Risk Analysis of Passalora sequoiae Invasion to China with Imported Coniferous Wood

According to international standard plant quarantine measures and principle risk analysis(ISPM No.11),a risk assessment was carried out for Passalora sequoiae through geographical distribution,possibility of colonization,probability of diffusion,economic importance and difficulty in risk management.Results show that P.sequoiae has a greater risk of introduction and diffusion,and it has distributed in parts of China.It is suggested that P.sequoiae should be added to the list of forest dangerous pests in China.Besides,porting departments should focus on the pathogen on imported host seedlings like Cryptomeria.

Analysis of the Tragedy of Vila Socóin Cubatão (São Paulo, Brazil) Using the Haddon Matrix: A Comprehensive Examination of Socio-Environmental Factors and Risk Mitigation Strategies

The tragedy of Vila Socó epitomizes the socio-environmental repercussions of rapid industrialization in Cubatão. Beginning in the 1940s with the construction of the Anchieta highway, the city experienced an influx of migrants drawn by burgeoning industries, leading to unplanned urban growth and the emergence of vulnerable communities like Vila Socó. This article examines the interconnected factors—such as demographic shifts, inadequate planning, and regulatory oversight—that culminated in the devastating fire of 1984, claiming numerous lives and highlighting systemic failures. Utilizing the Haddon Matrix, this study dissects the Vila Socó incident, emphasizing the roles of human error, infrastructure integrity, and socio-economic disparities in disaster causation. By contextualizing the tragedy within Cubatão’s industrial trajectory, it underscores the urgent need for comprehensive risk assessment and proactive mitigation strategies in rapidly developing regions globally. Beyond its immediate focus, this work offers broader insights into the dynamics of industrial disasters and their socio-economic implications. As pipelines continue to play a vital role in global energy infrastructure, the lessons drawn from Vila Socó’s tragedy resonate deeply, emphasizing the imperative of robust safety protocols and accountable governance to prevent similar catastrophes in the future.

Trends and hotspots in gastrointestinal neoplasms risk assessment: A bibliometric analysis from 1984 to 2022

BACKGROUND Gastrointestinal neoplasm(GN)significantly impact the global cancer burden and mortality,necessitating early detection and treatment.Understanding the evolution and current state of research in this field is vital.AIM To conducts a comprehensive bibliometric analysis of publications from 1984 to 2022 to elucidate the trends and hotspots in the GN risk assessment research,focusing on key contributors,institutions,and thematic evolution.METHODS This study conducted a bibliometric analysis of data from the Web of Science Core Collection database using the"bibliometrix"R package,VOSviewer,and CiteSpace.The analysis focused on the distribution of publications,contributions by institutions and countries,and trends in keywords.The methods included data synthesis,network analysis,and visualization of international collaboration networks.RESULTS This analysis of 1371 articles on GN risk assessment revealed a notable evolution in terms of research focus and collaboration.It highlights the United States'critical role in advancing this field,with significant contributions from institutions such as Brigham and Women's Hospital and the National Cancer Institute.The last five years,substantial advancements have been made,representing nearly 45%of the examined literature.Publication rates have dramatically increased,from 20 articles in 2002 to 112 in 2022,reflecting intensified research efforts.This study underscores a growing trend toward interdisciplinary and international collaboration,with the Journal of Clinical Oncology standing out as a key publication outlet.This shift toward more comprehensive and collaborative research methods marks a significant step in addressing GN risks.CONCLUSION This study underscores advancements in GN risk assessment through genetic analyses and machine learning and reveals significant geographical disparities in research emphasis.This calls for enhanced global collaboration and integration of artificial intelligence to improve cancer prevention and treatment accuracy,ultimately enhancing worldwide patient care.

Sensitivity and resistance risk analysis of Didymella bryoniae populations to fluopyram

Fluopyram is an succinate dehydrogenase inhibitors(SDHI)fungicide that has been registered in China to control gummy stem blight(GSB)in watermelons for many years.However,whether the field pathogens of GSB are still sensitive to fluopyram or not is unknown.Therefore,we collected 69 Didymella bryoniae isolates from the fields that usually use fluopyram to control GSB to determine the sensitivity change.The EC50(50%inhibition effect)values of fluopyram against D.bryoniae ranged from 0.0691 to 0.3503μg mL–1 and the variation factor was 5.07.The mean EC50 value was(0.1579±0.0669)μg mL–1 and the curve of sensitivity was unimodal.No resistant strains were found in the isolates,which means that the pathogens were still sensitive to fluopyram.The minimal inhibition concentration(MIC)of fluopyram against D.bryoniae was 3μg mL–1.Four low-resistant mutants and two mediumresistant mutants were obtained using fungicide taming and the resistance of mutants could be inherited stably.The growth rate of mutants decreased significantly compared with that of wild-type strains while the biomass of most mutants was similar to that of wild-type strains.The sensitivity of most resistant mutants to various stresses was increased compared with that of wild-type strains.The virulence of mutants receded except for low-resistant mutant XN51FR-1,which had the same lesion area as XN51 on the watermelon leaves.The results indicated that the fitness of resistant mutants was decreased compared with that of wild-type strains.The cross-resistance assay indicated that fluopyram-resistant mutants were positive cross-resistant to all six SDHI fungicides in this test but were still sensitive to fluazinam and tebuconazole.So the resistance risk of D.bryoniae to fluopyram was moderate.In addition,we found that the SdhB gene of low-resistant mutant XN30FR-1 had three new point mutations at positions K258N,A259P,and H277N.Medium-resistant mutant XN52FR-1 showed a mutation at position H277N and other mutants did not have any point mutation.

Analysis of risk factors leading to anxiety and depression in patients with prostate cancer after castration and the construction of a risk prediction model

BACKGROUND Cancer patients often suffer from severe stress reactions psychologically,such as anxiety and depression.Prostate cancer(PC)is one of the common cancer types,with most patients diagnosed at advanced stages that cannot be treated by radical surgery and which are accompanied by complications such as bodily pain and bone metastasis.Therefore,attention should be given to the mental health status of PC patients as well as physical adverse events in the course of clinical treatment.AIM To analyze the risk factors leading to anxiety and depression in PC patients after castration and build a risk prediction model.METHODS A retrospective analysis was performed on the data of 120 PC cases treated in Xi'an People's Hospital between January 2019 and January 2022.The patient cohort was divided into a training group(n=84)and a validation group(n=36)at a ratio of 7:3.The patients’anxiety symptoms and depression levels were assessed 2 wk after surgery with the Self-Rating Anxiety Scale(SAS)and the Selfrating Depression Scale(SDS),respectively.Logistic regression was used to analyze the risk factors affecting negative mood,and a risk prediction model was constructed.RESULTS In the training group,35 patients and 37 patients had an SAS score and an SDS score greater than or equal to 50,respectively.Based on the scores,we further subclassified patients into two groups:a bad mood group(n=35)and an emotional stability group(n=49).Multivariate logistic regression analysis showed that marital status,castration scheme,and postoperative Visual Analogue Scale(VAS)score were independent risk factors affecting a patient's bad mood(P<0.05).In the training and validation groups,patients with adverse emotions exhibited significantly higher risk scores than emotionally stable patients(P<0.0001).The area under the curve(AUC)of the risk prediction model for predicting bad mood in the training group was 0.743,the specificity was 70.96%,and the sensitivity was 66.03%,while in the validation group,the AUC,specificity,and sensitivity were 0.755,66.67%,and 76.19%,respectively.The Hosmer-Lemeshow test showed aχ^(2) of 4.2856,a P value of 0.830,and a C-index of 0.773(0.692-0.854).The calibration curve revealed that the predicted curve was basically consistent with the actual curve,and the calibration curve showed that the prediction model had good discrimination and accuracy.Decision curve analysis showed that the model had a high net profit.CONCLUSION In PC patients,marital status,castration scheme,and postoperative pain(VAS)score are important factors affecting postoperative anxiety and depression.The logistic regression model can be used to successfully predict the risk of adverse psychological emotions.

Cybersecurity Risk Management through Behavior-Based Contextual Analysis of Online Logs

This paper studies cyber risk management by integrating contextual log analysis with User and Entity Behavior Analytics (UEBA). Leveraging Python scripting and PostgreSQL database management, the solution enriches log data with contextual and behavioral information from Linux system logs and semantic datasets. By incorporating Common Vulnerability Scoring System (CVSS) metrics and customized risk scoring algorithms, the system calculates Insider Threat scores to identify potential security breaches. The integration of contextual log analysis and UEBA [1] offers a proactive defense against insider threats, reducing false positives and prioritizing high-risk alerts.

Intertwined depressive and cognitive trajectories and the risk of dementia and death in older adults:a competing risk analysis

Background Depressive symptoms and cognitive impairment often interact,rendering their associations controversial.To date,their joint trajectories and associations with dementia and death remain underexplored.Aims To explore the interactions between depressive symptoms and cognitive function,their developmental trajectories and the associations with all-cause dementia,Alzheimer’s disease(AD)and all-cause death in older adults.Methods Data were from the Health and Retirement Study.Depressive symptoms and cognitive function were measured using the 8-item Centre for Epidemiologic Studies Depression Scale and the Telephone Interview of Cognitive Status,respectively.All-cause dementia and AD were defined by self-reported or proxy-reported physician diagnoses.All-cause death was determined by interviews.The restricted cubic spline,group-based trajectory modelling and subdistribution hazard regression were used.Results Significant interactions between depressive symptoms and cognitive function in 2010 in their association with new-onset all-cause dementia and AD from 2010 to 2020 were found,especially in women(p for interaction<0.05).Independent trajectory analysis showed that emerging or high(vs no)depressive trajectories and poor or rapidly decreased cognitive trajectories(vs very good)from 1996 to 2010 were at significantly higher risk of subsequent all-cause dementia,AD and all-cause death.15 joint trajectories of depressive symptoms and cognitive function from 1996 to 2010 were determined,where rapidly decreased cognitive function was more common in those with no depressive symptoms.Compared with older adults with the trajectory of no depressive symptoms and very good cognitive function,those with the trajectory of no depressive symptoms but rapidly decreased cognitive function were much more likely to develop new-onset all-cause dementia and death,with subdistribution hazard ratios(95%confidence intervals)of 4.47(2.99 to 6.67)and 1.84(1.43 to 2.36),especially in women.Conclusions To effectively mitigate the risk of dementia and death,it is crucial to acknowledge the importance of preventing cognitive decline in older adults without depressive symptoms,particularly in women.

Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis

BACKGROUND The lack of specific symptoms of gastric cancer(GC)causes great challenges in its early diagnosis.Thus it is essential to identify the risk factors for early diagnosis and treatment of GC and to improve the survival rates.AIM To assist physicians in identifying changes in the output of publications and research hotspots related to risk factors for GC,constructing a list of key risk factors,and providing a reference for early identification of patients at high risk for GC.METHODS Research articles on risk factors for GC were searched in the Web of Science core collection,and relevant information was extracted after screening.The literature was analyzed using Microsoft Excel 2019,CiteSpace V,and VOSviewer 1.6.18.RESULTS A total of 2514 papers from 72 countries and 2507 research institutions were retrieved.China(n=1061),National Cancer Center(n=138),and Shoichiro Tsugane(n=36)were the most productive country,institution,or author,respectively.The research hotspots in the study of risk factors for GC are summarized in four areas,namely:Helicobacter pylori(H.pylori)infection,single nucleotide polymorphism,bio-diagnostic markers,and GC risk prediction models.CONCLUSION In this study,we found that H.pylori infection is the most significant risk factor for GC;single-nucleotide polymorphism(SNP)is the most dominant genetic factor for GC;bio-diagnostic markers are the most promising diagnostic modality for GC.GC risk prediction models are the latest current research hotspot.We conclude that the most important risk factors for the development of GC are H.pylori infection,SNP,smoking,diet,and alcohol.

Risk Factors of Depression Screened by Two-Sample Mendelian Randomization Analysis:A Systematic Review

Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.

Survival and risk analysis of patients with COVID-19 in Iran

Objective:To evaluate the risk factors of death caused by COVID-19 in Iran.Methods:This study was a retrospective cohort study from February 20,2020,to August 22,2022,in the hospitals in Isfahan,Iran.The data were collected through a researcher-made checklist.To determine the risk factors of the death,logistic regression and Cox regression models were used.For each variable,the odds ratio and 95%confidence interval were also reported.Results:1885 Patients were included.The age of deceased persons was significantly higher than that of the surviving persons.The risk of death for the age group above 60 years was about 14 times higher than that of people aged 19-35 years[95%CI:14.41(2.02-102.99),P<0.01].Hypertension[95%CI:1.92(1.47-2.5),P<0.01],diabetes[95%CI:1.62(1.23-2.13),P<0.001],and chronic obstructive pulmonary disease[95%CI:1.92(1.47-2.50),P<0.01]were also risk factors of mortality.Conclusions:This study reveals that the mortality rate due to COVID-19 is associated with old age,longer hospitalization in the ICU,increased length of stay,and comorbidities of high blood pressure,diabetes,and chronic pulmonary disease.

Analysis of risk factors of suicidal ideation in adolescent patients with depression and construction of prediction model

BACKGROUND Major depressive disorder is a common mental illness among adolescents and is the largest disease burden in this age group.Most adolescent patients with depression have suicidal ideation(SI);however,few studies have focused on the factors related to SI,and effective predictive models are lacking.AIM To construct a risk prediction model for SI in adolescent depression and provide a reference assessment tool for prevention.METHODS The data of 150 adolescent patients with depression at the First People's Hospital of Lianyungang from June 2020 to December 2022 were retrospectively analyzed.Based on whether or not they had SI,they were divided into a SI group(n=91)and a non-SI group(n=59).The general data and laboratory indices of the two groups were compared.Logistic regression was used to analyze the factors influencing SI in adolescent patients with depression,a nomogram prediction model was constructed based on the analysis results,and internal evaluation was performed.Receiver operating characteristic and calibration curves were used to evaluate the model’s efficacy,and the clinical application value was evaluated using decision curve analysis(DCA).RESULTS There were differences in trauma history,triggers,serum ferritin levels(SF),highsensitivity C-reactive protein levels(hs-CRP),and high-density lipoprotein(HDLC)levels between the two groups(P<0.05).Logistic regression analysis showed that trauma history,predisposing factors,SF,hs-CRP,and HDL-C were factors influencing SI in adolescent patients with depression.The area under the curve of the nomogram prediction model was 0.831(95%CI:0.763–0.899),sensitivity was 0.912,and specificity was 0.678.The higher net benefit of the DCA and the average absolute error of the calibration curve were 0.043,indicating that the model had a good fit.CONCLUSION The nomogram prediction model based on trauma history,triggers,ferritin,serum hs-CRP,and HDL-C levels can effectively predict the risk of SI in adolescent patients with depression.

Dislocation of primary total hip arthroplasty:Analysis of risk factors and preventive options

Total hip arthroplasty(THA)is one of the most successful elective operations in orthopedic surgery for improving pain and functional disability in patients with end-stage joint disease.However,dislocation continues to be a troublesome complication after THA,as it is a leading cause of revision and is associated with substantial social,health,and economic costs.It is a relatively rare,usually early occurrence that depends on both the patients’characteristics and the surgical aspects.The most recent and important finding is the special attention to be given preoperatively to spinopelvic mobility,which is closely related to the incidence of dislocation.Consequently,clinical and radiographic assessment of the lumbar spine is mandatory to identify an altered pelvic tilt that could suggest a different positioning of the cup.Lumbar spinal fusion is currently considered a risk factor for dislocation and revision regardless of whether it is performed prior to or after THA.Surgical options for its treatment and prevention include the use of prostheses with large diameter of femoral head size,dual mobility constructs,constrained liners,and modular neck stems.

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.

Volcanic Risk Perception and Coping Strategies from Mounts Cameroon and Nyiragongo Eruptions, Central Africa: A Comparative Analysis

Approximately 2,000,000 people are exposed to volcanic risks in communities situated at the flanks of Mounts Cameroon (MC) and Nyiragongo (MN) volcanoes in Central Africa. This study therefore sought to investigate risk perception from four previous eruptions of MC, namely the 1959, 1982, 1999, and 2000 eruptions;and two previous eruptions of MN: 1977 and 2002. The study was initiated with co-design workshops held with major stakeholders in the cities of Buea and Goma at the flanks of MC and MN, respectively, in 2017, to develop the research objectives for the study. A non-random questionnaire survey was later conducted within 14 and 15 communities in Buea and Goma respectively, on the effects, perceived risks, and coping strategies for the chosen eruptions. Three age groups (18 - 30, 31 - 45 and >45 years) and gender (male and female) were considered. The population at the flanks of both volcanoes cited scientific and indigenous factors to be responsible for eruptions from these volcanoes. At MC and MN, ≥45% of the sampled participants (with a higher female population) perceived that the sampled eruptions posed a very high risk to the population. In terms of the effects, the age group of 18 - 30 was the least knowledgeable. In terms of direct effect on persons, over 90% of participants at MC and MN attested that they were overcome by fear/panic. On measures to cope with any likely eruption, the following order was established at the flanks of both volcanoes: sensitization of population, use of religious (prayers) and of traditional/indigenous strategies. In terms of future coping strategies, while the males at MC maintained sensitization as the favourite option, 62% of the males at MN opted for traditional/indigenous strategies. The female population at both MC and MN showed a higher preference for religious strategies like prayers.

Risk Analysis of the Development of Sustainable Dongtan

Dongtan is set to be developed as a sustainable urban-rural integration,aiming to attract a wide range of commercial and leisure investments.The Shanghai Industrial Investment Corporation(SIIC),the largest international investment group owned by the Shanghai municipal government,is leading the Dongtan project in partnership with Arup.The project’s risks are categorized into eight major groups:(1)Force majeure,(2)people-related risks,(3)financial and economic risks,(4)political and country risks,(5)environmental risks,(6)completion-related risks,(7)design-related risks,and(8)technology risks.Among these,political risk is particularly notable for its high probability and significant impact.Effective project risk management is essential to foresee and address uncertainties that could jeopardize the project’s objectives and timelines.Appropriate strategies must be implemented to manage and mitigate these risks.

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.

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.

Investigation and Analysis of Lung Cancer Risk Factors in the Health Check-Up Population

Objective: To investigate and analyze the risk factors of lung cancer in the population of health checkups. Methods: A total of 500 cases of the health check-up population were selected for data study. Surveyed showed that 19 cases of lung cancer were grouped as the lung cancer group and the remaining 481 cases made up the control group, and the risk factors were analyzed. Results: Among men, there was a significant proportion of individuals aged 60-69 years old, and women aged 30-39 years old. Additionally, individuals aged 60 and above were at increased risk of developing lung cancer. The results of the multifactorial analysis were that the risk factors affecting the detection of lung cancer in healthy people were smoking history, family history of lung cancer, secondhand smoke, history of respiratory diseases, psychosomatic factors, living environment, and kitchen fumes. Conclusion: People over 60 years of age were prone to early lung cancer, followed by individuals aged 30-39 years. It is important to identify the risk factors of lung cancer to strengthen the screening of high-risk groups for early detection and treatment.

Correlation analysis of human papillomavirus E6/E7 mRNA detection with diagnosis,prognosis and recurrence risk in patients with cervical epithelioma

BACKGROUND Cervical intraepithelial neoplasia(CIN)is an important precursor of cervical cancer.Early detection and treatment can reduce the incidence of cervical cancer.AIM To investigate the detection rate of human papillomavirus(HPV)E6/E7 mRNA in cervical tissue of patients with different types of epithelial cell neoplasia(CIN)and its relationship with CIN progression and diagnosis.METHODS One hundred women with HPV infection detected by cervical exfoliation cytology between January 2022 and January 2023 were retrospectively selected.These patients were graded CIN based on colposcopy and cervical pathology.The positive expression rates of HPV E6/E7 mRNA and HPV[polymerase chain reaction(PCR)-reverse dot crossing]were compared among all groups.Patients with HPV E6/E7 mRNA expression in the grade 1 CIN group were followed up for 1 yr.The relationship between atypical squamous epithelium and high malignant epithelial neoplasia was investigated by univariate and multivariate analysis.RESULTS The diagnostic sensitivity,specificity,and sensitivity of PCR-reverse point hybrid ization technology for secondary CIN were 70.41%,70.66%,and 0.714,respectively.Sensitivity and specificity for secondary CIN were 752%and 7853%,respectively,the area under the curve value was 0.789.Logistic Multifactorial model analysis revealed that the HPV positive rates and the HPV E6/E7 mRNA positive rates were independent risk factors of CIN grade I(P<0.05).In CIN grade I patients with positive for HPV E6/E7 mRNA,in its orientation to grade CIN patients,in its orientation to grade CIN patients,at 69.2%,compared with patients negative for HPV E6/E7 mRNA(30.8%),significant difference(P<0.05).CONCLUSION HPV E6/E7 mRNA and HPV(PCR-reverse dot hybrid)positive expression have a close relationship with CINgrade disease progression and is an independent risk factor for high-grade CIN lesions.

Safety Risk Assessment Analysis of Bridge Construction Using Backpropagation Neural Network

The evaluation of construction safety risks has become a crucial task with the increasing development of bridge construction.This paper aims to provide an overview of the application of backpropagation neural networks in assessing safety risks during bridge construction.It introduces the situation,principles,methods,and advantages,as well as the current status and future development directions of backpropagation-related research.