Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019

Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The study of methyltransferase FTSJ2 gene expression and function in Medulloblastoma and Hepatoma cell line

FTSJ2屬於大腸桿菌RNA核醣體次單元甲基轉移酶RrmJ直同源蛋白家族之一，其功能推測為將硫-腺苷酸甲硫胺酸(S-adenosylmethionine, SAM) 去甲基化轉化為硫-腺苷酸同胱胺酸(S-adenosylhomocysteine, SAH)並對RNA行甲基化修飾。生物體內SAM的來源則仰賴於甲硫胺酸代謝循環的供應，當甲硫胺酸代謝失調時，會造成細胞內SAM與SAH比率改變，進而調控相關基因表現並影響細胞的生長產生影響。本研究將豬FTSJ2基因轉殖於人類神經髓母細胞瘤細胞株te671(te671-FTSJ2)與肝癌細胞株HepG2(HepG2-FTSJ2)，觀察FTSJ2大量表現對於甲硫胺酸代謝循環相關基因:甲硫胺酸腺苷酸轉移酶1A/2A(MAT1A/2A)、SAH水解酶(SAHH)、甲硫胺酸生成酶(MS)以及甜菜鹼-同胱胺酸甲基轉移酶(BHMT)的調控來評估對細胞內SAM /SAH比率是否具有影響以確認其甲基轉移酶的生物功能。結果發現HepG2轉殖FTSJ2提高了MAT1A的mRNA表現(p<0.05)，並顯著降低了MAT2A的轉錄以及增加了SAHH的蛋白表現；te671-FTSJ2則呈現SAHH顯著的減少。SAHH的減少導致了te671-FTSJ2中F-actin表現受到抑制，造成細胞生長趨緩；免疫螢光染色的結果發現FTSJ2在粒線體中大量表現，說明了FTSJ2與其原核生物直同源蛋白祖先一般，會進入粒線體進行甲基化修飾，並調控胞內SAM/SAH比率進而影響粒線體轉錄作用；另外由te671與HepG2的比較可知，不同組織細胞間其甲硫胺酸代謝循環相關基因表現態樣與面對外來基因調控時反應並不是相同的。FTSJ2 is a homologous protein of ribosomal RNA large subunit methyltransferase J (RrmJ) from bacteria. It may function as RrmJ that could catalyze S-adenosylhomocysteine (SAH) converted from demethylation of S-adenosylmethionine (SAM). Methionine adenosyltransferase (MAT) catalyzed the methionine and ATP to produce a principle biological methyl donor, SAM. There are two gene in MAT, MAT1A and MAT2A. It is known that the expression of MAT1A was level down in hepatocellular carcinoma (HCC), but MAT2A was increase. The MAT2A is also a negative control of intracellular SAM level. The functions of FTSJ2 are largely unknown, it is proposed that enhancement of FTSJ2 methyltransferase level may stimulate the MAT activity and SAH content in the cells. In this study, we overexpressed porcine FTSJ2 in HCC cell line HepG2 (G2-FTSJ2) and neuroblastoma cell line te671 (te671-FTSJ2) to prove the correlation between FTSJ2 and MAT. RT-PCR and Western blot were performed to analyze the expressions of MAT1a, MAT2a, SAH hydroase (SAHH), Methionine synthase (MS) and Batine-Homocysetine methyltransferase (BHMT) genes. Data showed that the expressions of MAT1A was 1.3 fold in G2-FTSJ2 than in HepG2 and Huh7. Contrary, MAT2A showed down regulation in G2-FTSJ2 than in HepG2 and Huh7 cell. Interestingly, overexpressed FTSJ2 in te671 cell decreased transcription of SAHH without affecting the RNA level of MAT1A and MAT2A. Our Results showed that FTSJ2 could participate in SAM metabolism cycle by affected the MAT and SAHH. In conclusion, the porcine FTSJ2 protein exhibits the potential function as methyltransferase in eukaryotic cells, especially responsible for abnormal methionine metabolism in HCC and neuroblastoma cell lines.誌謝…………………………………………………………………………i 摘要…………………………………………………………………………ii Abstract…………………………………………………………………….iii 表次……………………………………………………………………………vi 圖次……………………………………………………………………….......vii 壹、緒言………………………………………………………………….11 貳、文獻檢討………………………………………………………………12 一、 甲硫胺酸代謝循環與甲基化之關係…………………………………12 二、 已知甲硫胺酸代謝異常之相關疾病…………………………………18 三、 甲基轉化酶同源基因FTSJ2之介紹…………………………………24 四、 FTSJ2甲基轉化酶與甲硫胺酸代謝循環之探討.………………….32 五、FTSJ2基因於真核生物的功能性研究……………………………….35 叁、材料與方法…………………………………………………………………36 一、 組織之RNA萃取與cDNA之製備…………………………………36 二、 真核細胞豬隻FTSJ2表現質體pIRE-DsRED2-FTSJ2之建構……37 三、 肝癌細胞株HepG2與神經髓母細胞瘤細胞株te671來源與保存…44 四、 以細胞電穿孔法外源表現豬FTSJ2基因於細胞株HepG2及 te671…………………………………………………………………..45 五、外源FTSJ2表現偵測與甲硫胺酸代謝相關基因表現分析…………..46 六、細胞移動分析…………………………………………………………49 七、細胞侵襲(invasion)能力測試…………………………………………49 八、蛋白結構預測………………………………………………………50 九、北方墨點轉漬…………………………………………………………51 十、細胞免疫螢光染色……………………………………………………51 十一、統計分析……………………………………………………………52 肆、結果與討論……………………………………………………………53 一、FTSJ1與FTSJ2於人體組織表現之差異……………………………53 二、以RT-PCR分析FTSJ1與FTSJ2於肝癌細胞株之表現……………56 三、豬FTSJ2蛋白預測結構與人類內源FTSJ2蛋白結構比較…………56 四、轉染甲基轉移酶FTSJ2基因對細胞甲硫胺酸代謝調控的影響……58 (一) 反轉錄聚合反應分析FTSJ2轉殖對神經髓母細胞瘤 te671細胞株的影響……………………………….……59 (二) 反轉錄聚合鏈反應分析FTSJ2轉殖對HepG2肝癌細胞株的影響………………………………………………………………59 (三) FTSJ2轉殖對甲硫胺酸代謝循環相關蛋白之影響………….62 (四) 細胞免疫螢光染色分析FTSJ2之胞內分布………………….64 五、FTSJ2基因轉染對神經髓母細胞瘤te671細胞生長之影響………..67 六、FTSJ2調控SAHH表現量對F-actin之影響……………………………67 伍、結論……………………………………………………………………74 陸、參考文獻………………………………………………………………7

Radiographic Outcomes of Ganz versus Modified Triple Osteotomies in Femoral Head Medialization and Coverage in Acetabular Dysplasia

Variable techniques in periacetabular osteotomy have been formulated for the treatment of acetabular dysplasia. However, few studies have compared the radiographic outcomes between different osteotomy types. This study compared modified triple innominate (MTI) osteotomy and Ganz osteotomy with respect to radiographic outcomes. Patients receiving MTI osteotomies and Ganz osteotomies at any time between 2006 and 2018 in a tertiary medical centre were recruited. Only patients with unilateral osteotomies were recruited to eliminate potential influence from the contralateral hip following periacetabular osteotomy. Patients having hip-joint dislocation, receiving simultaneous proximal femoral osteotomy, or having fewer than 2 years of follow-up were excluded. The radiographic parameters of preoperative and postoperative anteroposterior radiographs of the pelvis were measured, and Sharp&rsquo;s angle (SA), the lateral centre-edge angle (CE angle), the femoral head extrusion index (FHEI), and the centre-head distance discrepancy (CHDD) were included for comparison. Among 55 participants, 23 received MTI osteotomies and 32 received Ganz osteotomies. The mean age at which patients underwent surgery was 21.9 years in the Ganz osteotomy group and 21.1 years in the MTI group. The mean follow-up length was 2.5 years. The preoperative radiographic parameters between groups differed only slightly and nonsignificantly. Both groups exhibited significantly improved SA, LCEA, and FHEI after surgery. The Ganz osteotomy group exhibited more favourable postoperative FHEI (13.5 vs. 24.3, p &lt; 0.0001), CHDD (3.7 vs. 11.5, p &lt; 0.0001), Sharp angle (45.0 vs. 41.8, p = 0.0489) and CE angles (28.3 vs. 21.1, p = 0.029) compared with the MTI osteotomy group. Notably, CHDD became better and worse following Ganz and MTI osteotomies, respectively; this suggests that the femoral head is pushed laterally in modified triple osteotomy. With respect to femoral head coverage and the medialization of the femoral head, Ganz osteotomy exhibits more favourable corrections in postoperative radiographic parameters than does MTI osteotomy

Radiographic Outcomes of Ganz versus Modified Triple Osteotomies in Femoral Head Medialization and Coverage in Acetabular Dysplasia

Variable techniques in periacetabular osteotomy have been formulated for the treatment of acetabular dysplasia. However, few studies have compared the radiographic outcomes between different osteotomy types. This study compared modified triple innominate (MTI) osteotomy and Ganz osteotomy with respect to radiographic outcomes. Patients receiving MTI osteotomies and Ganz osteotomies at any time between 2006 and 2018 in a tertiary medical centre were recruited. Only patients with unilateral osteotomies were recruited to eliminate potential influence from the contralateral hip following periacetabular osteotomy. Patients having hip-joint dislocation, receiving simultaneous proximal femoral osteotomy, or having fewer than 2 years of follow-up were excluded. The radiographic parameters of preoperative and postoperative anteroposterior radiographs of the pelvis were measured, and Sharp’s angle (SA), the lateral centre-edge angle (CE angle), the femoral head extrusion index (FHEI), and the centre-head distance discrepancy (CHDD) were included for comparison. Among 55 participants, 23 received MTI osteotomies and 32 received Ganz osteotomies. The mean age at which patients underwent surgery was 21.9 years in the Ganz osteotomy group and 21.1 years in the MTI group. The mean follow-up length was 2.5 years. The preoperative radiographic parameters between groups differed only slightly and nonsignificantly. Both groups exhibited significantly improved SA, LCEA, and FHEI after surgery. The Ganz osteotomy group exhibited more favourable postoperative FHEI (13.5 vs. 24.3, p p p = 0.0489) and CE angles (28.3 vs. 21.1, p = 0.029) compared with the MTI osteotomy group. Notably, CHDD became better and worse following Ganz and MTI osteotomies, respectively; this suggests that the femoral head is pushed laterally in modified triple osteotomy. With respect to femoral head coverage and the medialization of the femoral head, Ganz osteotomy exhibits more favourable corrections in postoperative radiographic parameters than does MTI osteotomy

FTSJ2, a heat shock-inducible mitochondrial protein, suppresses cell invasion and migration.

Ribosomal RNA large subunit methyltransferase J (RrmJ), an Escherichia coli heat shock protein, is responsible for 2'-O-ribose methylation in 23S rRNA. In mammals, three close homologs of RrmJ have been identified and have been designated as FTSJ1, FTSJ2 and FTSJ3; however, little is known about these genes. In this study, we characterized the mammalian FTSJ2, which was the most related protein to RrmJ in a phylogenetic analysis that had similar amino acid sequence features and tertiary protein structures of RrmJ. FTSJ2 was first identified in this study as a nucleus encoded mitochondrial protein that preserves the heat shock protein character in mammals in which the mRNA expressions was increased in porcine lung tissues and A549 cells after heat shock treatment. In addition, a recent study in non-small cell lung cancer (NSCLC) suggested that the FTSJ2 gene is located in a novel oncogenic locus. However, our results demonstrate that the expression of FTSJ2 mRNA was decreased in the more invasive subline (CL1-5) of the lung adenocarcinoma cells (CL1) compared with the less invasive subline (CL1-0), and overexpression of FTSJ2 resulted in the inhibition of cell invasion and migration in the rhabdomyosarcoma cell (TE671). In conclusion, our findings indicate that mammalian FTSJ2 is a mitochondrial ortholog of E. coli RrmJ and conserves the heat shock protein properties. Moreover, FTSJ2 possesses suppressive effects on the invasion and migration of cancer cells

Comparison of the h<i>FTSJ2</i> mRNA expression levels in two lung cancer sublines (CL1-0 and CL1-5).

<p>(<b>A</b>) Morphology of CL1-0 and CL1-5 cells. (<b>B</b>) Determination of the h<i>FTSJ2</i> mRNA expression levels in the CL1-0 and CL1-5 cells in triplicate. (<b>C</b>) Relative quantification of the h<i>FTSJ2</i> mRNA expression. <i>GAPDH</i> mRNA was used as an internal control. The values are equal to = the means±SE; n = 3; **<i>P</i><0.01 vs. the non-heat shock group.</p