Plasma metabolomics identifies S-adenosylmethionine as a biomarker and potential therapeutic target for vascular aging in older adult males

Brachial-ankle pulse wave velocity (baPWV) is a noninvasive index of vascular aging. However, the metabolic profile underlying vascular aging has not yet been fully elucidated. The current study aimed to identify circulating markers of vascular aging as assessed by baPWV and to elucidate its mechanism from a metabolomic perspective in older adults. A total of 60 and 61 Chinese male participants aged ≥80 years were recruited to the metabolome and validation cohorts, respectively. The baPWV of participants was measured using an automatic waveform analyzer. Plasma metabolic profile was investigated using ultra-performance liquid chromatography coupled with triple quadrupole linear ion trap tandem mass spectrometry. Orthogonal partial least squares (OPLS) regression modeling established the association between metabolic profile and baPWV to determine important metabolites predictive of vascular aging. Additionally, an enzyme-linked immunosorbent assay was employed to validate the metabolites in plasma and culture media of vascular smooth muscle cells in vitro. OPLS modeling identified 14 and 22 metabolites inversely and positively associated with baPWV, respectively. These 36 biomarkers were significantly enriched in seven metabolite sets, especially in cysteine and methionine metabolism (p <0.05). Notably, among metabolites involved in cysteine and methionine metabolism, S-adenosylmethionine (SAM) level was inversely related to baPWV, with a significant correlation coefficient in the OPLS model (p <0.05). Furthermore, the relationship between SAM and vascular aging was reconfirmed in an independent cohort and at the cellular level in vitro. SAM was independently associated with baPWV after adjustments for clinical covariates (β = -0.448, p <0.001) in the validation cohort. In summary, plasma metabolomics identified an inverse correlation between SAM and baPWV in older males. SAM has the potential to be a novel biomarker and therapeutic target for vascular aging.

Accuracy of quantitative viral secondary standards: a re-examination

Interlaboratory agreement of viral load assays depends on the accuracy and uniformity of quantitative calibrators. Previous work demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values in both log10 copies/mL and log10 international unit (IU)/mL, with bias from manufacturer-assigned nominal values of 0.0-0.9 log10 units (either copies or IU)/mL. Standards normalized to IU and those values assigned by dPCR rather than by real-time PCR (qPCR) showed better agreement with nominal values. The latter reinforces prior conclusions regarding the utility of using such methods for quantitative value assignment in reference materials. Quantitative standards have improved over the last several years, and the remaining bias from nominal values might be further reduced by universal implementation of dPCR methods for value assignment, normalized to IU.

IMPORTANCE

Interlaboratory agreement of viral load assays depends on accuracy and uniformity of quantitative calibrators. Previous work, published in JCM several years ago, demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values, indicating a substantial improvement in the production of accurate secondary viral standards, while supporting the need for further work in this area and for the broad adaption of international unit (IU) as a reporting standard for quantitative viral load results.

A Multi-Domain Convolutional Neural Network for EEG-Based Motor Imagery Decoding

Motor imagery (MI) decoding plays a crucial role in the advancement of electroencephalography (EEG)-based brain-computer interface (BCI) technology. Currently, most researches focus on complex deep learning structures for MI decoding. The growing complexity of networks may result in overfitting and lead to inaccurate decoding outcomes due to the redundant information. To address this limitation and make full use of the multi-domain EEG features, a multi-domain temporal-spatial-frequency convolutional neural network (TSFCNet) is proposed for MI decoding. The proposed network provides a novel mechanism that utilize the spatial and temporal EEG features combined with frequency and time-frequency characteristics. This network enables powerful feature extraction without complicated network structure. Specifically, the TSFCNet first employs the MixConv-Residual block to extract multiscale temporal features from multi-band filtered EEG data. Next, the temporal-spatial-frequency convolution block implements three shallow, parallel and independent convolutional operations in spatial, frequency and time-frequency domain, and captures high discriminative representations from these domains respectively. Finally, these features are effectively aggregated by average pooling layers and variance layers, and the network is trained with the joint supervision of the cross-entropy and the center loss. Our experimental results show that the TSFCNet outperforms the state-of-the-art models with superior classification accuracy and kappa values (82.72% and 0.7695 for dataset BCI competition IV 2a, 86.39% and 0.7324 for dataset BCI competition IV 2b). These competitive results demonstrate that the proposed network is promising for enhancing the decoding performance of MI BCIs.

Bayesian uncertainty modeling for P300-based brain-computer interface

P300 potential is important to cognitive neuroscience research, and has also been widely applied in brain-computer interfaces (BCIs). To detect P300, many neural network models, including convolutional neural networks (CNNs), have achieved outstanding results. However, EEG signals are usually high-dimensional. Moreover, since collecting EEG signals is time-consuming and expensive, EEG datasets are typically small. Therefore, data-sparse regions usually exist within EEG dataset. However, most existing models compute predictions based on point-estimate. They cannot evaluate prediction uncertainty and tend to make overconfident decisions on samples located in data-sparse regions. Hence, their predictions are unreliable. To solve this problem, we propose a Bayesian convolutional neural network (BCNN) for P300 detection. The network places probability distributions over weights to capture model uncertainty. In prediction phase, a set of neural networks can be obtained by Monte Carlo sampling. Integrating the predictions of these networks implies ensembling. Therefore, the reliability of prediction can be improved. Experimental results demonstrate that BCNN can achieve better P300 detection performance than point-estimate networks. In addition, placing a prior distribution over the weight acts as a regularization technique. Experimental results show that it improves the robustness of BCNN to overfitting on small dataset. More importantly, with BCNN, both weight uncertainty and prediction uncertainty can be obtained. The weight uncertainty is then used to optimize the network through pruning, and the prediction uncertainty is applied to reject unreliable decisions so as to reduce detection error. Therefore, uncertainty modeling provides important information to further improve BCI systems.

Favorable outcome in advanced pheochromocytoma and paraganglioma after hypofractionated intensity modulated radiotherapy

PURPOSE

The purpose of this study was to review outcomes of patients with advanced/metastatic pheochromocytoma/paraganglioma (PPGL) treated at our institution with Intensity-modulated radiotherapy (IMRT), describe the treatment outcomes, and determine predictors.

METHODS

A retrospective study on patients with advanced/metastatic PPGL who received IMRT at Peking Union Medical College Hospital between 2014 and 2019. A total of 14 patients with 17 lesions were included in this study. Ultra-hypofractionated radiation therapy was used for 7 lesions in 5 patients, while hypofractionated radiation therapy was used for 8 lesions in 7 patients. 2 patients got conventional fractionated radiotherapy. Patients who received external beam radiation therapy were given a median total radiation dose of 74.4/130 Gy (BED10/3) in a median of 13 fractions.

RESULTS

OS at 2 years was 78% for all patients. For lesions evaluated by RECIST response, at least stable disease of the target lesion was achieved in 94% and distant progression in 28.5%, with an average time to progression of 5.2 months. Patients with locally advanced primary tumors or recurred in situ (n = 8) achieved 100% local control, and none of them got recurrence or distant metastasis after radiotherapy at last follow-up (median 29 months). Of patients with catecholamine-related syndromes (n = 12), 91% of symptomatic lesions improved following radiation therapy and a more than 50% decline in catecholamines.

CONCLUSIONS

We have found hypofractionated IMRT effective as an additional therapy for patients with advanced primary tumors or recurrence in situ and not amenable to complete surgical resection.

Electromagnetic Source Imaging With a Combination of Sparse Bayesian Learning and Deep Neural Network

Accurate reconstruction of the brain activities from electroencephalography and magnetoencephalography (E/MEG) remains a long-standing challenge for the intrinsic ill-posedness in the inverse problem. In this study, to address this issue, we propose a novel data-driven source imaging framework based on sparse Bayesian learning and deep neural network (SI-SBLNN). Within this framework, the variational inference in conventional algorithm, which is built upon sparse Bayesian learning, is compressed via constructing a straightforward mapping from measurements to latent sparseness encoding parameters using deep neural network. The network is trained with synthesized data derived from the probabilistic graphical model embedded in the conventional algorithm. We achieved a realization of this framework with the algorithm, source imaging based on spatio-temporal basis function (SI-STBF), as backbone. In numerical simulations, the proposed algorithm validated its availability for different head models and robustness against distinct intensities of the noise. Meanwhile, it acquired superior performance compared to SI-STBF and several benchmarks in a variety of source configurations. Additionally, in real data experiments, it obtained the concordant results with the prior studies.

Eliminating or Shortening the Calibration for a P300 Brain–Computer Interface Based on a Convolutional Neural Network and Big Electroencephalography Data: An Online Study

A brain-computer interface (BCI) measures and analyzes brain activity and converts it into computer commands to control external devices. Traditional BCIs usually require full calibration, which is time-consuming and makes BCI systems inconvenient to use. In this study, we propose an online P300 BCI spelling system with zero or shortened calibration based on a convolutional neural network (CNN) and big electroencephalography (EEG) data. Specifically, three methods are proposed to train CNNs for the online detection of P300 potentials: (i) training a subject-independent CNN with data collected from 150 subjects; (ii) adapting the CNN online via a semisupervised learning/self-training method based on unlabeled data collected during the user's online operation; and (iii) fine-tuning the CNN with a transfer learning method based on a small quantity of labeled data collected before the user's online operation. Note that the calibration process is eliminated in the first two methods and dramatically shortened in the third method. Based on these methods, an online P300 spelling system is developed. Twenty subjects participated in our online experiments. Average accuracies of 89.38%, 94.00% and 93.50% were obtained by the subject-independent CNN, the self-training-based CNN and the transfer learning-based CNN, respectively. These results demonstrate the effectiveness of our methods, and thus, the convenience of the online P300-based BCI system is substantially improved.

Matrix Matters: Assessment of Commutability among BK Virus Assays and Standards

Quantitative testing of BK virus (BKPyV) nucleic acid has become the standard of care in transplant patients. While the relationship between interassay harmonization and commutability has been well characterized for other transplant-related viruses, it has been less well studied for BKPyV, particularly regarding differences in commutability between matrices. Here, interassay agreement was evaluated among six real-time nucleic acid amplification tests (NAATs) and one digital PCR (dPCR) BKPyV assay. Differences in the commutability of three quantitative standards was examined across all assays using a variety of statistical approaches. Panels, including 40 samples each of plasma and urine samples previously positive for BKPyV, together with one previously negative plasma sample and four previously negative urine samples, were tested using all assays, with each real-time NAAT utilizing its usual quantitative calibrators. Serial dilutions of WHO, National Institute for Standards and Technology (NIST), and commercially produced (Exact/Bio-Rad) reference materials were also run by each assay as unknowns. The agreement of the clinical sample values was assessed as a group and in a pairwise manner. The commutability was estimated using both relativistic and quantitative means. The quantitative agreement across assays in the urine samples was within a single log10 unit across all assays, while the results from the plasma samples varied by 2 to 3 log10 IU/mL. The commutability showed a similar disparity between the matrices. Recalibration using international standards diminished the resulting discrepancies in some but not all cases. Differences in the sample matrix can affect the commutability and interassay agreement of quantitative BKPyV assays. Differences in commutability between matrices may largely be due to factors other than those such as amplicon size, previously described as important in the case of cytomegalovirus. Continued efforts to standardize viral load measurements must address multiple sources of variability and account for differences in assay systems, quantitative standards, and sample matrices.

Enhancement of lower limb motor imagery ability via dual-level multimodal stimulation and sparse spatial pattern decoding method

Recently, motor imagery brain-computer interfaces (MI-BCIs) with stimulation systems have been developed in the field of motor function assistance and rehabilitation engineering. An efficient stimulation paradigm and Electroencephalogram (EEG) decoding method have been designed to enhance the performance of MI-BCI systems. Therefore, in this study, a multimodal dual-level stimulation paradigm is designed for lower-limb rehabilitation training, whereby visual and auditory stimulations act on the sensory organ while proprioceptive and functional electrical stimulations are provided to the lower limb. In addition, upper triangle filter bank sparse spatial pattern (UTFB-SSP) is proposed to automatically select the optimal frequency sub-bands related to desynchronization rhythm during enhanced imaginary movement to improve the decoding performance. The effectiveness of the proposed MI-BCI system is demonstrated on an the in-house experimental dataset and the BCI competition IV IIa dataset. The experimental results show that the proposed system can effectively enhance the MI performance by inducing the α, β and γ rhythms in lower-limb movement imagery tasks.

Electromagnetic Source Imaging via Bayesian Modeling with Smoothness in Spatial and Temporal Domains

Accurate reconstruction of cortical activation from electroencephalography and magnetoencephalography (E/MEG) is a long-standing challenge because of the inherently ill-posed inverse problem. In this paper, a novel algorithm under the empirical Bayesian framework, source imaging with smoothness in spatial and temporal domains (SI-SST), is proposed to address this issue. In SI-SST, current sources are decomposed into the product of spatial smoothing kernel, sparseness encoding coefficients, and temporal basis functions (TBFs). Further smoothness is integrated in the temporal domain with the employment of an underlying autoregressive model. Because sparseness encoding coefficients are constructed depending on overlapped clusters over cortex in this model, we derived a novel update rule based on fixed-point criterion instead of the convexity based approach which becomes invalid in this scenario. Entire variables and hyper parameters are updated alternatively in the variational inference procedure. SI-SST was assessed by multiple metrics with both simulated and experimental datasets. In practice, SI-SST had the superior reconstruction performance in both spatial extents and temporal profiles compared to the benchmarks.

Towards Assessment of Sound Localization in Disorders of Consciousness Using a Hybrid Audiovisual Brain-Computer Interface

Behavioral assessment of sound localization in the Coma Recovery Scale-Revised (CRS-R) poses a significant challenge due to motor disability in patients with disorders of consciousness (DOC). Brain-computer interfaces (BCIs), which can directly detect brain activities related to external stimuli, may thus provide an approach to assess DOC patients without the need for any physical behavior. In this study, a novel audiovisual BCI system was developed to simulate sound localization evaluation in CRS-R. Specifically, there were two alternatively flashed buttons on the left and right sides of the graphical user interface, one of which was randomly chosen as the target. The auditory stimuli of bell sounds were simultaneously presented by the ipsilateral loudspeaker during the flashing of the target button, which prompted patients to selectively attend to the target button. The recorded electroencephalography data were analyzed in real time to detect event-related potentials evoked by the target and further to determine whether the target was attended to or not. A significant BCI accuracy for a patient implied that he/she had sound localization. Among eighteen patients, eleven and four showed sound localization in the BCI and CRS-R, respectively. Furthermore, all patients showing sound localization in the CRS-R were among those detected by our BCI. The other seven patients who had no sound localization behavior in CRS-R were identified by the BCI assessment, and three of them showed improvements in the second CRS-R assessment after the BCI experiment. Thus, the proposed BCI system is promising for assisting the assessment of sound localization and improving the clinical diagnosis of DOC patients.

Single-Trial EEG Classification via Orthogonal Wavelet Decomposition-Based Feature Extraction

Achieving high classification performance is challenging due to non-stationarity and low signal-to-noise ratio (low SNR) characteristics of EEG signals. Spatial filtering is commonly used to improve the SNR yet the individual differences in the underlying temporal or frequency information is often ignored. This paper investigates motor imagery signals via orthogonal wavelet decomposition, by which the raw signals are decomposed into multiple unrelated sub-band components. Furthermore, channel-wise spectral filtering via weighting the sub-band components are implemented jointly with spatial filtering to improve the discriminability of EEG signals, with an l 2-norm regularization term embedded in the objective function to address the underlying over-fitting issue. Finally, sparse Bayesian learning with Gaussian prior is applied to the extracted power features, yielding an RVM classifier. The classification performance of SEOWADE is significantly better than those of several competing algorithms (CSP, FBCSP, CSSP, CSSSP, and shallow ConvNet). Moreover, scalp weight maps of the spatial filters optimized by SEOWADE are more neurophysiologically meaningful. In summary, these results demonstrate the effectiveness of SEOWADE in extracting relevant spatio-temporal information for single-trial EEG classification.

Application Prospects and Prospect of Metabolomics in the Identification of Sudden Cardiac Death

Abstract

In cases of sudden death, the prevention of sudden cardiac death and the analysis of the cause of death after sudden cardiac death have always been a difficult problem. Therefore, clinical research and forensic pathological identification of sudden cardiac death are of great significance. In recent years, metabolomics has gradually developed into a popular field of life science research. The detection of "metabolic fingerprints" of biological fluids can provide an important basis for early diagnosis of diseases and the discovery of potential biomarkers. This article reviews the current research status of sudden cardiac death and the research on metabolomics of cardiovascular diseases that is closely related to sudden cardiac death and analyzes the application prospects of metabolomics in the identification of the cause of sudden cardiac death.

POS0788 CIRCULATING EXOSOMES PROMOTE LUPUS NEPHRITIS IN MRL-LPR MICE

Background:

Systemic Lupus Erythematosus (SLE) is a prototypic autoimmune disease that characterized by the loss of self-tolerance and the production of autoantibodies (autoAbs) [1, 2]. Lupus nephritis (LN), the severe organ-threatening manifestations of SLE, could cause massive damage to patients[3, 4]. Currently, some exosomal microRNAs (miRNAs) are considered as potential biomarkers in SLE. However, the role of exosomal miRNAs in Lupus Nephritis (LN) remains unclear.

Objectives:

The purpose of this study was to investigate molecular mechanism of plasma exosomal miRNAs in the development of Lupus Nephritis.

Methods:

Circulating exosomes were isolated from plasma of patients with LN, SLE without LN (NLN). Plasma exosomes were authenticated by Western Blot, Nanosight Tracking Analysis (NTA) and transmission electron microscopy (TEM). Fluorescence microscopy of co-cultured plasma exosomes and podocytes demonstrated that exosomes were uptaken into podocytes. Moreover, cell apoptosis and the inflammation factors was assessed using Western Blot. We analyzed the expression profiles of miRNAs in LN and NLN exosomes and the expression profiles of mRNAs of podocytes stimulated with LN and NLN exosomes with the help of next generation sequencing (NGS).

Results:

We demonstrate that exosomes derived from LN plasma could be taken by neighboring podocytes and promote the apoptosis of podocytes and the expression of inflammation factors. In addition, the sequencing found that miRNAs were differentially expressed in LN and NLN exosomes and mRNAs were differentially expressed in podocytes stimulated with LN and NLN exosomes.

Conclusion:

LN plasma exosomes have a potency to stimulate the apoptosis of podocytes and the expression of inflammation factors. Moreover, differentially expressed miRNAs in exosomes play a potential role in the development of LN.

References:

[1]T. Colasanti, A. Maselli, F. Conti, M. Sanchez, C. Alessandri, C. Barbati, D. Vacirca, A. Tinari, F. Chiarotti, A. Giovannetti, F. Franconi, G. Valesini, W. Malorni, M. Pierdominici, E. Ortona, Autoantibodies to estrogen receptor α interfere with T lymphocyte homeostasis and are associated with disease activity in systemic lupus erythematosus, Arthritis and rheumatism, 64 (2012) 778-787.

[2]H.A. Al-Shobaili, A.A. Al Robaee, A.A. Alzolibani, Z. Rasheed, Antibodies against 4-hydroxy-2-nonenal modified epitopes recognized chromatin and its oxidized forms: role of chromatin, oxidized forms of chromatin and 4-hydroxy-2-nonenal modified epitopes in the etiopathogenesis of SLE, Disease markers, 33 (2012) 19-34.

[3]A. Kaul, C. Gordon, M.K. Crow, Z. Touma, M.B. Urowitz, R. van Vollenhoven, G. Ruiz-Irastorza, G. Hughes, Systemic lupus erythematosus, Nat Rev Dis Primers, 2 (2016) 16039.

[4]M.G. Tektonidou, A. Dasgupta, M.M. Ward, Risk of End-Stage Renal Disease in Patients With Lupus Nephritis, 1971-2015: A Systematic Review and Bayesian Meta-Analysis, Arthritis & rheumatology (Hoboken, N.J.), 68 (2016) 1432-1441.

Disclosure of Interests:

None declared

AB0343 THE CHARACTERISTICS OF T CELLS IN SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS WITH ANXIETY BASED ON MACHINE LEARNING

Background:

Systemic lupus erythematosus (SLE) is an autoimmune disease, the immune system of patients to be disordered, especially in T cell subsets1. They were prone to mental diseases, anxiety particularly, which lead to suicide2. The recent study had reported that CD4+ T cells in the peripheral blood played the key role in like anxiety behavior of mice3. Although there showed that the level of serum TNF-α in SLE patients with anxiety was higher than without anxiety4, finding the important special mediators especially in T cell subsets was still necessary for the prevention of anxiety in SLE patients.

Objectives:

In total, 108 SLE patients, which met the diagnostic criteria of the American Society of rheumatology (v1997), were enrolled in this study from Affilliated Hospital of Nantong University, China. Exclusion criteria included other autoimmune diseases and active infection (including hepatitis B or C virus, Epstein-Barr virus, human immunodeficiency virus or Mycobacterium tuberculosis infection).

Methods:

We surveyed the abundance of 74 immune cell subpopulations from 108 SLE patients using flow cytometry, and investigated their differences between patients with and without anxiety (24 versus 84). Moreover, machine learning including Lasso regression, Random forest (RF) and Sparsity partial least squares discriminant analysis (sPLS-DA) was employed to build models and futher selected important features for the classification of SLE patients with anxiety.

Results:

SLE patients with anxiety showed higher body mass index (BMI) and lower quality of life. In their peripheral blood, the proportion of internal cell subsets composition of Th cell and Treg cells changed. By machine learning, we finally found that BMI and PD1-CD28- Treg played important rules to developing lupus anxiety.

Conclusion:

In this study, machine learning was applied to build models to select the most important T cell subset in SLE patients with anxiety. These findings suggested that BMI and imbalance of PD1-CD28- Treg containing effector memory Treg cells and effector Treg cells mostly played important roles in the development of SLE anxiety.

Disclosure of Interests:

None declared

POS0401 THE APPLICATION OF MTX-LOADING DNA TETRAHEDRON IN TREATING COLLAGEN-INDUCED ARTHRITIS MICE VIA REGULATING MACROPHAGE

Background:

Rheumatoid arthritis (RA) is a systemic autoimmune disease which mainly affect joints. [1]. Macrophages often infiltrate in the inflammatory joints. Activated macrophages release TNF-α, IL-1β to accelerate tissue damage, is one of the most important targets for RA intervention. The traditional drugs currently used commonly have some disadvantages cannot be bypassed[2], while DNA nanostructure is a new type of drugs have precise design, and likewise takes biological effect together[3]. We synthesized a DNA tetrahedron loaded with MTX and conjugated with HA which targeted to macrophage.

Objectives:

To verify whether MTX-loading DNA tetrahedron can regulate the apoptosis and polarization of macrophage and finally improve the condition of CIA model mice by while decrease the side effect of MTX.

Methods:

DNA TET was synthesized by mixing signal strand DNA in TM buffer and heated to 95 °C for 10 min, then cooling to 4 °C. Electrophoresis was applied to confirm the formation of TET. The absorbance of MTX solution was detected by microplate reader to analyze the loading efficiency of MTX into TET. Fluorescence microscope was used to observe the intake of TET into cells. CCK8 experiment was applied to measure the vitality of cells. Flow cytometry was used to detect the apoptosis and polarization. CIA model was established based on DBA/1 mice. Mice were randomly divided into five groups: normal group injected with NS; after established CIA model, CIA group injected with NS, MTX group injected with MTX solution, MTX-TET group injected with MTX-TET NP.

Results:

We synthesized DNA tetrahedron(A) and used 8% PAGE electrophoresis to confirmed the successfully synthesis(B). Then We found that when TET concentration fixed, the loading MTX concentration gradually increased and saturated at 190μM(C). While completely loading needed at least 4 hours(D). Fluorescence showed that single DNA strand cannot be taken by RAW, while TET can be easily taken by RAW(E). CCK8 showed that empty TET had no obvious effect on cells, while MTX and MTX-TET with equivalent concentration can obviously suppress the vitality(F). Similarly, the apoptosis trial showed that TET can slightly decrease the apoptosis of RAW, MTX and MTX-TET can significantly promote the apoptosis(G). Flow cytometry showed that the MTX-TET can decrease the expression of M1 marker CD80 (H).

At last, we treat mice with NS, TET, MTX and MTX-TET once a week after CIA model established, and found that TET have no significantly effect on mice, while MTX and MTX-TET can alleviate the inflammation symptom of paws(I).

Conclusion:

Conclusions: We synthesized MTX-loading DNA tetrahedron conjugated with HA, and found that the MTX-TET NP have the excellent ability of promote RAW apoptosis and relieve proinflammatory M1 polarization. while also can alleviate the symptom of CIA mice.

References:

[1]Aletaha D, Smolen JS: Diagnosis and Management of Rheumatoid Arthritis: A Review. JAMA 2018, 320(13):1360-1372.

[2]Smolen JS, Aletaha D, McInnes IB: Rheumatoid arthritis. Lancet 2016, 388(10055):2023-2038.

[3]Hu Q, Li H, Wang L, Gu H, Fan C: DNA Nanotechnology-Enabled Drug Delivery Systems. Chem Rev 2019, 119(10):6459-6506.

Figure 1.

Disclosure of Interests:

None declared

OP0073 SINGLE-CELL TRANSCRIPTOMICS UNCOVERS DEFECTIVE BONE MARROW EARLY B CELL DEVELOPMENT IN A SUBSET OF LUPUS PATIENTS ASSOCIATED WITH AGGRAVATED INFLAMMATION

Background:

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that occurs when the body’s immune system attacks own tissues and organs. B cells play a central role in SLE pathogenesis by producing autoantibodies as well as antibody-independent functions. Peripheral B cell abnormality is well known in lupus patients such as expansions of plasmablasts and atypical memory B cells, which are associated with active diseases. However, little is known about the B cell development in the bone marrow of lupus patients.

Objectives:

We conduct this survey to explore the disorder of the B cell development in the bone marrow of lupus patients.

Methods:

In this study, we have performed the scRNASeq to profile the bone marrow B cell compartment in lupus patients and healthy donors.

Results:

We identified that in a subset of lupus patients, the early B cells (proB and preB cells) were strongly decreased, which were confirmed by flow cytometry in an expanded cohort. Furthermore, bone marrow B cells from these patients showed a strong proinflammatory signature revealed by pathway analysis. Interestingly, BCR repertoire analysis showed that the IGHV-4-34 was highly enriched in these patients, indicating an enhanced B cell tolerance defect. Finally, a panel of proinflammatory cytokines (TNF-a, IL-1a, IL-12p70, IFN-g, et al.) were strongly increased in the bone marrow plasma of these patients compared with early B normal patients and healthy donors, confirming a localized proinflammatory microenvironment.

Conclusion:

Altogether, the current study has revealed that a defective early B cell development in lupus patients is associated with a more severe B cell tolerance defect and aggravated inflammation, which may shed new light on developing novel therapies by targeting relevant pathways.

References:

[1]Min Wang, Hua Chen, Jia Qiu, et al. Antagonizing miR-7 suppresses B cell hyperresponsiveness and inhibits lupus development. J Autoimmun 2020.

[2]A M Jacobi, D M Goldenberg, F Hiepe, et al. Differential effects of epratuzumab on peripheral blood B cells of patients with systemic lupus erythematosus versus normal controls. Ann Rheum Dis, 2008.

Acknowledgements:

This work was funded by Special project of clinical medicine of Nantong University (Grant/Award number: 2019LQ001), National Natural Science Foundation of China (Grant/Award number: 81671616, 81871278 and 82071838).

Disclosure of Interests:

None declared

AB0639 EXOSOMES DERIVED FROM ENDOTHELIAL CELLS PREVENT OSTEOBLAST APOPTOSIS IN STEROID-INDUCED OSTEONECROSIS OF THE FEMORAL HEAD RAT MODEL VIA THE PI3K/AKT/Bcl-2 SIGNAL PATHWAY

Background:

Osteonecrosis of the femoral head (ONFH) is a common disease caused by many trauma factors and un-trauma factors. Among those un-trauma factors, steroid-induced osteonecrosis of the femoral head (SNFH) accounted for a large proportion and mainly concentrated in young people. SNFH has been reported as an irreversible disease and associated with the damage of blood vessels and the loss balance of bone homeostasis. Circulating endothelial progenitor cells (CEPCs), one part of circulating endothelial cells (CECs), are immature precursor cells with proliferative potential. The damage of vascular endothelial cells in SNFH has been confirmed by many studies, but the changes of CECs and CEPCs in the peripheral blood of patients with SNFH have not been studied yet.

Objectives:

The objective of the study is to explore the number of CECs and CEPCs in SNFH patients and normal people and then investigate whether EC-secreted exosomes (EC-exos) could prevent the progression of SNFH in rat model and its mechanism of action.

Methods:

We collect peripheral blood of 3 SNFH patients and 3 heathy people and detected the levels of CECs and CEPCs by Flow cytometer. TEM, NTA and western blot was used to characterize the isolated EC-exos. Annexin V-FITC/PI double staining with flow cytometric analysis and western blot were used to evaluate MC3T3-E1 cells apoptosis. CCK-8, scratching experiment and transwell were used to evaluate MC3T3-E1 cells viability and migration ability. Micro-CT and morphological staining were used to evaluate the progress of SNFH in rat model.

Results:

Firstly, we found that the number of CECs and CEPCs in the peripheral blood was decreased in SNFH patients than normal people. Then our results indicated that EC-exos could improve the migration, viability and prevent apoptosis of osteoblasts under dexamethasone by activating the PI3K/AKT/Bcl-2 signal pathway in vitro. Finally, our Micro-CT and morphological staining results in SNFH rat model revealed that EC-exos prevented the progression of SNFH.

Conclusion:

EC-exos could enhance the cell viability and migration ability of osteoblasts under dexamethasone and play an anti-apoptosis role against steroids-induced osteoblast apoptosis by activating the PI3K/AKT/Bcl-2 signal pathway. EC-exos prevented the progression of SNFH in rat model.

References:

[1]Zalavras CG, Lieberman JR. Osteonecrosis of the femoral head: evaluation and treatment. J Am Acad Orthop Surg. 2014;22(7):455-64.

[2]Microsurgery Department of the Orthopedics Branch of the Chinese Medical Doctor A, Group from the O, Bone Defect Branch of the Chinese Association of R, Reconstructive S, Microsurgery, Reconstructive Surgery Group of the Orthopedics Branch of the Chinese Medical A. Chinese Guideline for the Diagnosis and Treatment of Osteonecrosis of the Femoral Head in Adults. Orthop Surg. 2017;9(1):3-12.

[3]Mont MA, Jones LC, Hungerford DS. Nontraumatic osteonecrosis of the femoral head: ten years later. J Bone Joint Surg Am. 2006;88(5):1117-32.

[4]Yuan HF, Zhang J, Guo CA, Yan ZQ. Clinical outcomes of osteonecrosis of the femoral head after autologous bone marrow stem cell implantation: a meta-analysis of seven case-control studies. Clinics (Sao Paulo). 2016;71(2):110-3.

[5]Houdek MT, Wyles CC, Packard BD, Terzic A, Behfar A, Sierra RJ. Decreased Osteogenic Activity of Mesenchymal Stem Cells in Patients With Corticosteroid-Induced Osteonecrosis of the Femoral Head. J Arthroplasty. 2016;31(4):893-8.

Disclosure of Interests:

None declared.

POS0787 BERBERINE MODULATE LUPUS SYNDROME VIA THE REGULATION OF GUT MICROBIOTA IN MRL/LPR MICE

Background:

Intestinal flora disorder and immune abnormalities have been reported in systemic lupus erythematosus (SLE) patients1,2. Berberine (BBR) showed significant effects in regulating the intestinal flora, repairing gut barriers and regulating immune cells3,4. While few reports mentioned the abnormal gut microbiota and metabolites in Chinese SLE patients.

Objectives:

Our investigation tried to illustrate the relationship between gut microbiota, intestinal metabolites and disease activity in Chinese SLE patients. And the effect of BBR to intestinal dysbacteriosis, multiple organ damages and over-activated immune system in MRL/Lpr mice.

Methods:

16S high-throughput (16S rRNA) sequence, qRT-PCR and gas chromatography technology were used to determine the gut microbiota and metabolites in 104 SLE patients from Affiliated Hospital of Nantong University, China. BBR was orally treated to the MRL/Lpr mice in low, medium and high doses. After 6 weeks treatment, mice were sacrificed. Serum, faeces and organs were collected for further studies.

Results:

Chinese SLE patients showed higher abundance of Bacteroidetes and lower abundance of Firmcutes. The results of qRT-PCR showed high Firmcutes/Bacteroidetes (F/B) ratio of SLE patients. The F/B ratio was negative correlated with SLE disease activity index (SLEDA) score. Almost all the tested short-chain fatty acids (SCFAs) found statistically significant results in SLE and LN (lupus nephritis) patients, especially the propanoic acid and butyric. BBR altered the relative abundance of Bacteroides and Verrucomicrobia and the butyric acid content in colon of MRL/Lpr mice. The increase of tight junction protein also indicated the gut barrier was repaired by BBR. Treg and Tfr cells in spleen and mesenteric lymph node (MLN) were increased. These results revealed a positive therapeutic effect of berberine on SLE from gut microbiota to immune status.

Conclusion:

Our study highlights current status of intestinal dysbacteriosis in Chinese patients with SLE and differences in intestinal metabolites among patients with different disease states. The regulation of intestinal flora and the repairment of gut barrier by intestinal metabolites in BBR treated mice seemed to be the factor that directed the immune responses and disease outcomes. The ultimate goal of our study was to determine the beneficial effects of regulating the gut microbiota on the treatment of SLE. The application of berberine is a relatively safe and convenient way. In the coming investigations, we plan to focus on the study of berberine and its metabolites on intestinal function and systemic immunity.

References:

[1]Guo, M. et al. Alteration in gut microbiota is associated with dysregulation of cytokines and glucocorticoid therapy in systemic lupus erythematosus. Gut microbes11, 1758-1773, doi:10.1080/19490976.2020.1768644 (2020).

[2]Mu, Q. et al. Control of lupus nephritis by changes of gut microbiota. Microbiome5, 73, doi:10.1186/s40168-017-0300-8 (2017).

[3]Habtemariam, S. Berberine pharmacology and the gut microbiota: A hidden therapeutic link. Pharmacological research155, 104722, doi:10.1016/j.phrs.2020.104722 (2020).

[4]Cui, H. et al. Berberine Regulates Treg/Th17 Balance to Treat Ulcerative Colitis Through Modulating the Gut Microbiota in the Colon. Frontiers in pharmacology9, 571, doi:10.3389/fphar.2018.00571 (2018).

Figure 1.

Disclosure of Interests:

None declared

POS0761 INVESTIGATION ON THE EFFECT AND MECHANISM OF ABNORMALLY ACTIVATED CD8+ T CELLS FROM BONE MARROW ON HEMATOPOIETIC STEM CELLS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS

Background:

SLE is an autoimmune disease characterized by the abnormal function of lymphocytes. The impairment of hematopoietic function of bone marrow participates in its pathogenesis, in which T cells play an important role. However, study on bone marrow T cells in SLE patients is very limited.

Objectives:

This study aims to characterize the phenotype and molecular characteristics of abnormally activated CD8+T cells in bone marrow of SLE patients and explore the mechanism of hematopoietic stem cells (HSCs) reduction caused by the abnormally activated CD8+T cells in bone marrow of patients with SLE.

Methods:

A total of 8 SLE patients and 5 age- and sex-matched controls were recruited in our study. Among them, 3 SLE patients and 4 donors were collected bone marrow and peripheral blood samples for Single-cell RNA sequencing (scRNA-seq) and functional studies. BM and peripheral T cell subsets were measured by flow cytometry. Plasma cytokines and secreted immunoglobulins were detected by Luminex. Disease activity of SLE patients was measured using the SLE Disease Activity Index (SLEDAI). All analyses were performed using R language and Flowjo 9.

Results:

In the present study, SLE patients had increased CD8+T%αβT cells and decreased CD4+T%αβT cells in bone marrow of SLE, compared to healthy controls. A large number of CD38+HLADR+CD8+T cells existed in the bone marrow and peripheral blood of SLE patients. Those patients also showed reduced number of HSCs, and with a downward trend of the numbers of peripheral red blood cells, white blood cells, neutrophils, hemoglobin, and platelets. By scRNA-seq, the CD38+HLADR+CD8+T cells contained high levels of GZMK, GZMA, PRF1, IFNG, and TNF in the bone marrow of SLE patients. the CD38+HLADR+CD8+T cells exhibited significant relationship with HSCs, white blood cells, neutrophils, and platelets.

Conclusion:

These findings demonstrated that the abnormally activated CD8+T cells in bone marrow can reduce the number of HSCs by the expression of killer molecules, which contributes to the impairment of hematopoietic function and the development of SLE. This project focuses on the specific bone marrow T cell subset in SLE. The completement of this project provides information for exploring the mechanism of hematopoiesis involvement.

References:

[1]Anderson E, Shah B, Davidson A, Furie R. Lessons learned from bone marrow failure in systemic lupus erythematosus: Case reports and review of the literature. Semin Arthritis Rheum. 2018;48(1):90-104.

[2]Sun LY, Zhou KX, Feng XB, Zhang HY, Ding XQ, Jin O, Lu LW, Lau CS, Hou YY, Fan LM. Abnormal surface markers expression on bone marrow CD34+cells and correlation with disease activity in patients with systemic lupus erythematosus. Clin Rheumatol. 2007;26(12):2073-2079.

Acknowledgements:

We want to thank Lu Meng, Teng Li, Wei Zhou, and Jiaxin Guo for their assistance with this study.

Disclosure of Interests:

None declared

POS0785 CHANGING EXPRESSION PROFILES OF LONG NONCODING RNAS, MIRNAS, MRNAS AND CIRCULAR RNAS IN LABIAL SALIVARY GLANDS OF PRIMARY SJÖGREN’S SYNDROME (PSS)

Background:

Primary Sjögren’s syndrome (pSS) is a relatively common autoimmune disease characterized by oral and ocular dryness. An increasing number of studies have revealed that long non-coding RNA (lncRNA), miRNA, mRNA and circular RNA (circRNA) contributes to the pathogenesis of autoimmune diseases.

Objectives:

To explore lncRNA, miRNA, mRNA and circRNA expression profiles in labial salivary glands (LSGs) in pSS patients and their biological functions in the regulation of pSS.

Methods:

The expression of 75,550 lncRNAs, 2,318 miRNA, 20,292 mRNAs and 6,877 circRNAs were determined in the LSG of six pSS patients and six healthy controls using microarray experiments. Validation was performed in pSS patients and controls using real-time PCR. LncRNA-mRNA co-expression and gene-pathway networks were constructed using bioinformatics software.

Results:

A total of 599 lncRNAs (upregulated: 279, downregulated: 320), 78 miRNAs (upregulated: 26, downregulated: 52), 615 mRNAs (upregulated: 590, downregulated: 25) and 160 mRNAs (upregulated: 110, downregulated: 50) were differentially expressed in the LSGs of pSS patients. Five of these lncRNAs were validated using real-time PCR. lncRNA HCP5, lncRNA SNHG5, lncRNA IFI44L, lncRNA CMPK2 were significantly upregulated and lncRNA TTYH1 were downregulated in pSS. GO and KEGG biological pathway analysis were performed to predict the functions of differentially expressed lncRNAs and co-expressed potential targeting genes. Subsequently, a ceRNA (lncRNA-miRNA-mRNA) network including 2320 ceRNA pairs was constructed based on predicted miRNAs shared by lncRNAs and mRNAs.

Conclusion:

The expression profile provided a systematic perspective on the potential functions of lncRNAs miRNAs, mRNAs and circRNAs in the pathogenesis of pSS. Therefore, this study will aid in the development of new diagnostic biomarkers and drug therapies.

References:

[1]Le Dantec C, Varin MM, Brooks WH, Pers JO, Youinou P, Renaudineau Y. Epigenetics and Sjogren’s syndrome.Curr Pharm Biotechnol. 2012 Aug;13(10):2046-53.

Disclosure of Interests:

None declared

Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces

A brain-computer interface (BCI) measures and analyzes brain activity and converts this activity into computer commands to control external devices. In contrast to traditional BCIs that require a subject-specific calibration process before being operated, a subject-independent BCI learns a subject-independent model and eliminates subject-specific calibration for new users. However, building subject-independent BCIs remains difficult because electroencephalography (EEG) is highly noisy and varies by subject. In this study, we propose an invariant pattern learning method based on a convolutional neural network (CNN) and big EEG data for subject-independent P300 BCIs. The CNN was trained using EEG data from a large number of subjects, allowing it to extract subject-independent features and make predictions for new users. We collected EEG data from 200 subjects in a P300-based spelling task using two different types of amplifiers. The offline analysis showed that almost all subjects obtained significant cross-subject and cross-amplifier effects, with an average accuracy of more than 80%. Furthermore, more than half of the subjects achieved accuracies above 85%. These results indicated that our method was effective for building a subject-independent P300 BCI, with which more than 50% of users could achieve high accuracies without subject-specific calibration.

AB0146 HAND AND WRIST ACTIVE RANGE OF MOTIONS AND CONTRIBUTING FACTORS IN RHEUMATOID ARTHRITIS: A CROSS-SECTIONAL STUDY

Background:

Patients with rheumatoid arthritis (RA) usually impaired range of motions (ROMs), especially hand and wrist active ROMs (AROMs), thus influencing their ability to perform daily activities and health-related quality of life (HR-QoL). However, little is known about the potential factors of reduced hand and wrist AROMs and their relations to quality of life in Chinese RA patients.

Objectives:

To explore the contributing factors of hand and wrist AROMs and their associations with HR-QoL and functional limitation in Chinese RA population.

Methods:

In this cross-sectional study, 108 patients were enrolled from Affiliated Hospital of Nantong University between November 2018 and July 2019. We measured all the participants’ AROMs with different directions of the hand and wrist in both sides, including volar flexion, ulnar deviation, radial deviation and radial deviation of the wrist joint, the first metacarpophalangeal (MCP1) flexion, interphalangeal (IP) flexion, volar abduction, radial abduction and thumb opposition (cm) in the thumb, average flexion, hypertension and abduction of the MCP2-5, average proximal interphalangeal (PIP) 2-5 and distal interphalangeal (DIP) 2-5 flexions, total active range of motion (TAM) of the second to the fifth fingers (TAM2-TAM5). Their sociodemographic, physical, psychological, disease-related data, acute phase reactants, laboratory indicators, drug usage and HR-QoL were examined as well. Statistical analysis used Pearson’s and Spearman’s correlation analysis, univariate and multivariate linear regression analyses.

Results:

In univariate analyses, we found that living in rural area, longer disease duration, comorbidity, hospitalization, more swollen joints, higher disease activity, pain level, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), red blood cell count and glucocorticoids usage were associated with most of the decreased hand and wrist AROMs (P ≤ 0.050), while higher education and annual income were related to most of the increased hand and wrist AROMs (P ≤ 0.048). In multivariate analyses, higher disease duration (P ≤ 0.023) and higher disease activity (P ≤ 0.033) were corelated with most of the decreased hand and wrist AROMs. Interestingly, the psychological factor, anxiety, was only positively associated with thumb opposition in both univariate and multivariate analyses (P ≤ 0.001). Additionally, most of the declined hand and wrist AROMs were associated with functional impairment and poor HR-QoL, especially in physical components (P < 0.05).

Conclusion:

Various factors, especially longer disease duration and higher disease activity, were related to decreased hand and wrist AROMs, and thus causing functional impairment and poor HR-QoL in RA patients. Clinical physicians and medical faculties should pay more attention to disease activity and disease-related symptoms of these patients in order to maintain their activity of daily living (ADL) ability and improve HR-QoL.

References:

[1]Rheumatoid arthritis. Nat Rev Dis Primers. 2018;4:18002.

[2]Zhang L, Cao H, Zhang Q, Fu T, Yin R, Xia Y, et al. Motion analysis of the wrist joints in Chinese rheumatoid arthritis patients: a cross-sectional study. BMC Musculoskelet Disord. 2018;19(1):270.

Acknowledgements:

This work was funded by Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant/Award number: KYCX19_2071), National Natural Science Foundation of China (Grant/Award number: 81871278, Science and technology Project of Jiangsu Province (Grant/Award number: BE2018671)

Disclosure of Interests:

None declared

Capsule Network for ERP Detection in Brain-Computer Interface

Event-related potential (ERP) is bioelectrical activity that occurs in the brain in response to specific events or stimuli, reflecting the electrophysiological changes in the brain during cognitive processes. ERP is important in cognitive neuroscience and has been applied to brain-computer interfaces (BCIs). However, because ERP signals collected on the scalp are weak, mixed with spontaneous electroencephalogram (EEG) signals, and their temporal and spatial features are complex, accurate ERP detection is challenging. Compared to traditional neural networks, the capsule network (CapsNet) replaces scalar-output neurons with vector-output capsules, allowing the various input information to be well preserved in the capsules. In this study, we expect to utilize CapsNet to extract the discriminative spatial-temporal features of ERP and encode them in capsules to reduce the loss of valuable information, thereby improving the ERP detection performance for BCI. Therefore, we propose ERP-CapsNet to perform ERP detection in a BCI speller application. The experimental results on BCI Competition datasets and the Akimpech dataset show that ERP-CapsNet achieves better classification performances than do the state-of-the-art techniques. We also use a decoder to investigate the attributes of ERPs encoded in capsules. The results show that ERP-CapsNet relies on the P300 and P100 components to detect ERP. Therefore, ERP-CapsNet not only acts as an outstanding method for ERP detection, but also provides useful insights into the ERP detection mechanism.

Multi-omics integration identifies key upstream regulators of pathomechanisms in hypertrophic cardiomyopathy due to truncating MYBPC3 mutations

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is the most common genetic disease of the cardiac muscle, frequently caused by mutations in MYBPC3. However, little is known about the upstream pathways and key regulators causing the disease. Therefore, we employed a multi-omics approach to study the pathomechanisms underlying HCM comparing patient hearts harboring MYBPC3 mutations to control hearts.

RESULTS

Using H3K27ac ChIP-seq and RNA-seq we obtained 9310 differentially acetylated regions and 2033 differentially expressed genes, respectively, between 13 HCM and 10 control hearts. We obtained 441 differentially expressed proteins between 11 HCM and 8 control hearts using proteomics. By integrating multi-omics datasets, we identified a set of DNA regions and genes that differentiate HCM from control hearts and 53 protein-coding genes as the major contributors. This comprehensive analysis consistently points toward altered extracellular matrix formation, muscle contraction, and metabolism. Therefore, we studied enriched transcription factor (TF) binding motifs and identified 9 motif-encoded TFs, including KLF15, ETV4, AR, CLOCK, ETS2, GATA5, MEIS1, RXRA, and ZFX. Selected candidates were examined in stem cell-derived cardiomyocytes with and without mutated MYBPC3. Furthermore, we observed an abundance of acetylation signals and transcripts derived from cardiomyocytes compared to non-myocyte populations.

CONCLUSIONS

By integrating histone acetylome, transcriptome, and proteome profiles, we identified major effector genes and protein networks that drive the pathological changes in HCM with mutated MYBPC3. Our work identifies 38 highly affected protein-coding genes as potential plasma HCM biomarkers and 9 TFs as potential upstream regulators of these pathomechanisms that may serve as possible therapeutic targets.

Microsatellite markers reveal polymorphisms at the 3′ untranslated region of the SLC11A1 gene in Zhongdian Yellow cattle (Bos taurus)

Solute carrier family 11-member A1 (SLC11A1) gene encodes natural macrophage resistance-associated protein which regulates activity of macrophages against intracellular pathogens. The objective of this study was to study the polymorphism in the microsatellites present at 3′ untranslated region (UTR) of the SLC11A1 gene in 113 Zhongdian Yellow cattle (Bos taurus). Using DNA bi-directional sequencing, we detected seven alleles (GT10–16) for the first microsatellite (MS1), five alleles (GT12–16) for MS2, and four alleles (GT4–7) for MS3. MS3 is studied for the first time and revealed four novel variants (alleles GT4–7). Alleles GT12 (45.1%), GT13 (59.3%), and GT5 (85.4%) were the most frequent alleles at MS1, MS2, and MS3, respectively, Genotypes G12/12, G13/13, and G5/5 had the highest frequency 0.239, 0.540, and 0.743 at MS1, MS2, and MS3, respectively. Haplotypic data revealed that GT12/GT13 was the most frequent haplotype observed followed by GT12/14 haplotype. Three nucleotide variations were observed in MS1 and MS2. Comparative analysis of GT12/GT12 and GT13/GT13 genotype with other bovine genotypes showed significant difference (P > 0.05). Our results suggest that the homozygous genotypes GT12/GT12 and GT13/GT13 in Zhongdian Yellow cattle might be related to disease resistance. The findings reported in this study would be helpful in cattle breeding programs.

Spatiotemporal-Filtering-Based Channel Selection for Single-Trial EEG Classification

Achieving high classification performance in electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often entails a large number of channels, which impedes their use in practical applications. Despite the previous efforts, it remains a challenge to determine the optimal subset of channels in a subject-specific manner without heavily compromising the classification performance. In this article, we propose a new method, called spatiotemporal-filtering-based channel selection (STECS), to automatically identify a designated number of discriminative channels by leveraging the spatiotemporal information of the EEG data. In STECS, the channel selection problem is cast under the framework of spatiotemporal filter optimization by incorporating a group sparsity constraints, and a computationally efficient algorithm is developed to solve the optimization problem. The performance of STECS is assessed on three motor imagery EEG datasets. Compared with state-of-the-art spatiotemporal filtering algorithms using full EEG channels, STECS yields comparable classification performance with only half of the channels. Moreover, STECS significantly outperforms the existing channel selection methods. These results suggest that this algorithm holds promise for simplifying BCI setups and facilitating practical utility.

A P300-Based BCI System Using Stereoelectroencephalography and Its Application in a Brain Mechanistic Study

Stereoelectroencephalography (SEEG) signals can be obtained by implanting deep intracranial electrodes. SEEG depth electrodes can record brain activity from the shallow cortical layer and deep brain structures, which is not achievable through other recording techniques. Moreover, SEEG has the advantage of a high signal-to-noise ratio (SNR). Therefore, it provides a potential way to establish a highly efficient brain-computer interface (BCI) and aid in understanding human brain activity. In this study, we implemented a P300-based BCI using SEEG signals. A single-character oddball paradigm was applied to elicit P300. To predict target characters, we fed the feature vectors extracted from the signals collected by five SEEG contacts into a Bayesian linear discriminant analysis (BLDA) classifier. Thirteen epileptic patients implanted with SEEG electrodes participated in the experiment and achieved an average online spelling accuracy of 93.85%. Moreover, through single-contact decoding analysis and simulated online analysis, we found that the SEEG-based BCI system achieved a high performance even when using a single signal channel. Furthermore, contacts with high decoding accuracies were mainly distributed in the visual ventral pathway, especially the fusiform gyrus (FG) and lingual gyrus (LG), which played an important role in building P300-based SEEG BCIs. These results might provide new insights into P300 mechanistic studies and the corresponding BCIs.

Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain-Computer Interfaces

Motor imagery (MI) decoding is an important part of brain-computer interface (BCI) research, which translates the subject's intentions into commands that external devices can execute. The traditional methods for discriminative feature extraction, such as common spatial pattern (CSP) and filter bank common spatial pattern (FBCSP), have only focused on the energy features of the electroencephalography (EEG) and thus ignored the further exploration of temporal information. However, the temporal information of spatially filtered EEG may be critical to the performance improvement of MI decoding. In this paper, we proposed a deep learning approach termed filter-bank spatial filtering and temporal-spatial convolutional neural network (FBSF-TSCNN) for MI decoding, where the FBSF block transforms the raw EEG signals into an appropriate intermediate EEG presentation, and then the TSCNN block decodes the intermediate EEG signals. Moreover, a novel stage-wise training strategy is proposed to mitigate the difficult optimization problem of the TSCNN block in the case of insufficient training samples. Firstly, the feature extraction layers are trained by optimization of the triplet loss. Then, the classification layers are trained by optimization of the cross-entropy loss. Finally, the entire network (TSCNN) is fine-tuned by the back-propagation (BP) algorithm. Experimental evaluations on the BCI IV 2a and SMR-BCI datasets reveal that the proposed stage-wise training strategy yields significant performance improvement compared with the conventional end-to-end training strategy, and the proposed approach is comparable with the state-of-the-art method.

Molecular cloning, tissue expression and polymorphism analysis of the Caveolin-3 gene in ducks

1. Duck meat is considered a delicacy, but choosing the best meat is problematic. Caveolin-3 (CAV-3) is a muscle-specific protein marker in animals. The goal of the current study was to detect the characteristics of CAV-3 gene in ducks. 2. Full-length CAV-3 was acquired from ducks (Anas platyrhynchos) using reverse transcriptase PCR and rapid amplification of cDNA ends. DNAMAN software was used for homology comparisons. Quantitative reverse transcription-PCR, PCR-single-strand conformation polymorphism, and sequencing were used to determine CAV-3 expression and polymorphism of a single nucleotide, respectively. The study examined four types of ducks, including Jinding, Chaohu, Cherry Valley, and Gaoyou ducks. 3. The study acquired 1066 bp of CAV-3 cDNA sequences, including a 456 bp complete open reading frame encoding 151 amino acids. Both coding sequences (CDSs) and translated amino acids exhibited highest homology with Gallus gallus (CDS homology 91.67%, amino acids 94.04%), followed by mammalian species (CDS homology 79.0%, amino acids 78.0%). Single nucleotide polymorphism analysis revealed five mutations in exons (A489G, G501A, A557G, T563A, and A602G), and a C805T mutation in an intron. Among amplified polymorphic loci detected using primer 2, allele frequency was higher for A (489A501G507A563T602A) than B (489G501G507G563T602C) or C (489G501A507G563A602C). The highest occurred in Cherry Valley ducks (0.7587). Using primer 4, the M allele frequency was higher than that of the N allele. CAV-3 was most highly expressed in the heart, followed by skeletal muscles. Additionally, CAV-3 had higher expression in heart and breast muscle of overfed Muscovy ducks than control ducks, but no difference was seen in thigh muscle. 4. CAV-3 in ducks had the highest homology with Gallus gallus CAV-3, and it could be used as a marker for muscle quality in ducks.

Effects of glucocorticoids on osteoporosis in rheumatoid arthritis: a systematic review and meta-analysis

We evaluated the effects of glucocorticoids on bone mineral density (BMD), and prevalence of osteoporosis and fracture in rheumatoid arthritis (RA) by meta-analysis. Until June 26, 2019, we conducted a systematic literature search in EMBASE, Web of science, PubMed, and Cochrane Library to obtain BMD and the prevalence of osteoporosis and fracture in glucocorticoid-treated subjects with RA. The BMD of the treatment and control groups were analyzed by meta-analysis (Stata. version 15), and the 95% confidence interval (CI) was calculated. We identified 15 observational studies, including 46,711 RA subjects and 857 healthy controls. The BMD of the lumbar spine (- 0.038 g/cm²; CI, - 0.052, - 0.024) and femoral neck (- 0.017 g/cm²; - 0.030, - 0.003) in RA treated with glucocorticoids were significantly lower than those in RA controls. Compared with healthy control group, the BMD of the lumbar spine (- 0.094 g/cm²; - 0.126, - 0.061) and femoral neck (- 0.097 g/cm², - 0.109, - 0.085) of RA treated with glucocorticoids decreased more significantly. The prevalence of osteoporosis in whole body, spine, and femur was 38.6% (0.305, 0.466), 32.9% (0.277, 0.381), and 21.7% (0.106, 0.328), respectively. And the prevalence of vertebral fracture was 13.0% (0.058, 0.203). Glucocorticoids may lead to a decline in skeletal health in subjects with RA, especially in vertebral and femoral BMD, compared with normal people or RA without glucocorticoid therapy. Meanwhile, osteoporosis and fractures were also common. Therapeutic measures should be targeted at individuals, which needs further study. Through meta-analysis, we found that glucocorticoids have some negative effects on the bone health of subjects with rheumatoid arthritis. Therefore, when using glucocorticoids to treat rheumatoid arthritis, we should take strategic measures to prevent the decline of bone quality.

Self-adaptive shared control with brain state evaluation network for human-wheelchair cooperation

OBJECTIVE

For the shared control systems, how to trade off the control weight between robot autonomy and human operator is an important issue, especially for BCI-based systems. However, most of existing shared controllers have paid less attention to the effects caused by subjects with different levels of brain control ability.

APPROACH

In this paper, a brain state evaluation network, termed BSE-NET, is proposed to evaluate subjects' brain control ability online based on quantized attention-gated kernel reinforcement learning. With the output of BSE-NET (confidence score), a shared controller is designed to dynamically adjust the control weight between robot autonomy and human operator.

MAIN RESULTS

The experimental results show that most of subjects achieved high and stable experimental success rate of approximately 90%. Furthermore, for subjects with different accuracy on EEG decoding, a proper confidence score can be dynamically generated to reflect their levels of brain control ability, and the proposed system can effectively adjust the control weight in all-time shared control.

SIGNIFICANCE

We discuss how our proposed method shows promise for BCI applications that can evaluate subjects' brain control ability online as well as provide a method for the research on self-adaptive shared control to adaptively balance control weight between subject's instruction and robot autonomy.

Comparison of sound location variations in free and reverberant fields: An event-related potential study

This study compares event-related potentials (ERPs) elicited by variations of sound location in free and reverberant fields. The virtual sound sources located at azimuths 0°-40° were synthesized with head-related transfer functions and binaural room impulse responses for free and reverberant fields, respectively. The sound stimulus at 0° was assigned as standard in the oddball paradigm. Results show that the P3 amplitude is larger in the free field and acoustical conditions have no significant effect on the amplitudes of N2 and mismatch negativity. Moreover, a linear relationship between sound angle and amplitude of ERP components is observed.

AB1331-HPR ACTIVE DISEASE ACTIVITY IN ANKYLOSIS SPONDYLITIS: WORSE OUTCOMES AND POORER HR-QOL

Background:

Ankylosing spondylitis (AS) is a chronic inflammatory disease that mainly affects the sacroiliac joints and the spine, resulting in decline in quality of life[1,2]. Poor QoL is significantly related to high disease activity[3]. However, there is no systematic report on which prognosis indicators are affected by disease activity in AS patients.

Objectives:

This study aimed to evaluate the patient-reported outcome measures and health-related quality of life (HR-QoL) in AS patients defined on the basis of the Bath Spondylitis Ankylosing Disease Activity Index (BASDAI).

Methods:

204 AS patients were involved in this study. A serious of questionnaires were used to overall assess AS patients, which include: Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Bath Ankylosing Spondylitis Functional Index (BASFI), the 10 cm Visual Analog Scale (VAS), the Self-Rating Anxiety Scale (SAS), the Self-Rating Depression Scale (SDS), the Pittsburgh Sleep Quality Index (PSQI), the Health Assessment Questionnaire-Disability Index (HAQ-DI), the Fatigue Severity Scale(FSS) and the Short Form 36 Health Survey (SF-36). Independent samples t-test, Mann–Whitney U-test, Chi-square analysis and Pearson /Spearman correlation were used to analyze the data.

Results:

The results demonstrated 31.4% AS patients were in active disease activity stage. Active AS patients were older, unemployed, and had less exercise therapy than stable AS patients. Besides, AS patients with active disease activity presented more severe pain(P<0.001), poor physical function(P<0.001) and spinal mobility(P<0.001). They were more anxious(P<0.001), depressed(P<0.001) and had more sleep disturbance(P=0.001). Compared with active AS patients, stable AS patients had more leukocytes(P=0.040), lymphocytes(P=0.002), erythrocytes(P=0.001) and hemoglobin(P<0.001). Active disease activity had a significant impact on all dimensions of quality of life in AS patients(P<0.001).

Conclusion:

These findings suggested that medical personnel should pay more attention to active AS patients and make effective interventions to improve quality of life.

References:

[1]Exarchou S, Lindstrom U, Askling J, Eriksson JK, Forsblad-d’Elia H, Neovius M, Turesson C, Kristensen LE, Jacobsson LT (2015) The prevalence of clinically diagnosed ankylosing spondylitis and its clinical manifestations: a nationwide register study. Arthritis research & therapy 17:118. doi:10.1186/s13075-015-0627-0

[2]Qian Q, Xu X, He H, Ji H, Zhang H, Ding Y, Dai SM, Zou Y, Zhu Q, Yang C, Ye S, Jiang L, Tang JP, Tong Q, He D, Zhao D, Li Y, Ma Y, Zhou J, Yuan Z, Zhang J, Jin L, Zhou X, Reveille JD, Zou H, Wang J (2017) Clinical patterns and characteristics of ankylosing spondylitis in China. Clinical rheumatology 36 (7):1561-1568. doi:10.1007/s10067-017-3660-3

[3]Huang JC, Qian BP, Qiu Y, Wang B, Yu Y, Zhu ZZ, Hu J, Qu Z (2017) Quality of life and correlation with clinical and radiographic variables in patients with ankylosing spondylitis: a retrospective case series study. BMC musculoskeletal disorders 18 (1):352. doi:10.1186/s12891-017-1711-1

Acknowledgments:

Thanks to all the authors for their efforts and thanks to all members of the Department of Rheumatology of Affiliated Hospital of Nantong University for their helpfulness in the acquisition of data.

Disclosure of Interests:

None declared

THU0044 SINGLE CELL ANALYSIS OF BONE MARROW AND PERIPHERAL ALTERED B CELL DIFFERENTIATION IN PATIENTS WITH ACTIVE SLE AND THE MECHANISM OF ABNORMAL EARLY B CELL DEVELOPMENT

Background:

B cell differentiation and dysfunction play a key role in the pathogenesis of Systemic lupus erythematosus (SLE). Bone marrow (BM) is the development organ of B cells, and also the home and residence place of plasma cells and memory B cells. However, there is a lack of studies on B cells in BM with lupus.

Objectives:

To map the development of BM and peripheral B cells and investigate the mechanism of abnormal early B cell development in SLE.

Methods:

A total of 11 SLE patients and 5 age- and sex-matched controls were recruited.BM and peripheral B cell subsets were measured by flow cytometry. sorting-purified B cell subsets were subject toSingle-cell RNA sequencing (scRNA-seq) and functional studies. Plasma cytokines and secreted immunoglobulins were detected by Luminex or ELISA. Disease activity of SLE patients was measured using the SLE Disease Activity Index (SLEDAI).

Results:

In the present study, we find out that the percentage of monocytes in MNC (p=0.070) and plasma cells(p=0.001)in CD19+ were significantly decreased in BM of SLE, compared to healthy controls. While, SLE patients had increased T%MNC(p=0.008) and B%CD19+(p=0.002) in BM that controls. In detail, the B cell subsets of bone marrow in patients with active lupus (SLEDAI≥8 score) were seriously disordered, showing the increasing T%MNC(p=0.049), propre-B%CD19+ (p=0.006)and immature B cell%CD19+ (p=0.010) than healthy donors. propre-B%CD19+ exhibited good relationship with SLEDAI. By integrating single B cell expression profiling and repertoire analysis, we map the development of B cells in BM and peripheral and pathogenic characteristics of early B cells, especially propre-B.

Conclusion:

These findings demonstrated that early B cells in BM, especially propre-B are abnormally differentiated with dysregulations. BM is an important organ targeted by SLE. This studyis not only to clarify the internal mechanism of the disorder of differentiation of B cells, but also to provide new clues for the targeted diagnosis and treatment of SLE.

References:

[1]Palanichamy, A., et al.,Neutrophil-mediated IFN activation in the bone marrow alters B cell development in human and murine systemic lupus erythematosus.J Immunol, 2014.192(3): p. 906-18.

[2]Papadaki, H.A., J.C. Marsh, and G.D. Eliopoulos,Bone marrow stem cells and stromal cells in autoimmune cytopenias.Leuk Lymphoma, 2002.43(4): p. 753-60.

[3]Karrar, S. and D.S. Cunninghame Graham,Abnormal B Cell Development in Systemic Lupus Erythematosus: What the Genetics Tell Us.Arthritis Rheumatol, 2018.70(4): p. 496-507.

[4]Woods, M., Y.R. Zou, and A. Davidson,Defects in Germinal Center Selection in SLE.Front Immunol, 2015.6: p. 425.

[5]Upregulation of p16INK4A promotes cellular senescence of bone marrow-derived mesenchymal stem cells from systemic lupus erythematosus patients.Cell Signal, 2012.24(12): p. 2307-14.

Disclosure of Interests:

None declared

AB1330-HPR ASSOCIATION OF INTERSTITIAL LUNG DISEASE AND QUALITY OF LIFE IN CHINESE RHEUMATOID ARTHRITIS

Background:

The health-related quality of life (HRQL) of patients with rheumatoid arthritis associated interstitial lung disease (RA-ILD) is less concerned(1). This study hypothesized that HRQL of such patients decreased.

Objectives:

The aim of this study was to assess the difference in HRQL between RA with and without ILD, and to predict risk factors of HRQL in Chinese RA-ILD.

Methods:

A cross-sectional survey of RA-ILD patients included socio-demographic characteristics, clinical variables, psychological factors and HRQL. Data were analyzed by Student’s t or chi-square test. Linear regression analysis was used to investigate the predictors of HRQL in RA-ILD.

Results:

The data showed that 35.17% (51/145) of RA patients had ILD. There are significant differences in age, sex, smoking history, disease duration and activity between RA with and without ILD. HRQL of RA-ILD was impaired. Physical component score (PCS) of patients with RA-ILD was also worse than that of RA without ILD (48.91±2.48 vs. 50.80±2.55). Linear regression analysis showed that DAS28 and fatigue were risk factors for PCS in patients with RA-ILD, while depression and rural residence were risk factors for mental components summary in Table 1.

Table 1.

Stepwise multiple linear regression analysis of PCS and MCS in RA-ILD

PredictorsBSEtP95%CIPCSDAS28-0.7770.227-3.4250.001-1.236,-0.319Fatigue-0.6550.206-3.1770.003-1.071, -0.238MCSDepression2.1880.6693.2720.0020.836, 3.539Rural residents-1.6090.756-2.1280.040-3.137,-0.081

Footnotes: CI=Confidence interval. PCS=Physical component score; MCS=Mental component score; DAS28=28-joint disease activity score.

Conclusion:

Compared with RA without ILD, HRQL of patients with RA-ILD was significantly impaired. Disease activity, fatigue, depression and rural residence were independent predictors of HRQL in Chinese RA-ILD.

References:

[1]Zamora-Legoff JA, Krause ML, Crowson CS, Ryu JH, Matteson EL. Patterns ofinterstitial lung disease and mortality in rheumatoid arthritis. Rheumatology (Oxford, England). 2017;56(3):344-50.

Disclosure of Interests:

None declared

SAT0625-HPR FATIGUE AND CONTRIBUTING FACTORS IN CHINESE PATIENTS WITH ANKYLOSING SPONDYLITIS

Background:

Ankylosing spondylitis (AS) is a systemic chronic inflammatory disease, which most likely occurs in young men. It mainly affects sacroiliac joints, axial skeleton, thoracic cage and seriously decreasing quality of life in AS patients[1,2]. In recent years, fatigue of AS patients has been paid more and more attention[3]. Fatigue is a complex feeling, diseased individuals describe fatigue as a sense of tiredness at rest, exhaustion with activity, lack of energy which affects daily work, inertia or lack of endurance, or as loss of vitality. It has been confirmed that fatigue is not only a symptom but may also be quantified by fatigue scores and can be modified by various measures depending on the underlying cause[4]. However, there has been no study about fatigue in AS patients in China.

Objectives:

This study aimed to evaluate the predictors of fatigue and the effects of fatigue on HR-QoL among patients with AS.

Methods:

A total of 150 AS patients were involved in the study. A series of questionnaires included: Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Bath Ankylosing Spondylitis Functional Index (BASFI), the 10 cm Visual Analog Scale (VAS), the Self-Rating Anxiety Scale (SAS), the Self-Rating Depression Scale (SDS), the Pittsburgh Sleep Quality Index (PSQI), the Health Assessment Questionnaire-Disability Index (HAQ-DI), the Short Form 36 Health Survey (SF-36) and the Fatigue Severity Scale(FSS). Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation and binary logistic regression were used to analyze the data.

Results:

The results demonstrated that 48.7% individuals with AS suffered from fatigue. Compared with AS patients without fatigue, AS patients with fatigue showed higher WHR(P<0.05), increased BASDAI (P<0.01) and poorer BASFI (P<0.05). Meanwhile, AS patients with fatigue tended to have more severe pain(P<0.05), higher degree of anxiety(P=0.001), more serious functional disability(P=0.001) and worse sleep quality(P=0.001). Binary logistic regression indicated that WHR (OR=1.78,P<0.05), BASDAI (OR=1.34,P=0.01), sleep disturbance (OR=2.35,P<0.05) were independent predictors of fatigue in AS patients. Additionally, the occurrence of fatigue significantly reduced the quality of life in AS patients both physically and psychologically.

Conclusion:

These findings suggested that medical personnel should pay more attention to AS patients with fatigue and take effective measures to relieve fatigue.

References:

[1]Law L, Beckman Rehnman J, Deminger A, Klingberg E, Jacobsson LTH, Forsblad-d’Elia H (2018) Factors related to health-related quality of life in ankylosing spondylitis, overall and stratified by sex. Arthritis research & therapy 20 (1):284. doi:10.1186/s13075-018-1784-8

[2]Hanson A, Brown MA (2017) Genetics and the Causes of Ankylosing Spondylitis. Rheumatic diseases clinics of North America 43 (3):401-414. doi:10.1016/j.rdc.2017.04.006

[3]Ulus Y, Akyol Y, Bilgici A, Kuru O (2019) Association of work instability with fatigue and emotional status in patients with ankylosing spondylitis: comparison with healthy controls. Clinical rheumatology 38 (4):1017-1024. doi:10.1007/s10067-018-4366-x

[4]Finsterer J, Mahjoub SZ (2014) Fatigue in healthy and diseased individuals. The American journal of hospice & palliative care 31 (5):562-575. doi:10.1177/1049909113494748

Acknowledgments:

Thanks to all the authors for their efforts and thanks to all members of the Department of Rheumatology of Affiliated Hospital of Nantong University for their helpfulness in the acquisition of data.

Disclosure of Interests:

None declared

AB1329-HPR THE CURRENT STATUS AND ASSOCIATED FACTORS OF FATIGUE IN CHINESE PATIENTS WITH GOUT

Background:

Fatigue of chronic diseases has been paid more and more attention. but the status of fatigue in gout patients has not been reported all the world[1].

Objectives:

In the absence of previous studies, our study aims to investigate the fatigue status, explore the potential predictors of fatigue and the effects of fatigue on health-related quality of life (HRQoL) among Chinese gout patients.

Methods:

This cross-sectional study was conducted from the Affiliated Hospital of Nantong University. A series of questionnaires were applied: Fatigue Scale-14 (FS-14), the 10 cm visual analog scale (VAS), the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder questionnaire (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), Health Assessment Questionnaire(HAQ), the Short Form 36 health survey (SF-36). Laboratory examinations were taken to obtain some biochemical indicators. Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation, Stepwise linear regression and binary logistic regression were used to analyze the data.

Results:

411 gout patients were included in this study. Among them, more than 50% patients reported physical fatigue in FS-14, severe disease, poor psychological status and reduced HRQoL were associated with fatigue. Multiple stepwise linear regression and binary logistic regression were applied and showed that pain, sleep quality, anxiety, depression and functional disorder were the potential predictors of fatigue. In addition, we found that the more severe the fatigue, the lower the patient’s HRQoL.

Conclusion:

Fatigue among gout patients is exceedingly common. The results of this study suggested that rheumatologists should pay closely attention to gout patients who suffer from serious fatigue, especially those with pain, poorer sleep quality, anxiety, depression and functional disorder.

References:

[1]Henry, A., Tourbah, A., Camus, G., Deschamps, R., Mailhan, L., Castex, C., Gout, O. & Montreuil, M. (2019) Anxiety and depression in patients with multiple sclerosis: The mediating effects of perceived social support, Multiple sclerosis and related disorders. 27, 46-51.

Disclosure of Interests:

None declared

AB1328-HPR INCREASED BODY MASS INDEX AFFECTS SPINAL MOBILITY RATHER THAN DISEASE ACTIVITY IN ANKYLOSING SPONDYLITIS

Background:

Studies have reported the association between overweight or obesity and ankylosing spondylitis (AS), but their relation is still unclear in China.

Objectives:

To explore the prevalence of overweight or obesity and its effect on other indicators and their relationships in Chinese AS patients.

Methods:

Demographic and clinical variables were collected from 207 AS patients. Patients were categorized to normal BMI group (BMI < 23kg/m2) and overweight group (BMI ≥ 23kg/m2). We used Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Health Assessment Questionnaire (HAQ), Ankylosing Spondylitis Quality of Life (ASQoL) and Medical Outcomes Study Short Form 36 (SF-36) to evaluate disease activity, physical function, spinal mobility, functional limitation and health-related quality of life, respectively. Statistical analysis used independent t test, Mann-Whitney U test, Chi-square test and Spearman’s rank correlation test.

Results:

56.5% (117) AS patients were overweight or obese, among which 80.3% (94) were male. In the overweight group, patients were older, more being married, and have higher BMI, higher waist circumference, higher waist-to-hip ratio, longer disease duration, higher BASMI score, higher white blood cell count (WBC), higher lymphocyte and higher platelet count compared to the non-overweight group (P≤ 0.038). However, there was no distinct difference in BASDAI score between the two groups (P= 0.891). In the correlation analyses, gender and marital status (P≤ 0.036) were correlated negatively with BMI; while age, waist circumference, waist-to-hip ratio, WBC, lymphocyte count and red blood cell (P≤ 0.036) were correlated positively with BMI.

Conclusion:

Overweight or obesity is common in Chinese AS patients. Increased BMI affects not disease activity but spinal mobility, which indicates that patients with high BMI are more likely to have limitations in flexion, extension, lateral bending and torsion of spine.

References:

[1]Bowness P. Hla-B27. Annu Rev Immunol. 2015;33:29-48.

[2]de Araújo TA, Mota MC, Crispim CA. Obesity and sleepiness in women with fibromyalgia. Rheumatology International. 2014;35(2):281-7.

Acknowledgments:

This study was funded by Science and technology Project of Nantong City (Grant/Award Number: MSZ18217), Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant/Award number: KYCX19_2071 and KYCX18_2410), National Natural Science Foundation of China (Grant/Award number: 81671616 and 81871278), Science and technology Project of Jiangsu Province (Grant/Award number: BE2018671) and Clinical Research Center of Stem Cells, Affiliated Hospital of Nantong University, Nantong (Grant/Award number: HS2018001).

Disclosure of Interests:

None declared

THU0075 MIR-21 IN EXOSOMES DRIVED FROM DENTAL PULP STEM CELLS AMELIORATE THE TREGS/TH17 IMMUNE RESPONSE VIA TARGETING STAT3 IN COLLAGEN-INDUCED ARTHRITIS MICE

Background:

Rheumatoid arthritis (RA) is a common and systemic autoimmune disease1.It is vital for deciphering pathogenesis to define the precise CD4+Tcell subsets that are expanded or dysregulated in RA patients2.An increase in the Th17 cell subset and a decrease in Tregs resulting imbalance of Tregs/Th17 may be responsible for the occurrence and development of RA3. Dental pulp stem cells (DPSCs) appear be a new therapeutic tool for immunological diseases4,5.InRA, the mechanism of the effect of miR-21 drivedfromDPSCsexosomes (DPSCs-exo) on the balance of Tregs/Th17 is still unclear.

Objectives:

We explored the effect of exosomes drived from DPSCson RA and investigated the correlation between DPSCs-exo and Tregs/Th17 balance.

Methods:

Exosomes were isolated through differential centrifugation. Collagen-induced arthritis(CIA) mice were builded to detect histological change and Tregs/Th17 ratio.CD4+Tcells were isolated from PBMCs. Exosomes and CD4+T cells were co-cultured to study the regulation of Tregs/Th17 balance.The relationship between miR-21 and Tregs/Th17 balance was studied by flow cytometry, qRT-PCR and Western blotting etc.

Results:

After Dpscs-exo treatment, the clinical scores and paw swelling of CIA mice decreased.At the same time, the expression of Treg cells increased and the expression of Th17 cells decreased in the spleen,changing the ratio of Tregs/Th17.Exosomes and CD4+T cells were co-culture,showing that Treg cellsincreased and Th17 cellsdecreased. MiR-21 is highly expressed in RA patients.MiR-21 in exosomes were Knockout and overexpressed.The balance ofTregs/Th17 decreased when miR-21 were knockout and increased when miR-21were overexpressed. In addition, STAT3 in CD4+T cells were overexpressed and co-culture with DPSCs-exo,which inhibited Tregs/Th17.

Conclusion:

We elucidated the mechanism of the regulation of Tregs/Th17 balance by DPSCs-exo, that is, miR-21 in exosomes drived from dental pulp stem cells ameliorate the Tregs /Th17 immune response via targeting STAT3 in collagen-induced arthritis mice.

References:

[1]MF, B.et al.Hexokinase 2 as a novel selective metabolic target for rheumatoid arthritis.77, 1636-1643,doi:10.1136/annrheumdis-2018-213103 (2018).

[2]CY, F.et al.Mixed-effects association of single cells identifies an expanded effector CD4 T cell subset in rheumatoid arthritis.10,doi:10.1126/scitranslmed.aaq0305 (2018).

[3]Q, S.et al.Impaired Tip60-mediated Foxp3 acetylation attenuates regulatory T cell development in rheumatoid arthritis.100, 27-39,doi:10.1016/j.jaut.2019.02.007 (2019).

[4]L, J.et al.Comparison of immunomodulatory properties of exosomes derived from bone marrow mesenchymal stem cells and dental pulp stem cells.67, 432-442,doi:10.1007/s12026-019-09088-6 (2019).

[5]B, M., A, L., M, B., W, L. & cells, S. B. J. S. Concise Review: Dental Pulp Stem Cells: A Novel Cell Therapy for Retinal and Central Nervous System Repair.35, 61-67,doi:10.1002/stem.2398 (2017).

Disclosure of Interests: None declared

Hyperbaric oxygen treatment mitigates liver damage in mice with noise exposure

Noise exposure relates to various pathological disorders including liver damage, preventive measures of which are being demanded. Hyperbaric oxygen treatment (HBOT), as a non-invasive procedure, exerts convincing therapeutic potency on multiple liver diseases. The efficacy of HBOT in mitigating noise induced liver damage (NILD) and associated mechanisms would be elucidated here. Mice were subject to broad band noise (20-20k Hz, 90-110 dB) for 5 days by 3 hours/day. HBOT with 2.5 atmosphere absolute (ata) was employed before noise exposure. Morphology of liver tissue was examined by hematoxylin-eosin (HE) staining. Oil Red O (ORO), transferase-mediated dUTP nick end labelling (TUNEL) test and western blot were utilized to detect lipid accumulation, apoptotic cells and protein expression, respectively. Ceramide (Cer) level was assayed by immunohistochemistry (IHC) analysis. With noise exposure, conspicuous structural derangement and lipid deposition occurred in liver tissue of mice, which was alleviated significantly by the application of HBOT. Meanwhile, HBOT reduced the proportion of apoptotic hepatocytes, restraining the superoxide production in noise exposed mice. In view of underlying mechanisms, noise enhanced the acid sphingomyelinase (ASM) protein expression and the Cer generation in liver tissue of mice which was reversed substantially by HBOT. Altogether, HBOT ameliorates the structural and functional derangement of liver by neutralizing the ASM/Cer pathway in noise exposed mice.

EEG- and EOG-Based Asynchronous Hybrid BCI: A System Integrating a Speller, a Web Browser, an E-Mail Client, and a File Explorer

This paper presents a new asynchronous hybrid brain-computer interface (BCI) system that integrates a speller, a web browser, an e-mail client, and a file explorer using electroencephalographic (EEG) and electrooculography (EOG) signals. More specifically, an EOG-based button selection method, which requires the user to blink his/her eyes synchronously with the target button's flashes during button selection, is first presented. Next, we propose a mouse control method by combining EEG and EOG signals, in which the left-/right-hand motor imagery (MI)-related EEG is used to control the horizontal movement of the mouse and the blink-related EOG is used to control the vertical movement of the mouse and to select/reject a target. These two methods are further combined to develop the integrated hybrid BCI system. With the hybrid BCI, users can input text, access the internet, communicate with others via e-mail, and manage files in their computer using only EEG and EOG without any body movements. Ten healthy subjects participated in a comprehensive online experiment, and superior performance was achieved compared with our previously developed P300- and MI-based BCI and some other asynchronous BCIs, therefore demonstrating the system's effectiveness.

A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface

To enhance the performance of the brain-actuated robot system, a novel shared controller based on Bayesian approach is proposed for intelligently combining robot automatic control and brain-actuated control, which takes into account the uncertainty of robot perception, action and human control. Based on maximum a posteriori probability (MAP), this method establishes the probabilistic models of human and robot control commands to realize the optimal control of a brain-actuated shared control system. Application on an intelligent Bayesian shared control system based on steady-state visual evoked potential (SSVEP)-based brain machine interface (BMI) is presented for all-time continuous wheelchair navigation task. Moreover, to obtain more accurate brain control commands for shared controller and adapt the proposed system to the uncertainty of electroencephalogram (EEG), a hierarchical brain control mechanism with feedback rule is designed. Experiments have been conducted to verify the proposed system in several scenarios. Eleven subjects participated in our experiments and the results illustrate the effectiveness of the proposed method.

An electro-osmotic microfluidic system to characterize cancer cell migration under confinement

We have developed a novel electro-osmotic microfluidic system to apply precisely controlled osmolarity gradients to cancer cells in micro-channels. We observed that albeit adhesion is not required for cells to migrate in such a confined microenvironment, the migrating velocity of cells is strongly influenced by the interactions between the cells and the channel wall, with a stronger adhesion leading to diminished cell motility. Furthermore, through examining more than 20 different types of cancer cells, we found a linear positive correlation between the protein concentration of the aquaporin-4 (AQP4) and the cell migrating speed. Knockdown of AQP4 in invasive re-populated cancer stem cells reduced their migration capability down to the level that is comparable to their parental cancer cells. Interestingly, these observations can all be quantitatively explained by the osmotic engine model where the cell movement is assumed to be driven by cross-membrane ion/water transport, while adhesion acts as a frictional resistance against the cell motility. By providing versatile and controllable features in regulating and characterizing the migration capability of cells, our system may serve as a useful tool in quantifying how cell motility is influenced by different physical and biochemical factors, as well as elucidating the mechanisms behind, in the future.