Causal association between 25-hydroxyvitamin D status and cataract development:A two-sample Mendelian randomization study

BACKGROUND Vitamin deficiencies are linked to various eye diseases,and the influence of vitamin D on cataract formation has been noted in prior research.However,detailed investigations into the causal relationship between 25-(OH)D status and cataract development remain scarce.AIM To explore a possible causal link between cataracts and vitamin D.METHODS In this study,we explored the causal link between 25-(OH)D levels and cataract development using Mendelian randomization.Our analytical approach included inverse-variance weighting(IVW),MR-Egger,weighted median,simple mode,and weighted mode methods.The primary analyses utilized IVW with random effects,supplemented by sensitivity and heterogeneity tests using both IVW and MR-Egger.MR-Egger was also applied for pleiotropy testing.Additionally,a leave-one-out analysis helped identify potentially impactful single-nucleotide polymorphisms.RESULTS The analysis revealed a positive association between 25-(OH)D levels and the risk of developing cataracts(OR=1.11,95%CI:1.00-1.22;P=0.032).The heterogeneity test revealed that our IVW analysis exhibited minimal heterogeneity(P>0.05),and the pleiotropy test findings confirmed the absence of pleiotropy within our IVW analysis(P>0.05).Furthermore,a search of the human genotype-phenotype association database failed to identify any potentially relevant risk-factor single nucleotide polymorphisms.CONCLUSION There is a potential causal link between 25-(OH)D levels and the development of cataracts,suggesting that greater 25-(OH)D levels may be a contributing risk factor for cataract formation.Further experimental research is required to confirm these findings.

Learning Dynamic Causal Relationships Among Sugar Prices

In this paper, we are interested in exploring the dynamic causal relationships among two sets of three variables in different quarters. One set is futures sugar closing price in Zhengzhou futures exchange market （ZC）, spot sugar price in Zhengzhou （ZS） and futures sugar closing price in New York futures exchange market（NC） and the other includes futures sugar opening price in Zhengzhou （ZO）, ZS and NC. For each quarter, we first use Bayesian model selection to obtain the optimal causal graph with the highest BD scores and then use Bayesian model averaging approach to explore the causal relationship between every two variables. From the real data analysis, the two conclusions almost coincide, which shows that the two methods are practical.

Exploring the Impact of Alcohol Consumption and Smoking on Primary Open Angle Glaucoma: A Mendelian Randomization Study

Objective: Utilizing Mendelian Randomization, this study employs Single Nucleotide Polymorphisms (SNPs) as instrumental variables to explore the causal relationships between bibulosity, smoking, and Primary Open Angle Glaucoma (POAG). Methods: GWAS data for bibulosity, smoking, and POAG were obtained from the Social Science Genetic Association Consortium website and the IEU OpenGWAS Project website, respectively. Using a P-value threshold of −8, a linkage disequilibrium coefficient (r2) of 0.001, and a linkage disequilibrium region width of 10,000 kb, the data were aggregated, resulting in 6 SNPs for bibulosity and 253 SNPs for smoking. Three regression models, MR-Egger, Weighted Median Estimator (WME), and Random-Effects Inverse-Variance Weighted (IVW) were applied to analyze the causal impact of bibulosity and smoking on POAG. Results: The GWAS data for alcohol consumption and smoking were derived from European populations, while the GWAS data for Primary Open-Angle Glaucoma (POAG) were sourced from East Asian populations, with no gender restrictions. Analysis using three different regression models revealed that neither excessive alcohol consumption nor smoking significantly increased the risk of developing POAG. Specifically, the odds ratios with 95% confidence intervals for the alcohol consumption group were 0.854 (0.597 - 1.221) in MR-Egger regression, 0.922 (0.691 - 1.231) in WME regression, and 0.944 (0.711 - 1.252) in IVW regression. For the smoking group, the odds ratios were 1.146 (0.546 - 2.406) in MR-Egger regression, 0.850 (0.653 - 1.111) in WME regression, and 0.939 (0.780 - 1.131) in IVW regression. Given the significant heterogeneity in the SNPs associated with smoking, the focus was primarily on the results from the IVW regression model. Conclusion: Alcohol consumption and smoking are not significant risk factors for the development of POAG.

Revisiting the Relationship Between Urbanization and Economic Development in China Since the Reform and Opening-up

The relationship between urbanization and economic development has become a hot topic in the scientific community due to its great practical significance,and economic and social value.However,this relationship continues to change dynamically.In the new stage of urbanization,it is urgent to reveal the causal relationship quantitatively and diagnose the future direction systematically.Based on this,this paper calculates the contribution rate of China’s urbanization to economic development from 1978 to 2019 and uses the panel data cointegration test method to explore the causal relationship between urbanization and economic development in China.The study has three principal results.First,the contribution rate of urbanization to economic growth has maintained the overall growth trend from1978 to 2019,but the growth rate of urbanization’s contribution to economic growth has been relatively low since 2012.It is an important reason that the real estate sector has moved into a new stage of transformation.Second,the cointegration test shows that economic development is a significant factor in advancing urbanization and the urbanization is the product of economic development.Urbanization has a positive feedback effect on economic development,but this effect does not pass the 5%significance level test.The impulse response function shows that the impact of urbanization on economic development is relatively small and stable,indicating that it is limited that the boost of economic development by land-centered urbanization.Third,China’s urbanization and economic development have both shown rapid growth for some time,but their relationship is still the low level of coordination,which has also led to a downward trend in the contribution of new-type,people-oriented urbanization to economic growth in recent years.In the future,China’s urbanization and economy need to maintain relatively medium-low speed growth in the medium-long term,and we should boost the coordinated development of urbanization and economy from low level to high level.

Fusobacterium nucleatum——The Cause of Human Colorectal Cancer

Objective: Accumulating evidence indicates that the gut microbiome has an increasingly important role in human disease and health. Fusobacterium nucleatum has been identified in several studies as the leading gut bacterium which is present in colorectal cancer (CRC). Still it is not clear if Fusobacterium plays a causal role. Methods: To explore the cause-effect relationship between Fusobacterium nucleatum and colorectal cancer, a systematic review and re-analysis of studies published were performed. The method of the conditio sine qua non relationship was used to proof the hypothesis without Fusobacterium nucleatum infection, no colorectal cancer. The mathematical formula of the causal relationship k was used to proof the hypothesis, whether there is a cause-effect relationship between Fusobacterium nucleatum and colorectal cancer. Significance was indicated by a p-value of less than 0.05. Result: The data analyzed support the Null-hypothesis that without Fusobacterium nucleatum infection, no colorectal cancer. In the same respect, the studies analyzed provide highly significant cause-effect relationship between Fusobacterium nucleatum and colorectal cancer. Conclusion: The findings of this study suggest that Fusobacterium (nucleatum) is the cause of colorectal cancer.

Helicobacter pylori——The Cause of Human Gastric Cancer

Background: Many studies documented an association between a Helicobacter pylori infection and the development of human gastric cancer. None of these studies were able to identify Helicobacter pylori as a cause or as the cause of human gastric cancer. The basic relation between gastric cancer and Helicobacter pylori still remains uncertain. Objectives: This systematic review and re-analysis of Naomi Uemura et al. available long-term, prospective study of 1526 Japanese patients are performed so that some new and meaningful inference can be drawn. Materials and Methods: Data obtained by Naomi Uemura et al. who conducted a long-term, prospective study of 1526 Japanese patients with a mean follow up about 7.8 years and endoscopy at enrolment and in the following between one and three years after enrolment were reanalysed. Statistical Analysis Used: The method of the conditio sine qua non relationship was used to proof the hypothesis without a Helicobacter pylori infection no development of human gastric cancer. The mathematical formula of the causal relationship was used to proof the hypothesis, whether there is a cause effect relationship between a Helicobacter pylori infection and human gastric cancer. Significance was indicated by a p-value of less than 0.05. Results: Based on the data published by Uemura et al. we were able to make evidence that without a Helicobacter pylori infection no development of human gastric cancer. In other words, a Helicobacter pylori infection is a conditio sine qua non of human gastric cancer. In the same respect, the data of Uemura et al. provide significant evidence that a Helicobacter pylori infection is the cause of human gastric cancer. Conclusions: Without a Helicobacter pylori infection of human stomach no development of human gastric cancer. Helicobacter pylori is the cause of human gastric cancer (k = +0.07368483, p-value = 0.00399664).

Epstein Bar Virus——The Cause of Hodgkin’s Lymphoma

Objective: Epstein-Barr virus (EBV), a herpes virus which persists in memory B cells in the peripheral blood for the lifetime of a person, is accused to be associated with several malignancies. Hodgkin’s lymphoma (HL) has long been suspected to have an Epstein-Barr virus infection as a causal agent. Some recent studies identified an EBV latent infection to a high degree in Hodgkin’s lymphoma. However, despite intensive study, the role of Epstein-Barr virus infection in Hodgkin lymphoma remains enigmatic. Methods: To explore the cause-effect relationship between EBV and HL and so to understand the role of EBV in HL etiology more clearly, a systematic review and re-analysis of studies published is performed. The method of the conditio per quam relationship was used to proof the hypothesis if Epstein-Barr virus infection (DNA) in human lymph nodes is present then Hodgkin lymphoma is present too. The mathematical formula of the causal relationship k was used to proof the hypothesis, whether there is a cause effect relationship between an Epstein-Barr virus infection (EBV DNA) and Hodgkin lymphoma. Significance was indicated by a p-value of less than 0.05. Result: The data analyzed support the Null-hypotheses that if Epstein-Barr virus infection (EBV DNA) is present in human lymph nodes then Hodgkin lymphoma is present too. In the same respect, the studies analyzed provide highly significant evidence that Epstein-Barr virus the cause of Hodgkin lymphoma. Conclusion: The findings of this study suggest that Epstein-Barr virus is the cause of Hodgkin’s lymphoma besides of the complexity of Hodgkin’s disease.

Using Delphi and fuzzy DEMATEL for analyzing the intertwined relationships of the barriers of university technology transfer: Evidence from a developing economy

Universities are highly responsible for knowledge creation and technology development.However,university technology transfer(UTT)is considered a challenge in bringing innovative technologies for commercialization and community services.Thus,identifying the barriers and their complex interrelationships that hinder the successful implementation of UTT provides a better understanding of the process,which may be considered as inputs to crucial decision-making initiatives.While this approach is highly relevant in the domain field,it remains a point of departure in the current literature.This paper addresses this gap by holistically determining the UTT barriers and their intertwined relationships.Using the Delphi method and the fuzzy decision-making trial and evaluation laboratory(DEMATEL)to carry out this objective,a case study in a state university in the Philippines is presented in this work.Results show that lack of resources has the strongest causal relationship among the 24 UTT barriers.Whereas,poor marketing/technical/negotiation skills of technology transfer office obtained the highest impacts received and is categorized as the main net effect.These findings are intended to guide various stakeholders in understanding the influence of barriers in the formulation of strategies and initiatives to carry out effectively the UTT process.

Blood cell counts and nonalcoholic fatty liver disease: Evidence from Mendelian randomization analysis

BACKGROUND Previous research has highlighted correlations between blood cell counts and chronic liver disease.Nonetheless,the causal relationships remain unknown.AIM To evaluate the causal effect of blood cell traits on liver enzymes and nonalcoholic fatty liver disease(NAFLD)risk.METHODS Independent genetic variants strongly associated with blood cell traits were extracted from a genome-wide association study(GWAS)conducted by the Blood Cell Consortium.Summary-level data for liver enzymes were obtained from the United Kingdom Biobank.NAFLD data were obtained from a GWAS meta-analysis(8434 cases and 770180 controls,discovery dataset)and the Fingen GWAS(2275 cases and 372727 controls,replication dataset).This analysis was conducted using the inverse-variance weighted method,followed by various sensitivity analyses.RESULTS One SD increase in the genetically predicted haemoglobin concentration(HGB)was associated with aβof 0.0078(95%CI:0.0059-0.0096),0.0108(95%CI:0.0080-0.0136),0.0361(95%CI:0.0156-0.0567),and 0.0083(95%CI:00046-0.0121)for alkaline phosphatase(ALP),alanine aminotransferase(ALT),aspartate aminotransferase,and gammaglutamyl transferase,respectively.Genetically predicted haematocrit was associated with ALP(β=0.0078,95%CI:0.0052-0.0104)and ALT(β=0.0057,95%CI:0.0039-0.0075).Genetically determined HGB and the reticulocyte fraction of red blood cells increased the risk of NAFLD[odds ratio(OR)=1.199,95%CI:1.087-1.322]and(OR=1.157,95%CI:1.071-1.250).The results of the sensitivity analyses remained significant.CONCLUSION Novel causal blood cell traits related to liver enzymes and NAFLD development were revealed through Mendelian randomization analysis,which may facilitate the diagnosis and prevention of NAFLD.

Causal Analysis of Futures Sugar Prices in Zhengzhou

In this paper, we are interested in investigating the causal relationships among futures sugar prices in the Zhengzhou futures exchange market （ZF）, the spot sugar prices in Zhengzhou （ZS） and the futures sugar prices in New York futures exchange market （NF）. A useful tool called Bayesian network is introduced to analyze the problem. Since there are only three variables in our Bayesian network, the algorithm is straightforward： we display all the 25 possible network structures and adopt certain scoring metrics to evaluate them. We applied five different scoring metrics in total. Firstly, for each metric, we obtained 24 scores, each calculated from one of the 24 possible structures i.e. a Directed Acyclic Graph （DAG）. Then we eliminated the network structure which represents the independence of the three variables according to our prior knowledge concerning the futures sugar market. After that, the optimal network structure which implies the causal relationships was selected according to the corresponding scoring metric. Finally, after comparing the results from different scoring metrics, we obtained the relatively affirmative conclusion that ZS causes ZF from both the Bayesian Dirichlet （BD） metric, Bayesian Dirichlet-Akaike Information Criterion （BD-AIC） metric, Bayesian Dirichlet-Bayesian Information Criterion （BD-BIC） metric and Bayesian Information Criterion （BIC） metric. The conclusions that NF causes ZF and ZF causes ZS from the Akaike Information Criterion （AIC） metric and ZF causes ZS from the BIC metric were useful and significant to our investigation.

Research on COVID-19 Internet Derived Public Opinions Prediction Based on the Event Evolution Graph

As one of the ways to reflect the views of the masses in modern society,online reviews have great value in public opinion research.The analysis of potential public opinion information from online reviews has a certain value for the government to clarify the next work direction.In this paper,the event evolution graph is designed to make COVID-19 network public opinion prediction.The causal relationship was extracted in the network reviews after the COVID-19 incident to build an event evolution graph of COVID-19 and predict the possibility of the occurrence of the derivative public opinion.The research results show the hot events and evolution direction of COVID-19 network public opinion in a clear way,and it can provide reference for the network regulatory department to implement intervention.