Associations of multiple hydroxy-polycyclic aromatic hydrocarbons with serum levels of lipids in the workers from coking and non-ferrous smelting industries.

Epidemiological evidence indicates that exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with certain metabolic diseases. However, the relationship between PAHs and serum lipid profiles in exposed subjects remain unknown. Herein, the associations of multiple (8) urinary hydroxylated PAHs (OH-PAHs) in workers of coking (n = 655) and non-ferrous smelting (n = 614) industries with serum lipid levels (marking lipid metabolism) were examined. Multivariable linear regression, Bayesian kernel machine regression, and quantile g-computation were used. Most urinary OH-PAHs were significantly higher (p < 0.001) in coking workers than in non-ferrous smelting workers. In workers of both industries, OH-PAH exposure was associated with elevated levels of serum total cholesterol, total triglyceride, and low-density lipoprotein, as well as reduced high-density lipoprotein levels. Specifically, urinary 4-hydroxyphenanthrene was significantly positively associated with serum total cholesterol, total triglyceride, and low-density lipoprotein levels in non-ferrous smelting workers; however, the completely opposite association of 4-hydroxyphenanthrene with these lipid levels was observed in coking workers. The results of this pioneering examination suggest that exposure to OH-PAHs may contribute to dyslipidemia in coking and non-ferrous smelting workers, and distinct patterns of change were observed. Further prospective studies involving larger sample sizes are needed to further validate the findings.

Exploring the association between social media and farmers' knowledge of a worldwide invasive agricultural pest, Spodoptera frugiperda (Lepidoptera: Noctuidae).

BACKGROUND: Public education has profound effects on the management effectiveness of invasive alien species by shaping stakeholders' knowledge systems. However, our understanding of the association between social media and farmers' knowledge is lacking for the majority of invasive agricultural pests. In this study, we used the fall armyworm (FAW), Spodoptera frugiperda, one of the most invasive insects globally, as a case to test the hypothesis that social media has a significant association with farmers' knowledge of FAW. To address this, we developed a theoretical framework, conducted extensive household questionnaires in the China-Myanmar-Laos border region (China), and used quantitative descriptions and binary logistic regressions in statistical analyses. RESULTS: Our results showed that (1) farmers frequently reported using 12 social media applications on smartphones (SMASs), and obtained FAW-relevant information from six of them, with high preferences for WeChat and TikTok, (2) farmers possessed a generally high level of knowledge of FAW which was significantly associated with their socio-demographic profiles, and (3) FAW-relevant information from SMASs was significantly associated with certain aspects of farmers' knowledge of FAW. CONCLUSIONS: We concluded that social media has a significant association with farmers' knowledge of FAW. We suggest that well-designed and -conducted educational programs based on the use of SMASs could help improve the management of FAW, and the Department of Agricultural Extension could play an important and necessary role. Our findings provide insights into this novel educational approach for the management of serious invasive agricultural pests. © 2023 Society of Chemical Industry.

Associations between inhalation of typical volatile and semi-volatile organic compounds in e-waste dismantling workers with liver function damage.

Studies in cell culture and animal models suggest hepatotoxicity of some volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs), however, their effects in human populations under real exposure conditions have never been clarified. In this cross-sectional study, 224 participants, 38 e-waste dismantling workers and 186 subjects residing near to the dismantling sites in southern China, were evaluated for personal inhalational exposure to 72 VOCs and 91 SVOCs according to site-specific atmospheric chemical concentrations and personal exposure time. Additionally, their serum samples were subjected to liver function tests (LFTs), including total protein (TP), albumin (ALB), globulin (GLB), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), and bilirubin. Linear regression analysis of the VOC/SVOC levels against the LFTs results indicated that VOC exposure was negatively associated with the TP, ALB, GLB levels (indicating liver-specific protein synthesis functions), while positively associated with AST, ALT, GGT activities (marking liver damage). Somehow, SVOC exposure appeared to be positively associated with not only AST and ALT but also TP and ALB. These findings were supported by the quantile g-computation analysis and confirmed in the Bayesian kernel machine regression model. This study indicates that simultaneous inhalation of VOCs and SVOCs may impair human liver functions.

The characteristics of the complete chloroplast genome of Staurogyne concinnula (Hance) O. Kuntze (Acanthaceae).

Staurogyne concinnula (Hance) O. Kuntze (Acanthaceae) is an important ornamental herb mainly distributed in the southern region of China, including Fujian, Guangdong, Hainan, and Taiwan provinces. However, the complete chloroplast genome of S. concinnula, which could serve as a genetic resource for studies on its taxonomy and evolution, is poorly studied at present. In this study, we reported the complete chloroplast genome of S. concinnula that was assembled using high-throughput sequencing data. The chloroplast genome was 153,783 bp long, with a typical quadripartite structure containing a small single-copy region (SSC; 17,855 bp), a large single-copy region (LSC; 84,636 bp) and a pair of inverted repeats (IRs; each 25,646 bp). The overall GC content of the chloroplast genome was 38.04%. A total of 86 protein-coding genes (PCGs), 8 rRNA genes, and 37 tRNA genes were predicted. Phylogenetic analysis based on the combined sequences of 86 PCGs with the other 16 closely related species of Acanthaceae indicated that S. concinnula is closely related to Avicennia marina. The genomic data and finding from the phylogenetic studies of S. concinnula could provide useful information and give light to in-depth studies on the evolution pattern of the understudied species, as well as Staurogyne.

METTL3/YTHDF2 m6A axis promotes the malignant progression of bladder cancer by epigenetically suppressing RRAS.

The present study aimed to explore the potential roles of the methyltransferase­like 3 (METTL3)­mediated methylation of RAS related (RRAS) mRNA in the tumorigenesis and development of bladder cancer (BCa). For this purpose, the relative expression levels of METTL3 in BCa specimens and cell lines were measured using reverse transcription­quantitative PCR (RT­qPCR) and western blot analysis. The association between the METTL3 expression level and the clinical characteristics of patients with BCa was analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis databases. Cellular experiments were performed to confirm the effects of METTL3 on the proliferative, migratory and invasive capacities of BCa cells. RT­qPCR, western blot analysis, methylated RNA immunoprecipitation (MeRIP)­qPCR and dual­luciferase report assays were utilized to verify the METTL3/RRAS/YTH N6­methyladenosine (m6A) RNA binding protein 2 (YTHDF2) regulatory axis in BCa. The results revealed that METTL3 expression was markedly increased in BCa specimens and cell lines, and was associated with poor clinical characteristics of patients with BCa. In vitro and in vivo assays demonstrated that the silencing of METTL3 markedly suppressed the proliferative, migratory and invasive capacities of BCa cells. MeRIP­PCR and dual­luciferase report assays indicated that METTL3 could bind to the m6A sites of RRAS mRNA and suppress the transcriptional activity of RRAS. YTHDF2 could recognize the m6A sites of RRAS and mediate RRAS degradation. On the whole, the findings of the present study reveal the pivotal role of METTL3­catalyzed m6A modification in BCa tumorigenesis and development. The change could facilitate BCa tumor growth and metastasis by suppressing RRAS expression in an m6A YTHDF2­dependent manner. Targeting the METTL3/RRAS/YTHDF2 regulatory axis may thus prove to be a promising strategy for the diagnosis and therapy of BCa.

A U-Shaped Network Based on Multi-level Feature and Dual-Attention Coordination Mechanism for Coronary Artery Segmentation of CCTA Images.

PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With the deep convolutional neural network, this work aims to develop an intelligent and lightweight coronary artery segmentation algorithm that can be deployed in hospital systems to assist clinicians in quantitatively analyzing CHD. METHODS: With the multi-level feature fusion, we proposed Dual-Attention Coordination U-Net (DAC-UNet) that achieves automated coronary artery segmentation in 2D CCTA images. The coronary artery occupies a small region, and the foreground and background are extremely unbalanced. For this reason, the more original information can be retained by fusing related features between adjacent layers, which is conducive to recovering the small coronary artery area. The dual-attention coordination mechanism can select valid information and filter redundant information. Moreover, the complementation and coordination of double attention factors can enhance the integrity of features of coronary arteries, reduce the interference of non-coronary arteries, and prevent over-learning. With gradual learning, the balanced character of double attention factors promotes the generalization ability of the model to enhance coronary artery localization and contour detail segmentation. RESULTS: Compared with existing related segmentation methods, our method achieves a certain degree of improvement in 2D CCTA images for the segmentation accuracy of coronary arteries with a mean Dice index of 0.7920. Furthermore, the method can obtain relatively accurate results even in a small sample dataset and is easy to implement and deploy, which is promising. The code is available at: https://github.com/windfly666/Segmentation . CONCLUSION: Our method can capture the coronary artery structure end-to-end, which can be used as a fundamental means for automatic detection of coronary artery stenosis, blood flow reserve fraction analysis, and assisting clinicians in diagnosing CHD.

Multifunctional bio-films based on silk nanofibres/peach gum polysaccharide for highly sensitive temperature, flame, and water detection.

Given their environment friendliness, light weight, and availability, bio-films have attracted wide interest for various applications in sensor materials. However, obtaining sensors with good environmental stability, excellent flame retardancy, and high wet strength remains a challenge. Herein, we prepared sensitive water, temperature and flame-responsive multi-function bio-films (named as PSCG bio-films) by combining peach gum polysaccharide, silk nanofibres, citric acid, and graphene. The PSCG bio-films demonstrated good flexibility, rapid and consistent water absorption, and stable wet strength at different temperatures. The bio-films showed excellent water sensitivity and rapid fire responsiveness within a short time frame (2 s); moreover, the response and recovery times of the bio-films in the temperature range of 50-150 °C were 0.1 and 0.3 s, respectively. In addition, the bio-films can be applied to micro-sized fire early warning devices and personalized breath monitoring. Our work presents a facile and green approach (without toxic solvent) to fabricate multi-function sensors with applications in various industries.

Study on the mechanism of Phellinus igniarius total flavonoids in reducing uric acid and protecting uric acid renal injury in vitro.

Background: Uric acid nephropathy (UN) is a complication of hyperuricemia (HUA), which has a great impact on people's lives. Here, we evaluated the therapeutic potential of total flavonoids of Phellinus igniarius (TFPI) in vivo and studied the anti UN effect of TFPI in vitro. Methods: Hyperuricemia was induced by intraperitoneal injection of potassium oxonate in ICR mice. After intervention with TFPI, we evaluated the levels of serum uric acid (UA) and creatinine (CR), and the contents of xanthine oxidase (XOD) and adenosine deaminase (ADA) in liver. To explore the effect and molecular mechanism of TFPI on UN, we treated HK-2 cells with monosodium urate (MSU) to study the effect of TFPI on apoptosis and inflammation. In addition, to explore the mechanism of TFPI on uric acid transport we evaluated the relationship between uric acid transporter ABCG2 and inflammatory signaling pathway TLR4-NLRP3. Results: In the model mice, TFPI significantly decreased the levels of UA and Cr, which may be related to the inhibition of XOD enzyme activity. In HK-2 cells, the response of TFPI to MSU can effectively inhibit apoptosis and activation of TLR4-NLRP3 signaling pathway and promote the expression of ABCG2. Conclusions: TFPI can significantly inhibit the release of inflammatory factors and promote the expression of ABCG2 by targeting TLR4 receptor and NLRP3 inflammasome. And targeted inhibition of XOD enzyme activity to reduce uric acid level and inhibit the development of UN.

Cryptanalysis of an Image Encryption Algorithm Based on a 2D Hyperchaotic Map.

Recently, an image encryption scheme based on a 2D hyperchaotic map is proposed. It adopts the permutation-diffusion architecture and consists of three steps, which are permutation, forward diffusion, and backward diffusion. In this paper, we break this cipher with both the chosen-plaintext attack (CPA) and the chosen-ciphertext attack (CCA). According to our analysis, we found the two complex diffusion processes could be simplified into two simple diffusions and a modular addition operation. Based on this, the equivalent key can be obtained with CPA and CCA. Detailed theoretical derivations and the results of experiments confirmed the feasibility of our attack methods. When the image size was 256×256, the running time of the attacks was less than 2 hours on a laptop with a 2.59 GHz Intel Core i7 and 16 GB DDR3 memory. Other sizes of images were also tested, and some rules were found. In addition, the probability of other attacks has also been discussed, and some suggestions for improvements are given. The source codes are publicly available and can be found online.

Obstructive Sleep Apnea with COVID-19.

The novel coronavirus disease-2019 (COVID-19) and the ensuing pandemic have greatly impacted the global healthcare system due to its high infectiousness, associated high mortality, and a complete lack of immunity in the population. Globally, the COVID-19 pandemic has unleashed a health crisis that has not only seriously disrupted people's lives but also affected their normal sleep, along with physical and mental health; this situation is especially exacerbated in people suffering from pre-existing conditions, such as sleep apnea. A recent meta-analysis of 18 studies by Miller et al. (September 2020) showed that obstructive sleep apnea (OSA) is related to higher mortality and morbidity in patients with COVID-19 and is most likely independent of other risk factors. A recent meta-analysis indicated that COVID-19 patients with OSA are more severely affected than those without OSA, thereby providing further evidence that concurrent OSA may elevate the severity of COVID-19 infection, along with the risk of mortality. The COVID-19 pandemic has significantly impacted the diagnosis and therapeutic management of patients with OSA. Thus, it is necessary to identify and develop new diagnostic and therapeutic avenues in the future. In this context, the current study summarizes known associations between COVID-19 and OSA and the regular diagnostic and therapeutic strategies for OSA in the light of COVID-19 pandemic prevention and control.

A study on the current state and equity level of social participation ability among older adults in Henan Province, China.

BACKGROUND: The social participation ability among older adults (SPAOA) plays an important role in enhancing their quality of life and utilization of medical services. This study aimed to evaluate the current state and equity level of SPAOA in Henan Province, China, as well as explore the factors associated with the current state and equity level of SPAOA. METHODS: This study analyzed data from the "2019 Henan Provincial Older Adults Ability Assessment Survey", which included 4,593 older people (over 60 years old). The relationships among the SPAOA indicators were explored using the Structural Equation Model (SEM). The Dynamic Material Element Analysis (DMA) and Logistic Regression (LR) were used to examine the current state of SPAOA and its associated factors. The equity level of SPAOA and its correlated factors were determined using the concentration index and T Theil index. RESULTS: SPAOA received an overall score of 91.89 ± 9.83. Daily living, perception ability and mental state were positively correlated with SPAOA (r = 0.13, 0.83, 0.11, all P < 0.05). Results of LR indicated that the most significant predictors of SPAOA were age, education level, pre-retirement occupation, and income (all P < 0.05). The concentration index of SPAOA based on age and income were -0.0058 and 0.0096, respectively. SPAOA had a total T Theil index of 0.030-0.031, and the contribution rate of the difference within the group was greater than 94%. CONCLUSIONS: While the overall level of SPAOA has been demonstrated to be outstanding, persons with a higher educational level and income are likely to benefit the most. The observed unequal distribution of SPAOA is primarily related to disparities in age or income within the group. To better serve older adults and improve their position and equity in terms of social participation ability, policymakers could emphasize older males with little income who live in urban areas, as well as unhealthy older females who live in rural residences.

Risk factors for kidney stone disease recurrence: a comprehensive meta-analysis.

BACKGROUND: Kidney stone disease (KSD) is a common illness that causes an economic burden globally. It is easy for patients to relapse once they have suffered from this disease. The reported recurrence rate of KSD ranged from 6.1% to 66.9%. We performed this meta-analysis to identify various potential risk factors for the recurrence of KSD. METHODS: The PubMed, Embase and Web of Science databases were searched using suitable keywords from inception to Mar 2022. A total of 2,663 records were collected initially. After screening the literature according to the inclusion and exclusion criteria, 53 articles (40 retrospective studies; 13 prospective studies) including 488,130 patients were enrolled. The study protocol was registered with PROSPERO (No. CRD42020171771). RESULTS: The pooled results indicated that 12 risk factors including younger age (n = 18), higher BMI (n = 16), family history of kidney stones (n = 12), personal history of kidney stones (n = 11), hypertension (n = 5), uric acid stone (n = 4), race of Caucasian (n = 3), suspected kidney stone episode before the first confirmed stone episode (n = 3), surgery (n = 3), any concurrent asymptomatic (nonobstructing) stone (n = 2), pelvic or lower pole kidney stone (n = 2), and 24 h urine test completion (n = 2) were identified to be associated with KSD recurrence. In the subgroup analysis, patients with higher BMI (OR = 1.062), personal history of nephrolithiasis (OR = 1.402), or surgery (OR = 3.178) had a higher risk of radiographic KSD recurrence. CONCLUSIONS: We identified 12 risk factors related to the recurrence of KSD. The results of this analysis could serve to construct recurrence prediction models. It could also supply a basis for preventing the recurrence of KSD.

Educational Approaches Help Bridge Perception Gaps of Invasive Alien Species (Mikania micrantha) between Managers and Non-managers.

Invasive alien species (IAS) significantly impact biodiversity, human health, and economies, and considerable resources are often used to manage their spread. Few studies have focused on the human perception of IAS management, and little is known about approaches to improve stakeholder perception. This study examined perception gaps between managers and non-managers of a notorious weed Mikania micrantha and the preference for educational approaches to bridge those gaps. Household questionnaires and key informant interviews were conducted in the China-Myanmar Border Region (China), and ordinal logistic regressions and Wilcoxon rank sum tests were used in statistical analyses. We found a high level of perception of M. micrantha among stakeholders, and a significant influence of socio-demographic factors including gender, educational level, ethnic group, and geographical location. Scores of the identification, damage, control measure, and manual treatment of M. micrantha were significantly higher for managers than those for non-managers, indicating that there were certain perception gaps between two stakeholder groups. Nine educational approaches were identified as being effective in improving stakeholder perception of IAS, of which training workshops were mostly preferred, followed by brochures (or leaflets) and other promotional materials. Additionally, we propose that well-designed and well-conducted educational approaches would benefit stakeholder perception of IAS, and that integration of IAS management into a comprehensive rural development scheme would improve its long-term performance in marginalized rural communities.

Polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X nanotheranostic platform for nasopharyngeal carcinoma imaging and photothermal therapy.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a type of head and neck malignant tumor with a high incidence in specific regional distribution, and its traditional therapies face some challenges. It has become an urgent need to seek new therapeutic strategies without or with low toxicity and side effects. At present, more and more researchers has been attracting attention by nanotheranostic platform. Therefore, our team synthesized the polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X (USPIO-PEG-sLex) nanotheranostic platform with high temperature pyrolysis. RESULTS: The USPIO-PEG-sLex nanoparticles had excellent photothermal conversion property, and the temperature of USPIO-PEG-sLex nanoparticles solution increased with its concentration and power density of near-infrared (NIR) on 808 nm wavelengths. Five USPIO-PEG-sLex nanoparticles with different concentrations of 0 mg/ml, 0.025 mg/ml, 0.05 mg/ml, 0.1 mg/ml and 0.2 mg/ml were prepared. The biological toxicity results showed that the viability of NPC 5-8F cells is related to the concentration of USPIO-PEG-sLex nanoparticles and the culture time (P < 0.001). The results of photothermal therapy (PTT) in vitro indicated that the viability of 5-8F cells decreased significantly with the concentration of USPIO-PEG-sLex nanoparticles increases (P < 0.001), and the viability of NPC 5-8F cells were 91.04% ± 5.20%, 77.83% ± 3.01%, 73.48% ± 5.55%, 59.50% ± 10.98%, 17.11% ± 3.14%, respectively. The USPIO-PEG-sLex nanoparticles could target the tumor area, and reduce the T2* value of tumor tissue. The T2* values of tumor pre- and post-injection were 30.870 ± 5.604 and 18.335 ± 4.351, respectively (P < 0.001). In addition, USPIO-PEG-sLex nanoparticles as a photothermal agent for PTT could effectively inhibit tumor progression. The ratio of volume change between tail vein injection group, control group, nanoparticles without laser irradiation group and blank group after 5 treatments were 3.04 ± 0.57, 5.80 ± 1.06, 8.09 ± 1.96, 7.89 ± 2.20, respectively (P < 0.001). CONCLUSIONS: Our synthesized USPIO-PEG-sLex nanotheranostic platform, and it may be become a new strategy for the treatment of NPC.

Efficacy and safety of renal denervation for hypertension in patients with chronic kidney disease: a meta-analysis.

BACKGROUND: Renal denervation (RDN) is a new treatment for hypertension in patients with chronic kidney disease (CKD), but its efficacy is still debated. This meta-analysis aimed to evaluate the efficacy and safety of RDN for hypertension in patients with CKD. METHODS: PubMed, Web of Science, EMBASE, and Ovid databases were searched for relevant studies published. We performed both fixed- and random-effects meta-analyses of the changes in blood pressure, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) after RDN. RESULTS: The meta-analysis included 238 patients from 11 single-center, non-randomized, uncontrolled studies. Office blood pressure and 24-hour ambulatory blood pressure (24 h-ABP) showed a significant reduction 1 month after RDN (p < 0.05). This decrease of 24 h-ABP persisted for 24 months after RDN showed difference systolic blood pressure (p < 0.001) and diastolic blood pressure (p = 0.001). The 24 h-ABP exhibited a similar trend in the subgroup analysis. eGFR measurements obtained at each time point of analysis after RDN were not significantly different from those obtained before (p > 0.05). UACR levels were significantly reduced at 3 months and 6 months after RDN (p < 0.001). After RDN, the heart rate showed no significant changes (p > 0.05), and few major complications were encountered. CONCLUSIONS: The meta-analysis showed that RDN may be effective and safe for treating CKD patients with hypertension. Well-designed randomized controlled trials of RDN are urgently needed to confirm the safety and reproducibility of RDN and to assess its impact on clinical outcomes.

Identification of unique long non-coding RNAs as putative biomarkers for chromophobe renal cell carcinoma.

Aim: To investigate whether long non-coding RNAs (lncRNAs) can be utilized as molecular biomarkers in predicting the occurrence and progression of chromophobe renal cell carcinoma. Methods & results: Genetic and related clinical traits of chromophobe renal cell carcinoma were downloaded from the Cancer Genome Atlas and used to construct modules using weighted gene coexpression network analysis. In total, 44,889 genes were allocated into 21 coexpression modules depending on intergenic correlation. Among them, the green module was the most significant key module identified by module-trait correlation calculations (R2 = 0.43 and p = 4e-04). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that genes in the green module were enriched in many pathways. Coexpression, protein-protein interaction networks, screening for differentially expressed genes, and survival analysis were used to select hub lncRNAs. Five hub lncRNAs (TTK, CENPE, KIF2C, BUB1, and RAD51AP1) were selected out. Conclusion: Our findings suggest that the five lncRNAs may act as potential biomarkers for chromophobe renal cell carcinoma progression and prognosis.

Identification of Hub Biomarkers and Immune-Related Pathways Participating in the Progression of Antineutrophil Cytoplasmic Antibody-Associated Glomerulonephritis.

Background: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systemic autoimmune disease that generally induces the progression of rapidly progressive glomerulonephritis (GN). The purpose of this study was to identify key biomarkers and immune-related pathways involved in the progression of ANCA-associated GN (ANCA-GN) and their relationship with immune cell infiltration. Methods: Gene microarray data were downloaded from the Gene Expression Omnibus (GEO). Hub markers for ANCA-GN were mined based on differential expression analysis, weighted gene co-expression network analysis (WGCNA) and lasso regression, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) of the differential genes. The infiltration levels of 28 immune cells in the expression profile and their relationship to hub gene markers were analysed using single-sample GSEA (ssGSEA). In addition, the accuracy of the hub markers in diagnosing ANCA-GN was subsequently evaluated using the receiver operating characteristic curve (ROC). Results: A total of 651 differential genes were screened. Twelve co-expression modules were obtained via WGCNA; of which, one hub module (black module) had the highest correlation with ANCA-GN. A total of 66 intersecting genes were acquired by combining differential genes. Five hub genes were subsequently obtained by lasso analysis as potential biomarkers for ANCA-GN. The immune infiltration results revealed the most significant relationship among monocytes, CD4+ T cells and CD8+ T cells. ROC curve analysis demonstrated a prime diagnostic value of the five hub genes. According to the functional enrichment analysis of the differential genes, hub genes were mainly enhanced in immune- and inflammation-related pathways. Conclusion: B cells and monocytes were closely associated with the pathogenesis of ANCA-GN. Hub genes (CYP3A5, SLC12A3, BGN, TAPBP and TMEM184B) may be involved in the progression of ANCA-GN through immune-related signal pathways.

Meta-Analytical Accuracy of ANCA Renal Risk Score for Prediction of Renal Outcome in Patients With ANCA-Associated Glomerulonephritis.

Background: To evaluate the diagnostic accuracy of antineutrophil cytoplasmic antibody (ANCA) renal risk score (ARRS) for prediction of renal outcome in patients with ANCA-associated glomerulonephritis (ANCA-GN). Methods: We searched PubMed, EMBASE, Ovid, Web of Science, the Cochrane Library, and ClinicalTrials.gov for studies, which used ARRS to predict end-stage renal disease (ESRD) in patients with ANCA-GN. Two reviewers independently screened articles for inclusion, assessed the quality of studies with both an adapted Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. We calculated the combined patients with ESRD in the ARRS categories and presented the summary and individual estimates based on the ARRS categories. Then, the sensitivity, specificity, diagnostic odds ratio (DOR), positive/negative likelihood ratio, and the area under the receiver operating characteristic (AUROC) curves of the pooled data for ARRS were used to assess the accuracy of the "above the low-risk threshold" (ARRS ≥ 2) and "high-risk grade" (ARRS ≥ 8) for renal outcome of patients with ANCA-GN. The hierarchical summary ROC (HSROC) was used to verify the accuracy value. The clinical utility of ARRS was evaluated by the Fagan plot. Heterogeneity was explored using meta-regression and subgroup analysis. Results: A total of 12 distinct cohorts from 11 articles involving 1,568 patients with ANCA-GN were analyzed. The cumulative patients with ESRD at the maximum follow-up of 60 months was 5% (95% CI: 0.02-0.07; p < 0.001) for ANCA-GN with low ARRS (0-1 points) and significantly increased to 22% (95% CI: 0.15-0.29; p < 0.001) medium ARRS (2-7 points). The combined cumulative patients with ESRD was 59% (95% CI: 0.49-0.69; p < 0.001) high ARRS (8-11 points). The pooled sensitivity of ARRS ≥ 2 in predicting ESRD was 98% with a specificity of 30% and a DOR of 15.08 and the mean AUROC value was 0.82. The pooled sensitivity of ARRS ≥ 8 in predicting ESRD was 58% with a specificity of 86% and a DOR of 7.59. The meta-regression and subgroup analysis indicated that variation in the geographic regions, study design, index risk, follow-up time, age of patient, publication year, and number of patient could be the potential sources of heterogeneity in the diagnosis of ARRS ≥ 8. Conclusion: This meta-analysis emphasized the good performance of the ARRS score in predicting the renal outcome in patients with ANCA-GN. However, these findings should be verified by future large-scale prospective studies.

A novel prognostic model based on immunogenomics for clear cell renal cell carcinoma.

BACKGROUND: Immune cell infiltration into tumor tissue is closely related to the clinical outcomes of patients with clear cell renal cell carcinoma (ccRCC). This study aimed to screen out potential immune genes associated with ccRCC, analyze their relationships with clinical outcomes, and construct a signature to predict ccRCC. METHODS: The transcriptome RNA-sequencing data in 539 ccRCC and 72 adjacent normal tissues were obtained from TCGA database. Biomedical computational algorithms were conducted to identify immune-related differential expressed genes (IRDGs) and enriched pathways. Then, LASSO Cox and multivariate Cox analyses were performed to screen out genes that were then used to construct the prognostic model. RESULTS: A total of 116 down-regulated and 565 up-regulated IRDGs were identified. Pathway enrichment analysis suggested that IRDGs was mainly enriched in the pathway of "cytokines and cytokine receptors". The entire data of ccRCC were randomly divided into the training set and the test set with a ratio of 1:1. A 4-gene signature was then constructed using LASSO Cox analysis and multivariate Cox analysis in the training set. This prognostic signature could stratify patients into high- and low-risk groups successfully, and serve as an independent predictor when adjusted with clinical factors by univariate and multivariate Cox regression analysis. These results were verified in the test set and the entire set. Besides, the abundance of CD4 + T cells and dendritic cells increased in the high-risk group. Finally, we built a nomogram incorporating risk score and clinical factors to predict the overall survival of ccRCC patients. CONCLUSIONS: These findings may contribute to the research of ccRCC in immunization part.

Identifying Influencers in Social Networks.

Social network analysis is a multidisciplinary research covering informatics, mathematics, sociology, management, psychology, etc. In the last decade, the development of online social media has provided individuals with a fascinating platform of sharing knowledge and interests. The emergence of various social networks has greatly enriched our daily life, and simultaneously, it brings a challenging task to identify influencers among multiple social networks. The key problem lies in the various interactions among individuals and huge data scale. Aiming at solving the problem, this paper employs a general multilayer network model to represent the multiple social networks, and then proposes the node influence indicator merely based on the local neighboring information. Extensive experiments on 21 real-world datasets are conducted to verify the performance of the proposed method, which shows superiority to the competitors. It is of remarkable significance in revealing the evolutions in social networks and we hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising field.