肥城市农村居民肺癌发病趋势分析及预测

目的:分析山东省肥城市2000年1月1日至2012年12月31日农村居民肺癌发病率的变化情况,预测2013年至2018年发病率变化趋势,为制定肺癌防治策略提供参考。方法:采用肥城市2000年1月1日至2012年12月31日农村居民肿瘤发病登记资料,采用Joinpoint模型分析发病率变化情况,计算年度变化百分比(annual percent change,APC);采用差分自回归移动平均模型(autoregressive integrated moving average model,ARIMA)模型对发病率进行预测。结果:肥城市农村居民新发肺癌3 908例,其中男性2 633例,女性1 275例,发病率为40.77/10万(中标率为32.95/10万,世标率为32.97/10万),男性发病率是女性的2.14倍(P<0.001);肺癌发病率呈逐年上升趋势,无转折点,发病率由25.13/10万上升至64.92/10万,APC值为9.74%(P<0.001)男、女性人群发病率均呈上升趋势(P<0.001);肺癌发病率的年龄变化趋势可分为3段:0~59岁、60~79岁和80岁及以上,发病率在0~59岁年龄段呈快速上升趋势(APC=113.38,P<0.001),60~79岁增幅趋缓(APC=20.39,P<0.05),80岁及以上开始缓慢下降(APC=-21.20,P>0.05);2013年至2018年,肺癌发病率仍呈逐年上升趋势,2018年将达到87.92/10万,年均增长率为4.92%。结论:肺癌的发生与人口老龄化、不良行为习惯和环境危险因素等密切相关,随着人口老龄化进程的加快,肺癌的发病率仍将持续升高;肺癌的防治应结合其发病特点,制定针对性策略。

Colorectal cancer burden and trends:Comparison between China and major burden countries in the world

Objective:To summarize the colorectal cancer(CRC)burden and trend in the world,and compare the difference of CRC burden between other countries and China.Methods:Incidence and mortality data were extracted from the GLOBOCAN2018 and Cancer Incidence in Five Continents.Age-specific incidence trend was conducted by Joinpoint analysis and average annual percent changes were calculated.Results:About 1.85 million new cases and 0.88 million deaths were expected in 2018 worldwide,including 0.52 million(28.20%)new cases and 0.25 million(28.11%)deaths in China.Hungary had the highest age-standardized incidence and mortality rates in the world,while for China,the incidence and mortality rates were only half of that.CRC incidence and mortality were highly correlated with human development index(HDI).Unlike the rapid increase in Republic of Korea and the downward trend in Canada and Australia,the age-standardized incidence rates by world standard population in China and Norway were rising gradually.The age-specific incidence rate in the age group of 50-59 years in China was increasing rapidly,while in Republic of Korea and Canada,the fastest growing age group was 30-39 years.Conclusions:The variations of CRC burden reflect the difference of risk factors,as well as levels of HDI and screening(early detection activities).The burden of CRC in China is high,and the incidence of CRC continues to increase,which may lead to a sustained increase in the burden of CRC in China in the future.Screening should be expanded to control CRC,and focused on young people in China.

Signatures within esophageal microbiota with progression of esophageal squamous cell carcinoma

Objective: Esophageal squamous cell carcinoma(ESCC) is one of the dominant malignances worldwide, but currently there is less focus on the microbiota with ESCC and its precancerous lesions.Methods: Paired esophageal biopsy and swab specimens were obtained from 236 participants in Linzhou, China.Data from 16 S ribosomal RNA gene sequencing were processed using quantitative insights into microbial ecology(QIIME2) and R Studio to evaluate differences. The Wilcoxon rank sum test and Kruskal-Wallis rank sum test were used to compare diversity and characteristic genera by specimens and participant groups. Ordinal logistic regression model was used to build microbiol prediction model.Results: Microbial diversity was similar between biopsy and swab specimens, including operational taxonomic unit(OTU) numbers and Shannon index. There were variations and similarities of esophageal microbiota among different pathological characteristics of ESCC. Top 10 relative abundance genera in all groups include Streptococcus, Prevotella, Veillonella, Actinobacillus, Haemophilus, Neisseria, Alloprevotella, Rothia, Gemella and Porphyromonas. Genus Streptococcus, Haemophilus, Neisseria and Porphyromonas showed significantly difference in disease groups when compared to normal control, whereas Streptococcus showed an increasing tendency with the progression of ESCC and others showed a decreasing tendency. About models based on all combinations of characteristic genera, only taken Streptococcus and Neisseria into model, the prediction performance was the ideal one, of which the area under the curve(AUC) was 0.738.Conclusions: Esophageal biopsy and swab specimens could yield similar microbial characterization. The combination of Streptococcus and Neisseria has the potential to predict the progression of ESCC, which is needed to confirm by large-scale, prospective cohort studies.

A Surfing Concurrence Transaction Model for Key-Value NoSQL Databases

As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, many scholars have tried different techniques. Unfortunately, there is a lack of research on Redis’s transaction in the existing literatures. This paper proposes a transaction model for key-value NoSQL databases including Redis to make possible allowing users to access data in the ACID (Atomicity, Consistency, Isolation and Durability) way, and this model is vividly called the surfing concurrence transaction model. The architecture, important features and implementation principle are described in detail. The key algorithms also were given in the form of pseudo program code, and the performance also was evaluated. With the proposed model, the transactions of Key-Value NoSQL databases can be performed in a lock free and MVCC (Multi-Version Concurrency Control) free manner. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology.

Identification of plasma proteomic signatures associated with the progression of cardia gastric cancer and precancerous lesions

Objective:Considering that there are no effective biomarkers for the screening of cardia gastric cancer(CGC),we developed a noninvasive diagnostic approach,employing data-independent acquisition(DIA)proteomics to identify candidate protein markers.Methods:Plasma samples were obtained from 40 subjects,10 each for CGC,cardia high-grade dysplasia(CHGD),cardia low-grade dysplasia(CLGD),and healthy controls.Proteomic profiles were obtained through liquid chromatography-mass spectrometry(LC-MS/MS-based DIA proteomics.Candidate plasma proteins were identified by weighted gene co-expression network analysis(WGCNA)combined with machine learning and further validated by the Human Protein Atlas(HPA)database.The area under the receiver operating characteristic curve(AUC)was used to evaluate the performance of the biomarker panel.Results:There was a clear distinction in proteomic features among CGC,CHGD,CLGD,and the healthy controls.According to the WGCNA,we found 42 positively associated and 164 inversely associated proteins related to CGC progression and demonstrated several canonical cancer-associated pathways.Combined with the results from random forests,LASSO regression,and immunohistochemical results from the HPA database,we identified three candidate proteins(GSTP1,CSRP1,and LY6G6F)that could together distinguish CLGD(AUC=0.91),CHGD(AUC=0.99)and CGC(AUC=0.98)from healthy controls with excellent accuracy.Conclusions:The panel of protein biomarkers showed promising diagnostic potential for CGC and precancerous lesions.Further validation and a larger-scale study are warranted to assess its potential clinical applications,suggesting a potential avenue for CGC prevention in the future.

Associations between cancer family history and esophageal cancer and precancerous lesions in high-risk areas of China

Background:Family clustering of esophageal cancer(EC)has been found in high-risk areas of China.However,the relationships between cancer family history and esophageal cancer and precancerous lesions(ECPL)have not been comprehensively reported in recent years.This study aimed to provide evidence for identification of high-risk populations.Methods:This study was conducted in five high-risk areas in China from 2017 to 2019,based on the National Cohort of Esophageal Cancer.The permanent residents aged 40 to 69 years were examined by endoscopy,and pathological examination was performed for suspicious lesions.Information on demographic characteristics,environmental factors,and cancer family history was collected.Unconditional logistic regression was applied to evaluate odds ratios between family history related factors and ECPL.Results:Among 33,008 participants,6143(18.61%)reported positive family history of EC.The proportion of positive family history varied significantly among high-risk areas.After adjusting for risk factors,participants with a family history of positive cancer,gastric and esophageal cancer or EC had 1.49-fold(95%confidence interval[CI]:1.36-1.62),1.52-fold(95%CI:1.38-1.67),or 1.66-fold(95%CI:1.50-1.84)higher risks of ECPL,respectively.Participants with single or multiple first-degree relatives(FDR)of positive EC history had 1.65-fold(95%CI:1.47-1.84)or 1.93-fold(95%CI:1.46-2.54)higher risks of ECPL.Participants with FDRs who developed EC before 35,45,and 50 years of age had 4.05-fold(95%CI:1.30-12.65),2.11-fold(95%CI:1.37-3.25),and 1.91-fold(95%CI:1.44-2.54)higher risks of ECPL,respectively.Conclusions:Participants with positive family history of EC had significantly higher risk of ECPL.This risk increased with the number of EC positive FDRs and EC family history of early onset.Distinctive genetic risk factors of the population in high-risk areas of China require further investigation.Trial registration:ChiCTR-EOC-17010553.

Prediction of job characteristics for intelligent resource allocation in HPC systems:a survey and future directions

Nowadays,high-performance computing(HPC)clusters are increasingly popular.Large volumes of job logs recording many years of operation traces have been accumulated.In the same time,the HPC cloud makes it possible to access HPC services remotely.For executing applications,both HPC end-users and cloud users need to request specific resources for different workloads by themselves.As users are usually not familiar with the hardware details and software layers,as well as the performance behavior of the underlying HPC systems.It is hard for them to select optimal resource configurations in terms of performance,cost,and energy efficiency.Hence,how to provide on-demand services with intelligent resource allocation is a critical issue in the HPC community.Prediction of job characteristics plays a key role for intelligent resource allocation.This paper presents a survey of the existing work and future directions for prediction of job characteristics for intelligent resource allocation in HPC systems.We first review the existing techniques in obtaining performance and energy consumption data of jobs.Then we survey the techniques for single-objective oriented predictions on runtime,queue time,power and energy consumption,cost and optimal resource configuration for input jobs,as well as multi-objective oriented predictions.We conclude after discussing future trends,research challenges and possible solutions towards intelligent resource allocation in HPC systems.

Microbial and epidemiological factors in early detection of esophageal squamous cell carcinoma and precancerous lesions

To the Editor:Esophageal cancer(EC)ranks ninth and fifth among the leading cause of global cancer-related morbidity and mortality,respectively.[1]Esophageal squamous cell carcinoma(ESCC)is the predominant histologic subtype of EC in China.Population screening effectively decreases the morbidity and mortality of ESCC,highlighting the necessity of early detection and early diagnosis.