Objective:This study aimed to analyze the temporal trends in cancer mortality in China from 2013-2021 and project the future trends through 2030.Methods:This study was based on the China Causes of Death Surveillance D...Objective:This study aimed to analyze the temporal trends in cancer mortality in China from 2013-2021 and project the future trends through 2030.Methods:This study was based on the China Causes of Death Surveillance Dataset,which covers 2.37 billion person-years.Age-standardized mortality rates(ASMRs)were calculated using Segi’s world standard population and the trends were evaluated via Joinpoint regression.Bayesian age-period-cohort models were used for mortality projections.Contributions of demographic changes(population size and age structure)and risk factors to the mortality burden were quantified using the decomposition analysis.Results:The combined ASMRs for all cancers decreased annually by 2.3%,driven by significant declines in esophageal(4.8%),stomach(4.5%),and liver cancers(2.7%).In contrast,the pancreatic and prostate cancer ASMRs increased by 2.0% and 3.4% annually,respectively.Urban areas demonstrated a more rapid decline in the combined ASMRs for all cancers[average annual percent change(AAPC)=-3.0% in urban areas vs.-2.0% in rural areas],highlighting persistent disparities.Population aging contributed 20%-50% to death increases between 2013 and 2021.The combined ASMRs for all cancers,like the findings of temporal trend analyses,will continue to decrease and the regional(urban and rural)difference is projected to simulate that of the temporal trend through 2030.In fact,cancer deaths are projected to reach 2.4 million by 2030.Conclusions:The cancer burden in China is facing the dual challenges of population aging and urban-rural disparities.It is necessary to prioritize rural screening,control risk factors,such as smoking and diet,and integrate more efficacious cancer prevention and control programmes into the policy to reduce mortality in the future.展开更多
目的锌指蛋白335(Zfp335)参与调控胸腺T细胞的早期发育和外周T细胞亚群的分化,本研究旨在探讨Zfp335调控调节性T细胞(Treg)在肿瘤免疫中的作用和机制。方法用他莫昔芬在Treg中特异性敲除Zfp335基因[Zfp335^(fl/fl)叉头盒P3(FOXP3)creERT...目的锌指蛋白335(Zfp335)参与调控胸腺T细胞的早期发育和外周T细胞亚群的分化,本研究旨在探讨Zfp335调控调节性T细胞(Treg)在肿瘤免疫中的作用和机制。方法用他莫昔芬在Treg中特异性敲除Zfp335基因[Zfp335^(fl/fl)叉头盒P3(FOXP3)creERT2],并构建MC38移植瘤模型。接种肿瘤后第7天,观察并测量肿瘤的大小,第12天剥离肿瘤组织,用流式细胞术检测野生型(WT)组和Zfp335敲除(Zfp335^(CKO))组小鼠肿瘤浸润淋巴细胞中CD4^(+)T细胞、CD8^(+)T细胞和Treg的比例,以及效应性Treg(eTreg)的线粒体功能。结果自接种肿瘤后第10天开始,Zfp335^(CKO)组肿瘤体积显著小于WT组。Zfp335^(CKO)组CD4^(+)T细胞和CD8^(+)T细胞的肿瘤浸润比例、及其对应的效应细胞比例显著高于WT组。Zfp335^(CKO)组CD4^(+)T细胞和CD8^(+)T细胞分泌细胞因子γ干扰素(IFN-γ)、肿瘤坏死因子α(TNF-α)的比例显著高于WT组,Zfp335^(CKO)组CD8^(+)T细胞分泌颗粒酶B(GzmB)的比例显著高于WT组。Zfp335^(CKO)组Treg、诱导性共刺激分子(ICOS)+Treg比例显著低于WT组。Zfp335^(CKO)组eTreg表达Mitotracker Deep Red的水平显著低于WT组。结论在肿瘤发生过程中,Treg特异性缺失Zfp335导致其活化减弱,与eTreg的线粒体功能降低有关;Zfp335^(CKO)小鼠肿瘤浸润的效应性T细胞增多、分泌杀伤性细胞因子增多,进而抵抗肿瘤发展。展开更多
[目的]分析江苏省无锡市2009—2023年居民胃癌死亡变化趋势以及30岁及以上居民年龄、时期、出生队列对胃癌死亡风险的影响。[方法]收集2009—2023年无锡市胃癌死亡资料,计算胃癌的粗死亡率、标化死亡率、寿命损失年(years of life lost,...[目的]分析江苏省无锡市2009—2023年居民胃癌死亡变化趋势以及30岁及以上居民年龄、时期、出生队列对胃癌死亡风险的影响。[方法]收集2009—2023年无锡市胃癌死亡资料,计算胃癌的粗死亡率、标化死亡率、寿命损失年(years of life lost,YLL)、YLL率。使用Join-point回归计算平均年度变化百分比(average annual percentage change,AAPC)分析死亡变化趋势。拟合年龄-时期-队列模型分析30岁及以上人群胃癌死亡风险和死亡负担的年龄、时期及队列效应。[结果]2009—2023年无锡市胃癌共死亡32348例,粗死亡率为44.24/10万,标化死亡率为25.10/10万,YLL共计681618.33人年。胃癌粗死亡率、标化死亡率、YLL率整体均呈下降趋势,AAPC分别为-1.77%(95%CI:-2.10%~-1.43%)、-4.59%(95%CI:-4.97%~-4.20%)和-2.14%(95%CI:-2.56%~-1.74%)。2009—2023年男性胃癌粗死亡率、标化死亡率、YLL均高于女性,但是女性各指标下降速度均快于男性。年龄效应显示,胃癌死亡风险总体随年龄的增长而增加,YLL率随年龄呈先上升后下降的趋势。时期效应显示,随着时间的推移,胃癌死亡风险和死亡负担逐渐下降。队列效应显示,越晚出生的队列胃癌死亡风险和死亡负担越低。[结论]2009—2023年无锡市30岁及以上居民胃癌死亡风险和死亡负担均呈下降趋势。胃癌死亡风险和死亡负担受性别差异和年龄效应影响较大,未来应重点加强中老年男性人群的胃癌筛查和早期干预。展开更多
Tumor macrovascular invasion(MVI)frequently occurs in highly metastatic tumors,with high mortality and poor prognosis.Conventional in vitro three-dimensional(3D)models,including organoids and organ-on-a-chip systems,f...Tumor macrovascular invasion(MVI)frequently occurs in highly metastatic tumors,with high mortality and poor prognosis.Conventional in vitro three-dimensional(3D)models,including organoids and organ-on-a-chip systems,fail to replicate the characteristics of MVI due to their limited sizes and lack of a hemodynamic environment.Here,we fabricate a polymeric aerogel tube(PAT)and load its inner and outer surfaces with endothelial cells and tumor cells to construct the macrovascular invaded tumor model.The large-sized interconnecting porous structure of the PAT allows cell accommodation,growth and migration.Under continuous perfusion culture,the model has a complete endothelial cell layer and tumor cells aggressively grow toward the endothelium to form the structure that tumor tissue wraps around the blood vessel,resulting in dense tumor tissues with a biomimetic extracellular matrix for resembling the tumor macrovascular invasion process.We evaluate the tumor retention and gene transfection efficiency of nanomedicines using this model.Additionally,human immune cells are introduced into this system to enable the investigation of anti-tumor efficacy and immune activation of therapeutics.Altogether,we present the first in vitro model of MVI,offering a powerful tool for evaluating multiple bio-effects of therapeutic agents in advanced cancers.展开更多
Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradi...Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradientinformation, and are inspired by the bio-inspired and socially motivated heuristics. Metaheuristic optimizationalgorithms are increasingly applied to complex feature selection problems in high-dimensional medical datasets.Among these, Teaching-Learning-Based optimization (TLBO) has proven effective for continuous design tasks bybalancing exploration and exploitation phases. However, its binary version (BTLBO) suffers from limited exploitationability, often converging prematurely or getting trapped in local optima, particularly when applied to discrete featureselection tasks. Previous studies reported that BTLBO yields lower classification accuracy and higher feature subsetvariance compared to other hybrid methods in benchmark tests, motivating the development of hybrid approaches.This study proposes a novel hybrid algorithm, BTLBO-Cheetah Optimizer (BTLBO-CO), which integrates the globalexploration strength of BTLBO with the local exploitation efficiency of the Cheetah Optimization (CO) algorithm. Theobjective is to enhance the feature selection process for cancer classification tasks involving high-dimensional data. Theproposed BTLBO-CO algorithm was evaluated on six benchmark cancer datasets: 11 tumors (T), Lung Cancer (LUC),Leukemia (LEU), Small Round Blue Cell Tumor or SRBCT (SR), Diffuse Large B-cell Lymphoma or DLBCL (DL), andProstate Tumor (PT).The results demonstrate superior classification accuracy across all six datasets, achieving 93.71%,96.12%, 98.13%, 97.11%, 98.44%, and 98.84%, respectively.These results validate the effectiveness of the hybrid approachin addressing diverse feature selection challenges using a Support Vector Machine (SVM) classifier.展开更多
基金supported by the CAMS Innovation Fund for Medical Sciences(Grant No.2021-I2M-1-011)the Capital’s Funds for Health Improvement and Research(Grant No.CFH2024-2G-40214).
文摘Objective:This study aimed to analyze the temporal trends in cancer mortality in China from 2013-2021 and project the future trends through 2030.Methods:This study was based on the China Causes of Death Surveillance Dataset,which covers 2.37 billion person-years.Age-standardized mortality rates(ASMRs)were calculated using Segi’s world standard population and the trends were evaluated via Joinpoint regression.Bayesian age-period-cohort models were used for mortality projections.Contributions of demographic changes(population size and age structure)and risk factors to the mortality burden were quantified using the decomposition analysis.Results:The combined ASMRs for all cancers decreased annually by 2.3%,driven by significant declines in esophageal(4.8%),stomach(4.5%),and liver cancers(2.7%).In contrast,the pancreatic and prostate cancer ASMRs increased by 2.0% and 3.4% annually,respectively.Urban areas demonstrated a more rapid decline in the combined ASMRs for all cancers[average annual percent change(AAPC)=-3.0% in urban areas vs.-2.0% in rural areas],highlighting persistent disparities.Population aging contributed 20%-50% to death increases between 2013 and 2021.The combined ASMRs for all cancers,like the findings of temporal trend analyses,will continue to decrease and the regional(urban and rural)difference is projected to simulate that of the temporal trend through 2030.In fact,cancer deaths are projected to reach 2.4 million by 2030.Conclusions:The cancer burden in China is facing the dual challenges of population aging and urban-rural disparities.It is necessary to prioritize rural screening,control risk factors,such as smoking and diet,and integrate more efficacious cancer prevention and control programmes into the policy to reduce mortality in the future.
文摘目的锌指蛋白335(Zfp335)参与调控胸腺T细胞的早期发育和外周T细胞亚群的分化,本研究旨在探讨Zfp335调控调节性T细胞(Treg)在肿瘤免疫中的作用和机制。方法用他莫昔芬在Treg中特异性敲除Zfp335基因[Zfp335^(fl/fl)叉头盒P3(FOXP3)creERT2],并构建MC38移植瘤模型。接种肿瘤后第7天,观察并测量肿瘤的大小,第12天剥离肿瘤组织,用流式细胞术检测野生型(WT)组和Zfp335敲除(Zfp335^(CKO))组小鼠肿瘤浸润淋巴细胞中CD4^(+)T细胞、CD8^(+)T细胞和Treg的比例,以及效应性Treg(eTreg)的线粒体功能。结果自接种肿瘤后第10天开始,Zfp335^(CKO)组肿瘤体积显著小于WT组。Zfp335^(CKO)组CD4^(+)T细胞和CD8^(+)T细胞的肿瘤浸润比例、及其对应的效应细胞比例显著高于WT组。Zfp335^(CKO)组CD4^(+)T细胞和CD8^(+)T细胞分泌细胞因子γ干扰素(IFN-γ)、肿瘤坏死因子α(TNF-α)的比例显著高于WT组,Zfp335^(CKO)组CD8^(+)T细胞分泌颗粒酶B(GzmB)的比例显著高于WT组。Zfp335^(CKO)组Treg、诱导性共刺激分子(ICOS)+Treg比例显著低于WT组。Zfp335^(CKO)组eTreg表达Mitotracker Deep Red的水平显著低于WT组。结论在肿瘤发生过程中,Treg特异性缺失Zfp335导致其活化减弱,与eTreg的线粒体功能降低有关;Zfp335^(CKO)小鼠肿瘤浸润的效应性T细胞增多、分泌杀伤性细胞因子增多,进而抵抗肿瘤发展。
文摘[目的]分析江苏省无锡市2009—2023年居民胃癌死亡变化趋势以及30岁及以上居民年龄、时期、出生队列对胃癌死亡风险的影响。[方法]收集2009—2023年无锡市胃癌死亡资料,计算胃癌的粗死亡率、标化死亡率、寿命损失年(years of life lost,YLL)、YLL率。使用Join-point回归计算平均年度变化百分比(average annual percentage change,AAPC)分析死亡变化趋势。拟合年龄-时期-队列模型分析30岁及以上人群胃癌死亡风险和死亡负担的年龄、时期及队列效应。[结果]2009—2023年无锡市胃癌共死亡32348例,粗死亡率为44.24/10万,标化死亡率为25.10/10万,YLL共计681618.33人年。胃癌粗死亡率、标化死亡率、YLL率整体均呈下降趋势,AAPC分别为-1.77%(95%CI:-2.10%~-1.43%)、-4.59%(95%CI:-4.97%~-4.20%)和-2.14%(95%CI:-2.56%~-1.74%)。2009—2023年男性胃癌粗死亡率、标化死亡率、YLL均高于女性,但是女性各指标下降速度均快于男性。年龄效应显示,胃癌死亡风险总体随年龄的增长而增加,YLL率随年龄呈先上升后下降的趋势。时期效应显示,随着时间的推移,胃癌死亡风险和死亡负担逐渐下降。队列效应显示,越晚出生的队列胃癌死亡风险和死亡负担越低。[结论]2009—2023年无锡市30岁及以上居民胃癌死亡风险和死亡负担均呈下降趋势。胃癌死亡风险和死亡负担受性别差异和年龄效应影响较大,未来应重点加强中老年男性人群的胃癌筛查和早期干预。
基金the National Key R&D Program of China(No.2022YFB3804700)the National Natural Science Foundation of China(No.2242780422234004)+4 种基金Guangdong Provincial Key Laboratory of Advanced Biomaterials(No.2022B1212010003)Guangdong Innovative and Entrepreneurial Research Team Program(No.2019ZT08Y191)the Shenzhen Science and Technology Program(Nos.KQTD20190929172743294,JCYJ20220818101407017,SGDX20230116091642001,GJHZ20220913142610019,and KJZD20240903101359020)Guangdong Major Talent Introduction Project(No.2019CX01Y196)Tencent Foundation through the XPLORER PRIZE.The authors acknowledge the assistance of SUSTech Core Research Facilities and the Cryo-EM facility of SouthernUniversity of Science and Technology for providing the facility support.
文摘Tumor macrovascular invasion(MVI)frequently occurs in highly metastatic tumors,with high mortality and poor prognosis.Conventional in vitro three-dimensional(3D)models,including organoids and organ-on-a-chip systems,fail to replicate the characteristics of MVI due to their limited sizes and lack of a hemodynamic environment.Here,we fabricate a polymeric aerogel tube(PAT)and load its inner and outer surfaces with endothelial cells and tumor cells to construct the macrovascular invaded tumor model.The large-sized interconnecting porous structure of the PAT allows cell accommodation,growth and migration.Under continuous perfusion culture,the model has a complete endothelial cell layer and tumor cells aggressively grow toward the endothelium to form the structure that tumor tissue wraps around the blood vessel,resulting in dense tumor tissues with a biomimetic extracellular matrix for resembling the tumor macrovascular invasion process.We evaluate the tumor retention and gene transfection efficiency of nanomedicines using this model.Additionally,human immune cells are introduced into this system to enable the investigation of anti-tumor efficacy and immune activation of therapeutics.Altogether,we present the first in vitro model of MVI,offering a powerful tool for evaluating multiple bio-effects of therapeutic agents in advanced cancers.
基金funded by the Deanship of Research andGraduate Studies at King Khalid University through the Large Research Project under grant number RGP2/417/46.
文摘Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradientinformation, and are inspired by the bio-inspired and socially motivated heuristics. Metaheuristic optimizationalgorithms are increasingly applied to complex feature selection problems in high-dimensional medical datasets.Among these, Teaching-Learning-Based optimization (TLBO) has proven effective for continuous design tasks bybalancing exploration and exploitation phases. However, its binary version (BTLBO) suffers from limited exploitationability, often converging prematurely or getting trapped in local optima, particularly when applied to discrete featureselection tasks. Previous studies reported that BTLBO yields lower classification accuracy and higher feature subsetvariance compared to other hybrid methods in benchmark tests, motivating the development of hybrid approaches.This study proposes a novel hybrid algorithm, BTLBO-Cheetah Optimizer (BTLBO-CO), which integrates the globalexploration strength of BTLBO with the local exploitation efficiency of the Cheetah Optimization (CO) algorithm. Theobjective is to enhance the feature selection process for cancer classification tasks involving high-dimensional data. Theproposed BTLBO-CO algorithm was evaluated on six benchmark cancer datasets: 11 tumors (T), Lung Cancer (LUC),Leukemia (LEU), Small Round Blue Cell Tumor or SRBCT (SR), Diffuse Large B-cell Lymphoma or DLBCL (DL), andProstate Tumor (PT).The results demonstrate superior classification accuracy across all six datasets, achieving 93.71%,96.12%, 98.13%, 97.11%, 98.44%, and 98.84%, respectively.These results validate the effectiveness of the hybrid approachin addressing diverse feature selection challenges using a Support Vector Machine (SVM) classifier.
