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Abstract Background The different symptoms of major depressive disorder (MDD) in adolescents compared to adults suggested there may be differences in the pathophysiology between adolescents and adults with MDD. However, despite the amygdala being considered critical in the pathophysiology, there was limited knowledge about the commonalities and differences in the resting-state functional connectivity (rsFC) of amygdala subregions in MDD patients of different age groups. Methods In the current study, 65 adolescents (46 with MDD and 19 controls) and 91 adults (35 with MDD and 56 controls) were included. A seed-based functional connectivity analysis was performed for each of the amygdala subregions. A 2 × 2 ANOVA was used to analyze the main effect of age, diagnosis, and their interaction on the rsFC of each subregion. Results A significant main effect of age was revealed in the rsFC of bilateral centromedial (CM) subregions and right laterobasal (LB) subregion with several brain regions in the limbic system and frontoparietal network. The significant main effect of diagnosis showed MDD patients of different ages showed higher connectivity than controls between the right LB and left middle frontal gyrus (MFG). Conclusions The rsFC of specific amygdala subregions with brain regions in the limbic system and frontoparietal network is affected by age, indicating a distinct amygdala connectivity profile in adolescents. The decreased rsFC between the right LB and the left MFG in adolescents and adults with MDD could serve as a diagnostic biomarker and a target of nonpharmacological treatment for MDD.

Abstract Differences in clinical manifestations and biological underpinnings between Major Depressive Disorder (MDD) onset during adolescence and adulthood have been posited in previous studies, implying an influential role of age of onset (AOO) in the clinical subtyping and therapeutic approaches to MDD. However, direct comparisons between the two cohorts and their age-matched controls have been lacking in extant investigations. In this investigation, 156 volunteers participated, comprising 46 adolescents with MDD (adolescent-onset group), 35 adults with MDD (adult-onset group), 19 healthy adolescents, and 56 healthy adults. Resting-state functional MRI scans were undergone by all participants. Large-scale network analyses were applied. Subsequently, a 2 × 2 ANOVA was employed to analyze the main effects of diagnosis, age, and their interaction effect on functional connectivity (FC). Furthermore, regression analysis was employed to scrutinize the association between anomalous FC and HAMD sub-scores. Increased FC in visual network (VN), limbic network (LN), VN-dorsal attention network (DAN), VN-LN, and LN-Default Mode (DMN) was found in both adolescent-onset and adult-onset MDD; however, the increased FC in DAN and LN were only found in adult-onset MDD and the decreased FC in DAN was only found in adolescent-onset MDD. Additionally, the relationship between HAMD factor 1 anxiety somatization and altered FC of DAN, VN, and VN-DAN was moderated by AOO. In conclusion, shared and distinctive large-scale network alterations in adolescent-onset and adult-onset MDD patients were suggested by our findings, providing valuable contributions towards refining clinical subtyping and treatment approaches for MDD.

Abstract Background As the global aging process continues to accelerate, heart failure (HF) has become an important cause of increased morbidity and mortality in elderly patients. Chronic atrial fibrillation (AF) is a major risk factor for HF. Patients with HF combined with AF are more difficult to treat and have a worse prognosis. The aim of this study was to explore the risk factors for 1-year mortality in patients with HF combined with AF and to develop a risk prediction assessment model. Methods We recruited hospitalized patients with HF and AF who received standardized care in the Department of Cardiology at Shengjing Hospital of China Medical University from January 2013 to December 2018. The patients were randomly divided into modeling and internal validation groups using a random number generator at a 1:1 ratio. Multivariate Cox regression analysis was used to identify risk factors for all-cause mortality during a one-year follow-up period. Then, a nomogram was constructed based on the weights of each index and validated. Receiver operating characteristic curve, the area under the curve (AUC), decision curve, and calibration curve analyses for survival were used to evaluate the model’s predictive and clinical validities and calibration. Results We included 3,406 patients who met the eligibility criteria; 1,703 cases each were included in the modeling and internal validation groups. Eight statistically significant predictors were identified: age, sex, New York Heart Association cardiac function class III or IV, a history of myocardial infarction, and the albumin, triglycerides, N-terminal pro-b-type natriuretic peptide, and blood urea nitrogen levels. The AUCs were 0.793 (95% confidence interval: 0.763–0.823) and 0.794 (95% confidence interval: 0.763–0.823) in the modeling and validation cohorts, respectively. Conclusions We present a predictive model for all-cause mortality in patients with coexisting HF and AF comprising eight key factors. This model gives clinicians a simple assessment tool that may improve the clinical management of these patients.

The whole train design of an Electric Multiple Unit (EMU) involves multiple domains and scenarios, thus requiring comprehensive consideration of various factors during the design process. Traditional design methods often utilize text-based approaches to model systems; however, such documentation-based designs often suffer from semantic heterogeneity, inconsistent data sources, and also struggle to provide a more intuitive overview of the overall design process. To address these issues, this paper proposes a method based on ontology–knowledge collaborative drive to achieve integration of the overall EMU design. Firstly, we employ the System Modeling Language (SysML) to construct the Model-Based Systems Engineering (MBSE) model of the EMU, establishing functional and physical architecture element models, with the EMU MBSE model serving as input. Subsequently, in the requirement model, architecture model, and traceability model, we utilize top-level ontology to construct the EMU ontology framework in a top-down manner. Lastly, leveraging the Neo4j database, we employ a knowledge graph (KG) approach to fill domain knowledge into each model in a bottom-up manner, thereby realizing the ontology–knowledge collaborative drive for the overall EMU design construction. The effectiveness of the proposed method is validated using the EMU Passenger Information System (PIS) and Traction transformer System (TS) as examples.

Abstract Background Porcine circovirus-like virus P1 is the animal virus with the smallest genome discovered so far, and it has become widely distributed in the Chinese mainland in recent years. Results In this study, a BALB/c mouse model was used to reveal P1 infection in female reproductive systems and the vertical transmission of the virus. The female reproductive system, including the ovary and uterus, was harvested on day 14 postinfection and examined for pathological lesions. One-day-old mice without colostrum born from infected or uninfected mothers were collected, and P1 virus distribution in the different organs was investigated. During the trials, all the mice showed no clinical symptoms or gross lesions. However, stillbirth did occur in groups infected with the P1 virus. P1 nucleic acid was detected in the heart, liver, spleen, lung, kidney, and brain tissues of 1-day-old mice born from infected mice. Microscopic lesions in P1-infected female mice were characterized by necrosis of the ovarian follicular granulosa cells and abscission, follicular atresia, necrosis of the endometrial epithelial and uterine glandular epithelial cells, and hyperplasia of the squamous endometrial epithelium. The spermatocytes in the seminiferous tubules of the infected male mice were disorderly arranged, and the germ and Sertoli cells were shed, necrotic, and decreased in number. Immunohistochemical results identified P1-positive particles in the nucleus and cytoplasm of cells from the ovary and uterus of female mice. Conclusions This study shows that the P1 virus could cause pathological damage to the reproductive system of female mice and could be transmitted vertically.

Insufficient denitrification and limited phosphorus uptake hinder nitrogen and phosphorus removal in constructed wetlands (CWs). Sponge iron is a promising material for the removal of phosphorus and nitrogen because of its strong reducing power, high electronegativity, and inexpensive cost. The influence of factors including initial solution pH, dosage, and the Fe/C ratio was investigated. A vertical flow CW with sponge iron (CW-I) was established, and a traditional gravel bed (CW-G) was used as a control group. The kinetic analysis demonstrated that for both nitrogen and phosphorus, pseudo-second-order kinetics were superior. The theoretical adsorption capacities of sponge iron for nitrate (NO3−-N) and phosphate (PO43−-P) were 1294.5 mg/kg and 583.6 mg/kg, respectively. Under different hydraulic retention times (HRT), CW-I had better total nitrogen (TN) and total phosphorus (TP) removal efficiencies (6.08–15.18% and 5.00–20.67%, respectively) than CW-G. The enhancing effect of sponge iron on nitrogen and phosphorus removal was best when HRT was 48 h. The increase in HRT improved not only the nitrogen and phosphorus removal effects of CWs but also the reduction capacity of iron and the phosphorus removal effect. The main mechanisms of synergistic nitrogen and phosphorus removal were chemical reduction, ion exchange, electrostatic adsorption, and precipitation formation.

AimTo evaluate the safety and efficacy of the His-Purkinje system pacing (HPCSP) in the treatment of individuals with atrial fibrillation (AF) complicated by heart failure (HF).MethodsThe PubMed, Cochrane Library, Web of Science, and Embase databases were searched through September 1, 2022. The literature was initially screened based on the inclusion and exclusion criteria. The baseline characteristics of the subjects, implantation success rate, New York Heart Association (NYHA) classification, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), QRS duration, pacing threshold, and impedance were extracted and summarized; statistical analysis was performed using RevMan 5.3 software.ResultsIn all, 22 articles were included, involving 1,445 patients. Compared to biventricular pacing (BiVP), HPCSP resulted in improved cardiac function, including increased ejection fraction (MD = 5.69, 95% CI: 0.78–10.60, P = 0.02) and decreased LVEDd (MD = −3.50, 95% CI: −7.05–0.05, P = 0.05). It was also correlated with shorter QRS duration (MD = −38.30, 95% CI: −60.71–−15.88, P

Highlights A fast TSA scheme for pre-failure scanning. A physical mechanism-based attention structure for dynamic graph pooling. A node regression model that responds to key physical mechanisms. Generator label for richer output information. Top performance and post-hoc interpretation.

By integrating communications in different domains, integrated radio and optical networks can serve a wider range of applications and services. Integrated radio and optical network scenarios will involve more weak-computation-ability network nodes, such as small-cell base stations. To pursue efficient integrated radio and optical networks, more efficient ways to conduct transmission under the demand of edge and cloud collaboration are required. The lack of forward-looking resource allocation may easily lead to a waste of network resources without an expected return. Therefore, an efficient resource allocation scheme needs to consider certain issues: 1) a comprehensive perspective of traffic prediction; 2) a release of pressure on the transmission pipeline during the prediction process; and 3) a reduction of loss of edge nodes due to the computation. In this paper, benefiting from machine learning, we propose a resource allocation with edge-cloud collaborative traffic prediction (TP-ECC) in integrated radio and optical networks, where an efficient resource allocation scheme (ERAS) is designed based on the prediction results with the gated recurrent unit model. We maximize the utilization of limited resources to improve the awareness of network status. We present three evaluation indicators and build a network architecture to evaluate our resource allocation scheme. Through edge-cloud collaboration, our proposal can improve traffic prediction accuracy by 9.5% compared with single-point traffic prediction, and resource utilization is also improved by edge-cloud collaborative traffic prediction.

An open critical-size bone defect is a major medical problem because of the difficulty in self-healing, leading to an increased risk of bacterial infection owing to wound exposure, resulting in treatment failure. Herein, a composite hydrogel was synthesized by chitosan, gallic acid, and hyaluronic acid, termed “CGH.” Hydroxyapatite was modified with polydopamine (PDA@HAP) and introduced to CGH to obtain a mussel-inspired mineralized hydrogel (CGH/PDA@HAP). The CGH/PDA@HAP hydrogel exhibited excellent mechanical performances, including self-healing and injectable properties. Owing to its three-dimensional porous structure and polydopamine modifications, the cellular affinity of the hydrogel was enhanced. When adding PDA@HAP into CGH, Ca2+ and PO43- could release and then promoted differentiation of BMSCs into osteoblasts. Without any osteogenic agent or stem cells, the area of new bone at the site of defect was enhanced and the newly formed bone had a dense trabecular structure after implanting of the CGH/PDA@HAP hydrogel for 4 and 8 weeks. Moreover, the growth of Staphylococcus aureus and Escherichia coli was effectively inhibited through the grafting of gallic acid onto chitosan. Above, this study provides a reasonable alternative strategy to manage open bone defects.

Abstract Objective We design a diagnostic test to evaluate the effectiveness and accuracy of A non-intrusive Wearable Diagnostic Assessment System versus SNAP-IV for auxiliary diagnosis of children with ADHD. Methods This study included 55 children aged 6–16 years who were clinically diagnosed with ADHD by DSM-5, and 55 healthy children (typically developing). Each subject completes 10 tasks on the WeDA system (Wearable Diagnostic Assessment System) and Parents of each subject complete the SNAP-IV scale. We will calculate the validity indexes, including sensitivity, specificity, Youden's index, likelihood ratio, and other indexes including predictive value, diagnostic odds ratio, diagnostic accuracy and area under the curve [AUC] to assess the effectiveness of the WeDA system as well as the SNAP-IV. Results The sensitivity (94.55% vs. 76.36%) and the specificity (98.18% vs. 80.36%) of the WeDA system were significantly higher than the SNAP-IV. The AUC of the WeDA system (0.964) was higher than the SNAP-IV (0.907). There is non-statistically significant difference between groups (p = 0.068), and both of them have high diagnostic accuracy. In addition, the diagnostic efficacy of the WeDA system was higher than that of SNAP-IV in terms of the Youden index, diagnostic accuracy, likelihood ratio, diagnostic odds ratio and predictive value. Conclusion The advantages of the WeDA system in terms of diagnostic objectivity, scientific design and ease of operation make it a promising system for widespread use in clinical practice.

Primary sclerosing cholangitis (PSC), autoimmune hepatitis (AIH), and ulcerative colitis (UC) are immune diseases of the digestive system. Some patients develop overlap syndrome, the presentation of two or more of the clinical, biochemical, immunological, and histological features of these conditions simultaneously or sequentially. The incidence of UC in PSC-AIH overlap syndrome is as high as 50%. In contrast, PSC-AIH overlap syndrome is rare in UC patients. However, because it has a low prevalence and has been studied in less detail, PSC is often misdiagnosed as primary biliary cholangitis (PBC) in its early stage. Herein, we reported a case of a 38-year-old male patient who presented to a clinician in 2014 with irregular bowel habits. A colonoscopy suggested UC. In 2016, the patient was found to have abnormal liver function and was diagnosed with PBC by pathology. He was treated with ursodeoxycholic acid (UDCA) but this had no effect on his liver function. Additional liver biopsies in 2018 indicated PBC-AIH overlap syndrome. The patient refused hormone therapy for personal reasons. Following UDCA monotherapy, his liver function remained abnormal. The patient was reexamined after repeated abnormal liver function tests and bowel symptoms. Systematic laboratory testing, imaging diagnosis, colonoscopy, liver biopsy, and various pathological examinations conducted in 2021 were used to diagnose the patient with PSC-AIH-UC overlap syndrome. He was treated with various drugs, including UDCA, methylprednisolone, mycophenolate mofetil, and mesalazine. His liver function improved significantly after treatment and follow-up is ongoing. Our case report highlights the need to raise awareness about rare and difficult-to-diagnose clinical disorders.

Objective To supervise the clinical blood use of 19 hospitals, covering a district of Shanghai, during two years, and discover the problems in the process of blood transfusion, so as to put forward suggestions for corrective methods in grades and promote continuous improvement of clinical transfusion management. Methods A total of 19 hospitals were supervised in terms of hardware facilities, management level, professional and technical level, and blood typing test on the site, according to the Administrative Blood Management Measures for Medical Institutions, Technical Specification for Clinical Transfusion and Shanghai Medical Quality Supervision Score Statistical Table.All data were analyzed. Results These hospitals can properly perform clinical blood transfusion, but there were obvious differences.Tertiary hospitals were relatively better, yet need to strengthen the management of medical documents.Secondary hospitals remained to be improved, mainly in insufficient construction of Blood Transfusion Department (blood bank), the lack of management and maintenance of key equipment and the lack of standardization in medical documents writing.However, flaws in the supervision were general in private hospitals (most of which were affiliated hospitals), so the management of clinical blood use should be further strengthened. Conclusion For secondary hospitals or above, routinized writing of medical documents and promoted construction of Blood Transfusion Department (blood bank) should be strengthened.For private hospitals, especially affiliated hospitals, the management of clinical blood use should be further improved, including the examination rules corresponding to the blood use process and strict access and exit mechanism, so as to improve the overall management level of clinical blood use and ensure the safety of clinical blood use.

This paper proposes a dynamic-decision-based real-time dispatch method to coordinate the economic objective with multiple types of security dispatch objectives while reducing constraint violations in the process of adjusting the system operation point to the optimum. In each decision moment, the following tasks are executed in turn: ① locally linearizing the system model at the current operation point with the online model identification by using measurements; ② narrowing down the gaps between unsatisfied security requirements and their security thresholds in order of priority; ③ minimizing the generation cost; ④ minimizing the security indicators within their security thresholds. Compared with the existing real-time dispatch strategies, the proposed method can adjust the deviations caused by unpredictable power flow fluctuations, avoid dispatch bias caused by model parameter errors, and reduce the constraint violations in the dispatch decision process. The effectiveness of the proposed method is verified with the IEEE 39-bus system.

Background The neuroimaging mechanism of major depressive episodes with mixed features (MMF) is not clear.Aims This study aimed to investigate the functional connectivity of the default mode network (DMN) subsystems among patients with MMF and patients with major depressive disorder without mixed features (MDDnoMF).Methods This study recruited 47 patients with MDDnoMF and 27 patients with MMF from Beijing Anding Hospital, Capital Medical University, between April 2021 and June 2022. Forty-five healthy controls (HCs) were recruited. All subjects underwent resting-state functional magnetic resonance imaging scanning and clinical assessments. Intranetwork and internetwork functional connectivity were computed in the DMN core subsystem, dorsal medial prefrontal cortex (dMPFC) subsystem and medial temporal lobe (MTL) subsystem. Analysis of covariance method was performed to compare the intranetwork and internetwork functional connectivity in the DMN subsystems among the MDDnoMF, MMF and HC groups.Results The functional connectivity within the DMN core (F=6.32, pFDR=0.008) and MTL subsystems (F=4.45, pFDR=0.021) showed significant differences among the MDDnoMF, MMF and HC groups. Compared with the HC group, the patients with MDDnoMF and MMF had increased functional connectivity within the DMN MTL subsystem, and the patients with MMF also showed increased functional connectivity within the DMN core subsystem. Meanwhile, compared with the MDDnoMF, the patients with MMF had increased functional connectivity within the DMN core subsystem (mean difference (MDDnoMF−MMF)=−0.08, SE=0.04, p=0.048). However, no significant differences were found within the DMN dMPFC subsystem and all the internetwork functional connectivity.Conclusions Our results indicated abnormal functional connectivity patterns of DMN subsystems in patients with MMF, findings potentially beneficial to deepen our understanding of MMF’s neural basis.

The main challenges of chronic wounds represented by diabetic wounds are that the infection is not easily controlled and the healing is difficult, mainly due to the high-glucose microenvironment, M1 macrophage aggregation, and persistent inflammation. Previous studies inspired by endogenous electric fields have demonstrated that conductive materials can promote cell proliferation, migration, etc., to promote wound healing. However, no study has been conducted on the effect of conductive materials on local immunity. To this end, this study designed a graphene oxide-based conductive hydrogel to repair infected diabetic wounds. Self-healing injectable conductive hydrogels were synthesized by dynamic Schiff-base reaction and electrostatic interactions between oxidized hyaluronic acid, N-carboxyethyl chitosan, graphene oxide, and polymyxin B. The study found that the hydrogel has good biocompatibility and antibacterial properties. In addition, in vivo experiments confirmed that the hydrogel could modulate macrophage polarization to improve the local inflammatory microenvironment, promote neovascularization, and significantly accelerate the healing of diabetic wounds. Most notably, graphene oxide-based conductive hydrogels can modulate local immunity in diabetic wounds to promote healing. This study provides new guidelines for expanding research on conductive materials and new directions for promoting healing in infected diabetic wounds.

Pancreatic neuroendocrine neoplasms (PNEN) are tumors that originate from neuroendocrine cells. Only about 1% patients are related to mutation of tuberous sclerosis complex gene. Here, we reported a rare case with involvement of multiple organs and space-occupying lesions. Initially, the patient was thought to have metastasis of a pancreatic tumor. However, the patient was diagnosed as pancreatic neuroendocrine tumors, liver perivascular epithelioid tumors, splenic hamartoma, and renal angiomyolipoma by pathological examination after surgery. We performed genetic mutation detection to identify that tuberous sclerosis complex 2 gene presented with a heterozygous variant. Tuberous sclerosis often presents with widespread tumors, but it is less common to present with pancreatic neuroendocrine tumors and liver perivascular tumors as highlighted in the case. So we analyzed the relationship between TSC gene mutations and related tumors. And we also reviewed the current molecular mechanisms and treatments for tuberous sclerosis complex.

Childhood-onset schizophrenia (COS) is an unusual severe neurodevelopmental disorder of unknown etiology. In this study, we aimed to survey the missense variants in new cases of COS and also identify possible pathology biomarkers for COS. We found one list of mutated genes such as TTN, MUC12, and MUC2, which are the candidates to be involved in the etiology of COS. Next, we used WGSNA to predict COS disease-related genes and identified differential DNA methylation among COS disease groups, COS dangerous groups, and normal groups and found eight methylation sites that can be used as the diagnostic biomarkers. A total of six key genes are obtained through the intersection analysis between weighted correlation network analysis (WGCNA) mode, methylation-related genes, and differentially expressed genes (DGenes). These genes may play important roles in the progression of COS and serve as the potential biomarkers for future diagnosis. Our results might help to design the molecule or gene-targeted drugs for COS.

Increasing penetration of distributed generators (DGs) brings new challenges to the control and protection of distribution networks. This article proposes a control and protection framework based on Multi-agent System (MAS), in which situation awareness of zone agents plays an important role. The main protection is designed to locate and isolate faults based on the peer-to-peer communication among the zone agents. Fault-tolerant mechanisms, including self-inspection and backup protection, are developed to cope with the malfunction of individual MAS and local communication failure. An automatic parallel restoration scheme that doesn't require complete grid information is proposed to restore the power supply. Comprehensive simulation studies are carried out on a 71-bus distribution network with DGs using DIgSILENT, and the results have shown the effectiveness of the proposed self-healing framework.

In this paper, two supervised learning models based solutions are proposed for Electricity Theft Detection (ETD). In the first solution, Adaptive Synthetic Edited Nearest Neighbor (ADASYNENN) is used to solve class imbalanced problem. For feature extraction, Locally Linear Embedding (LLE) technique is utilized. Moreover, Self-Attention Generative Adversarial Network (SAGAN) is used in combination with Convolutional Neural Network (CNN) for the classification of electricity consumers. In the second solution, Synthetic Minority Oversampling Technique Edited Nearest Neighbor (SMOTEENN) is proposed. Moreover, a novel classification model, named as ERNET, which is based on EfficientNet, Residual Network (ResNet) and Gated Recurrent Unit (GRU), is used to detect Non-Technical Losses (NTLs). We also used a Sparse Auto Encoder (SAE) for effective feature extraction that makes the classification more robust and easy. Furthermore, a robust Root Mean Square Propagation (RMSProp) optimizer is used to improve the learning rate of the model. To validate the proposed models, simulations are performed using different performance metrics, such as precision, recall, F1-score, Area Under the Curve (AUC), FPR and Root Mean Square Error (RMSE). All simulations are performed using State Grid Corporation of China (SGCC) dataset. The proposed models are compared with benchmark models, such as SAGAN, Wide and Deep Convolutional Neural Network (WDCNN), CNN and Long Short Term Memory (LSTM). The simulation results prove that the proposed models outperform the existing models in terms of the aforementioned performance metrics.

Automated water body detection from satellite imagery is a fundamental stage for urban hydrological studies. In recent years, various deep convolutional neural network (DCNN)-based methods have been proposed to segment remote sensing data collected by conventional RGB or multispectral imagery for such studies. However, how to effectively explore the wider spectrum bands of multispectral sensors to achieve significantly better performance compared to the use of only RGB bands has been left underexplored. In this article, we propose a novel DCNN model—multichannel water body detection network (MC-WBDN)—that incorporates three innovative components, i.e., a multichannel fusion module, an Enhanced Atrous Spatial Pyramid Pooling module, and Space-to-Depth/Depth-to-Space operations, to outperform state-of-the-art DCNN-based water body detection methods. Experimental results convincingly show that our MC-WBDN model achieves remarkable water body detection performance, is more robust to light and weather variations, and can better distinguish tiny water bodies compared to other DCNN models.

The increasingly common usage of single-cell sequencing in cancer research enables analysis of tumor development mechanisms from a wider range of perspectives. Metabolic disorders are closely associated with liver cancer development. In recent years, liver cancer has been evaluated from different perspectives and classified into different subtypes to improve targeted treatment strategies. Here, we performed an analysis of liver cancer from the perspective of energy metabolism based on single-cell sequencing data. Single-cell and bulk sequencing data of liver cancer patients were obtained from GEO and TCGA/ICGC databases, respectively. Using the Seurat R package and protocols such as consensus clustering analysis, genes associated with energy metabolism in liver cancer were identified and validated. An energy metabolism-related score (EM score) was established based on five identified genes. Finally, the sensitivity of patients in different scoring groups to different chemotherapeutic agents and immune checkpoint inhibitors was analyzed. Tumor cells from liver cancer patients were found to divide into nine clusters, with cluster 4 having the highest energy metabolism score. Based on the marker genes of this cluster and TCGA database data, the five most stable key genes (ADH4, AKR1B10, CEBPZOS, ENO1, and FOXN2) were identified as energy metabolism-related genes in liver cancer. In addition, drug sensitivity analysis showed that patients in the low EM score group were more sensitive to immune checkpoint inhibitors and chemotherapeutic agents AICAR, metformin, and methotrexate.

BackgroundTransforming growth factor-beta (TGF-β) signaling is essential in initialization and progression of hepatocellular carcinoma (HCC). Therefore, a treatment targeting TGF-β pathway may be a promising option for HCC control.MethodsFirst, publicly available RNA-seq datasets and clinical characteristics of 374 HCC patients in The Cancer Genome Atlas (TCGA) database were downloaded. Then, Cox regression analysis and LASSO analysis were used to construct a prognostic model for TGF-β family genes. The area under the curve (AUC) of the risk signature was calculated to evaluate the predictive power of the model. Cox regression analysis was applied to predict whether TGF-β1 can be an independent prognosis factor for HCC. Next, hazard ratio and survival analyses were performed to investigate the correlation between TGF-β1 expression and survival time. Furthermore, differential expression level of TGF-β1 in HCC tissues and cells was determined. In addition, Gene Set Enrichment Analysis (GSEA) identified the top significantly activated and inhibited signal pathways related to high expression of TGF-β1. Finally, the CIBERSORT tool was adopted to correlate the tumor-infiltrating immune cells (TICs) with TGF-β1 expression in HCC cohorts.ResultsCox regression analysis and LASSO analysis revealed that seven TGF-β family members (including TGF-β1) could be used as prognostic factors for HCC. Interestingly, TGF-β1 was demonstrated to be an independent prognostic factor of HCC. RT-qPCR and immunofluorescence staining confirmed the high expression of TGF-β1 in HCC cell lines and tissues, which is significantly related to pathological classifications, poor prognosis, and short survival time. Finally, GSEA and CIBERSORT analyses suggested that TGF-β1 may interact with various immune cells and influence the prognosis of HCC patients through Tregs and γδ T cells.ConclusionWe established a novel prognostic prediction method to predict the risk scores of TGF-β genes in HCC prognosis. TGF-β1 is highly expressed in HCC cell lines and tissues, correlates to poor prognosis, and thus can be used as a potential biomarker to predict HCC prognosis. We showed that TGF-β1 may play its roles in HCC prognosis by modulating the immune microenvironment of tumor cells. Our data may shed more light on better understanding the role of TGF-β1 in HCC prognosis.

ObjectiveTo investigate the incidence and risk factors of gallbladder stones and polyps in individuals undergoing physical examinations in Liaoning province, China.MethodsThis is a retrospective study of adults who underwent routine health examinations at Xikang Medical Center in Liaoning Province (Shenyang, Dandong, and Dalian) from 01/2016 to 12/2020. The routine health examination included anthropometry, blood tests, and liver ultrasound. Based on liver ultrasound results, patients were grouped into those with gallbladder stones, those with gallbladder polyps, those with both stones and polyps, and those with neither.ResultsOf the 284,129 included subjects, 6,537 (2.30%) were diagnosed with gallbladder stones, and 18,873 (6.64%) were diagnosed with gallbladder polyps. The overall prevalence in Liaoning province increased each year, peaking in 2020. The prevalence of gallbladder stones was higher among females than males (2.39% vs. 2.23%, respectively), while the prevalence of gallbladder polyps was higher among males. The gallbladder polyp group had higher BMI, FBG, SBP, DBP, TG, TC, LDL-C, HDL-C, AST, ALP, GGT, BUN, Scr, SUA. Except for HDL-C, all factors were also higher in the gallbladder stone group. Patients with fatty liver had a higher prevalence of gallbladder stones and polyps than participants without fatty liver.ConclusionThe prevalence of gallbladder stones and polyps in Liaoning varies by sex, economic status of the city of residence, BMI, and metabolic indicators.

IgG4-related disease is an immune-mediated chronic, systemic, and autoinflammatory disease that can affect various organs throughout the body. The most commonly affected areas are the pancreas and biliary system. Due to the diverse clinical manifestations of the disease, it affects widely distributed organs. Thus, it is often easy to misdiagnose or miss. The digestive tract is a rarely affected system, and most IgG4-related gastric diseases manifest as tumors detected by endoscopy. This article reports two special cases with IgG4-related disease involving atrophic gastritis and intestinal polyps to provide a more empirical and theoretical basis for clinical diagnosis and treatment.

Abstract Background This study investigated the characteristics of corneal higher-order aberrations (HOAs) of the anterior surface, posterior surface, and total cornea in adolescents with mild to moderate myopia. Methods A total of 183 patients with myopia (183 eyes) aged 8 to 18 years were enrolled in this study. The axial length (AL) of the eyes was measured by an IOL-Master, and corneal curvatures (K-values) and HOAs were measured by a Pentacam anterior segment diagnostic analyzer. Results Results of this study showed that the anterior, posterior and total corneal horizontal coma Z3 1 were − 0.1249 ± 0.105 μm, 0.0009 ± 0.001 μm, and − 0.1331 ± 0.116 μm, respectively; the anterior, posterior and total corneal vertical coma Z3 − 1 were − 0.0212 ± 0.164 μm, 0.0003 ± 0.043 μm, and − 0.0216 ± 0.168 μm, respectively; and spherical aberration (SA) Z4 0 values were 0.2244 ± 0.091 μm, 0.1437 ± 0.029 um, and 0.1889 ± 0.090 μm, respectively. Total corneal Z3 1 was statistically correlated with posterior corneal astigmatism (K2b − K1b) (p = 0.038). Total corneal Z3 − 1 was correlated with anterior corneal astigmatism (K2f − K1f) (p = 0.027). Anterior, posterior, and total corneal Z4 0 were correlated with anterior and posterior corneal curvature (K1f, K2f, K1b, K2b) (p = 0.001). Posterior corneal Z4 0b was also significantly correlated with AL. Conclusions In adolescents with mild to moderate myopia, the posterior corneal surface shape may play a compensatory role in the balance of corneal aberrations, and the posterior corneal SA tended to become less negative as the AL increased. The corneal coma may also play a compensatory role in posterior corneal surface astigmatism, which was valuable for the treatment for improving visual quality. This conclusion still needs to be verified.

Stormwater runoff is identified as a major source of pollution in water bodies, and to limit the impact of these pollutants on groundwater quality, permeable asphalt pavement systems (PAPS) have been built worldwide. But so far, few have considered zeolite or regulated zeolite as a post-treatment in reservoirs in PAPS. This study aimed at investigating the efficiencies of modified zeolites in removing NH4+-N and TP from stormwater runoff and providing a novel insight into the research on the reuse of stormwater runoff by PAPS. The effect of PAPS with a zeolite-regulated reservoir on removing nutrient in stormwater was explored by artificial rainfall experiments and temporary storage experiments. Results showed that the removal rate of NH4+-N and TP in PAPS with a regulated-zeolite reservoir increased by 23.7% and 37.2%, respectively, during simulated rainfall events when compared to those without a regulated-zeolite reservoir. TP was mainly removed by the form of phosphorus precipitation such as Zr(H2PO4)2. Ion exchange and adsorption during the temporary storage period were considered as the main approaches for removal of NH4+-N and TP. This study can help develop an optimal strategy for the operation of PAPS in treating stormwater runoff from urban roads.

In this study, optimal reactive power regulation in distribution networks is achieved through the use of distributed reactive power regulators that can 1) perceive their own voltage magnitude and the P/Q flows in the connected branches, 2) communicate with nearby regulators, and 3) adjust the reactive power injections into the grid to minimize system power losses and maintain the bus voltages of nearby loads. Compared with many existing distributed reactive power regulation strategies, the proposed method can estimate and maintain the bus voltage of unmeasurable load buses within the limitations. Furthermore, this method releases the hardly achieved bus voltage angle requirement, which makes it practical for real-world.

Reliable online transient stability assessment (TSA) is fundamentally required for power system operation security. Compared with time-costly classical digital simulation methods, data-driven deep learning (DL) methods provide a promising technique to build a TSA model. However, general DL models show poor adaptability to the variation of power system topology. In this paper, we propose a new graph-based framework, which is termed as recurrent graph convolutional network based multi-task TSA (RGCN-MT-TSA). Both the graph convolutional network (GCN) and the long short-term memory (LSTM) unit are aggregated to form the recurrent graph convolutional network (RGCN), where the GCN explicitly integrate the bus (node) states with the topological characteristics while the LSTM subsequently captures the temporal features. We also propose a multi-task learning (MTL) scheme, which provides joint training of stability classification (Task-1) as well as critical generator identification (Task-2) in the framework, and accelerate the process with parallel computing. Test results on IEEE 39 Bus system and IEEE 300 Bus system indicate the superiority of the proposed scheme over existing models, as well as its robustness under various scenarios.

The global pandemic of the coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), places a heavy burden on global public health. Four SARS-CoV-2 variants of concern including B.1.1.7, B.1.351, B.1.617.2, and P.1, and two variants of interest including C.37 and B.1.621 have been reported to have potential immune escape, and one or more mutations endow them with worrisome epidemiologic, immunologic, or pathogenic characteristics. This review introduces the latest research progress on SARS-CoV-2 variants of interest and concern, key mutation sites, and their effects on virus infectivity, mortality, and immune escape. Moreover, we compared the effects of various clinical SARS-CoV-2 vaccines and convalescent sera on epidemic variants, and evaluated the neutralizing capability of several antibodies on epidemic variants. In the end, SARS-CoV-2 evolution strategies in different transmission stages, the impact of different vaccination strategies on SARS-CoV-2 immune escape, antibody therapy strategies and COVID-19 epidemic control prospects are discussed. This review will provide a systematic and comprehensive understanding of the secret of SARS-CoV-2 variants of interest/concern and immune escape.

Hepatocellular carcinoma (HCC) is a common cancer in the world, and its incidence is increasing yearly. Hepatitis B virus (HBV) infection and hepatitis C virus (HCV) infection are important causes of HCC. Liver cirrhosis, age, sex, smoking and drinking, and metabolic risk factors will increase the risk of cancer in HBV/HCV patients. And viral load, APRI, FIB-4, and liver stiffness can all predict the risk of HCC in patients with viral infection. In addition, effective prevention strategies are essential in reducing the risk of HCC. The prevention of HCC involves mainly tertiary prevention strategies, while the primary prevention is based on standardized vaccine injections to prevent the occurrence of HBV/HCV. Eliminating the route of transmission and vaccination will lead to a decrease in the incidence of HCC. Secondary prevention involves effective antiviral treatment of HBV/HCV to prevent the disease from progressing to HCC, and tertiary prevention is actively treating HCC to prevent its recurrence.

Background: Many case–control studies have investigated the association between dietary cholesterol and gastric cancer, yielding inconsistent findings. We carried out a systematic review and meta-analysis of observational studies to assess the relationship between dietary cholesterol intake and gastric cancer among adults.Methods: PubMed, Scopus, and Google Scholar were systematically searched to identify articles that evaluated the association of dietary cholesterol with gastric cancer up to May 2021. Pooled odds ratio (ORs) and 95% confidence intervals (CIs) were computed using random-effects models. Dose–response analysis was used to explore the shape and strength of the association.Results: Fourteen case–control studies with 6,490 gastric cancer patients and 17,793 controls met our inclusion criteria. In the meta-analysis of the highest vs. the lowest dietary cholesterol categories, a significantly higher (~35%) risk of gastric cancer was observed in association with high cholesterol consumption (pooled OR: 1.35, 95% CI: 1.29–1.62, I2 = 68%; 95%CI: 45–81%). Subgroup analysis also showed this positive relationship in population-based case–control studies, those conducted on non-US countries, those with a higher number of cases and high-quality studies, those that collected dietary data via interviews, studies not adjusted for Helicobacter pylori infection, and studies where the body mass index was controlled. Besides, a non-linear dose–response association was also identified (P = 0.03).Conclusion: This study demonstrated that dietary cholesterol intake could significantly augment the risk of gastric cancer in case–control studies. Prospective cohort studies with large sample sizes and long durations of follow-up are required to verify our results.

Operational optimization is essential in modern industry and unsuitable operations will deteriorate the performance of industrial processes. Since measuring error and multiple working conditions are inevitable in practice, it is necessary to reduce their negative impacts on operational optimization under the case-based reasoning (CBR) framework. In this paper, a local density-based abnormal case removal method is proposed to remove the abnormal cases in a case retrieval step, so as to prevent performance deterioration in industrial operational optimization. More specifically, the reasons as to why classic CBR would retrieve abnormal cases are analyzed from the perspective of case retrieval in industry. Then, a local density-based abnormal case removal algorithm is designed based on the Local Outlier Factor (LOF), and properly integrated into the traditional case retrieval step. Finally, the effectiveness and the superiority of the local density-based abnormal case removal method was tested by a numerical simulation and an industrial case study of the cut-made process of cigarette production. The results show that the proposed method improved the operational optimization performance of an industrial cut-made process by 23.5% compared with classic CBR, and by 13.3% compared with case-based fuzzy reasoning.

Based on the separation voltage type of cascaded H bridge-modular multilevel converters (CHB-MMC) and current predictive model control (CPMC) technology, a novel flexible fault-current limiter (NFFCL) is firstly proposed for restraining the negative impact of the distribution network's disturbance in this paper. When a disturbance occurs, the inner-loop CPMC of the multilevel converters establish the value function to offer the specific current, thus increasing the voltage deviation at both ends of the series capacitor or generating reverse harmonic compensation voltage. In that case, three single-phase MNFFCLs can be regarded as variable voltage sources to eliminate the negative effects of faults or harmonics. Owing to the multi-capacitance series structure, the maximum voltage drops of the single capacitance can be predetermined by the number of capacitors. And with the low voltage drop of single capacitance, the output current of the CHB-MMC can also be controlled within an acceptable range. Through the simulation results, the disturbance's negative impact on the non-fault area can be eliminated almost 100%.

Background/Aims: This paper aims to explore the effects of pyruvate kinase (PK) M2 gene silencing on the proliferation and apoptosis of colorectal cancer (CRC) LS-147T and SW620 cells. Methods: CRC LS-147T and SW620 cells highly expressing PKM2 were randomly selected by quantitative real-time polymerase chain reaction (qRT-PCR) and then assigned into the blank (no transfection), PKM2-shRNA (transfection with shRNA) and empty plasmid (transfection with empty plasmid) groups. Immunofluorescence was applied to detect PKM2 protein expression. qRT-PCR and Western blotting were conducted to assess mRNA and protein expression of PKM2, p53 and p21. The cell counting kit-8 (CCK-8) assay was used to assess cell proliferation. Flow cytometry was used to assess the cell cycle and apoptosis rate, and a senescence-associated β-galactosidase staining kit was used to assess cell senescence. Results: PKM2 exhibited high mRNA expression among CRC LS-147T and SW620 cells with remarkable protein expression noted in the cytoplasm and nucleus. The PKM2-shRNA group exhibited reduced PKM2 mRNA and protein expression, whereas p53 and p21 expression was increased compared with the blank and empty plasmid groups. Cell proliferation in PKM2-shRNA cells decreased significantly compared with the blank group and empty plasmid groups. The PKM2-shRNA group exhibited more cells in the G1 phase and fewer cells in the G2/M phase compared with the blank and empty plasmid groups. In addition, the PKM2-shRNA group exhibited significantly increased apoptosis rates and β-galactosidase activity compared with the blank and empty plasmid groups. Conclusion: Our study demonstrates that PKM2 gene silencing suppresses proliferation and promotes apoptosis in LS-147T and SW620 cells.

Combined with finite element numerical simulation analysis, the hot-spin forming technology of cylindrical AZ80 magnesium alloy parts was studied in the paper. The multipass hot-spin forming of magnesium alloy shell parts was simulated by the ABAQUS software to analyze the stress and strain distribution and change during spinning for the preliminary test process parameters in the magnesium alloy spinning test. Then, the process parameters were optimized during the hot spinning test, especially the matching relationship between temperature parameter and thinning rate parameter, and the hot spinning magnesium alloy shell parts with the expected technical specifications were finished.

The paper studies the complicated problem in the spinning process of the shell with longitudinal and latitudinal inner ribs. The finite element software ABAQUS is used to establish the finite element model of the cylindrical shell with the longitudinal and latitudinal inner ribs. The numerical simulation of the spinning process is carried out. The stress distribution and strain distribution of the inner and outer surfaces during the spin-forming process are determined, and the orthogonal test method is used to determine the optimization process test parameters. The influence of the main process parameters on the wall thickness difference of the inner rib shell is obtained by the range analysis: wall thickness reduction rate > rotary wheel feed speed > rotor working angle (arranging according to their influences). And then the corresponding process parameters recommended by the spinning test are given. The measurement problem of inner ribs is solved by building of the robot shape measurement system which helps detect the three-dimensional shape of the inner ribs, and the precision of the spun sample was detected by the point cloud deviation comparison.