POS0021 CHANGES OF GUT MICROBIOTA IN CONNECTIVE TISSUE DISEASE AND ITS RELATIONSHIP WITH LYMPHOCYTE SUBSETS AND CYTOKINES

Background

Connective tissue disease (CTD) is a group of autoimmune diseases characterized by the damage of connective tissue components in various parts of the body, which involved multiple organs and systems. Dysbiosis in the gut microbiome is associated with various autoimmune diseases such as CTD.

Objectives

To explore the characters of gut microbiota and their relationship with peripheral lymphocyte subsets and cytokines in patients with CTD.

Methods

Stool samples were collected from 63 CTD patients and 63 age- and sex-matched healthy controls(HCs). Microbial genomes were extracted for 16S rRNA gene sequencing. Gut microbiota characters (alpha diversity, beta diversity, and microbial composition) were analysed by R (version 4.0.1). Peripheral lymphocyte subsets were assessed by flow cytometry. Pearson correlation analysis was used to detect the correlation between the relative abundance of genus in the sample and the activity index; correlations with p < 0.05 were considered significant.

Results

Shannon and Simpson index revealed a decreased alpha diversity in CTD compared with that of HCs (p < 0.05), though not significantly difference in ACE and Chao1 parameters (p > 0.05, Figure 1A). Bray curtis distance-based beta-diversity analysis indicated significant differences in microbial communities between CTD and HCs (p = 0.0014, ANOSIM, Figure 1B). At the genus level, CTD patients had higher abundances of Terrisporobacter (p<0.01), Paraprevotella (p<0.01), CAG−352 (p<0.01), et al. but lower abundances of Streptococcus (p<0.01), Pseudomonas (p<0.01), Bacteroides(p<0.01), et al (Figure 1D). IgM was positively correlated with Lactococcus (p<0.05), Family_XIII_AD3011_group (p<0.05), Streptococcus (p<0.05). Th17 was positively correlated with Pseudomonas (p<0.01). Th2 was positively correlated with Christensenellaceae_R−7_group (p<0.001), UCG−010 (p<0.001) was positively correlated. Treg and Th2 were positively correlated with Christensenellaceae_R−7_group (p<0.01), UCG−010 (p<0.01). Treg was positively correlated with Lachnoclostridium (p<0.05) (Figure 1E).

Conclusion

Pattients with CTD had disbiosis of gut microbiota charaterized by impared diversity and abnomal composition,which was closely correlated with peripheral lymphocyte subsets.

References

[1]Laura Ghezzi,Claudia Cantoni,Gabriela V Pinget,et al.Targeting the gut to treat multiple sclerosis.J Clin Invest.2021 Jul 1;131(13):e143774. doi: 10.1172/JCI143774.

[2]Yoshihiko Tomofuji,Toshihiro Kishikawa,Yuichi Maeda,et al.Whole gut virome analysis of 476 Japanese revealed a link between phage and autoimmune disease.Ann Rheum Dis. 2022 Feb;81(2):278-288. doi: 10.1136/annrheumdis-2021-221267. Epub 2021 Dec 8.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0745 GUT DYSBIOSIS ASSOCIATED WITH PERIPHERAL LYMPHOCYTES AND CYTOKINES IN PATIENTS WITH SJÖGREN’S SYNDROME

Background

Primary Sjögren’s syndrome (pSS) is a systemic autoimmune disease characterized by disorders of lymphocyte subpopulations with various cytokines and auto-antibodies1. Growing evidences suggest that gut microbiome dysbiosis may contribute to the development of pSS2.

Objectives

To investigate the alterations to the gut microbiome and the correlation with peripheral lymphocytes and serum cytokines as well as inflammatory factors in pSS patients.

Methods

A total of 101 pSS patients and 101 age- and sex- matched healthy controls (HCs) were enrolled in this study from The Second Hospital of Shanxi Medical University (Taiyuan, Shanxi, China). Patients fulfilled the 2019 ACR/EULAR classification criteria. We conducted 16S rRNA gene sequencing using fecal microbiota samples and analyzed the peripheral lymphocyte subsets by flow cytometry. Serum cytokines, erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), unstimulated and stimulated whole saliva (UWS and SWS) secretion rate was also collected, respectively. Sequence data were compiled and processed using Qiime2 and OTU-profiling tables were constructed. Correlations between different taxa and gut microbiome, as well as clinical variables, were calculated by Spearman’s rank test.

Results

Patients with pSS exhibited a significant reduction in the richness and diversity of gut microbiota compared with those of HCs (Figure 1A-B, p < 0.05). Detailly, at the phylum level, pSS patients had a lower frequency of Firmicutes while higher Proteobacteria (Figure 1C, p < 0.05). Compared with HCs, 11 species of flora were discovered to be distinctly different at the genus level (p < 0.05). Patients presented fewer Faecalibacterium and Roseburia but more Lactobacillus (Figure 1D, p < 0.05). Lactobacillus negatively correlated with T cells (r=-0.407), CD8+T (r=-0.417) and Th2 (r=-0.323). There was a significant positive correlation between Faecalibacterium and IL-2(r=0.312), IFN-γ(r=0.338), TNF-α levels(r=0.322) (Figure 1E, p < 0.05). As for clinical disease measures, IL-6 increases were in line with ESR and CRP, while IL-2 levels inversely related to CRP. Additional UWS secretion rate and SWS secretion rate had negative correlation with ESR (Figure 1F, p < 0.05).

Conclusion

The structural disorder of gut microbiota was distinct in pSS which were associated with peripheral lymphocyte subsets and cytokines. Disorders of gut microbiota and immune systems may contribute to the occurrence and development of pSS.

References

[1]Mariette X, Criswell LA. Primary Sjogren’s Syndrome. N Engl J Med 2018;378(10):931-39. doi: 10.1056/NEJMcp1702514

[2]Trujillo-Vargas CM, Schaefer L, Alam J, et al. The gut-eye-lacrimal gland-microbiome axis in Sjogren Syndrome. Ocul Surf 2020;18(2):335-44. doi: 10.1016/j.jtos.2019.10.006

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0449 CHARACTERISTICS OF GUT MICROBIOTA AND ITS RELATIONSHIP WITH LYMPHOCYTE SUBSETS AND CYTOKINES IN PATIENTS WITH UNDIFFERENTIATED SPONDYLOARTHRITIS

Background

Gastrointestinal microbiota, particularly dysbiosis of gut microbiota composition have been correlated with the progression of autoimmune disorders, such as undifferentiated spondyloarthritis (USPA).

Objectives

This study aimed to identify the changed gut microbiota and its relationship with lymphocyte subsets and cytokines in USPA Patients.

Methods

A total of 210 participants were recruited in this study, comprising 105 USPA patients and 105 age and sex-matched healthy controls (HCs). Microbial genome was extracted from approximately 250mg fresh fecal samples from all participants using QIAamp PowerFecal DNA Kit (Qiagen). The V3-V4 variable regions of bacterial 16S rRNA genes were sequenced with the Illumina Miseq PE300 system. QIIME2 was used to process representative sequence clusters with a similarity cutoff of 100% (ASVs)1. Microbial diversity was estimated by the alpha diversity (observed, chao1, ACE, shannon, simpson, and ivsimpson) and beta diversity (bray distance). Biomarker species were identified based on STEMP between USPA and HC group. Correlations were analyzed with the Spearman rank correlation test.

Results

The alpha-diversity indices have no significant different between two groups (P >0.05, Figure 1A). Gut microbial community structure differed between USPA and HC, as revealed by ASV Bray–Curtis distances (P <0.05, Figure 1B). As for composition of gut microbiota, there were the increased levels of Escherichia_Shigella, Flavonifractor, Hungatella in the USPA group, and Lachnospirales, Roseburia, and Lachnospiraceae in HCs (Figure 1C). The relative abundance of Lachnospiraceae_UCG_001 and Enterobacter was negatively correlated with the absolute numbers of Th17 (P<0.05). Bifidobacterium was positively correlated with the absolute number of Th1 and Tregs (P<0.01, Figure 1D). The relative abundance of Fusobacterium, Incertae_Sedis, and Colidextribacter were negatively correlated with the absolute numbers of Il-10, IL-4, and IL-2 (P<0.05). Prevotella and Enterobacter were positively correlated with the absolute number of IL-6 and IL-4 respectively (P<0.05, Figure 1E). Bifidobacterium and Bilophila were neagtively correlated with the absolute number of NK cell (P<0.05, Figure 1F).

Figure 1.

(A) Comparison of alpha-diversity indexs between HC and USPA groups was shown using boxplot. (B) β diversity of the gut microbiome in USPA patients and HCs. Principal coordinate analysis plot generated from the bray distance analyse. (C) STEMP was used to detect difference in Flora according to USPA and HC. (D-F) Relationship between gut microbiota, and Lymphocyte subsets as well as cytokines. *P<0.05, **P<0.01.

Conclusion

Gut dysbiosis in USPA patients mainly characterized by reduced the diversity and impaired abundance of the intestinal flora, which was closely related to the disturbance of lymphocyte subpopulations and cytokines.

References

[1]Han L, Zhao K, Li Y, et al. A gut microbiota score predicting acute graft-versus-host disease following myeloablative allogeneic hematopoietic stem cell transplantation. Am J Transplant 2020;20(4):1014-27. doi: 10.1111/ajt.15654 [published Online First: 2019/10/13]

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

POS0330 DIFFERENCES IN GUT MICROBIOTA ASSOCIATED WITH LYMPHOCYTE SUBSETS, CYTOKINES AND DISEASE ACTIVITY IN ANKYLOSING SPONDYLITIS

Background

Ankylosing spondylitis (AS), a common chronic inflammatory disease, is a prototype of spondyloarthritis affecting sacroiliac joints and spine with or without peripheral arthritis and other systemic symptoms[1]. Environmental factors, especially microorganisms have been suggested to implicate with AS pathogenesis[2].

Objectives

Utilizing 16S rRNA genes sequencing on the feces of untreated AS patients and healthy controls (HCs), our study aimed to provide an in-depth understanding of AS gut microbiota and identifying a feasible diagnostic strategy for AS.

Methods

Fecal samples were collected from 62 AS patients and 62 age-and-gender- matched HCs. Microbial genome was extracted from approximately 250mg fresh fecal samples from all participants using QIAamp PowerFecal DNA Kit (Qiagen). The V3-V4 variable regions of bacterial 16S rRNA genes were sequenced with the Illumina Miseq PE300 system. QIIME2 based pipeline was used to process the raw sequence data. Alpha and beta diversities were assessed using result from QIIME2, and comparisons of gut microbiome profile were performed using linear discriminant analysis (LDA) effect size (LEfSe) to examine differences between AS and HCs. R (version 4. 0.1) was used for comparative statistics, and pearson’s correlation was used to assess the correlations between the relative abundances of bacterial genera and clinical parameters; correlations with p<0.05 were considered significant.

Results

AS for alpha-diversity, ACE and Chao1 indices were lower in AS compared with those HCs(Figure 1A, p<0.05), though no significant differences observed in Shannon and Simpson index. Bray curtis distance-based beta-diversity analysis revealed significant differences in the microbial community between AS and HCs (Figure 1B, p=0.003, ANOSIM). Fecal microbial communities in AS differed significantly from those in HCs, driven by higher abundances of Escherichia-Shigella, Turicibacter, Enterococcus, et al. and a lower abundance of Agathobacter, Roseburia, Eubacterium_eligens_group, et al (Figure 1C, p<0.05). There was a significant positive correlation between ESR and Klebsiella, Butyricicoccus, Roseburia, CRP and Faecalibacterium, Muribaculaceae, ASDAS-CRP score and Faecalibacterium, Ruminococcus, total lymphocyte cells and Agathobacter, Ruminococcus, T cell and Agathobacter, CD4+T cell and Agathobacter, B cell and Agathobacter, Streptococcus, Th1 and Prevotella, CAG−352, Th2 and Agathobacter, Th17 and Prevotella, Agathobacter, IL-2 and Agathobacter, IL-4 and Agathobacter, IL-6 and Lachnospiraceae_UCG−004, Muribaculaceae, IL-17 and Eubacterium_hallii_group, IFN-gama and Phascolarctobacterium.There were negative correlations between total lymphocytes and Escherichia−Shigella, CD4+T cell and Enterobacteriaceae, Th2 cell and Escherichia−Shigella, IL-10 and CAG−352, Ruminococcus (Figure 2, p<0.05).

Figure 1.

Feature of gut microbiota in AS patients and HCs. (A) Alpha-diversity assessed by richness (Chao1, ACE) and diversity (Shannon, Simpson), Median estimates compared across cohorts. (B) PCoA plot based on the Bray curtis distance of gut microbiota samples from AS patients vs. HC group(p=0.003, ANOSIM). (C) Panel demonstrated the average relative abundance of different genus in AS and HCs. (D) Distribution of gut microbiota at genus level.

Figure 2.

Correlations between the relative abundance of significantly different bacteria and clinical variables. *p<0.05, **p < 0.01, ***p <0 .001, ****p < 0.0001.

Conclusion

Human gut microbiome in patients with AS differed from that of the HCs. Characters of bacteria communities were associated with disease activity.

References

[1]Simone D, Al Mossawi M H, Bowness P. Progress in our understanding of the pathogenesis of ankylosing spondylitis [J]. Rheumatology (Oxford), 2018, 57(suppl_6): vi4-vi9.

[2]Zhou C, Zhao H, Xiao X Y, et al. Metagenomic profiling of the pro-inflammatory gut microbiota in ankylosing spondylitis [J]. J Autoimmun, 2020, 107(102360.

Acknowledgements

This project was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS1353 COMPOSITION AND ASSOCIATIONS OF THE GUT MICROBIOTA IN BECHET’S DISEASE WITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES

Background

Bechet’s disease (BD) is a chronic multisystemic vasculitis with genetic and abnormal immune response. Growing evidences suggests gut microbiota compositional alteration may have an association with immune dysfunction in patients with BD.

Objectives

This study aims to investigate the gut microbiota between BD and healthy controls (HCs) and analyse relevancy between bacterial and peripheral lymphocyte subsets and cytokines.

Methods

Fecal samples obtained from 22 BD patients and 22 normal-age and gender-matched HCs in this study. The gut microbiota were assessed with 16s rRNA sequencing and the flow cytometry was used to dectect peripheral lymphocyte subsets. C-reaction protein (CRP), Erythrocyte sedimentation rate (ESR), complement C3 and C4 were also assigned for disease activity measure. The edgeR package was used for differential abundance analysis. Difference of alpha diversity indices, bacterial abundances, and the F/B ratio were carried out using the Wilcoxon rank-sum test (R v.4.0.1). The differential abundance of flora and CRP, ESR, C3 and C4 between BD patients and HCs was assessed by pearson’s correlation analysis.

Results

As for alpha diversity, the Shannon (p < 0.05) and Simpsonance analysis. Difference of alpha diversity indices, bacterial abundances, and the F/B ratio were carried out using the Wilcoxon rank-sum test (R v.4.0.1). The differential abundamicrobial community structures between BD and HCs (R = 0.053, p = 0.051; Figure 1B). The gut microbiota compositions of BD differed form those of HCs (Figure 1C). Four species of flora distinctly difference were found in BD (p < 0.05; Figure 1D). There was significant positive correlations between Tregs and Verrucomicrobiota (p < 0.05), and Proteobacteria (p < 0.05), Th1 and Proteobacteria (p < 0.05), ESR and Verrucomicrobiota (p < 0.01), but negatives correlation between TNF-α and Desulfobactbiota (p < 0.05; Figure 1E).

Conclusion

Pattients with CTD had disbiosis of gut microbiota charaterized by impared diversity and abnomal composition, which was closely correlated with peripheral lymphocyte subsets and disease activity measures.

References

[1]Margaret Alexander, Qi Yan Ang, Renuka R Nayak, et al. Human gut bacterial metabolism drives Th17 activation and colitis. Cell Host Microbe. 2022 Jan 12;30(1):17-30.e9. doi: 10.1016/j.chom.2021.11.001. Epub 2021 Nov 24.

[2]Yi-Wen Tsai, Jia-Ling Dong, Yun-Jie Jian, et al. Gut Microbiota-Modulated Metabolomic Profiling Shapes the Etiology and Pathogenesis of Autoimmune Diseases. Microorganisms. 2021 Sep 10;9(9):1930. doi: 10.3390/microorganisms9091930.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0492 INTESTINAL MICROBIOLOGICAL DISORDER CLOSELY ASSOCIATED WITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES IN SYSTEMIC LUPUS ERYTHEMATOSUS

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by widespread inflammation and tissue damage in multiple organs[1]. Microbiome is one of environmental factors that has been suggested to contribute to the occurrence and development of SLE[2].

Objectives

This study aims to the understanding of the pathogenesis of SLE from the perspective of intestinal microorganisms and investigate the associations between flora and peripheral lymphocyte subpopulations and cytokines in SLE patients.

Methods

Fecal samples were collected from 96 patients with SLE, and 96 sex-and age-matched healthy controls (HCs). The gut microbiota were investigated via 16s rRNA sequencing and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. Indicators of disease activity such as erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), complement C3 and C4 were recorded. Differential abundance analysis was carried out using the edgeR algorithm. The Wilcoxon rank-sum test was used to compare alpha diversity indices, bacterial abundances, and the F/B ratio between groups. R (version 4.0.1) was used for comparative statistics, and pearson’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and serum levels of ESR, CRP, C3 and C4 in the samples; correlations with p < 0.05 were considered significant.

Results

The alpha estimators of richness (ACE and Chao 1) were significantly reduced in SLE feces samples compared with those of HCs (p < 0.0001). Bacterial diversity estimators, including the Shannon (p < 0.001) and Simpson’s (p < 0.01) indices, were also significantly lower in SLE (Figure 1A-D). The microbial community structures of the SLE and HCs could be separated by unweighted UnFrac-based principal coordinates analysis (PCoA) (R = 0.186, and p = 0.001; Figure 1E). Significant differences in gut microbiota composition between SLE and HCs were found using the edgeR algorithm. Compared with HCs, 24 species of flora were discovered to be distinctly different(p < 0.05). Moreover, there was a significant positive correlation between Tregs and Corynebacterium(p < 0.05), CD8+T and Corynebacterium (p < 0.05), CD4+T and Corynebacterium (p < 0.05), T and Corynebacterium (p < 0.05), Th1 and Escherichia−Shigella (p < 0.01), Th2 and Dielma (P<0.001) as well as Eubacterium eligens group (p < 0.05), NK and Faecalibacterium (p < 0.01). as well as Corynebacterium (p < 0.001), IL-6 and Coprococcus (p < 0.05), IL-10 and Eubacterium eligens group (p < 0.001) as well as Veillonella (p < 0.05). and Lachnospira (p < 0.01). As for clinical disease measures, there were positive correlations between CRP and Eubacterium ventriosum (p < 0.05). and Coprococcus (p < 0.05), C4 and the abundance of Corynebacterium (p < 0.05) (Figure 1F).

Conclusion

Patients with gut dysbiosis that mainly characterized by reduced the diversity and impaired abundance of the intestinal flora. Abnormality of T cell subsets and cytokines, especially the level of CD4+T, CD8+T, NK, Treg, Th, IL-6 and IL-10 cells contributes to the occurrence and progression of SLE, which may be related to the disturbance of gut microbiota. The discovery of the associated intestinal microbiota of SLE may provide a new idea for treatment.

References

[1]Fava A, Petri M. Systemic lupus erythematosus: diagnosis and clinical management. J Autoimmun. (2019) 96:1–13. 10.1016/j.jaut.2018.11.001

[2]He Z, Shao T, Li H, Xie Z, Wen C: Alterations of the gut microbiome in Chinese patients with systemic lupus erythematosus. Gut pathogens 2016, 8:64.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0556 ALTERATION OF THE GUT MICROBIOTA IN CHINESE POPULATION WITH RHEUMATOID ARTHRITIS

Background

Rheumatoid arthritis (RA) is an aggressive immune-mediated joint disease characterized by synovial proliferation and inflammation, cartilage destruction, and joint destruction. Growing evidences suggests a chronic inflammatory response induced by gut microbiome critically contribute to the development of rheumatoid arthritis.

Objectives

The aim of this study was to evaluate and quantify differences in the composition of gut microbiota in RA patients and investigate the associations between flora and clinical variables in RA patients.

Methods

Fecal samples from 145 RA patients and 145 age- and gender- matched healthy controls (HCs) were collected for bacterial 16S rRNA genes sequencing. The alpha-diversity, beta-diversity and the microbial composition (at the phylum and genus level) analysis of the gut microbiome were used to define the difference of gut microbiota profiles between RA patients and HCs. The peripheral lymphocytes of these patients were assessed by flow cytometry, and inflammatory biomarkers (ESR, CRP), auto-antibodies(ACPA, MCV) and cytokines measured by ELISA were recorded. Correlations between different taxa and clinical variables, were calculated by Spearman’s rank test.

Results

Consistent with trends observed for diversity, patients with RA had a lower richness compared with those of HCs (p < 0.01, Figure 1a), suggesting gut microbiome was markedly less diverse in composition in RA. Bray curtis distance-based beta diversity analysis revealed significant differences in the microbial community between RA and HCs (ANOSIM, R2=0.061, p=0.001, Figure 1b). Ten selected taxonomic biomarkers at different phylogenetic levels showed great discriminant ability, with Log10 LDA score > 4.0 (Figure 1e-g). Detailly, at the phylum level, RA patients had a lower frequency of Firmicutes while higher Proteobacteria. RA patients presented fewer Faecalibacterium but more Escherichia_Shigella at the genus level (Figure 1c-d). PICRUSt analysis found that in the KEGG pathways, the microbial gene functions related to Propanoate metabolism were higher in the fecal microbiome of RA patients (Figure 1h). Escherichia_Shigella positively correlated with ACPA antibodies (r=0.176, p < 0.05) and IL-4 (r=0.204, p < 0.05, Figure 1i), wheras Faecalibacterium as a probiotic showed no significant correlation with our clinical measures.

Figure 1.

Conclusion

Specific gut microbiota played an important role in the pathogenesis of RA, which may aid in the diagnosis or determination of the susceptibility of individuals to RA via detection of the gut microbiome.

References

[1]de Oliveira GLV, Leite AZ, Higuchi BS, et al. Intestinal dysbiosis and probiotic applications in autoimmune diseases. Immunology 2017;152(1):1-12. doi: 10.1111/imm.12765

[2]Chen J, Wright K, Davis JM, et al. An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis. Genome Med 2016;8(1):43. doi: 10.1186/s13073-016-0299-7

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

POS0143 COMPOSITION AND ASSOCIATIONS OF THE GUT MICROBIOTAWITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES IN IDIOPATHIC INFLAMMATORY MYOPATHIES

Background

The idiopathic inflammatory myopathies (IIM) are a group of acquired myopathies characterized by inflammatory lymphocytes infiltrates in muscle tissue1.Gut microbiota serves as a critical environmental component of autoimmune disease pathogenesis such as IIM2.

Objectives

This study sought to investigate the composition of gut microbiota and the relationship between microbiota structure and lymphocyte subpopulations and cytokines in IIM patients to recommend feasible intervention strategies.

Methods

Faecal samples were taken from 37 IIM patients and 37 age- and gender- matched healthy controls (HCs) in a sterile environment placed into the Second Hospital of Shanxi Medical University. Microbiome profiling was performed by sequencing of the V3-V4 variable regions of the 16S rRNA gene and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. The clinical laboratory data such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and immunoglobulin were also determined. In terms of gut microbia, the diversity and richness was evaluated from two aspects: alpha diversity and beta diversity with the indices of ACE, Chao1, Shannon and Simpson. Analyses were conducted using R version 4.0.1. Pearson correlation was applied to assess the relationship between the relative abundances of bacterial genera and clinical parameters, and p < 0.05 was considered to be statistically significant.

Results

The α-diversity analysis of the richness (Chao1) and diversity (Shannon and Simpson) were reduced in IIM samples compared with those of HCs (Figure 1A, p < 0.05). Bray curtis distance-based beta diversity analysis revealed significant differences in the microbial community between IIM and HCs (Figure 1B, p = 0.001, ANOSIM). Detailly, at the genera level, IIM patients had a higher abundance of Enterococcus, Veillonella, Streptococcus, et al. and a lower abundance of Roseburia, Lachnospira, Klebsiella, et al(Figure 1D, p < 0.05). In IIM patients, Fusobacteriota correlated positively with the ratio of Th1 cells (Figure 1E, p < 0.01), and there was a significant positive correlation between Synergistota and B lymphocyte (Figure 1E, p < 0.01). Besides, Euryarchaeota and Cyanobacteria were both positively and significantly related to IL-6, IFN-γ and C-reactive protein (CRP) (Figure 1E, p < 0.001).

Conclusion

Richness and diversity of intestinal flora in IIM patients were impaired, which might participate in the pathogenesis of IIM by disturbing lymphocyte subpopulations and cytokines. Regulating intestinal flora and restoring homeostasis might become a critical therapeutic methods of IIM.

References

[1]Xu Y, Sun J, Wan K, et al. Multiparametric cardiovascular magnetic resonance characteristics and dynamic changes in myocardial and skeletal muscles in idiopathic inflammatory cardiomyopathy. J Cardiovasc Magn Reson 2020;22(1):22. doi: 10.1186/s12968-020-00616-0.

[2]Mariampillai K, Granger B, Amelin D, et al. Development of a New Classification System for Idiopathic Inflammatory Myopathies Based on Clinical Manifestations and Myositis-Specific Autoantibodies. JAMA Neurol 2018;75(12):1528-1537. doi: 10.1001/jamaneurol.2018.2598.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0500 THE LEVEL OF PERIPHERAL BLOOD LYMPHOCYTE SUBSETS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS WITH RESPIRATORY TRACT INFECTION AND ITS CLINICAL SIGNIFICANCE

Background

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder. Infections are a most common cause of morbidity and mortality in this patient population[1] and at least 50% of patients with SLE are suffered with infections during the course of their disease [2]. Lymphocytes and Natural killer (NK) cells play an important role in the occurrence and development of SLE[3]. In this study, peripheral blood lymphocyte subsets were detected in these patients, providing reference for early diagnosis and treatment of SLE patients with respiratory tract infection.

Objectives

To analyze the detection level and clinical significance of peripheral blood lymphocyte subsets in patients with SLE with respiratory tract infection.

Methods

A total of 333 SLE patients with no recent infection, 95 SLE patients with respiratory tract infection, and 132 healthy individuals matched in age and sex were enrolled in the second Hospital of Shanxi Medical University from July 2014 to December 2016. The characteristics of lymphocyte subsets in the three groups were compared and receiver operating characteristic (ROC) curves were drawn to analyze the predictive value of lymphocyte subsets in SLE patients with respiratory tract infection.

Results

The counts of T, B, CD4 + T, CD8 + T, NK, Th1, Th2, Th17 and Tregs in SLE non-infection group and SLE infection group were [(1094.235 ± 574.495) / (702.781 ± 432.152), t= -7.169, P < 0.001], [(208.338 ± 210.448) / (177.55 ± 170.256), t = -1.306, P = 0.192], [(503.382 ± 303.498) / (304.075 ± 215.497), t = -7.168, P < 0.001], [(536.705 ± 344.218) / (358.034 ± 235.234), t = -5.802, P < 0.001], [(113.898 ± 101.48) / (61.768 ± 50.127), t = -6.831, P < 0.001], [(86.268 ± 89.081) / (47.92 ± 54.174), t = -3.367, P = 0.001], [(11.363 ± 9.834) / (6.628 ± 6.434), t = -3.622, P < 0.001], [(9.537 ± 10.12) / (5.346 ± 4.731), t = -3.646, P < 0.001], [(25.736 ± 27.013) / (20.78 ± 28.083), t =-1.037,P=0.301] (Figure 1).The above indexes in SLE infection group were lower than those in SLE non-infection groups. When lymphocyte subsets predict pulmonary infection in SLE, the AUC value of CD4 + count is the highest, and the cut-off is 387/ μ l(Table 1). The sensitivity and specificity of predicting SLE pulmonary infection were 75.8% and 38.6%(Figure 2).

Table 1.

Predictive value of peripheral blood lymphocyte subsets in SLE complicated with respiratory tract infection

IndicatorAUCP valueJordan indexcut-offSusceptibilitySpecificity(%)(%)B0.5690.04083.99500.1830.4210.238CD40.714<0.0010.3723870.7580.386CD80.682<0.0010.3254050.7260.401CD4+ T /CD8+ T0.5690.0410.0000.7850.5370.370NK0.687<0.0010.30982.50.7680.460

Conclusion

The absolute number of these subsets in infected SLE patients is significantly lower than that in uninfected patients, which indicates that the low absolute number of these cells can be used as an indicator of high infection risk in SLE patients. CD4 + T lymphocytes and NK cells in patients with respiratory tract infection are significantly lower, and can play a certain predictive value for SLE respiratory tract infection to a certain extent.

References

[1]Kedves M, Kosa F, Kunovszki P, Takacs P, Szabo MZ, et al. 2020. Large-scale mortality gap between SLE and control population is associated with increased infection-related mortality in lupus. Rheumatology (Oxford) 59:3443-51

[2]Wang J, Niu R, Jiang L, Wang Y, Shao X, et al. 2019. The diagnostic values of C-reactive protein and procalcitonin in identifying systemic lupus erythematosus infection and disease activity. Medicine (Baltimore) 98:e16798

[3]Luo Q, Kong Y, Fu B, Li X, Huang Q, et al. 2021. Increased TIM-3(+)PD-1(+) NK cells are associated with the disease activity and severity of systemic lupus erythematosus. Clin. Exp. Med.

Disclosure of Interests

None declared

POS0212 THE REDUCTION OF TURICIBACTER IN GUT MICROBIOTA ASSOCIATED WITH SJOGREN’S SYNDROME SECONDARY TO RHEUMATOID ARTHRITIS

Background

Secondary Sjogren’s syndrome(SS) is a common extra-articular manifestation of rheumatoid arthritis (RA)[1]. RA patients combined with SS have different outcomes from those without SS[2]. However, the studies investigated the characteristics of gut microbiota in patients with RA and SS is limited.

Objectives

To investigate the characteristics of gut microbiome and the associations between flora and peripheral lymphocyte subpopulations in RA patients with or without Sjogren’s syndrome.

Methods

A total of 326 samples from 145 RA patients without SS, 23 RA combined with SS patients(RA-SS) and 168 healthy controls (HCs) were recruit in this study from The Second Hospital of Shanxi Medical University (Taiyuan, Shanxi, China). The gut microbiota were investigated via 16s rRNA sequencing and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. The Wilcoxon rank-sum test was used to compare alpha diversity indicesbetween groups. Differential abundance analysis was carried out the STAMP software. Spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical meatures.

Results

Patients with RA and RA-SS exhibited a significant reduction in the richness and diversity of gut microbiota compared with those of HCs (Figure 1 A-B, p < 0.05), whereas there was no significant difference between RA and RA-SS patients. Principal co-ordinates analyses based on bray curtis distance suggested that these there microbiota states explained a definable proportion of observed variance in microbiota composition (ANOSIM R2 = 0.074, p < 0.001; Figure 1 C). Compared with HCs, 58 species of flora were discovered to be distinctly different in RA patients without SS at the genus level of which 6 species of flora unique to RA-SS patients were presented much fewer ([Eubacterium]_hallii_group, Anaerostipes, CAG-56, Fusobacterium, Turicibacter and Enterococcus). Among these RA-SS patients‘ unique species of flora, it seems that Turicibacter is the key species of flora, owing to whose has a positive correlation with most of lymphocytes such as T, B, CD4+T, CD8+T and NK cells suggesting a close association with intestinal immunity.(Figure 1 F-G,P<0.05)

Conclusion

RA patients with deficiency of Turicibacter in flora had higer occurrence of Sjögren’s syndrome sjogren’s syndrome complication, which was correlated with peripherial lymphocyte subpopulations and cytokines.

References

[1]Chen Y, Ma C, Liu L, He J, Zhu C, Zheng F, Dai W, Hong X, Liu D, Tang D et al: Analysis of gut microbiota and metabolites in patients with rheumatoid arthritis and identification of potential biomarkers. Aging 2021, 13(20):23689-23701.

[2]Brown LE, Frits ML, Iannaccone CK, Weinblatt ME, Shadick NA, Liao KP: Clinical characteristics of RA patients with secondary SS and association with joint damage. Rheumatology (Oxf) 2015, 54(5):816-820.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0523 THE ENTEROTYPES OF THE GUT MICROBIOTA IN CHINESE POPULATION WITH AUTOIMMUNE DISEASE

Background

An increasing number of autoimmune disorders (AD) have been associated with microbial dysbiosis[1, 2]. However, this dysbiosis is difficult to characterize for individual patients owing to the high heterogeneity of the gut microbiota. Thus, researchers must find an accurate method of characterizing the AD gut microbiota that is meaningful to clinical diagnosis.

Objectives

The aim of this study was to investigate the enterotype characters of intestinal flora in AD and their associations with peripheral lymphocyte subpopulations and cytokines.

Methods

A total of 339 AD patients and 339 age- and sex- matched healthy controls (HCs) were enrolled in this study. Mathematical modeling using Dirichlet multinomial mixtures (DMM) was applied to describe the variability in the microbiome data and cluster samples into enterotypes. The peripheral lymphocyte subsets were detected by flow cytometry and the cytokines were assessed by ELISA. Differential abundance analysis was carried out the STAMP software. R (version 4.1.0) was used for comparative statistics, and spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical variables.

Results

Laplace approximation of DMM suggested gut microbiota of AD patients and HCs both can be divided into two distinct enterotypes (Figure 1 A-B), and AD E1 and HC E1 were primarily dominated by Prevotella while AD E2 and HC E2 by Bacteroides. Interestingly, the Prevotella-enriched enterotype (AD E1 and HC E1) had a higher alpha diversity than The Bacteroides-enriched enterotype (AD E2 and HC E2). Patients with AD always had a lower richness and diversity compared with those of HCs in each enterotype (p< 0.001), suggesting gut microbiome was markedly less diverse in composition in AD. Bray curtis distance-based beta-diversity were also different (P<0.001, ANOSIM.R =0.23, Figure 1 C-H). Significant differences in gut microbiota composition at the genus level between AD patients and HCs were found using the STAMP software in each enterotype. Compared with HCs, 37 species in AD E1 patients and 40 species in AD E2 patients of flora were discovered to be distinctly different. In the co-upregulated flora of both enterotypes, Lactobacillus was inversely associated with a variety of lymphocytes such as T, CD4+T, NK, Th2, Th17, Treg cells(P<0.05), and positive correlation with IL-10 and IFN-γ(P<0.05,Figure 1 I). However, in the co-downregulated floras Coprococcus had a positive correlation with B, NK and Treg cells, and anaerostipes had a negativate corrleation with IL-2 and IL-4(P<0.05,Figure 1 J).

Conclusion

There were both two enterotypes in patients and HCs with autoimmune disease, E2 exhibited a loss of Prevotella but a growth of Bacteroides, while E1 presented the opposite results, which were closely correlated with peripheral lymphocyte subsets and cytokines.

References

[1]Levy M, Thaiss CA, Zeevi D, Dohnalová L, Zilberman-Schapira G, Mahdi JA, David E, Savidor A, Korem T, Herzig Y et al: Microbiota-Modulated Metabolites Shape the Intestinal Microenvironment by Regulating NLRP6 Inflammasome Signaling. Cell 2015, 163(6):1428-1443.

[2]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS1153 CHARACTERISTICS OF GUT MICROBIOME AND THEIR ASSOCIATIONS WITH PERIPHERAL LYMPHOCYTE SUBPOPULATIONS AND CYTOKINES IN RHEUMATOID ARTHRITIS PATIENTS COMPLICATED WITH OSTEOPOROSIS

Background

Osteoporosis(OP) is one of the major comorbidities of rheumatoid arthritis(RA) which is associated with immune disorders[1]. The gut microbiota has been highlighted to be an important environmental factor to influence immune system in maintaining bone health and regulating bone remodeling[2]. However, the alterations of intestinal flora and its relationship with immune system in RA patients with OP are unclear.

Objectives

To investigate the characteristics of gut microbiome as well as the associations between flora and peripheral lymphocyte subpopulations and cytokines in rheumatoid arthritis patients complicated with osteoporosis.

Methods

Total 28 RA patients were divided into 14 RA-non-OP and 14 gender- and age-matched RA-OP groups according to their bone mineral density (BMD) and the history of fragility fracture. Gut microbiota of participants were investigated by 16s rRNA and peripheral lymphocyte subsets and cytokines were assessed via flow cytometry. Indicators like erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), anti-cyclic citrullinated peptide antibody (ACPA) and anti-mutated citrullinated vimentin (MCV) antibody were recorded meanwhile. Alpha diversity (ACE, Chao1, Simpson, Shannon) and beta diversity indices were analyzed using QIIME2. Biomarker species were recognized based on STEMP. Spearman analysis was adopted for correlation of two variables. All P-values reported herein were two-tailed and P-value<0.05 was taken as statistically significant.

Results

The alpha-diversity have no significant difference between RA-non-OP and RA-OP groups (P >0.05, Figure 1A). The community structure of microflora differed between two groups (P <0.05, Figure 1B). As for the composition of intestinal flora at genus level, Faecalibacterium, Proteus, Catenibacterium, Enterobacter and Erysipelatoclostridium in RA-OP group as well as Lachnospiraceae_ND3007_group, Parasutterella, Megasphaera, Tyzzerella, UCG-005, Clostridium_sensu_stricto_1, UCG-002, Lachnospiraceae_NK4A136_group, Christensenellaceae_R-7_group, Prevotella, Parabacteroides in RA-non-OP group were significantly increased (Figure 1C). There were positive correlations between Lachnospiraceae_NK4A136_group and the level of T, Th1 and Th17 cells, but negative relevance with ESR, CRP and IL-10 (P <0.05). The relative abundance of Faecalibacterium was negatively correlated with IL-2, IL-4, TNF-α and positively with MCV (P <0.05). Clostridium_sensu_stricto_1 and Lachnospiraceae_ND3007_group were negatively correlated with ACPA and MCV respectively as well as IL-2 (P <0.05, Figure 1D-E).

Conclusion

Abnormality of immune system may contribute directly or indirectly to OP in RA, which may be related to the disturbance of gut microbiota.

References

[1]Horta-Baas G, Romero-Figueroa MDS, Montiel-Jarquín AJ, et al. Intestinal Dysbiosis and Rheumatoid Arthritis: A Link between Gut Microbiota and the Pathogenesis of Rheumatoid Arthritis. J Immunol Res. 2017;2017:4835189.

[2]Raterman HG, Bultink IE, Lems WF. Osteoporosis in patients with rheumatoid arthritis: an update in epidemiology, pathogenesis, and fracture prevention. Expert Opin Pharmacother. 2020 Oct;21(14):1725-1737.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0844 Characterizing Gut Microbial Enterotypes in undifferentiated spondyloarthritis

Background

The presence of dysbiosis in the gut microbiome is responsible for the initiation of autoinflammatory and autoimmune diseases. However, such dysbiosis is difficult to characterize in sweeping generalization owing to the high dimensional complexity of the gut microbiota.

Objectives

This study designed to characterize the gut microbial enterotype in patients with undifferentiated spondyloarthritis (USpA) from lower dimensionality and describe the dysbiosis.

Methods

The Fecal samples of 105 patients were diagnosed with USpA and gender- and age- matched 105 healthy controls (HC) were included in the intestinal microbiota composition analyses via Illumina sequencing of bacterial 16S rRNA genes. Microbiota-derived clustering was performed using Dirichlet multinomial mixtures (DMM) modeling. To identify discriminative features in abundance between enterotypes, the Linear Discriminant Analysis Effect Size (LEfSe) algorithm was used with the online interface Galaxy (Log10 LDA score > 4.0). The phyloseq R package to compute alpha diversity (ACE, Chao1, Shannon and Simpson indices), beta diversity (Bray-Curtis dissimilarity) and the microbial composition (at the genus level) to describe the richness and diversity of the microbiota between two enterotypes.

Results

As showed in Figure 1A and C, by evaluating the Laplace approximation to the negative log mode, 2 distinctly enterotypes were identified in the USpA and HC microbiota dataset. LEfSe Analysis indicated the distinctive abundant microbial clades between the 2 enterotypes (LDA score >4) in both the USpA and HC group respectively. At the genus level, Faecalibacterium and Prevotella was the driving genus of enterotype 1 and Bacteroides contributed to enterotype 2 (Figure 1B, D). The alpha-diversity and beta diversity between the distinctive enterotypes was highly significantly different (P < 0.01, Figure 1E, F). Distinct bacterial profiles were also observed in enterotype 1 and 2 (Figure 1G). Interestingly, no significant differences were found between USpA patients and HC for the corresponding same intestinal type. This may be because USpA was at a comparatively early stage of spondyloarthritis (SpA).

Conclusion

Two significantly distinct bacterial microbiota structures existed in the USpA patients which was consistent with the general healthy population.

References

[1]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

OP0087 INTEGRATED SYSTEMS ANALYSIS OF THE GUT MICROBIOTA PHENOTYPES IN THE RHEUMATOID ARTHRITIS

Background

Patients with rheumatoid arthritis (RA) displays extreme dysbiosis in microbiota. However, such dysbiosis is difficult to characterize owing to the high dimensional complexity of the gut microbiota1,2.

Objectives

The aim of this study was to discover the enterotype characters of intestinal flora in RA.

Methods

Fecal samples from 145 RA patients were collected for bacterial 16S rRNA genes sequencing. Mathematical modeling using Dirichlet multinomial mixtures (DMM) was applied to describe the variability in the microbiome data and cluster samples into enterotypes. The alpha-diversity, beta-diversity and the microbial composition analysis of the gut microbiome were used to define the difference of gut microbiota profiles between different enterotypes. The nonredundant taxonomic biomarkers for each enterotype were selected by using LEfSe. Inflammatory biomarkers (ESR, CRP), auto-antibodies(ACPA, MCV), peripheral lymphocytes subsets and cytokines were analyzed in our cohort using the Kruskal-Wallis test.

Results

Laplace approximation of DMM indicated two significantly distinct bacterial microbiota structures (RAE1 and RA E2) existed in the dataset (Figure 1a). Principal co-ordinates analyses confirmed that these two microbiota states explained a reasonable proportion of observed variance in microbiota composition(ANOSIM R2 = 0.267, p = 0.001; Figure 1b), with distinct bacterial genus distribution of in each enterotype (Figure 1c). RA E1 were primarily dominated by Prevotella while RA E2 by Bacteroides. Interestingly, Chao1, ACE, Shannon and Simpson revealed a higher alpha diversity in Prevotella-enriched enterotype (p< 0.001, Figure 1d). Fourteen selected taxonomic biomarkers at different phylogenetic levels showed great discriminant ability, with Log10 LDA score > 4.0 (Figure 1e-g). Further, inflammatory biomarkers (ESR, CRP) and auto-antibodies(ACPA, MCV) as well as the number of T, B and CD4+T, Th1, Th2, Th17, and Treg were consistent in RA E1 and RA E2 (p > 0.05, Figure 2h). But CD8+T were significantly higher in RA E2 than in RA E2 (p < 0.05).

Conclusion

Despite RA gut microbiota being of different dysbiosis, two patterns of dysbiosis, designated as RA-enterotypes, were predominant among the RA patient cohort. RA E2 exhibited a loss of Prevotella but a growth of Bacteroides, while RA E1 presented the opposite results.

References

[1]Arumugam M, Raes J, Pelletier E, et al. Enterotypes of the human gut microbiome. Nature 2011;473(7346):174-80. doi: 10.1038/nature09944

[2]Costea PI, Hildebrand F, Arumugam M, et al. Enterotypes in the landscape of gut microbial community composition. Nat Microbiol 2018;3(1):8-16. doi: 10.1038/s41564-017-0072-8

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

Selective delivery of low-affinity IL-2 to PD-1+ T cells rejuvenates antitumor immunity with reduced toxicity

PD-1 signaling on T cells is the major pathway that limits T cell immunity, but the efficacy of anti–PD-1 therapy has been limited to a small proportion of patients with advanced cancers. We fortuitously observed that anti–PD-1 therapy depends on IL-2 signaling, which raises the possibility that a lack of IL-2 limits anti–PD-1–induced effector T cell expansion. To selectively deliver IL-2 to PD-1⁺CD8⁺ tumor-infiltrating lymphocytes (TILs), we engineered a low-affinity IL-2 paired with anti–PD-1 (PD-1–laIL-2), which reduced affinity to peripheral Treg cells but enhanced avidity to PD-1⁺CD8⁺ TILs. PD-1–laIL-2 exerted better tumor control and lower toxicity than single or mixed treatments. Mechanistically, PD-1–laIL-2 could effectively expand dysfunctional and tumor-specific CD8⁺ T cells. Furthermore, we discovered that presumably dysfunctional PD-1⁺TIM3⁺ TILs are the dominant tumor-specific T cells responding to PD-1–laIL-2. Collectively, these results highlight that PD-1–laIL-2 can target and reactivate tumor-specific TILs for tumor regression as a unique strategy with stronger efficacy and lower toxicity.

Evaluation Algorithm for Team Strength Based on the Collected Healthcare Data through IoT and Smart Devices

In the past, the fans used to evaluate the strength of the team according to the victory and defeat ranking or according to their own intuition and preferences, however, the strength of the team is difficult to measure in analytical figures. The team's winning rate is not the only factor to be considered to determine the strength of the team. There are many factors to be considered for determining the strength of the team. According to the variation coefficient of basketball scoring frequency, the paper designs the principal model of basketball players' pitching target system. The data is captured by IoT devices and smart devices. The algorithm sets the number of the frequency of Gabor filter transformation features, controls the error accumulation, extracts the cascade features of basketball score video, constructs the video conversion discrimination rules, detects the basketball target, and obtains the tracking target contour to frame information. Finally, it realizes the target tracking detection of the team based on the team strength using an evaluation algorithm. The aim of this research work is to determine the strength of the team based on the healthcare data, team cohesiveness, and variance coefficient of basketball score frequency. The study on the coefficient of variation for basketball score frequency in teams can provide a theoretical research direction for team strength evaluation and meet the real-time needs of the coefficient of variation of basketball score frequency in teams. The empirical results show that the designed algorithm has the optimal execution time, more successful evaluation targets, high efficiency, and more reliability in evaluating the strength of the team.

A green, environment-friendly, high-consolidation-strength composite dust suppressant derived from xanthan gum

To solve issues of low consolidation strength, poor dust suppression effect, and secondary pollution of the current coal dust suppressors, a greener and higher-consolidation-strength composite dust suppressor was synthesized by the radical polymerization of xanthan gum (XG) as the graft substrate, methyl acrylate (MA), and vinyl acetate (VAc) as the graft monomers. Taking compressive strength as the main optimization index and viscosity and surface tension as the secondary indices, the optimum ratio of MA:VAc was 3:5 and the optimum solid content was 2%. Experiments reveal that the prepared dust suppressant can naturally infiltrate into coal to form a hard solidified layer. At a wind speed of 10 m/s, the solidified layer still maintained structural integrity, indicating that the dust suppressant exhibits a good dust fixation effect. The dust suppressant can not only maintain relatively stable performance for a period of time but also degrade naturally. Furthermore, molecular dynamics simulation reveals not only the interaction mechanism between coal molecules and the dust suppressor but also the wetting mechanism of the dust suppressor. Experimental and simulation results reveal that as a multifunctional dust suppressor with excellent performance, the as-prepared dust suppressor demonstrates the immense potential for the control of coal dust. Graphical abstract.

Rejuvenation of tumour-specific T cells through bispecific antibodies targeting PD-L1 on dendritic cells

Bispecific T-cell engagers (BiTEs) preferentially targeting tumour-associated antigens and stimulating CD3-mediated signalling are being used in patients to treat acute B-cell lymphoblastic leukemia. However, the potency of BiTEs in solid tumours is limited by their short half-life and their severe toxicity at relevant therapeutic doses. Here we report the design and in vivo performance of a bispecific antibody that simultaneously targets the murine T-cell co-receptor CD3ε and the murine immune checkpoint programmed-death ligand 1 (PD-L1). In multiple syngeneic tumour models, the bispecific antibody generated higher antitumour immune responses than conventional BiTEs targeting tumour-associated antigens and CD3ε. We found that the durable antigen-specific T-cell responses resulted from the rejuvenation of CD8 T cells, owing to the blockade of PD-L1 on dendritic cells (but not on tumour cells) and co-stimulation by B7-1&2 (a peripheral membrane protein on dendritic cells). Bispecific T-cell engagers targeting dendritic cells rather than tumour cells may represent a general means of T-cell rejuvenation for durable cancer immunotherapy.

[Susceptibility factors, types and management of infection in patients with liver cirrhosis]

Patients with liver cirrhosis are prone to infection due to various reasons such as weakened immunity and intestinal bacteria translocation. Among them, bacterial infections are the most common and are the main cause for liver failure progression, leading to increased mortality, while fungal infections, mainly caused by Candida mycoderma bacteria (Candida), are usually related to delayed diagnosis. Therefore, high vigilance, timely diagnosis and treatment of infection are important means to improve the treatment effectiveness in patients with end-stage liver disease. This paper focuses on the main characteristics and treatment methods of bacterial and fungal infections in patients with liver cirrhosis.

Self-sensing coaxial muscle fibers with bi-lengthwise actuation

Artificial muscle fibers as a promising biomimetic actuator are needed for such applications as smart soft robots, muscle function restoration, and physical augmentation. Currently developed artificial muscle fibers have shown attractive performance in contractile and torsional actuations. However, the contractile muscle fibers do not have the capability of stimulus-responsive elongation, and real-time identifying their contractile position by themselves is still challenging. We report herein the preparation of a Ti₃C₂T_x MXene/single walled carbon-nanotubes (SWCNTs)-coated carbon nanotube (CNT)@polydimethylsiloxane (PDMS) coaxial muscle fiber that integrates the important features of self-position sensing and bi-lengthwise actuation. The bi-lengthwise actuation is realized by utilizing the large expansion coefficient difference of PDMS in response to solvent and heat, which results in ∼5% maximum elongation by n-heptane adsorption and ∼19% maximum contraction by electric heating under the optimal conditions. Meanwhile, due to the piezoresistive effect of the MXene/SWCNTs layer, the resistance change of this coating layer is almost linearly dependent on the contraction of the coaxial muscle fiber, providing a function of real-time self-position sensing. Furthermore, an application of using a bundle of these multifunctional coaxial muscle fibers for a bionic arm has been demonstrated, which provides new insights into the design of integrated intelligent artificial muscles with synergistic multiple functions.

O-110 A randomised, controlled, assessor-blind trial assessing clinical outcomes of individualised dosing with follitropin delta in Asian IVF/ICSI patients

Study question

To evaluate the efficacy and safety of individualised dosing with follitropin delta versus conventional dosing with follitropin alfa in an Asian population undergoing ovarian stimulation.

Summary answer

Individualised dosing with follitropin delta results in significantly higher live birth rate and fewer early OHSS and/or preventive interventions compared to conventional follitropin alfa dosing.

What is known already

Previous randomised controlled trials conducted in Europe, North- and South America mainly including Caucasian IVF/ICSI patients as well as in Japan have demonstrated that ovarian stimulation with the individualised follitropin delta dosing regimen based on serum AMH level and body weight modulated the ovarian response and reduced the risk of OHSS without compromising pregnancy and live birth rates.

Study design, size, duration

Randomised, controlled, assessor-blind trial conducted in 1,009 Asian patients from mainland China, South Korea, Vietnam and Taiwan, undergoing their first IVF/ICSI cycle. Randomisation was stratified by age (&lt;35, 35-37, 38-40 years). The primary endpoint was ongoing pregnancy assessed 10-11 weeks after transfer (non-inferiority limit -10.0%; analysis adjusted for age strata). Patients &lt;35 years underwent single embryo transfer if a good-quality embryo was available, otherwise double embryo transfer. Patients ≥35 years underwent double embryo transfer.

Participants/materials, setting, methods

Follitropin delta (Rekovelle, Ferring Pharmaceuticals) daily treatment consisted of a fixed dose individualised according to each patient’s initial AMH level (&lt;15 pmol/L: 12 μg; ≥15 pmol/L: 0.19 to 0.10 μg/kg; min-max 6-12 μg) and body weight. Follitropin alfa (Gonal-f, Merck Serono) dose was 150 IU/day for the first five days with subsequent potential dose adjustments according to individual response. A GnRH antagonist protocol was applied. OHSS was classified based on Golan’s system.

Main results and the role of chance

The ongoing pregnancy rate was 31.3% with follitropin delta and 25.7% with follitropin alfa (adjusted difference 5.4% [95% CI: -0.2%; 11.0%]). The live birth rate was significantly higher at 31.3% with follitropin delta compared to 24.7% with follitropin alfa (adjusted difference 6.4% [95% CI: 0.9%; 11.9%]; p &lt; 0.05). Live birth rates per age stratum were as follows for follitropin delta and follitropin alfa; &lt;35 years: 31.0% versus 25.0%, 3537 years: 35.3% versus 26.7%, 38-40 years: 20.0% versus 14.3%. Early OHSS risk, evaluated as the incidence of early OHSS and/or preventive interventions, was significantly (p &lt; 0.01) reduced from 9.6% with follitropin alfa to 5.0% with follitropin delta. The number of oocytes was 10.0±6.1 with follitropin delta and 12.4±7.3 with follitropin alfa. Individualised follitropin delta dosing compared to conventional follitropin alfa dosing resulted in 2 more oocytes (9.6±5.3 versus 7.6±3.5) in potential low responders (AMH &lt;15 pmol/L) and 3 fewer oocytes (10.1±6.3 versus 13.8±7.5) in potential high responders (AMH ≥15 pmol/L). Among patients with AMH ≥15 pmol/L, excessive response occurred less frequently with individualised than conventional dosing (≥15 oocytes: 20.2% versus 39.1%; ≥20 oocytes: 6.7% versus 18.5%). Total gonadotropin dose was reduced from 109.9±32.9 μg with follitropin alfa to 77.5±24.4 μg with follitropin delta.

Limitations, reasons for caution

The trial only covered the clinical outcome of one treatment cycle with fresh cleavage-stage embryo transfers.

Wider implications of the findings

The present trial implies that in addition to reducing the early OHSS risk, individualised dosing has the potential to improve the take-home baby rate in fresh cycles across all ages and with a lower gonadotropin consumption. The benefits in outcomes appear to be explained by the modulation of ovarian response.

Trial registration number

NCT03296527