Actuality and underlying mechanisms of systemic immuneinflammation index and geriatric nutritional risk index prognostic value in hepatocellular carcinoma

This editorial contains comments on the article“Correlation between preoperative systemic immune inflammation index,nutritional risk index,and prognosis of radical resection of liver cancer”in a recent issue of the World Journal of Gastrointestinal Surgery.It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immuneinflammation index(SII)and geriatric nutritional risk index(GNRI)prediction features valuable.There are few publications on both SII and GNRI together in hepatocellular carcinoma(HCC)and patient prognosis after radical surgery.Neutrophils release cytokines,chemokines,and enzymes,degrade extracellular matrix,reduce cell adhesion,and create conditions for tumor cell invasion.Neutrophils promote the adhesion of tumor cells to endothelial cells,through physical anchoring.That results in the migration of tumor cells.Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs.Platelets can form a protective film on the surface of tumor cells.This allows avoiding blood flow damage as well as immune system attack.It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness.High SII is also associated with macro-and microvascular invasion and increased numbers of circulating tumor cells.A high GNRI was associated with significantly better progression-free and overall survival.HCC patients are a very special population that requires increased attention.SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings.The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features.Those features provide tumor nutrition,growth,and distribution throughout the body,such as vascular invasion.On the other hand,they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings.The article is of considerable interest.It would be helpful to continue the study follow-up to 2 years and longer.External validation of the data is needed.

Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer

BACKGROUND Radical surgery is the most commonly used treatment for hepatocellular carcinoma(HCC).However,the surgical effect remains not ideal,and prognostic evaluation is insufficient.Furthermore,clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.AIM To explore correlations between the systemic immune inflammatory index(SII)and geriatric nutritional risk index(GNRI)and HCC operation prognosis.METHODS This retrospective study included and collected follow up data from 100 HCC.Kaplan–Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival.SII and GNRI were calculated as follows:SII=neutrophil count×platelet count/lymphocyte count;GNRI=[1.489×albumin(g/L)+41.7×actual weight/ideal weight].We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic(ROC)curves,and the relationships between the SII,GNRI,and survival rate using Kaplan–Meier survival curves.Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.RESULTS After 1 year of follow-up,24 patients died and 76 survived.The area under the curve(AUC),sensitivity,specificity,and the optimal cutoff value of SII were 0.728(95%confidence interval:0.600-0.856),79.2%,63.2%,and 309.14,respectively.According to ROC curve analysis results for predicting postoperative death in HCC patients,the AUC of SII and GNRI combination was higher than that of SII or GNRI alone,and SII was higher than that of GNRI(P<0.05).The proportion of advanced differentiated tumors,tumor maximum diameter(5–10 cm,>10 cm),lymph node metastasis,and TNM stage III-IV in patients with SII>309.14 was higher than that in patients with SII≤309.14(P<0.05).The proportion of patients aged>70 years was higher in patients with GNRI≤98 than that in patients with GNRI>98(P<0.05).The 1-year survival rate of the SII>309.14 group(compared with the SII≤309.14 group)and GNRI≤98 group(compared with the GNRI>98 group)was lower(P<0.05).CONCLUSION The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.

Systematic Risk Analysis of Listed Financial Institutions from the Perspective of Complex Network

Based on the complex network theory,this paper studies the systemic financial risks in China’s financial market.According to the industry classification of the China Securities Regulatory Commission in 2012,the daily closing prices of 45 listed financial institutions are collected and the daily return rates of each financial institution are measured according to the logarithmic return rate calculation formula.In this paper,the risk spillover value ΔCoVaR is used to measure the contribution degree of each financial institution to systemic risk.Finally,the relationship between the risk spillover valueΔCoVaR and the node topology index of the risk transmission network is investigated by using a regression model,and some policy suggestions are put forward based on the regression results.

Frequency of Cardiovascular Risk Factors in Systemic Lupus Erythematosus: A Case-Control Study in a Department of Internal Medicine in Sub-Saharan Africa

Background: The morbidity and mortality of systemic lupus erythematosus are largely due to accelerated atherosclerosis. This is partly related to the high prevalence of traditional cardiovascular risk factors. The aim of our study was to determine the frequency of these factors in lupus patients compared to a control population in a department of internal medicine. Methods: We realized a case-control study in patients with systemic lupus erythematosus according to ACR criteria in 1997. Patients were matched by age and gender with controls subjects without autoimmune disease. We studied the frequency of traditional cardiovascular risk factors in both populations. The study was done in the department of internal medicine of Aristide Le Dantec teaching Hospital, in Senegal, during the period from August 2017 to December 2018. The statistical analysis was performed with SPSS 23.0 software and the level of significance was retained for a p-value Results: We recruited 100 subjects including 50 patients and 50 controls. The mean age was 33.5 ± 11.3 years in cases and 33.3 ± 11.3 years in controls. Dyslipidemia was significantly associated with systemic lupus erythematosus (p = 0.009). Levels of triglycerides (p Conclusion: Traditional cardiovascular risk factors including dyslipidemia and hyperuricemia were more common in patients. Similarly, renal failure was associated with lupus.

A Review of Systemic Lupus Erythematosus (SLE): Symptoms, Risk Factors, Treatment, and Health Related Quality of Life Issues

In this paper, we present a thorough review of one of the most life-threatening autoimmune diseases, Systemic lupus erythematosus (lupus). Symptoms, risk factors, including genetic and epidemiological factors are discussed. Treatment, life expectancies, and Health Related Quality of Life of patients with SLE will be discussed as well. Special attention will be given to Lupus Nephritis.

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

Systemic Risk of Conventional and Islamic Banks: Comparison with Graphical Network Models

The main aim of this paper is to compare the stability, in terms of systemic risk, of conventional and Islamic banking systems. To this aim, we propose correlation network models for stock market returns based on graphical Gaussian distributions, which allows us to capture the contagion effects that move along countries. We also consider Bayesian graphical models, to account for model uncertainty in the measurement of financial systems interconnectedness. Our proposed model is applied to the Middle East and North Africa (MENA) region banking sector, characterized by the presence of both conventional and Islamic banks, for the period from 2007 to the beginning of 2014. Our empirical findings show that there are differences in the systemic risk and stability of the two banking systems during crisis times. In addition, the differences are subject to country specific effects that are amplified during crisis period.

A global perspective on macroprudential policy interaction with systemic risk,real economic activity,and monetary intervention

The study empirically assesses how macroprudential policy interacts with systemic risk,industrial production,and monetary intervention on a global level from January 2006 to December 2018.We adopt the aggregate proxies of these variables,capturing their global effects,and use a novel econometric technique,namely,smooth local projections.The study finds that global macroprudential policy leads the monetary policy,exhibiting a countercyclical pattern concerning industrial production.The latter has an inverse bidirectional linkage with systemic risk.Thus,an ex-ante tight macroprudential policy can indirectly mitigate global systemic risk through its pro-growth effect on industrial production,although no convincing evidence exists for the direct impact of a macroprudential intervention on systemic risk.The study results endure several extensions and a robustness check,which builds on alternative measures of global systemic stress and real economic activity,thereby legitimizing the increased importance attached to the macroprudential policy since the 2007–2009 global financial crisis.

Performance of Cardiovascular Risk Equations versus Vascular Ultrasound in Systemic Lupus Erythematosus in a Black African Population

Introduction: Cardiovascular risk is increased in systemic lupus erythematosus. Cardiovascular events are the first cause of death in lupus after five years duration. Prevention of cardiovascular events needs a good evaluation of the risk. In this work, we tried to evaluate the performance of conventional and adjusted forms of cardiovascular risk equations to predict high risk in lupus patients, in comparison with carotid ultrasound. Method: We realized a cross-sectional study during the period from 24 August 2017 to 22 November 2018. Consenting patient meeting the 1997 American college of Rheumatology criteria of systemic lupus erythematosus were recruited. The clinical characteristics and the treatment data were informed. Traditional cardiovascular risk factors were also investigated, and the assessment of cardiovascular risk was performed by Framingham and SCORE equations and their modified forms (multiplication by a factor of 1.5). Carotid ultrasound was used to detect atherosclerosis by measuring intima media thickness and searching for carotid plaques. In last, we compared cardiovascular risk levels by equations to results of carotid ultrasound. Statistical analysis and data collection were performed using SPSS 23.0 software. Results: Forty-nine patients with a sex ratio of 0.13 and a mean age of 33.5 (±11.3) years were enrolled. More than half of patients had dyslipidemia. More than 80% of the population were at low cardiovascular risk according to the equations. However, 16% of cases had carotid atherosclerosis. Between 50% and 100% of patients having atherosclerosis were considered at low or moderate risk by equations. The best sensitivity to predict cardiovascular risk was given by modified Framingham (50%). Conclusion: In our study, conventional and modified risk equations had a bad performance to predict cardiovascular risk in systemic lupus erythematosus.

Research on Systemic Risk Spillover Effect of Chinese Listed Commercial Banks——Based on Quantile CoVaR Model

The banking industry plays an important role in China's financial market, and the systemic risk of the banking industry has astrong risk spillover effect. This paper measures the systemic risk spillover effect of Chinese listed commercial banks byconstructing the quantile CoVaR model. The study concluded that when an extreme risk event occurs, the overall risk spillovereffect of a single bank on the banking system is greater than the risk spillover effect of the banking system on a single bank, thevalue of VaR is smaller than the actual risk value when measuring the risk value of commercial banks and the CoVaR model ismore accurate in measuring systemic risk.

Systemic Risk in Chinese Commodity Futures Markets: A Graph Theory Analysis

This paper sets out to explore the contagion of systemic risk in Chinese commodity futures market based on specific tools of the graph-theory.More precisely,we use minimum spanning trees as a way to identify the most probable path for the transmission of prices shocks.In the sample of 30 kinds of Chinese commodity futures,we construct the MST and obtain the most probable and the shortest path for the transmission of a prices shock.We find that metal futures play an important role in commodity futures market and copper stands at the heart of the system(The core position of the system is very important for the transmission of system risk).And our results also reveal that when the risk occurs,the MST structure becomes smaller,leading to the most effective transmission path of risk becomes shorter.

Engineering complex systems applied to risk management in the mining industry

Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can be found in human behaviour and uncertainty. This complexity, structural or dynamic can be organizational, technological, or nested in their relationship. ISO international standard 31000:2009 definition of risk management ‘‘coordinated activities to direct and control an organization with regard to risk", when applied to economic sectors, industry, services, project, or activity, it requires the use of models or theories as guidelines. Therefore, as its basic elements comprehend human behaviour and/or uncertainty, risk management to be effective and adapted as much as possible to reality, must be operational within complex systems, as already demonstrated in different R&D environments. Risk management faces demanding challenges when approaching specific and endogenous needs, such as the mining sector. This paper presents a multivariable function analysis methodology approach based on complex system modelling and through real data corresponding to a risk management tool in the mining sector.

Personal predictive model based on systemic inflammation markers for estimation of postoperative pancreatic fistula following pancreaticoduodenectomy

BACKGROUND Postoperative pancreatic fistula(PF)is a serious life-threatening complication after pancreaticoduodenectomy(PD).Our research aimed to develop a machine learning(ML)-aided model for PF risk stratification.AIM To develop an ML-aided model for PF risk stratification.METHODS We retrospectively collected 618 patients who underwent PD from two tertiary medical centers between January 2012 and August 2021.We used an ML algorithm to build predictive models,and subject prediction index,that is,decision curve analysis,area under operating characteristic curve(AUC)and clinical impact curve to assess the predictive efficiency of each model.RESULTS A total of 29 variables were used to build the ML predictive model.Among them,the best predictive model was random forest classifier(RFC),the AUC was[0.897,95%confidence interval(CI):0.370–1.424],while the AUC of the artificial neural network,eXtreme gradient boosting,support vector machine,and decision tree were between 0.726(95%CI:0.191–1.261)and 0.882(95%CI:0.321–1.443).CONCLUSION Fluctuating serological inflammatory markers and prognostic nutritional index can be used to predict postoperative PF.

Risk Assessment Framework and Algorithm of Power Systems Based on the Partitioned Multi-objective Risk Method

针对平均风险指标无法区分高损失-低概率事件及低损失-高概率事件的缺点,提出了电力系统的分割多目标风险分析框架。该框架将电力系统的风险状态细分为低损失、中等损失和高损失3个风险范围,并提出3个损失范围条件风险函数和条件风险概率的概念。采用经典的容量停运表模型,建立了这些条件期望指标的计算方法。对IEEE-RTS及TH-RTS2000系统进行了分割多目标风险评估,研究不同负荷水平下系统风险在3个损失范围的分布及转移情况,并分析损失分割点对系统风险的影响。通过分割多目标风险分析,风险分析者和决策者可以权衡系统的平均风险以及高、中、低损失范围的条件期望风险,从而对系统的风险状况有一个全面和深入的了解。

Risk identification and regulatory system design for the carbon market

Currently,the global carbon trading systems are fragmented and belong to different governments or are under the jurisdiction of different regions,resulting in a series of new problems,such as how to link dispersed trading systems,how to compare the emission reduction of various markets and other issues.Since the development of the international carbon market is relatively immature with uncertain life expectancy and volatility during its short history,and there is a lack of quantitative data on the long-term record,the market could provide few risk management tools.Meanwhile,with the launches of China's regional carbon trading pilots in seven provinces since 2013 and combined with the national voluntary emission trading system,carbon trading will become an important mechanism for China in achieving its emission reduction target.In the first stage,the carbon finance market is at least faced with mechanism design risks,market supply risks and compliance risks.Therefore,to secure the development of the carbon market and for public interest,relevant government departments of China should identify the risks facing the market and should make the basic principles and goals,such as ensuring effective trading and pricing mechanisms to avoid fraud and price manipulation,and balancing transparency and confidentiality of information.Consequently,the governments should develop a comprehensive carbon finance regulatory system covering regulatory legislation,regulatory institutions and their authorities,regulatory scope as well as regulatory objects.

Risk Assessment Index System of Natural Gas Industrial Chain in China

This paper establishes a risk assessment index system for the natural gas industrial chain. China＇s natural gas industrial chain is entering a stage of rapid growth. In order to guarantee healthy development of the natural gas industrial chain, it is urgent to establish a risk alert system, which is based on a risk assessment index system. First of all, the risks of the natural gas industrial chain are defined in the paper; then the risk factors are analyzed according to the present status of the natural gas industrial chain, and five categories of risk factors are summarized： resource risk, transport risk, marketing risk, risk of unbalanced chain links, and environment risk. The paper presents the principles of the risk assessment index system. The natural gas industrial chain risk assessment index system is established with four levels and forty-six risk indices.

Novel risk scoring system for prediction of pancreatic fistula after pancreaticoduodenectomy

BACKGROUND The available prediction models for clinically relevant postoperative pancreatic fistula (CR-POPF) do not incorporate both preoperative and intraoperative variables. AIM To construct a new risk scoring system for CR-POPF that includes both preoperative and intraoperative factors. METHODS This was a retrospective study of patients who underwent pancreaticoduodenectomy (PD) or pylorus-preserving PD (PPPD) between January 2011 and December 2016 at the First Affiliated Hospital of Soochow University. Patients were divided into a study (01/2011 to 12/2014) or validation (01/2015 to 12/2016) group according to the time of admission. POPF severity was classified into three grades: Biochemical leak (grade A) and CR-POPF (grades B and C). Logistic regression was used to create a predictive scoring system. RESULTS Preoperative serum albumin ≥ 35 g/L [P = 0.032, odds ratio (OR)= 0.92, 95% confidence interval (CI): 0.85-0.99], hard pancreatic texture (P = 0.004, OR = 0.25, 95%CI: 0.10-0.64), pancreatic duct diameter ≥ 3 mm (P = 0.029, OR = 0.50, 95%CI: 0.27-0.93), and intraoperative blood loss ≥ 500 mL (P = 0.006, OR = 1.002, 95%CI:1.001-1.003) were independently associated with CR-POPF. We established a 10-point risk scoring system to predict CR-POPF. The area under the curve was 0.821 (95%CI: 0.736-0.905) and the cut-off value was 3.5. Including drain amylase levels improved the predictive power of the model. CONCLUSION This study established a 10-point scoring system to predict CR-POPF after PD/PPPD using preoperative and intraoperative parameters. Ultimately, this system could be used to distinguish between high- and low-risk populations in order to facilitate timely interventions after PD.

AN EXPERT SYSTEM ON ASSESSING ROCKBURST RISKS FOR SOUTH AFRICAN DEEP GOLD MINES

Expert systems are methods that can cope with rock engineer’s expertise effectively.An expert system on assessing rockburst risks for South African deep gold mines is described.Expertise was represented by rules, frames and mathematical models integratively. About 950 rules was built in the knowledge base, which can be learned by the suggested learning algorithm. A new uncertain reasoning algorithm was proposed. According to the features such as depth below surface, energy release rate (ERR), excess shear stress (ESS), geological structure, face angle with structure, distance from structure, extent of mining, mining type, width of bracket pillar, stope width, local support, regional support and gully support, rockburst risk is assessed either "Low", "Moderate", "High" or "Severe". A computer program system was developed by Turbo Prolog. The results of testing cases show its applicability of the system.