing to the non-selectivity action of (+)-JQ1 towards all BET family members, the role of BRD4 and that of its bromodomains (BD1 and BD2) in angiogenesis remains elusive. Herein, we identified a potent BRD4 inhibitor, ZL0513 (7), which exhibited significant anti-angiogenic effects in chick embryo chorioallantoic membrane (CAM) and yolk sac membrane (YSM) models. This inhibitor also directly suppressed the viability and tube formation of human umbilical vascular endothelial cells (HUVECs). Moreover, ZL0513 (7) was found to inhibit the phosphorylation of c-jun and c-fos, important members of activating protein-1 (AP-1) transcription factor complexes that enhance angiogenesis. The findings on this novel BRD4 inhibitor indicate that, in addition to being a powerful pharmacological tool for further elucidating the roles and functions of BRD4 and its BD domains in angiogenesis, it may serve as a potential therapeutic strategy for targeting the vasculature in various angiogenesis-dysregulated human diseases.Angiogenesis dysregulation contributes to inflammation, infections, immune disorders, and carcinogenesis. Bromodomain-containing protein 4 (BRD4) is an epigenetic reader that recognizes histone proteins and acts as a transcriptional regulator to trigger tumor growth and the inflammatory response. The pan-bromodomain and extra-terminal domain (BET) inhibitor, (+)-JQ1 ( N-terminal bromodomains (BDs), BD1 and BD2, which can recognize acetylated lysine residues and non-histone proteins to transcriptionally regulate gene expression, cell cycle progression, cell proliferation, and apoptosis  proteins is composed of bromodomain-containing protein 2 (BRD2), BRD3, BRD4, and bromodomain testis-specific protein (BRDT). BRD4, an epigenetic reader, is one of the most important BET proteins and plays an important role in angiogenesis and the development of inflammation-associated diseases, cardiovascular diseases, central nervous system disorders and cancers . Similarpoptosis . The seqpoptosis . BRD4 ispoptosis . Consequ50 values , that exhibits significant anti-angiogenic effect in chick embryo chorioallantoic membrane (CAM) and yolk sac membrane (YSM) models. This inhibitor can also directly suppress the viability and tube formation of human umbilical vascular endothelial cells (HUVECs). Herein, we also report the mechanistic findings of this inhibitor to suppress angiogenesis by regulating the phosphorylation of AP-1 transcription factors c-jun and c-fos.Through the screening of our in-house compound library targeting BET family proteins , we have1), was purchased from Sigma-Aldrich . The stereoisomer of active (+)-JQ1, (−)-JQ1, which fails to significantly interact with any bromodomain of BET family members and was purchased from MedChemExpress  as a negative control. Each compound was dissolved in dimethylsulfoxide  at a concentration of 20 mg/ml and maintained at −80°C. All the compounds of the in-house chemical library targeting BET family members were designed and synthesized by Dr. Zhou’s laboratory at the University of Texas Medical Branch (UTMB) following previously reported protocols (7) was synthesized according to the detailed procedures described in the patent WO2018112037 A1, filed by the UTMB OTT, and a recent publication (2) and ZL0513 (7), was 98.0 and 97.3%, respectively, which was determined using HPLC analysis -JQ1  were obtained from American Type Culture Collection . The cells were grown in endothelial cell growth medium supplemented with growth supplements  and cultured at 37°C in a humidified incubator supplemented with 5% CO2) was cut above the air chamber of egg while the chick embryo was growing through the ninth day. BET family member inhibitors or DMSO  were placed directly onto the live chick embryo CAM through the window at the indicated concentrations and incubated for 48 h. Then, the eggshells were cut carefully along the axis of the median line, and the content was discarded. The CAM vasculature around the eggshell windows was observed and photographed under a stereomicroscope (Olympus SZX16). The microvessel density (MVD) was calculated as the percentage of blood vessel area in the total drug-treated area using the Image-Pro Plus 6.0 software .Fertilized white leghorn chicken eggs were obtained from the Avian Farm of South China Agriculture University  and the shells were cleaned with 1% geramine. The eggs were incubated under 50–60% humidity at 37.5°C. A small window  was added into the center of the rings and cultured in the incubator for 24 h. Images of the vessels in the silastic rings were captured at 0 and 24 h, respectively. The images were quantitatively analyzed by Image-Pro Plus 6.0, and then the number of blood vessels 24 h after drug treatment and the MVD at 0 and 24 h were quantified using IPP 6.0. The growth rate in the DMSO-treated silica gel circle was considered to be one.50 values of the tested BET family member inhibitors for the BRD4 and BRD2 proteins bromodomains (BDs) were detected using a commercially available TR-FRET assay kits  according to the manufacturer’s instructions and our recent publications -JQ1 (negative control drug) and DMSO (solvent group) were added at the indicated concentrations. Forty-eight hours after treatment, 10 μl of CCK-8 reagent was added to each well and incubated at 37°C for an additional 3 h. The absorbance was evaluated at 450 nm to determine cell viability.7), (+)-JQ-1 (1), (−)-JQ1, or DMSO for 48 h were harvested and seeded in a Matrigel-precoated 96-well plate at a density of 3 × 104 cells/well. At the same time, the cells were also treated with the same dose of ZL0513 (7), (+)-JQ-1 (1), (−)-JQ1, or DMSO in endothelial cell growth medium without growth supplements. Then, the cells were maintained at 37°C for an additional 5 h to observe the inhibitory effects of ZL0513 (7), (+)-JQ-1 (1), (−)-JQ1, and DMSO on the angiogenic ability of vascular endothelial cells. The circumference of the formed tubes was measured under an inverted light microscope.The HUVECs treated with 8.5 μM ZL0513 (1), or ZL0513 (7) for 48 h. Then, the proteins of these cells were extracted using RIPA buffer and separated by 10% (w/v) sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). The separated proteins were transferred onto a polyvinylidene fluoride (PVDF) membrane  and blocked using 5% (w/v) non-fat powder milk at room temperature. Next, the membranes were incubated in the relative primary antibody and horseradish peroxidase (HRP)-conjugated secondary antibodies. Then, the Image Quant LAS 4000 system  was used for the direct visualization of the membranes. The protein bands were densitometrically quantified using Quantity-One protein analysis software . The relative expression of the proteins was normalized to the expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH).HUVECs were treated with DMSO, (−)-JQ1, (+)-JQ1  were considered to indicate a significant difference.All the data are presented as the means ± standard deviation (SD) from three independent experiments. Student’s 1), ZL0454 (2), and MS436 (3), as well as other representative compounds that are selected from a primary assay used to explore anti-angiogenesis through functional studies. Specifically, the (+)-JQ1, a widely used BET family member inhibitor, was employed as the positive control for comparison.Given that a number of small molecular BET inhibitors and their cocrystal structures with BET family members are available, we have designed and synthesized an in-house chemical library by targeting BET family proteins through structure-based drug design, fragment-based drug design, and computer-aided drug design . The pre1), ZL0454 (2), MS436 (3), ZL0513 (7), ZL0519 (9), and ZL0549 (11) showed the strongest positive inhibition (+++) of angiogenesis among all the selected compounds in the library. Representative photographs of CAMs after treatment with DMSO or strong inhibitory drugs are shown in The effects of all these selected compounds on angiogenesis were first determined through use of the chick embryo CAM model. The CAM assay is a well-established model for screening anti-angiogenic agents, because the ability of compounds to prevent blood vessel formation can be easily detected . Each of1), ZL0454 (2), MS463 (3), and ZL0513 (7) exhibited the most impressive inhibitory effect on MVD (3) and ZL0513 (7) on MVD was better than that of the (+)-JQ1 positive control. The structures of all these compounds are shown in Then, the anti-angiogenic impact on the growth of the blood vessel branch by the selected BET inhibitors in the chick embryo CAM model was quantified using IPP software. The statistical analysis showed that, among these selective compounds, (+)-JQ1 (2), MS463 (3), and ZL0513 (7) applied at different concentrations. Compounds of 25, 50, and 100 μM were added to the CAM of 9-day-old chick embryos and incubated for 48 h, and then, the CAMs were photographed for further analysis of the anti-angiogenic drug efficacy. The results showed a dense capillary plexus and multiple tiny capillaries originating from terminal capillaries in the DMSO group (2), MS463 (3), or ZL0513 (7) compared with that of the group treated with DMSO (1), MS463 (2), and ZL0513 (7) significantly inhibited MVD in a concentration-dependent manner (1), MS463 (2), and ZL0513 (7) exhibited stronger inhibitory efficacy than (+)-JQ1 on MVD at each of the treated concentrations.We confirmed the angiogenic inhibition efficacy of ZL0454 (1), ZL0454 (2), MS463 (3), and ZL0513 (7) was also evaluated through a comparison with that of its close family member BRD2. Then, the IC50 of the compounds that prevent BRD4 (BD1 or BD2)/BRD2 (BD1 or BD2) and acetylated histone interactions was calculated by TR-FRET assay in vitro. As shown in 1), MS436 (2), and ZL0513 (7) exhibited significant inhibitory activity towards BRD4 over BRD2. In addition, ZL0454 (1) showed no preference between BD1 and BD2, as previously reported (2), ZL0513 (7) exhibited a potent preference towards BRD4 BD1 over BRD4 BD2. Moreover, the IC50 value of ZL0513 (7) was higher than that of MS436 (2). As presented in our recently published report, ZL0513 (7) exhibits a potent preference towards BRD4 BD1 but not the other BET family members or the BD2 domain (7) may be a new potent BRD4 inhibitor for use as an orally bioavailable pharmacological tool to further explore the biological functions of the BD1 domain of BRD4.As acetylated histone peptides are known substrates for bromodomain-containing proteins, we initially screened the complexes for their ability to modulate the protein–protein interaction between acetylated lysine and BET family members. The BRD4 selectivity profile of (+)-JQ1 (reported . Similar2 domain . Collect7) because of its potent inhibitory effect against angiogenesis compared with positive control groups. Furthermore, ZL0513 (7) was selected for further analysis of the anti-angiogenic role of the BRD4, and (+)-JQ1 (1) was used as a reference compound for comparison. ZL0513 (7) and (+)-JQ1 (1) was added at 100 μM to the YSM of 3-day-old chick embryos, which were then photographed at the indicated times for further analysis of the anti-angiogenic drug capabilities. As shown in 1) and ZL0513 (7). The statistical analysis showed that the blood vessel density and the number of blood vessels were significantly reduced after 24-h treatment with (+)-JQ1 (1) and ZL0513 (7) compared with that after DMSO treatment (7) inhibition efficacy on angiogenesis in the chick embryo YSM was significantly higher than that of (+)-JQ1 (1) treatment.The chick embryo YSM model, another well-developed model for screening anti-angiogenic drugs, was employed to confirm the anti-angiogenic role of ZL0513 (7) possesses an inhibitory effect similar to that of JQ1 on the viability of HUVECs, focusing on a drug concentration range from 0.3 to 15 μM. Furthermore, (−)-JQ1 was employed as a negative control, and DMSO was employed as a solvent control. ZL0513 (7), similar to (+)-JQ1 (1), could inhibit cell viability in a concentration-dependent manner with the 50% inhibition at 8.5 μM (1) suppressed cell viability at a slightly lower 50% inhibition concentration (5 μM) than that of ZL0513 (7). Applied as 96-h posttreatments at a concentration of 8.5 μM, (+)-JQ1 (1) and ZL0513 (7) each significantly suppressed cell viability compared with the effect of DMSO or (−)-JQ1 in HUVECs (A previous report indicated that JQ1 significantly inhibited the viability of HUVECs in a concentration-dependent manner . Therefo7) in vitro through a tube formation assay. HUVECs were seeded on Matrigel, and then treated with (+)-JQ1 (1) and ZL0513 (7) at 8.5 μM and allowed to form tubes. As shown in 1) or ZL0513 (7) was smaller than that of the tubes treated with DMSO or (−)-JQ1. The statistical analysis showed that a reduction in tube circumference was observed in both the (+)-JQ1 (1)- and ZL0513 (7)-treated groups, compared with that in the cells treated with DMSO. In addition, (−)-JQ1 had no inhibitory effect on tube formation compared with that induced by DMSO. However, the length of tubes was not significantly different in the (+)-JQ1 (1)- and ZL0513 (7)-treated groups.In addition, we examined the anti-angiogenic role of ZL0513 (1) inhibited AP-1 activity and further decreased the expression of the AP-1 component FOSL1 in HUVECs (1) and ZL0513 (7) could inhibit the expression of c-jun and c-fos, other components of AP-1. The results showed that, compared with DMSO, both (+)-JQ1 (1) and ZL0513 (7) significantly inhibited the expression of c-jun, but not c-fos, and the phosphorylation of both c-jun and c-fos (A previous report indicated that (+)-JQ1  has a better selectivity of BRD4 over BRD2 at the similar level to that of ZL0580, another BRD4 inhibitor we recently reported (7) can markedly suppress angiogenesis.BET family members  contain two highly conserved bromodomains (BD1 and BD2), an ET domain, and a C-terminal domain. Disrupting the interactions between BET bromodomains and acetylated lysine residues is one of the most drug-induced therapeutic approaches and can effectively inhibit cancer and inflammation . Thereforeported . In our reported . Furtherreported . Since t2), which are BRD4-selective but not BD1 and BD2 bromodomain- selective inhibitors, inhibited acute airway inflammation (7), which can significantly inhibit angiogenesis. In our recently published report, we demonstrated that ZL0513 (7) exhibited potent preference towards BRD4 BD1 but not the other BET family members or the BD2 domain, a finding unambiguously validated by co-crystal structure of the inhibitor in complex with the human BRD4 BD1 protein (7) was also determined by examining the level of H3K122Ac. ZL0513 (7) was also found to block poly(I:C)-induced H3K122Ac (7) functions as a BRD4 inhibitor, and the BRD4 possesses pro-angiogenic capabilities and plays an important role in angiogenesis-related diseases.The bromodomains BD1 and BD2 have been validated as epigenetic reader domains that selectively recognize acetylated lysine residues on the tails of histone proteins and non-histone proteins and are used to investigate pan-BET inhibitors in various diseases . Among aammation . Therefo protein . Since BH3K122Ac . In summAP-1 can mediate VEGF-induced HUVEC migration and proliferation . Among m7) that exhibit significant anti-angiogenic effects in CAM and YSM models. This inhibitor can also directly inhibit the viability and tube formation capability of HUVECs. Moreover, ZL0513 (7) was found to inhibit the phosphorylation of c-jun and c-fos, important members of AP-1 transcription factor complexes that enhance angiogenesis. The findings on this novel BRD4 inhibitor suggests that, in addition to being a powerful pharmacological tool for further elucidating the roles and functions of BRD4 and its BD domains in angiogenesis, it may also serve as a potential therapeutic strategy for targeting the vasculature in various angiogenesis-dysregulated human diseases.In summary, we have identified a potent BRD4 inhibitor ZL0513 , Natural Science Foundation of Guangdong Province (Grant number 2018A030313186), UTMB Technology Commercialization Program, Sanofi Innovation Awards (iAwards), Crohn’s & Colitis Foundation Entrepreneurial Investing (EI) Initiative award, Research Fellowship Award from the Crohn’s & Colitis Foundation of America (Grant number 548813), and Innovation and university promotion project of Guangdong Pharmaceutical University (Grant number 2017KCXTD020).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In terms of risk assessment, C. elegans has been a successful animal model for toxicological profiling as it allows for monitoring of vital physiological endpoints such as body length, locomotion, development, brood size, and survival (Meyer and Williams 2014). We have previously shown that TCS disrupts SKN-1/Nrf2-mediated oxidative stress response in C. elegans larvae . Here, we examine the hatching rate of C. elegans wild-type (N2) embryos in response to acute TCS exposure (see Methods). As shown in Fig. 1B-1D, TCS caused pronounced shrinkage of the inner cell mass of embryos in a dose-dependent fashion. As the inner cell mass shrinks, we speculate that TCS may disturb the osmotic regulation of the developing embryo. Of note, we have recently reported that non-ionic surfactants antagonize the toxicity of phenolic endocrine-disrupting chemicals in C. elegans larvae . Likewise, the non-ionic surfactant polysorbate 20 , significantly ameliorated TCS-induced mortality and restored hatching to physiological rates . Since hydrophobic substances may be emulsified in micelles formed by non-ionic surfactants, we suggest that Tw20 may inhibit TCS-induced embryonic mortality by micellar solubilization.Triclosan (TCS) is a chlorinated, phenolic antimicrobial  widely used in personal care products, such as antiseptics and disinfectants, and as an additive in cosmetics, household cleaners, plastics, paints, and textiles, among others (Alfhili and Lee 2019). Despite restricted commercial use in the USA, TCS is still detected at very high rate in human samples (Weatherly and Gosse 2017), possibly because of increased use in building materials, or older polypropylene copolymers (PPCs). TCS has raised concerns regarding its health risks and environmental impact (Alfhili C. elegans wild-type Bristol isolate (N2) worms were obtained from the Caenorhabditis Genetics Center (CGC). Toxicity assay was conducted using TCS and Tw20. Embryos were obtained from adult wild-type (N2) worms using 5 mL alkaline-bleaching solution as per . The embryos were treated with 0, 0.1, 0.2, 0.5, and 1 mM TCS in the absence or presence of 0.1% Tw20 for 1 hour at 20°C. TCS-treated embryos were washed three times with M9 buffer solution to remove remaining TCS and then incubated in M9 buffer solution with or without Tw20 at 20°C for 20 hours. The hatching rate was determined by scoring hatched, L1-staged larvae and dead embryos under a dissecting microscope. The morphology of control and TCS-treated worms was examined by DAPI staining. TCS-treated worms were fixed in 3% Paraformaldehyde for 20 minutes at 20°C and post-fixed in cold 100% methanol for 5 minutes at 20°C. The fixed worms were washed three times with 1x PBST solution and stained with 100 ng/mL DAPI for 10 minutes at 20°C. The morphology of DAPI-stained worms was observed under a fluorescence microscopy.Triclosan  phenol; TCS) and Tw20 (Polysorbate 20) were purchased from Sigma Aldrich .2O, 20 mL commercial bleach, 5 mL 10 N NaOH.1. Alkaline-bleaching solution: 75 mL H2. TCS stock and working solutions: TCS was dissolved in ethanol as a solvent (100 mM stock). TCS stock solution was diluted to working solutions of 0.1, 0.2, 0.5, and 1 mM in M9 buffer solution with or without 0.1% Tw20.2PO4, 6 g Na2HPO4, 5 g NaCl, and 0.25 g MgSO4 per liter.3. M9 buffer: 3 g KH2HPO4 (pH7.2).4. 3% paraformaldehyde fixation solution: 16% EM grade paraformaldehyde (EM Sciences) is diluted to a final concentration of 3% in 0.1 M K2O.5. 1x PBST (10 mL): 1 mL 10x PBS, 0.01 mL 100% Tw20, 8.99 mL H