The immunomodulatory of interleukin-33 in rheumatoid arthritis: A systematic review.

Rheumatoid arthritis (RA) is a systemic chronic autoimmune disease that primarily affects the joints and surrounding soft tissues, characterized by chronic inflammation and proliferation of the synovium. Various immune cells are involved in the pathophysiology of RA. The complex interplay of factors such as chronic inflammation, genetic susceptibility, dysregulation of serum antibody levels, among others, contribute to the complexity of the disease mechanism, disease activity, and treatment of RA. Recently, the cytokine storm leading to increased disease activity in RA has gained significant attention. Interleukin-33 (IL-33), a member of the IL-1 family, plays a crucial role in inflammation and immune regulation. ST2 (suppression of tumorigenicity 2 receptor), the receptor for IL-33, is widely expressed on the surface of various immune cells. When IL-33 binds to its receptor ST2, it activates downstream signaling pathways to exert immunoregulatory effects. In RA, IL-33 regulates the progression of the disease by modulating immune cells such as circulating monocytes, tissue-resident macrophages, synovial fibroblasts, mast cells, dendritic cells, neutrophils, T cells, B cells, endothelial cells, and others. We have summarized and analyzed these findings to elucidate the pathways through which IL-33 regulates RA. Furthermore, IL-33 has been detected in the synovium, serum, and synovial fluid of RA patients. Due to inconsistent research results, we conducted a meta-analysis on the association between serum IL-33, synovial fluid IL-33, and the risk of developing RA in patients. The pooled SMD was 1.29 (95% CI: 1.15-1.44), indicating that IL-33 promotes the onset and pathophysiological progression of RA. Therefore, IL-33 may serve as a biomarker for predicting the risk of developing RA and treatment outcomes. As existing drugs for RA still cannot address drug resistance in some patients, new therapeutic approaches are needed to alleviate the significant burden on RA patients and healthcare systems. In light of this, we analyzed the potential of targeting the IL-33/ST2-related signaling pathway to modulate immune cells associated with RA and alleviate inflammation. We also reviewed IL-33 and RA susceptibility-related single nucleotide polymorphisms, suggesting potential involvement of IL-33 and macrophage-related drug-resistant genes in RA resistance therapy. Our review elucidates the role of IL-33 in the pathophysiology of RA, offering new insights for the treatment of RA.

Alignment of single-cell RNA-seq samples without overcorrection using kernel density matching.

Single-cell RNA sequencing (scRNA-seq) technology is poised to replace bulk cell RNA sequencing for many biological and medical applications as it allows users to measure gene expression levels in a cell type-specific manner. However, data produced by scRNA-seq often exhibit batch effects that can be specific to a cell type, to a sample, or to an experiment, which prevent integration or comparisons across multiple experiments. Here, we present Dmatch, a method that leverages an external expression atlas of human primary cells and kernel density matching to align multiple scRNA-seq experiments for downstream biological analysis. Dmatch facilitates alignment of scRNA-seq data sets with cell types that may overlap only partially and thus allows integration of multiple distinct scRNA-seq experiments to extract biological insights. In simulation, Dmatch compares favorably to other alignment methods, both in terms of reducing sample-specific clustering and in terms of avoiding overcorrection. When applied to scRNA-seq data collected from clinical samples in a healthy individual and five autoimmune disease patients, Dmatch enabled cell type-specific differential gene expression comparisons across biopsy sites and disease conditions and uncovered a shared population of pro-inflammatory monocytes across biopsy sites in RA patients. We further show that Dmatch increases the number of eQTLs mapped from population scRNA-seq data. Dmatch is fast, scalable, and improves the utility of scRNA-seq for several important applications. Dmatch is freely available online.

Blocking the ATR-SerRS-VEGFA pathway targets angiogenesis for UV-induced cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) is the second most prevalent form of skin cancer, with an escalating incidence rate and a notable potential (up to 5%) for metastasis. Ultraviolet radiation (UVA and UVB) exposure is the primary risk factor for cSCC carcinogenesis, with literature suggesting ultraviolet radiation (UVR) promotes vascular endothelial growth factor A (VEGFA) expression. This study aims to investigate UVR-induced upregulation of VEGFA and explore combination therapeutic strategies. The skin squamous cell carcinoma cell line A431 was exposed to specific durations of ultraviolet radiation. The effect of emodin on ATR/SerRS/VEGFA pathway was observed. The cell masses were also transplanted subcutaneously into mice (n = 8). ATR inhibitor combined with emodin was used to observe the growth and angiogenesis of the xenografts. The results showed that UV treatment significantly enhanced the phosphorylation of SerRS and the expression level of VEGFA in A431 cells (p < 0.05). Treatment with emodin significantly inhibited this expression (p < 0.05), and the combination of emodin and ATR inhibitor further enhanced the inhibitory effect (p < 0.05). This phenomenon was further confirmed in the xenograft model, which showed that the combination of ATR inhibitor and emodin significantly inhibited the expression of VEGFA to inhibit angiogenesis (p < 0.05), thus showing an inhibitory effect on cSCC. This study innovatively reveals the molecular mechanism of UV-induced angiogenesis in cSCC and confirms SerRS as a novel target to inhibit cSCC angiogenesis and progression in vitro and in vivo studies.

CD147 regulates the formation and function of immune synapses.

CD147 is a T cell activation-associated molecule which is closely involved in the formation of the immune synapse (IS). However, the precise role of CD147 in T cell activation and IS formation remains unclear. In the present study, we demonstrated that CD147 translocated to the IS upon T cell activation and was primarily distributed in the peripheral super molecular cluster (p-SMAC). The knock down of CD147 expression in T cells, but not in B cells, impaired IS formation. CD147 participated in IS formation between T cells and different types of antigen-presenting cells (APCs), including macrophages and dendritic cells. Ligation of CD147 with its monoclonal antibody (mAb) HAb18 effectively inhibited T cell activation and IL-2 secretion. CD98, a critical molecule interacting with CD147, was distributed in IS in a CD147-dependent way. Phosphorylation levels of T cell receptor (TCR) related molecules, like ZAP-70, ERK, and cJun, were down-regulated by CD147 ligation, which is crucial for the interaction of CD147 and TCR signaling transduction. CD147 is indispensable for the formation of immune synapses and plays an important role in the regulation of its function.

Finger Vein Identification Based on Large Kernel Convolution and Attention Mechanism.

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method named Let-Net (large kernel and attention mechanism network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to capture a broader spectrum of spatial contextual information, utilizing deep convolution in conjunction with residual connections to curtail the volume of model parameters. Subsequently, an integrated attention mechanism is applied to augment information flow within the channel and spatial dimensions, effectively modeling global information for the extraction of crucial FV features. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications.

Alterations in the human oral microbiota in systemic lupus erythematosus.

BACKGROUND: Alterations in oral microbiota in patients with systemic lupus erythematosus (SLE) is less evaluated. The aim of this study was to compare the characteristics of the oral microbiome in SLE patients and healthy controls, and construct an SLE classifier based on the oral microbiota. METHODS: We sequenced tongue-coating samples of individuals in treatment-naïve SLE (n = 182) and matched healthy controls (n = 280). We characterized the oral microbiome and constructed a microbial classifier in the derivation cohort and validated the results in the validation cohorts. Furthermore, the oral microbiome of posttreatment SLE (n = 73) was characterized. RESULTS: The oral microbial diversity of SLE was increased, and the microbial community was different between SLE and healthy controls. The genera Prevotella and Veillonella were enriched, while Streptococcus and Porphyromonas were reduced in SLE. In addition, an increase was noted in 27 predicted microbial functions, while a decrease was noted in 34 other functions. Thirty-nine operational taxonomy units (OTUs) were identified to be related with seven clinical indicators. Two OTUs were identified to construct a classifier, which yielded area under the curve values of 0.9166 (95% CI 0.8848-0.9483, p < 0.0001), 0.8422 (95% CI 0.7687-0.9157, p < 0.0001), and 0.8406 (95% CI 0.7677-0.9135, p < 0.0001) in the derivation, validation, and cross-regional validation groups, respectively. Moreover, as disease activity increased, Abiotrophia and Lactobacillales increased, while Phyllobacterium and unclassified Micrococcusaceae decreased. Finally, nine OTUs were selected to construct a classifier distinguishing posttreatment SLE patients from healthy controls, which achieved a diagnostic efficacy of 0.9942 (95% CI 0.9884-1, p < 0.0001). CONCLUSIONS: Our study comprehensively characterizes the oral microbiome of SLE and shows the potential of the oral microbiota as a non-invasive diagnostic biomarker in SLE.

Laboratory risk factors for coexistent primary biliary cholangitis in patients with Sjögren's syndrome: a retrospective study.

BACKGROUND: Limited research exists on the laboratory characteristics of coexistent primary biliary cholangitis (PBC) and Sjögren's syndrome (SS). This study aimed to investigate the laboratory risk factors for the coexistence of PBC in patients with SS. METHODS: Eighty-two patients with coexistent SS and PBC (median age 52.50 years) and 82 age- and sex-matched SS controls were retrospectively enrolled between July 2015 and July 2021. The clinical and laboratory characteristics of the two groups were compared. Laboratory risk factors for the coexistence of PBC in patients with SS were analyzed using logistic regression analysis. RESULTS: Both groups had a similar prevalence of hypertension, diabetes, thyroid disease, and interstitial lung disease. Compared with the SS group, patients in the SS + PBC group had higher levels of liver enzymes, immunoglobulins M (IgM), G2, and G3 (P < 0.05). The percentage of patients with an antinuclear antibody (ANA) titre > 1:10000 in the SS + PBC group was 56.1%, higher than that in the SS group (19.5%, P < 0.05). Additionally, cytoplasmic, centromeric, and nuclear membranous patterns of ANA and positive anti-centromere antibody (ACA) were observed more frequently in the SS + PBC group (P < 0.05). Logistic regression analysis showed that elevated IgM levels, high ANA titre, cytoplasmic pattern, and ACA were independent risk factors for PBC coexistence in SS. CONCLUSIONS: In addition to established risk factors, elevated IgM levels, positive ACA, and high ANA titre with cytoplasmic pattern provide clues to clinicians for the early screening and diagnosis of PBC in patients with SS.

Isoindigo-Based Dual-Acceptor Conjugated Polymers Incorporated Conjugation Length and Intramolecular Charge Transfer for High-Efficient Photothermal Conversion.

Photothermal tumor therapy (PTT) and photoacoustic imaging (PA) have emerged as promising noninvasive diagnostic and therapeutic approaches for cancer treatment. However, the development of efficient PTT agents with high photostability and strong near-infrared (NIR) absorption remains challenging. This study synthesizes three isoindigo-based dual-acceptor conjugated polymers (CPs) (P-IIG-TPD, P-IIG-DPP, and P-IIG-EDOT-BT) via a green and nontoxic direct arylation polymerization (DArP) method and characterizes their optical, electrochemical, and NIR photothermal conversion properties. By incorporating two acceptors into the backbone, the resulting polymers exhibit enhanced photothermal conversion efficiency (PCE) due to improved synergy among conjugation length, planarity, and intramolecular charge transfer (ICT). The nanoparticles (NPs) of P-IIG-EDOT-BT and P-IIG-DPP have a uniform size distribution around 140 nm and exhibit remarkable NIR absorption at 808 nm. In addition, P-IIG-EDOT-BT and P-IIG-DPP NPs exhibit high PCEs of 62% and 78%, respectively. This study promotes the molecular design of CPs as NIR photothermal conversion materials and provides guidance for the development of novel dual-acceptor CPs for tumor diagnosis and treatment.

A self-oscillating gel system with complex dynamic behavior based on a time delay between the oscillations.

The time delay existing between the chemical oscillation and mechanical oscillation (C-M delay) in a self-oscillating gel (SOG) system is observable in previous experimental studies. However, how the C-M delay affects the dynamic behavior of a large anisotropic SOG has not been quantified or reported systematically. In this study, we observed that the oscillation period increases with a decrease in the cross-linking density of the anisotropic SOG, and this determined whether regular mechanical oscillation occurs. Unlike before, the disrupted mechanical oscillations interestingly tend to be regular and periodic under visible light, which is an inhibitor for the B-Z reaction incorporating the Ru complex as a catalyst (Ru-BZ reaction). Moreover, the study of the C-M delay at different scales has far-reaching implications for intelligent soft actuators.

Security Risk Intelligent Assessment of Power Distribution Internet of Things via Entropy-Weight Method and Cloud Model.

The current power distribution Internet of Things (PDIoT) lacks security protection terminals and techniques. Network security has a large exposure surface that can be attacked from multiple paths. In addition, there are many network security vulnerabilities and weak security protection capabilities of power distribution Internet of Things terminals. Therefore, it is crucial to conduct a scientific assessment of the security of PDIoT. However, traditional security assessment methods are relatively subjective and ambiguous. To address the problems, we propose to use the entropy-weight method and cloud model theory to assess the security risk of the PDIoT. We first analyze the factors of security risks in PDIoT systems and establish a three-layer PDIoT security evaluation index system, including a perception layer, network layer, and application layer. The index system has three first-level indicators and sixteen second-level indicators. Then, the entropy-weight method is used to optimize the weight of each index. Additionally, the cloud model theory is employed to calculate the affiliation degree and eigenvalue of each evaluation index. Based on a comprehensive analysis of all evaluation indexes, we can achieve the security level of PDIoT. Taking the PDIoT of Meizhou Power Supply Bureau of Guangdong Power Grid as an example for empirical testing, the experimental results show that the evaluation results are consistent with the actual situation, which proves that the proposed method is effective and feasible.

Automatic quantification and grading of hip bone marrow oedema in ankylosing spondylitis based on deep learning.

OBJECTIVE: This study has developed a new automatic algorithm for the quantificationy and grading of ankylosing spondylitis (AS)-hip arthritis with magnetic resonance imaging (MRI). METHODS: (1) This study designs a new segmentation network based on deep learning, and a classification network based on deep learning. (2) We train the segmentation model and classification model with the training data and validate the performance of the model. (3) The segmentation results of inflammation in MRI images were obtained and the hip joint was quantified using the segmentation results. RESULTS: A retrospective analysis was performed on 141 cases; 101 patients were included in the derived cohort and 40 in the validation cohort. In the derivation group, median percentage of bone marrow oedema (BME) for each grade was as follows: 36% for grade 1 (<15%), 42% for grade 2 (15-30%),and 22% for grade 3 (≥30%). The accuracy of 44 cases on 835 AS images was 85.7%. Our model made 31 correct decisions out of 40 AS test cases. This study showed that THE accuracy rate 85.7%. CONCLUSIONS: An automatic computer-based analysis of MRI has the potential of being a useful method for the diagnosis and grading of AS hip BME.

A synthetic promoter system for well-controlled protein expression with different carbon sources in Saccharomyces cerevisiae.

BACKGROUND: Saccharomyces cerevisiae is an important synthetic biology chassis for microbial production of valuable molecules. Promoter engineering has been frequently applied to generate more synthetic promoters with a variety of defined characteristics in order to achieve a well-regulated genetic network for high production efficiency. Galactose-inducible (GAL) expression systems, composed of GAL promoters and multiple GAL regulators, have been widely used for protein overexpression and pathway construction in S. cerevisiae. However, the function of each element in synthetic promoters and how they interact with GAL regulators are not well known. RESULTS: Here, a library of synthetic GAL promoters demonstrate that upstream activating sequences (UASs) and core promoters have a synergistic relationship that determines the performance of each promoter under different carbon sources. We found that the strengths of synthetic GAL promoters could be fine-tuned by manipulating the sequence, number, and substitution of UASs. Core promoter replacement generated synthetic promoters with a twofold strength improvement compared with the GAL1 promoter under multiple different carbon sources in a strain with GAL1 and GAL80 engineering. These results represent an expansion of the classic GAL expression system with an increased dynamic range and a good tolerance of different carbon sources. CONCLUSIONS: In this study, the effect of each element on synthetic GAL promoters has been evaluated and a series of well-controlled synthetic promoters are constructed. By studying the interaction of synthetic promoters and GAL regulators, synthetic promoters with an increased dynamic range under different carbon sources are created.

Effects of illness perceptions on health-related quality of life in patients with rheumatoid arthritis in China.

OBJECTIVES: For patients with rheumatoid arthritis (RA) in China, little is known of how their illness perceptions affect their health-related quality of life (HRQoL). The present study investigated associations between specific illness perceptions due to RA and HRQoL features. METHODS: For 191 patients with RA, illness perceptions were measured using the Brief Illness Perceptions Questionnaire (BIPQ) comprising 8 domains. HRQoL was determined with the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). Multivariate linear regression analyses were performed. RESULTS: The overall BIPQ of patients with RA was 49.09 ± 11.06. The highest and lowest scores were for concern (9.15 ± 1.81) and personal control (4.30 ± 2.52), respectively. Multivariate stepwise regression analyses showed that the overall BIPQ was significantly negatively associated with each HRQoL feature, and HRQoL total score (ß = - 0.343, P < 0.001, 95% CI - 7.080 to - 4.077). Positive associations between BIPQ features and HRQoL included personal control (ß = 0.119, P = 0.004, 95% CI 2.857-14.194) and treatment control (ß = 0.084, P = 0.029, 95% CI 0.640-12.391). Negative associations with HRQoL were identity (ß = - 0.105, P = 0.034, 95% CI - 13.159 to - 0.430) and emotional response (ß = - 0.207, P < 0.001, 95% CI - 18.334 to - 6.811). CONCLUSIONS: Patients with RA in China perceive their illness in ways that affect their HRQoL. These results suggest that strategies that target these perceptions may improve the quality of life of these patients.

Behcet's disease with peripheral nervous system involvement successfully treated with golimumab: a case report and review of the literature.

Nervous system involvement is a rare and serious complication of Behcet's disease (BD), and the peripheral type is rarer. This article aimed to describe a case of BD with the peripheral nervous system (PNS) involvement and present a comprehensive literature review. One case of BD with PNS involvement was reported and related literature was retrospectively reviewed via PubMed/MEDLINE and Scopus database. The patient was resistant to traditional treatments, such as glucocorticoids and immunosuppressants, but had rapid quiescence after using golimumab. Our literature review suggests that the involved peripheral nerves in BD were diverse, the most common were the tibial nerves and peroneal nerves, vasculitis might be the main cause, and prednisone was still the cornerstone of treatment. TNF-α inhibitors have been increasingly used for refractory BD in recent years. This well-illustrated case demonstrates the potential benefit of golimumab to the patient with PNS involvement. Given the diversity and complexity of PNS involvement, we recommend golimumab as a new trial treatment in clinical practice.

Dysregulation of Innate Lymphoid Cells in Patients with Active Rheumatoid Arthritis and Mice with Collagen-Induced Arthritis.

Innate lymphoid cells (ILCs) have roles in many diseases and immune pathways. To determine the roles of these cells in patients with rheumatoid arthritis (RA) and mice with collagen-induced arthritis (CIA), we measured ILC subsets using flow cytometry and multiplex immunofluorescence staining. Patients with stable RA had greater proportions of ILC2s and decreased proportions of ILC1s and ILC3s (all p < 0.05). The 28-joint disease activity (DAS28) score had positive correlations with the proportion of ILC1s and negative correlations with ILC2s (both p < 0.05). ILC2s of patients with RA expressed more IL-4 than healthy controls (p < 0.05). The proportions of ILC1s and ILC2s were greater in mice with CIA (both p < 0.05), especially the ILC2s in mice without arthritis after immunization and had correlations with multiple inflammatory and anti-inflammatory cytokines. Multiplex immunofluorescence staining described the distribution of ILCs in spleen tissues. Our results indicate that dysregulation of ILCs occurs during the pathogenesis of RA and CIA.

Performance of the PET vascular activity score (PETVAS) for qualitative and quantitative assessment of inflammatory activity in Takayasu's arteritis patients.

PURPOSE: To assess the performance of PET vascular activity score (PETVAS) in comparison with SUVmax, inflammatory biomarkers and ITAS-2010 score in a cohort of TAK patients. METHODS: Sixty-four PET/CT scans acquired from 54 TAK patients were analyzed. The inflammatory activity was qualitatively determined by physician's global assessment and quantitatively determined by ITAS-2010 score. SUVmax and PETVAS were acquired by consensus review. Levels of the inflammatory biomarkers C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and pentraxin-3 (PTX-3) were measured. Performance of the qualitative diagnoses and the quantitative correlation were, respectively, compared by receiver operating characteristic (ROC) curve and Spearman correlation coefficient. RESULTS: The biomarkers (CRP, ESR, PTX-3), PET uptake values (SUVmax, PETVAS), and ITAS-2010 scores were all significantly higher in active patients than in non-active ones. The area under the ROC curve and Youden Index of PETVAS and PTX-3 were higher than those of SUVmax, CRP, ESR, and ITAS-2010. PETVAS and PTX-3 resulted in a higher Spearman correlation coefficient with ITAS-2010 than other criteria, either among all patients or within the active group. Alteration trends of PETVAS and PTX-3 during follow-up showed a tighter correlation with clinical progression/remission assessment than other criteria. CONCLUSIONS: In TAK evaluation, PETVAS is superior for qualitative and quantitative assessment, compared with the regional SUVmax. Compared to CRP and ESR, inflammatory biomarker PTX-3 shows better qualitative performance and a higher correlation with PETVAS and ITAS-2010. These findings indicate that the use of PETVAS and PTX-3, instead of SUVmax and CRP/ESR, has potential advantages in the clinical evaluation of TAK.

Angiopoietin-like 2 is a potential biomarker for diabetic foot patients.

BACKGROUND: Circulating angiopoietin-like 2 (ANGPTL2) protein levels are known to be significantly increased in numerous chronic inflammatory diseases and are associated with the diagnosis and/or prognosis of cardiovascular diseases, diabetes, chronic kidney disease, and various types of cancers. However, no data regarding the relationship between ANGPTL2 and diabetic foot ulcers (DFUs) are available. Here, we explored the potential link between ANGPTL2 and DFUs. METHODS: A total of 68 participants with type 2 diabetes mellitus (T2DM) were recruited, including 28 patients with DFU and 40 diabetic patients without DFUs. The clinical characteristics of T2DM patients with and without DFUs were compared. Serum concentrations of ANGPTL2 and VEGF were measured using enzyme-linked immunosorbent assay (ELISA) kits. The correlations between ANGPTL2 and clinical variables were analyzed. Multiple linear regression and logistic regression models were constructed to test the associations between ANGPTL2 and the severity and presence of DFUs. RESULTS: Serum levels of ANGPTL2 were higher in patients with DFUs than those in diabetic controls. Serum ANGPTL2 levels were higher in the advanced stages of DFUs. Spearman correlation analysis revealed strong positive associations of ANGPTL2 with CRP, VEGF and ESR in all subjects. In addition, serum ANGPTL2 was still positively correlated with DFUs stage after adjusting the risk factors. After adjusting for age, sex, HbA1C and duration of diabetes, ANGPTL2 was found to be independently associated with the presence of DFUs. CONCLUSIONS: Circulating ANGPTL2 levels are an independent risk factor for DFUs. This suggests that ANGPTL2 may play important roles in the development of DFUs, a possibility that needs to investigated in prospective studies.

A cross-sectional survey of knowledge, attitude and practice associated with COVID-19 among undergraduate students in China.

BACKGROUND: The COVID-19 pandemic has become a great threat to public health, which has greatly impacted the study and life of undergraduate students in China. This study aims to perform a survey of their knowledge, attitude and practice (KAP) associated with COVID-19. METHODS: A cross-sectional survey was designed to gather information regarding the COVID-19 related KAP among undergraduates during the home isolation in the outbreak. Subjects were recruited from 10 universities in Shaanxi Province, China. Enrollees voluntarily submitted their answers to a pre-designed questionnaire online. RESULTS: A total of 872 subjects (female, 534; male, 338) were enrolled with ages from 17 to 25 years old. This cohort included 430 medical and 442 non-medical students, 580 freshmen and 292 higher school year students. There were 453 from public schools and 442 from private school, residing in 28 regions and provinces at the time of study. Results showed that appropriate knowledge was acquired by 82.34% subjects; the levels were significantly higher in undergraduates from public universities and medical majors than those from private schools and non-medical majors (p<0.05). 73.81% subjects reported positive attitudes; females showed significantly higher levels of positive attitudes than males (p<0.05). Proactive practice was found in 87.94% subjects. Using a common scoring method, the overall scores for Knowledge, Attitude and Practice were 4.12 ± 0.749 (range: 0 ~ 5), 8.54 ± 1.201 (range: 0 ~ 10), and 8.91 ± 1.431 (range: 0 ~ 10), respectively. There was a positive correlation between attitude and practice (r = 0.319, p < 0.05) in the whole study group. Total KAP score was 21.57 ± 2.291 (range: 0 ~ 25), which was significantly different between gender groups and major groups. CONCLUSIONS: Most undergraduates acquired necessary knowledge, positive attitude and proactive practice in response to COVID-19 outbreak; but their KAP scores significantly varied by gender, major and school types.

Mediation effect of body mass index on the association between spicy food intake and hyperuricemia in rural Chinese adults: the Henan rural cohort study.

BACKGROUND: The relationship of spicy food intake with hyperuricemia remains unknown. The objective of this study was to examine the association between spicy food intake and hyperuricemia, and whether this association was mediated by body mass index (BMI) in Chinese rural population. METHODS: 38, 027 adults aged 18-79 years were recruited from the Henan Rural Cohort Study. Information on spicy food intake was obtained using a validated questionnaire survey. Multivariable logistic regression model was used to estimate the association between spicy food intake and hyperuricemia, multiple linear regression model was performed to estimate the relationships between spicy food intake, BMI and serum urate level. BMI was used as a mediator to evaluate the mediation effect. RESULTS: After adjusting for potential confounders, compared with no spicy food flavor, the odds ratio (OR) and 95% confidence interval (CI) of mild, middle, and heavy flavor for hyperuricemia were 1.09 (1.00-1.19), 1.10 (0.97-1.24), and 1.21 (1.10-1.46), respectively (Ptrend = 0.017). Similarly, compared with those without intake in spicy food, the multivariable adjusted OR (95% CI) of 1-2 days/week, 3-5 days/week, and 6-7 days/week were 1.15 (1.01-1.31), 1.14 (1.01-1.30) and 1.15 (1.05-1.26), respectively (Ptrend = 0.007). However, when we further controlling for BMI, the associations were substantially attenuated. Furthermore, mediation analysis showed that BMI play a full mediating role in the relationship of spicy food intake with hyperuricemia. CONCLUSION: Spicy food flavor and intake frequency are positively related with hyperuricemia in Chinese rural population. BMI may play a full mediating role in the relationship. TRIAL REGISTRATION: The Henan Rural Cohort Study registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699 ). Date of registration: 2015-07-06.

Digital Forensics of Scanned QR Code Images for Printer Source Identification Using Bottleneck Residual Block.

With the rapid development of information technology and the widespread use of the Internet, QR codes are widely used in all walks of life and have a profound impact on people's work and life. However, the QR code itself is likely to be printed and forged, which will cause serious economic losses and criminal offenses. Therefore, it is of great significance to identify the printer source of QR code. A method of printer source identification for scanned QR Code image blocks based on convolutional neural network (PSINet) is proposed, which innovatively introduces a bottleneck residual block (BRB). We give a detailed theoretical discussion and experimental analysis of PSINet in terms of network input, the first convolution layer design based on residual structure, and the overall architecture of the proposed convolution neural network (CNN). Experimental results show that the proposed PSINet in this paper can obtain extremely excellent printer source identification performance, the accuracy of printer source identification of QR code on eight printers can reach 99.82%, which is not only better than LeNet and AlexNet widely used in the field of digital image forensics, but also exceeds state-of-the-art deep learning methods in the field of printer source identification.