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Background:Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disease. Despite advancements in treatment, the patients still suffer from flares. Since flares impact both prognosis and organ damage, the prevention of flares is a key therapeutic goal. However, gene expression profiles associated with flares remain poorly understood, making it challenging to implement individualized treatment strategies.Objectives:To identify gene expression profiles predicting subsequent flares in patients achieving lupus low disease activity state (LLDAS).Methods:We conducted a prospective cohort study. We set up two cohorts by extracting SLE patients achieving LLDAS from our two bulk RNA-seq studies, ImmuNexUT[1,2] and AMED-SLE[3], designating a test cohort and a validation cohort, respectively. We followed up these cohorts, assessing flares based on SELENA-SLEDAI flare index.Results:A total of 63 and 18 patients were enrolled in the test and validation cohorts in this analysis, with a mean age of 46 ± 12 and 47 ± 21 years. 5 (7.9%) and 1 (5.6%) were male. The 3-year flare-free survival of each cohort was 61.6% ± 6.16% and 66.7% ± 11.1% with a median follow-up time of 1071 days and 1482 days, respectively. Weighted correlation network analysis revealed the interferon-stimulated genes (ISG) module was associated with subsequent flares across all immune subsets except neutrophil and low-density granulocyte (LDG). To calculate an interferon (IFN) score, we applied a scoring system previously reported based on RT-qPCR data [4] with some modifications to our bulk RNA-seq data. We defined a subset IFN score (sIFN score) as the IFN score of each subset of each patient and a patient IFN score (pIFN score) as the adjusted first component score using probabilistic principal component analysis for the sIFN scores. The pIFN score was highly correlated to the sIFN scores across all immune subsets (correlation coefficients ≥ 0.93). The subgroup with a high pIFN score showed poorer survival for flare and severe flare (Figure 1a and b). To uncover the pathways and the subsets associated with interferon signature, we performed a differential gene expression analysis with the sIFN score as a covariate. The gene set enrichment analysis showed that the pathways associated with cell cycle were enriched in Th1, memory CD8 subsets, and plasmablast along with the sIFN score (Figure 1c). Oxidative phosphorylation (OXPHOS) pathways tended to be enriched in T cells, B cells, and dendritic cells, but were suppressed in neutrophil, LDG, intermediate and non-classical monocytes as the sIFN score increased. We stratified the patients into 2 subgroups by hierarchical clustering based on the gene set variation analysis (GSVA) scores of OXPHOS. The high OXPHOS subgroup reflected high OXPHOS scores in Th1 and memory CD8 subsets, exhibiting poorer survival for flare (Figure 1d–e). Similar results were observed for cell cycle. By Lasso-Cox regression model analysis incorporating the pathway scores in Th1 and clinical variables like drug dosing, it was indicated that the OXPHOS score in Th1 had the most significant impact on survival for flare. In the validation cohort, these results were replicated.Conclusion:The LLDAS patients with higher pIFN scores are more likely to experience subsequent flares, associated with the activation of OXPHOS and cell cycle in Th1 and memory CD8 subsets.REFERENCES:[1] Ota M, et al. Cell. 2021;184(11):3006-3021.e17. doi:10.1016/j.cell.2021.03.056.[2] Nakano M, et al. Cell. 2022;185(18):3375-3389.e21. doi:10.1016/j.cell.2022.07.021.[3] Takeshima Y, et al. Ann Rheum Dis. 2022;81(6):845-853. doi:10.1136/annrheumdis-2021-221464.[4] El-Sherbiny YM, et al. Sci Rep. 2018;8(1):5793. doi:10.1038/s41598-018-24198-1.Figure 1.Flare-free survival by pIFN score and OXPHOS scoreAcknowledgements:NIL.Disclosure of Interests:Tatsuki Abe: None declared, Takahiro Itamiya TI has received grant/research support from Chugai Pharmaceutical., Yumi Tsuchida: None declared, Haruka Tsuchiya HT has received speaking fees and/or honoraria from Chugai Pharmaceutical., Hirofumi Shoda HS has received speaking fees from Chugai pharmaceutical., Tomohisa Okamura TO has received speaking fees from Bristol Myers Squibb., TO has received grant/research support from Chugai Pharmaceutical., Keishi Fujio KF has received speaking fees from Chugai Pharmaceutical., KF has received grant/research support from Chugai Pharmaceutical.

Background:The loss of tolerance to nuclear antigens characterizes systemic lupus erythematosus (SLE), where CD4 T cells play a pivotal role in aiding B cells that produce autoantibodies. Despite this, the extent of aberrant T cell plasticity in SLE remains incompletely understood.Objectives:Our aim is to investigate T cell plasticity in SLE patients and characterize its association with SLE disease phenotype, utilizing large-scale peripheral blood T cell RNA-seq data from the Immune Cell Gene Expression Atlas from the University of Tokyo (ImmuNexUT) [1,2].Methods:We recruited 134 healthy controls (HC), 117 SLE patients, and 317 patients with 9 other immune-mediated diseases (Figure 1A). Nine CD4 T cell subsets and four CD8 T cell subsets were fine-sorted from each patient for RNA-seq analysis, resulting in 6392 T cell samples. Utilizing T cell receptor (TCR) repertoire analysis, we extracted 159 TCR repertoire features, encompassing V and J gene usage and CDR3 amino acid patterns from both α and β chains. We characterized inter-subset T cell signatures by comparing the features of TCR repertoire sequences or transcriptomes with those of other T cell subsets, such as Fr. II eTreg in comparison to other CD4 T cell subsets. Case-control signatures of T cell subsets were analyzed, comparing SLE (and other diseases) to HC. Subsequent correlation analysis provided insights into aberrant T cell differentiation in patients in vivo. We assessed the TCR clonotype overlap between CD4 T cell subsets using logistic mixed effect analysis. With transcriptomic Fr. II eTreg inter-subset signatures, we developed the “Th1 Treg score” to quantify the Treg-likeliness of each Th1 sample. The clinical relevancy of Th1 Treg score was evaluated. The identified signatures and correlations were validated for reproducibility using publicly available (single cell) RNA-seq datasets.Results:Analysis of inter-subset signatures within T cell subsets unveiled distinctive gene signatures (for example, FOXP3, TRIB1, and TNFRSF9 for Fr. II eTreg, and TBX21 and CXCR3 for Th1). Additionally, characteristic TCR CDR3 amino acid usages were identified, such as highly hydrophobic amino acids in Fr. II eTreg and acidic amino acids in Th1. Correlation analysis showed the most robust association between the inter-subset Fr. II eTreg signature and the case-control signature of SLE Th1 (Figure 1B). Further validation through TCR repertoire clonotype overlap analysis affirmed the heightened plasticity in SLE compared to healthy controls, particularly between Fr. II eTreg and effector CD4 T cells, including Th1 (Figure 1C, odds ratio = 3.1, P = 9.1 × 10-6 in Th1). Evaluation of Th1 Treg scores in SLE patients revealed a positive correlation with SLEDAI-2K score (Figure 1D). Moreover, Th1 Treg scores were elevated in active SLE patients presenting with fever or nephritis.Conclusion:Our study unveils plasticity between regulatory T cells and effector Th1 cells in SLE, shedding new light on SLE pathophysiology. This finding holds potential as a biomarker reflecting disease activity.REFERENCES:[1] Ota, M. et al. Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases. Cell 184,3006-3021.e17 (2021).[2] Nakano, M. et al. Distinct transcriptome architectures underlying lupus establishment and exacerbation. Cell 185, 3375-3389.e3321 (2022).Figure 1.Plasticity of SLE regulatory T cells. (A) Study overview. 9 other immune-mediated diseases are systemic sclerosis, idiopathic inflammatory myopathy, rheumatoid arthritis, ANCA-associated vasculitis, Behçet’s disease, mixed connective tissue disease, adult-onset Still’s disease, Sjögren’s syndrome, and Takayasu arteritis. (B) The correlation of Inter-subset signature of Fr. II eTreg and Case-control signature of SLE Th1. (C) TCR clonotype overlap analysis with Fr. II eTreg in SLE. (D) The correlation between SLEDAI-2K score and SLE Th1 Treg score.Acknowledgements:We thank all the study participants and all the members of the recruitment sites for the collection of data.Disclosure of Interests:Keishi Fujio receives consulting honoraria from Chugai Pharmaceutical., Keishi Fujio receives research support from Chugai Pharmaceutical., Yasuo Nagafuchi belonged to the Social Cooperation Program, Department of Functional Genomics and Immunological Diseases, supported by Chugai Pharmaceutical., Masahiro Nakano: None declared, Mineto Ota belonged to the Social Cooperation Program, Department of Functional Genomics and Immunological Diseases, supported by Chugai Pharmaceutical., Hiroaki Hatano: None declared, Takahiro Itamiya belong to the Social Cooperation Program, Department of Functional Genomics and Immunological Diseases, supported by Chugai Pharmaceutical., Tomohisa Okamura belong to the Social Cooperation Program, Department of Functional Genomics and Immunological Diseases, supported by Chugai Pharmaceutical., Kazuyoshi Ishigaki: None declared.

BackgroundDespite of recent developments in therapeutic agents for rheumatoid arthritis (RA) patients[1], it is reported that half of the patients are unable to achieve remission even with existing drugs[2]. Therefore, there is an urgent need to gain mechanistic insight into treatment resistance. Nowadays, single-cell RNA sequencing (scRNA-seq) technology have dramatically improved our understanding of the heterogeneity in synovial cells. However, it has not been fully elucidated how the cell clusters are related to treatment response, especially in Asian races[3].ObjectivesWe intend to analyze the RA synovium from Japanese patients based on single-cell transcriptomics to explore the pathological key players related to treatment resistance.MethodsSynovial specimens were collected from 31 RA patients using an ultrasound-guided needle biopsy. The proportion of 5 immune cell subsets (CD4+ T cells, CD8+ T cells, B cells, NK cells, monocytes) and mesenchymal cells (synovial fibroblasts (SF), endothelial cells, mural cells) were analyzed by flow cytometry. CD45+ and CD45- live cells were isolated, and scRNA-seq libraries were prepared using the 10x chromium system.ResultsWe classified the patients into the following three groups based on treatment status at the time of biopsy; treatment-naïve, inadequate response to conventional synthetic disease-modifying antirheumatic drugs (csDMARDs-IR), or biological DMARDs (bDMARDs-IR). The proportion of CD8+ T cells, especially GZMB+ GZMK+ CD8+ T cells, was significantly lower in csDMARDs-IR patients compared to treatment-naïve patients. This population was characterized by enhanced expression of IFNG and GZMK, the cooperative inducers of IL-6 production from SF. Meanwhile, an increased proportion of SF, especially THY1low sublining and CD34+ sublining, was observed in csDMARDs-IR and bDMARDs-IR patients. Intriguingly, by integrating gene set variation analysis (GSVA) with transcriptomic data of cytokine-stimulated SF in vitro4, THY1low sublining was indicated to be activated independently of the effects of inflammatory cytokines (e.g., TNF-α, IL-1β, IFNs) (Figure 1). Collectively, this SF subpopulation was inferred to be less susceptible to cytokine-blocking agents such as IL-6 receptor or TNF-α inhibitors.ConclusionThe synovial analysis has the potential to be useful in parsing the mechanism of treatment resistance in Japanese RA patients, and gaining insights into novel therapeutic targets.References[1] Tan Y, Buch MH. ‘Difficult to treat’ rheumatoid arthritis: current position and considerations for next steps. RMD Open. 2022 Jul;8(2):e002387.[2] Burmester GR, Bijlsma JWJ, Cutolo M, et al. Managing rheumatic and musculoskeletal diseases - past, present and future. Nat Rev Rheumatol. 2017 Jul;13(7):443-448.[3] Chang F, Wei K, Slowikowski K, et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat Immunol. 2019;20(7):928-42.[4] Tsuchiya H, Ota M, Sumitomo S, et al. Parsing multiomics landscape of activated synovial fibroblasts highlights drug targets linked to genetic risk of rheumatoid arthritis. Ann Rheum Dis. 2021 Apr;80(4):440-450.Figure 1.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

When using the superconducting technology industrially, it is not always possible to install a refrigerator near a high temperature superconducting coil for cooling it. In the method using heat conduction cooling, cooling result as expected cannot be obtained due to temperature difference between a refrigerator and a superconducting coil via a heat transfer plate when the distance of the refrigerator and the coil is long. Therefore, a method of cooling a superconducting coil by circulating helium gas has been proposed. Helium gas discharged by a compressor at room temperature is cooled by a pre-cooling heat exchanger, thereafter cooled by a GM refrigerator. The cold helium gas cools the coil and current leads. In this study, the helium circulation cooling system was investigated by using one-dimensional numerical analysis and experiment at different helium gas mass flows.

Objective:To observe and characterise vessel injury after stenting using optical coherence tomography (OCT), to propose a systematic OCT classification for periprocedural vessel trauma, to evaluate its frequency in stable versus unstable patients and to assess its clinical impact during the hospitalisation period.Setting:Stenting causes vessel injury.Design and interventions:All consecutive patients in whom OCT was performed after stent implantation were included in the study. Qualitative and quantitative assessment of tissue prolapse, intra-stent dissection and edge dissection were performed.Results:Seventy-three patients (80 vessels) were analysed. Tissue prolapse within the stented segment was visible in 78/80 vessels (97.5%). Median number of tissue prolapse sites was 8 (IQR 4–19), mean (SD) area 1.04 (0.9) mm2. Intra-stent dissection flaps were visible in 69/80 vessels (86.3%) (median number 3 (IQR 1.25–6), maximum flap length 450 (220) μm). Fifty-five out of 80 vessels (68.8%) showed dissection cavities (median number 2 (IQR 0–4.75), maximum depth 340 (170) μm). Edge dissection was visible in 20 vessels (mean (SD) length flap 744 (439) μm). The frequency of tissue prolapse or intra-stent dissection was similar in stable and unstable patients (95.6% vs 100%, p = 0.5 for tissue prolapse; 91.1% vs 82.9%, p = 0.3 for intra-stent dissection). There were no events during the hospitalisation period.Conclusions:OCT allows a detailed visualisation of vessel injury after stent implantation and enables a systematic classification and quantification in vivo. In this study, frequency of tissue prolapse or intra-stent dissections after stenting was high, irrespective of the clinical presentation of the patients, and was not associated with clinical events during hospitalisation.

BackgroundRheumatoid arthritis (RA) patients are heterogeneity in their clinical phenotype and in response to molecular targeted therapies. To date, only limited number of studies addressed the immunological changes that lie behind the clinical heterogeneity.ObjectivesTo identify immunological correlates of clinical phenotypes and predictors of treatment response, we performed peripheral blood multi-omics profiling of patients initiating abatacept treatment.MethodsIn the PREDICTABA study, we have recruited 104 RA patients starting abatacept treatment at six hospitals in Japan (Figure 1A). Peripheral blood mass cytometry analysis was performed in discovery and validation cohorts (n=79 and 22). In total, 10 million T and B cells were clustered by cell surface protein expression (Figure 1B, 1C). After accounting for the effects of age, sex, CDAI disease activity, anti-CCP antibody titer, and donor batch effects, immune cell clusters were tested for their association with baseline treatment and future abatacept treatment response (CDAI improvement at 6 months) using mixed-effects modeling of association of single cells [1]. Peripheral blood RNA-seq identified immune cell signatures and immune pathway signatures.ResultsAt baseline, median age was 73 years. 80% were female and 80% were seropositive. Median CDAI improved from 17 to 5 after 6 months of abatacept treatment. RNA-seq immune cell gene signatures validated mass cytometry immune cell cluster frequencies. Naive CD8 T cells were negatively associated with age (odds ratio (OR) 0.57 and 0.32, P-values<0.001). Naive B cells were negatively associated with baseline prednisolone use (OR 0.53 and 0.25, P-values<0.001). Plasmablasts were negatively associated with baseline methotrexate use (OR 0.59 and P-value<0.001, Figure 1B, 1D, 1E), and with IL6_JAK_STAT3 signaling gene signature (Rho=-0.36, P-value<0.001). Finally, CD8+CD25+ T cells showed suggestive association with CDAI improvement after abatacept treatment (OR 1.4 and 1.6, P-values 0.01 and 0.07, Figure 1C, 1F, 1G).ConclusionThrough immunophenotyping analysis of RA patients, we have revealed that B cell subsets are associated with conventional RA treatments. Abundance of CD8+CD25+ T cells may be predicative of good abatacept response.Reference[1] Fonseka CY, Rao DA, Teslovich NC, Korsunsky I, Hannes SK, Slowikowski K, Gurish MF, Donlin LT, Lederer JA, Weinblatt ME et al: Mixed-effects association of single cells identifies an expanded effector CD4(+) T cell subset in rheumatoid arthritis. Sci Transl Med 2018, 10(463).Characters from table content including title and footnotes:Figure 1.(A) Overview of the study. (B-C) UMAP visualization of B cells (B) and CD8 T cells (C) from mass cytometry analysis. (D) Mixed-effects modeling of association of single cells (MASC) between 32 mass cytometry T and B cell clusters and baseline methotrexate (MTX) dose. Red dashed line indicates Bonferroni corrected P-value threshold for P-value < 0.05. (E) Negative correlation between baseline MTX dose and B_C7 Plasmablast frequencies by the Spearman’s rank correlation coefficient test. (F) MASC analysis of CDAI improvement rate at 6 months after the start of abatacept treatment. (G) The correlation between CDAI improvement rate at 6 months after abatacept treatment and CD8_C5: CD8+CD25+ T cells cluster by the Spearman’s rank correlation coefficient test. (B-G) Discovery cohort dataAcknowledgementsWe thank all the study participants and all the members of the recruitment sites for the collection of clinical data. The supercomputing resource SHIROKANE was provided by the Human Genome Center at The University of Tokyo.Disclosure of InterestsYasuo Nagafuchi Speakers bureau: Bristol-Myers Squibb, Employee of: I belong to the Social Cooperation Program, Department of functional genomics and immunological diseases, supported by Chugai Pharmaceutical., Saeko Yamada Speakers bureau: Bristol-Myers Squibb, Mineto Ota Employee of: I belong to the Social Cooperation Program, Department of functional genomics and immunological diseases, supported by Chugai Pharmaceutical, Hiroaki Hatano: None declared, Kanae Kubo Speakers bureau: Bristol-Myers Squibb, Kenichi Shimane: None declared, Keigo Setoguchi: None declared, Takanori Azuma: None declared, Mizuko Mamura: None declared, Tomohisa Okamura Employee of: I belong to the Social Cooperation Program, Department of functional genomics and immunological diseases, supported by Chugai Pharmaceutical., Kazuyoshi Ishigaki Speakers bureau: Bristol-Myers Squibb, Keishi Fujio Speakers bureau: Bristol-Myers Squibb, Grant/research support from: Bristol-Myers Squibb, Ono pharmaceutical.

Aging is a major risk factor for cancer, but the precise mechanism by which aging promotes carcinogenesis remains largely unknown. Here, using genetically modified mouse models, we show that p16 high senescent (p16 h -sn) fibroblasts accumulate with age, constitute inflammatory cancer-associated fibroblasts (CAFs) and promote tumor growth in bladder cancer models. Single-cell RNA sequencing of fibroblasts from aged mice revealed higher expression of the C–X–C motif chemokine 12 gene ( Cxcl12 ) in p16 h -sn fibroblasts than in p16 low fibroblasts. Elimination of p16 h -sn cells or inhibition of CXCL12 signaling notebly suppressed bladder tumor growth in vivo. We identified high expression levels of SMOC2 , GUCY1A1 ( GUCY1A3 ), CXCL12 , CRISPLD2 , GAS1 and LUM as a signature of p16 h -sn CAFs in humans and mice, which was associated with age and poor prognosis in patients with advanced and nonadvanced bladder cancer. Here we show that p16 h -sn fibroblasts in the aged bladder create a cancer-permissive niche and promote tumor growth by secreting CXCL12. Meguro et al. show an accumulation of p16 high senescent fibroblasts in the aging bladder that serves as a cancer-permissive niche and promotes tumor growth by secreting CXCL12. Inhibition of senescence or CXCL12 signaling suppresses bladder tumor growth.

Background:Idiopathic inflammatory myopathy (IIM) includes heterogeneous phenotypes such as polymyositis (PM), dermatomyositis (DM), and antisynthetase syndrome. The underlying mechanisms of muscle damage remain poorly understood.Objectives:The aim of this study was to investigate the transcriptome and immunophenotypic features of muscle biopsies from patients with IIM.Methods:Bulk RNA-sequencing was performed on muscle biopsy samples from patients with IIM (PM; n=9, DM; n=16, classified according to the Bohan and Peter criteria) (Figure 1). DM patients were further divided into subgroups negative or positive for anti-aminoacyl tRNA synthetase (ARS) antibodies (n=9 and n=7, respectively). Weighted gene coexpression network analysis (WGCNA), differentially expressed gene (DEG) analysis, and gene set variation analysis (GSVA) were conducted to evaluate specific pathways and functions. Cell proportions were estimated through a deconvolution approach. Mann-Whitney U test and Spearman correlation analyses were used to investigate the differences in cell proportions and relationships with clinical features.Results:Among the total of 25 patients with IIM, WGCNA revealed serum creatine kinase (CK) and aldolase levels were significantly correlated with specific gene modules that were associated with cellular respiration, mitochondrial translation, phagocytosis, and cytokine production (Figure 2A and 2B). Additionally, significant positive correlations were observed between CK and the proportions of CD16 negative (CD16n Mono) and positive monocytes (CD16p Mono), as well as myeloid dendritic cells (Figure 2C). DM patients demonstrated higher proportions of CD16n Mono (p=0.043), whereas higher proportions of Th2 cells were found in PM patients (p=0.049). GSVA revealed elevated interferon (IFN)-α response and complement signatures in DM (p=0.017, 0.008, respectively). DEGs in DM were also associated with the response to type I IFN pathway and complement system. Among the DM patients, ARS-DM patients exhibited a higher proportion of Th1 cells (p=0.007) and DEGs were associated with oxidative phosphorylation.Conclusion:This research elucidates potential mechanisms underlying muscle damage, highlighting the significant involvement of myeloid cells in DM as compared to PM. Furthermore, DM was associated with higher complement signaling. Distinctive gene expression variations in muscle biopsies from patients with IIM suggest that different pathologic mechanisms underlie muscle damage in each phenotype.REFERENCES:NIL.Figure 1.Overview of this studyFigure 2.Relationship between clinical parameters and transcriptome in muscle specimens.Acknowledgements:This research was supported by the Japan Agency for Medical Research and Development (AMED) under Grant Number 19ek0410047.Disclosure of Interests:Shinji Izuka Eisai Co., Ltd, Natsuka Umezawa Chugai Pharmaceutical, Chugai Pharmaceutical, Boehringer Ingelheim Japan, Astellas Pharma, Kyowa Kirin Co., Ltd, Otsuka Pharmaceutical Factory, Toshihiko Komai Tanabe Mitsubishi, Kissei, Pfizer, Chugai, Daiichi-Sankyo, Eli Lilly, Novartis, Eisai, Aasahi Kasei, GlaxoSmithKline, GlaxoSmithKline, Yusuke Sugimori: None declared, Naoki Kimura GlaxoSmithKline Co., Ltd., Eisai Co., Ltd., AbbVie LLC, Asahi Kasei Pharma Corporation, Novartis Pharma K.K., Astellas Pharma Inc., AstraZeneca K.K., Chugai Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Ayumi Pharmaceutical Corporation, Nobelpharma Co., Ltd., Asahi Kasei Pharma Corporation, AbbVie LLC, Chugai Pharmaceutical Co., Ltd., UCB Japan Co. Ltd., CSL Behring Co., Ltd., The Japanese Blood Products Organization, Fumitaka Mizoguchi: None declared, Yuichiro Fujieda: None declared, Keita Ninagawa The Uehara Memorial Foundation, Takeshi Iwasaki: None declared, Katsuya Suzuki: None declared, Tsutomu Takeuchi: None declared, Koichiro Ohmura Asahi Kasei Pharma、Chugai Pharmaceutical、Mitsubishi Tanabe Pharma, Tsuneyo Mimori EUROIMMUN、Nippon Shinyaku Co., Ltd., Tatsuya Atsumi AbbVie Inc., Alexion Inc., Asahi-Kasei Co,. Astellas Pharma Inc., AstraZeneca plc., Bayer Yakuhin, Bristol-Myers Squibb Co., Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Eisai Co. Ltd., Eli Lilly Japan K.K., Gilead Sciences K.K., GlaxoSmithKline K.K., Janssen Pharmaceutical K.K., Novartis Pharma K.K., and Nippon Boehringer Ingelheim Co., Ltd., Mitsubishi Tanabe Pharma Co.,. Pfizer Inc., Taiho Pharmaceutical Co., Ltd. and UCB Japan Co. Ltd., GlaxoSmithKline K.K. AstraZeneca plc. Nippon Boehringer Ingelheim Co., Ltd., Novartis Pharma K.K., Otsuka Pharmaceutical Co., Ltd, GlaxoSmithKline K.K., Eiryo Kawakami lundbeck、Astellas Pharma Inc, Akari Suzuki Daiichi Sankyo and Chugai Pharmaceutical, Yuta Kochi Uehara Memorial Foundation, Kobayashi Foundation, Kazuhiko Yamamoto Chugai Pharmaceutical, Chugai Pharmaceutical, Shinsuke Yasuda Asahi-Kasei, Ono pharmaceuticals, Chugai, Asahi-Kasei, Abbvie, Tanabe-Mitsubishi, Ono Pharmaceutical, Lilly, GSK, Astrazeneka, Immunoforge, Chugai, Asahi-Kasei, Abbvie, Ayumi, Behringer, Tomohisa Okamura Chugai Pharmaceutical, Chugai Pharmaceutical, Mineto Ota GlaxoSmithKline, Keishi Fujio Chugai Pharmaceutical, Chugai Pharmaceutical.

Experiments are performed on the flow past a sphere moving vertically at constant speeds in a salt-stratified fluid. Shadowgraph method and fluorescent dye are used for the flow visualization, and particle image velocimetry is used for the velocity measurement in the vertical plane. Vertical ‘jets’ or columnar structures are observed in the shadowgraph for all the Froude numbers Fr(0.2 ≲ Fr ≲ 70) investigated, and the wake structures in the whole parameter space of Fr and the Reynolds number Re(30 ≲ Re ≲ 4000) are classified into seven types, five of which are newly found. Those include two types of thin jets, one of which is short with its top disturbed by internal waves to have a peculiar ‘bell-shaped’ structure, while the other has an indefinitely long length. There are two other new types of jet with periodically generated ‘knots’, one of which is straight, while the other has a spiral structure. A simply meandering jet has also been found. These wake structures are significantly different from those in homogeneous fluids except under very weak stratification, showing that the stratification effects on vertical motion are much more significant than those on horizontal motion.

Background/Objectives: There have been few studies on the association of fruit and vegetable (FV) intake with cardiovascular disease (CVD) risk in Asian populations where both dietary habits and disease structure are different from western countries. No study in Asia has found its significant association with stroke. We examined associations of FV intake with mortality risk from total CVD, stroke and coronary heart diseases (CHDs) in a representative Japanese sample. Methods: A total of 9112 participants aged from 24-year follow-up data in the NIPPON DATA80, of which baseline data were obtained in the National Nutrition Survey Japan in 1980, were studied. Dietary data were obtained from 3-day weighing dietary records. Participants were divided into sex-specific quartiles of energy adjusted intake of FV. Multivariate-adjusted hazard ratios (HRs) were calculated between strata of the total of FV intake, fruit intake and vegetable intake. The adjustment included age, sex, smoking, drinking habit and energy adjusted intakes of sodium and some other food groups. Results: Participants with higher FV intake were older, ate more fish, milk and dairy products and soybeans and legumes and ate less meat. Multivariate-adjusted HR (95% confidence interval; P ; P for trend) for the highest versus the lowest quartile of the total of FV intake was 0.74 (0.61–0.91; 0.004; 0.003) for total CVD, 0.80 (0.59–1.09; 0.105; 0.036) for stroke and 0.57 (0.37–0.87; 0.010; 0.109) for CHD. Conclusions: The results showed that higher total intake of FVs was significantly associated with reduced risk of CVD mortality in Japan.