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Accumulating evidence suggests that differentially expressed non-coding circular RNAs (circRNAs) play critical roles in the progress of autoimmune diseases. However, the role of circRNAs in systemic lupus erythematosus (SLE) remains unclear. We initially used next-generation sequencing (NGS) to comprehensively analyze circRNA expression profiles in peripheral blood mononuclear cells (PBMCs) from 10 SLE patients, stratified by their disease activity characteristics (stable or active SLE), and 10 healthy controls (HCs). Candidate circRNAs identified were first validated by quantitative reverse-transcription (qRT)-PCR in PBMC samples from a training-phase cohort of five SLE patients and five HCs. The significantly dysregulated circRNAs were then confirmed by qRT-PCR in a validation cohort of 23 SLE patients and 21 HCs, and in an external validation cohort with 64 SLE patients, 58 HCs, and 50 patients with rheumatoid arthritis (RA). In addition, we conducted bioinformatics analysis and western blotting investigating the relationships between the candidate circRNAs and SLE progression. Multilayer integrative analysis of circRNA regulation showed that 84 circRNAs were upregulated and 30 were downregulated in patients with SLE compared with HCs. We then analyzed the intersection of these differentially expressed circRNAs in an SLE-stable cohort, an SLE-active cohort, and HCs. This enabled us to narrow down dysregulated circRNAs to 15 upregulated circRNAs. Only hsa_circ_0000479 was significantly upregulated in PBMCs of patients with SLE compared with HCs ( < 0.05). Furthermore, the diagnostic potential of hsa_circ_0000479 expression to distinguish SLE patients from HCs and RA patients was also significantly increased in the validation-phase and external-validation-phase cohorts ( < 0.05). When distinguishing SLE patients from HCs, the diagnostic specificities of hsa_circ_0000479 were 0.619 and 1.0 in two validation cohorts, respectively (AUCs = 0.731 and 0.730, respectively). It was also significantly increased in either stable SLE patients or active SLE patients compared with HCs in these two cohorts ( < 0.05). We also used bioinformatics analysis to show that hsa_circ_0000479 regulates SLE progression by modulating metabolic pathways and the Wnt signaling pathway. Western blotting revealed that the expression of Wnt-16 protein was significantly decreased in SLE. Our results suggest that hsa_circ_0000479 has potential as a novel biomarker for the diagnosis of SLE.

Our understanding of circulating microRNAs (miRNAs) related to systemic lupus erythematosus (SLE) remains very limited. In this study, we screened SLE-specific miRNAs in plasma from 42 B cell-related miRNAs by using miRNA PCR Array. The selected miRNAs were first confirmed in plasma samples from 50 SLE patients, 16 rheumatoid arthritis (RA) patients, and 20 healthy donors using qRT-PCR. We then investigated the relationship between expressions of the selected miRNAs and SLE clinical indicators. As a result, 14 miRNAs (miR-103, miR-150, miR-20a, miR-223, miR-27a, miR-15b, miR-16, miR-181a, miR-19b, miR-22, miR-23a, miR-25, miR-92a, and miR-93) were significantly decreased in the plasma of SLE patients compared with healthy controls (  < 0.05) and could act as the diagnostic signature to distinguish SLE patients from healthy donors. Six miRNAs (miR-92a, miR-27a, miR-19b, miR-23a, miR-223, and miR-16) expressed in plasma were significantly lower in SLE patients than in RA patients (  < 0.05), revealing the potentially diagnostic signature to distinguish SLE patients from RA patients. Furthermore, the downregulated expression of miR-19b, miR-25, miR-93, and miR-15b was associated with SLE disease activity (  < 0.05) while miR-15b and miR-22 expressions were significantly lower in SLE patients with low estimate glomerular filtration rate (eGFR < 60 ml/min/1.73 m ) (  < 0.05). The diagnostic potential of miR-15b for SLE disease activity and lupus nephritis (LN) with low eGFR was validated on an independent validation set with 69 SLE patients and a cross-validation set with 80 SLE patients. In summary, the signature of circulating miRNAs will provide novel biomarkers for the diagnosis of SLE and evaluation of disease activity and LN.

Tax data is a typical time series data, which is subject to the interaction and influence of economic and political factors and has dynamic and highly nonlinear characteristics. The key to correct tax forecasting is the choice of forecasting algorithm. Traditional tax forecasting methods, such as factor scoring method, factor regression method, and system adjustment method, have a certain guiding role in actual work, but there are still many shortcomings, such as the limitation from the distribution and size of sample data and difficulty of grasping the nonlinear phenomena in economic system. Grey-Markov chain model formed by the combination of grey forecasting and Markov chain forecasting can not only reveal the general developmental trend of time series data, but also predict their state change patterns. Based on the summary and analysis of previous research works, this paper expounds the current research status and significance of tax forecasting, elaborates the development background, current status, and future challenges of the Grey-Markov chain model, introduces the basic principles of grey forecasting model and Markov chain model, constructs the Grey-Markov chain model, analyzes the model’s residual error and posteriori error tests, conducts the analysis of Grey-Markov chain model, performs grey forecasting model construction and its state division, implements the calculation of transition probability matrix and the determination of tax forecasting value, discusses the application of the Grey-Markov chain model in tax forecasting, and finally carries out a simulation experiment and its result analysis. The study results show that, compared with separate grey forecasting, Markov chain forecasting, and other commonly used time series forecasting methods, the Grey-Markov chain model increases the accuracy of tax forecasts by an average of 2.3–13.1%. This indicates that the combinative forecasting of Grey-Markov chain model can make full use of the information provided by time series data for tax analysis and forecasting. It can not only avoid the influence of economic, political, and human subjective factors, but also have simple calculations, higher accuracy, and stronger practicality. The study results of this paper provide a reference for further researches on the analysis and application of Grey-Markov chain model in tax forecasting.

To study the anti-seismic performance of steel structure under high temperature, the finite element analysis software ABAQUS was used to study the seismic performance of Q235 steel welded box section column at service stage under normal temperature and high temperature fire. The effects of welding residual stress, slenderness ratio, width thickness ratio and axial load level on the hysteretic behavior of columns were analyzed and the stable bearing capacity and hysteretic performance of the column under high temperature were investigated. The results show that the maximum bearing capacity of the column decreases with the increase of the residual stress peak value. With the increase of temperature, a decrease in the maximum bearing capacity of columns under constant axial force and horizontal cyclic load and an increase in the ductility occur.

Background Studies have highlighted a possible crosstalk between the pathogeneses of COVID-19 and systemic lupus erythematosus (SLE); however, the interactive mechanisms remain unclear. We aimed to elucidate the impact of COVID-19 on SLE using clinical information and the underlying mechanisms of both diseases. Methods RNA-seq datasets were used to identify shared hub gene signatures between COVID-19 and SLE, while genome-wide association study datasets were used to delineate the interaction mechanisms of the key signaling pathways. Finally, single-cell RNA-seq datasets were used to determine the primary target cells expressing the shared hub genes and key signaling pathways. Results COVID-19 may affect patients with SLE through hematologic involvement and exacerbated inflammatory responses. We identified 14 shared hub genes between COVID-19 and SLE that were significantly associated with interferon (IFN)-I/II. We also screened and obtained four core transcription factors related to these hub genes, confirming the regulatory role of the IFN-I/II-mediated Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway on these hub genes. Further, SLE and COVID-19 can interact via IFN-I/II and IFN-I/II receptors, promoting the levels of monokines, including interleukin (IL)-6/10, tumor necrosis factor-α, and IFN-γ, and elevating the incidence rate and risk of cytokine release syndrome. Therefore, in SLE and COVID-19, both hub genes and core TFs are enriched within monocytes/macrophages. Conclusions The interaction between SLE and COVID-19 promotes the activation of the IFN-I/II-triggered JAK-STAT signaling pathway in monocytes/macrophages. These findings provide a new direction and rationale for diagnosing and treating patients with SLE–COVID-19 comorbidity.

A high ratio of blank fruit in hazelnut (Corylus heterophylla Fisch) is a very common phenomenon that causes serious yield losses in northeast China. The development of blank fruit in the Corylus genus is known to be associated with embryo abortion. However, little is known about the molecular mechanisms responsible for embryo abortion during the nut development stage. Genomic information for C. heterophylla Fisch is not available; therefore, data related to transcriptome and gene expression profiling of developing and abortive ovules are needed. In this study, de novo transcriptome sequencing and RNA-seq analysis were conducted using short-read sequencing technology (Illumina HiSeq 2000). The results of the transcriptome assembly analysis revealed genetic information that was associated with the fruit development stage. Two digital gene expression libraries were constructed, one for a full (normally developing) ovule and one for an empty (abortive) ovule. Transcriptome sequencing and assembly results revealed 55,353 unigenes, including 18,751 clusters and 36,602 singletons. These results were annotated using the public databases NR, NT, Swiss-Prot, KEGG, COG, and GO. Using digital gene expression profiling, gene expression differences in developing and abortive ovules were identified. A total of 1,637 and 715 unigenes were significantly upregulated and downregulated, respectively, in abortive ovules, compared with developing ovules. Quantitative real-time polymerase chain reaction analysis was used in order to verify the differential expression of some genes. The transcriptome and digital gene expression profiling data of normally developing and abortive ovules in hazelnut provide exhaustive information that will improve our understanding of the molecular mechanisms of abortive ovule formation in hazelnut.

Background Metabolic syndrome (MetS) is significantly associated with the risk of cardiovascular disease and its prevalence is showing a trend of getting younger. Previous studies on the relationship between elements and MetS were mostly reported in adults with single element analysis, while reports in children with combined effects of multiple elements were very limited. The aim of this study is to investigate the association between whole blood Cu, Mg and Zn in both single and combined effects and MetS components in rural Chinese children aged 6–12 years based on the data from 2010–2012 China National Nutrition and Health Survey. Methods A total of 911 children (51.2% male, 48.7% female) aged 6–12 years were included. Basic characteristics and MetS component parameters were collected and determined by trained stuffs. Elements were detected by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Multivariate logistic regression analysis was performed to examine the independent relationship between elements and MetS components. Results In single metal analysis, copper was positively associated with elevated waist (OR = 2.00, 1.18–3.28) and all of the metals were associated with elevated TG. And the comprehensive analysis of multiple elements were mostly consistent with the results of single element analysis (low Cu + high Zn with elevated TG (OR = 2.21, 1.18–4.13), high Cu + low Mg with elevated TG (OR = 0.40, 0.16–0.95), high Cu + high Mg with elevated waist (OR = 2.03, 1.26–3.27)), except the combination of Zn and Mg (high Zn + low Mg with reduced HDL-C (OR = 0.47, 0.28–0.77)). Conclusions Our study suggested Cu, Zn and Mg in children are indeed associated with metabolic syndrome components, whether in single element or multi-element combined analysis. The results will be confirmed through additional cohort research.

The emerging epitranscriptome plays an essential role in autoimmune disease. As a novel mRNA modification, N4-acetylcytidine (ac4C) could promote mRNA stability and translational efficiency. However, whether epigenetic mechanisms of RNA ac4C modification are involved in systemic lupus erythematosus (SLE) remains unclear. Herein, we detected eleven modifications in CD4+ T cells of SLE patients using mass spectrometry (LC-MS/MS). Furthermore, using samples from four CD4+ T cell pools, we identified lower modification of ac4C mRNA in SLE patients as compared to that in healthy controls (HCs). Meanwhile, significantly lower mRNA acetyltransferase NAT10 expression was detected in lupus CD4+ T cells by RT-qPCR. We then illustrated the transcriptome-wide ac4C profile in CD4+ T cells of SLE patients by ac4C-RIP-Seq and found ac4C distribution in mRNA transcripts to be highly conserved and enriched in mRNA coding sequence regions. Using bioinformatics analysis, the 3879 and 4073 ac4C hyper-acetylated and hypoacetylated peaks found in SLE samples, respectively, were found to be significantly involved in SLE-related function enrichments, including multiple metabolic and transcription-related processes, ROS-induced cellular signaling, apoptosis signaling, and NF-κB signaling. Moreover, we demonstrated the ac4C-modified regulatory network of gene biological functions in lupus CD4+ T cells. Notably, we determined that the 26 upregulated genes with hyperacetylation played essential roles in autoimmune diseases and disease-related processes. Additionally, the unique ac4C-related transcripts, including USP18 , GPX1 , and RGL1 , regulate mRNA catabolic processes and translational initiation. Our study identified novel dysregulated ac4C mRNAs associated with critical immune and inflammatory responses, that have translational potential in lupus CD4+ T cells. Hence, our findings reveal transcriptional significance and potential therapeutic targets of mRNA ac4C modifications in SLE pathogenesis.

Background Systemic lupus erythematosus (SLE) is a multisystemic autoimmune disease with various clinical manifestations. MicroRNAs (miRNAs) and immunometabolism are recognized as key elements in SLE pathogenesis; however, the relationship between miRNAs in peripheral blood mononuclear cells (PBMCs) and metabolism in SLE remains unclear. Methods We detected PBMC miRNA and mRNA profiles from 3 pooled SLE patients and 3 healthy controls (HCs) using next-generation sequencing, predicted miRNA targets in dysregulated mRNAs, predicted functions and interactions of differentially expressed genes using bioinformatics analysis, validated candidate miRNAs using qRT-PCR, and investigated the association between the expression of candidate miRNAs and SLE clinical characteristics. Moreover, we validated the direct and transcriptional regulatory effect of NovelmiRNA-25 on adenosine monophosphate deaminase 2 ( AMPD2 ) using a dual-luciferase reporter assay and western blot and confirmed AMPD2 mRNA and protein expression in PBMCs using qRT-PCR and western blot, respectively. Results Multilayer integrative analysis of microRNA and mRNA regulation showed that 10 miRNAs were down-regulated and 19 miRNAs were up-regulated in SLE patient PBMCs compared with HCs. Bioinformatics analysis of regulatory networks between miRNAs and mRNAs showed that 19 miRNAs were related to metabolic processes. Two candidate miRNAs, NovelmiRNA-25 and miR-1273h-5p, which were significantly increased in the PBMCs of SLE patients (P < 0.05), represented diagnostic biomarkers with sensitivities of 94.74% and 89.47%, respectively (area under the curve = 0.574 and 0.788, respectively). NovelmiRNA-25 expression in PBMCs was associated with disease activity in SLE patients, in both active and stable groups (P < 0.05). NovelmiRNA-25 overexpression downregulated AMPD2 expression in HEK293T cells through direct targeting of the AMPD2 3ʹUTR (P < 0.01), while inhibition of NovelmiRNA-25 activity led to increased AMPD2 expression (P < 0.01). NovelmiRNA-25 overexpression also downregulated AMPD2 protein expression in HEK293T cells; AMPD2 protein expression in SLE patient PBMCs was decreased. Our results show that differentially expressed miRNAs play an important role in SLE. Conclusions Our data demonstrate a novel mechanism in SLE development that involves the targeting of AMPD2 expression by NovelmiRNA-25. miRNAs may serve as novel biomarkers for the diagnosis and evaluation of disease activity of SLE and represent potential therapeutic targets for this disease.

Background The WHO/UNICEF/ICCIDD define iodine deficiency during pregnancy as median urinary iodine concentration (MUIC) ≤ 150 μg/L. China implemented universal salt iodization (USI) in 1995, and recent surveillance showed nationwide elimination of iodine deficiency disorders (IDD). Data from 2014 showed that the MUIC in 19,500 pregnant women was 154.6 μg/L and 145 μg/L in 9000 pregnant women in 2015. However, symptoms of iodine deficiency were absent. Our study sought to evaluate whether MUIC below 150 μg/L affects thyroid function of Chinese pregnant women and their newborns in Chinese context. Methods We screened 103 women with normal thyroid function and MUIC lower than 150 μg/L during week 6 of pregnancy at Peking Union Medical College Hospital. Patient demographics and dietary salt intake were recorded. Subjects were followed at 12, 24, and 32 gestational weeks. At each visit, a 3-day dietary record, drinking water samples, and edible salt samples were collected and analyzed for total dietary iodine intake. Additionally, 24-h urine iodine and creatinine were measured. Blood tests assessed thyroid function in both mothers and newborns. Results Of 103 pregnant women enrolled, 79 completed all follow-up visits. Most subjects maintained normal thyroid function throughout pregnancy. However, 19 had thyroid dysfunction based on thyroid stimulating hormone and free thyroxine levels. The median serum iodine was 71 μg/L (95% CI: 44, 109). The median thyroglobulin was < 13 μg/L. values above this level indicate iodine deficiency in pregnant women. The median dietary iodine intake during pregnancy, derived from the 3-day record and measures of water and salt, was 231.17 μg/d. Assuming 90% urinary iodine excretion (UIE), 200.11 μg/d UIE means the 222.34 μg iodine loss per day, suggesting that subjects had a positive iodine balance throughout pregnancy. All neonatal blood samples showed TSH levels lower than 10 mIU/L, indicating normal thyroid function. No significant difference was found among gestational weeks for urinary iodine, and the MUIC in subjects who completed 3 follow-up visits was 107.41 μg/L. Conclusion Twenty years after implementing USI, expectant Chinese mothers with MUIC of 107.4 μg/L, less than the WHO’s 150 μg/L benchmark, maintained thyroid function in both themselves and their newborn babies.