Bibliografias temáticas / Cai zheng bu

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Literatura científica selecionada sobre o tema "Cai zheng bu"

Autor: Grafiati
Publicado: 25 de julho de 2024
Última modificação: 31 de julho de 2024

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Artigos de revistas sobre o assunto "Cai zheng bu"

1

Rahman, Mohammad L., Xiao-Ou Shu, Douglas Walker, Dean P. Jones, Wei Hu, Bu-tian Ji, Batel Blechter et al. "Abstract 6056: A nested case-control study of untargeted plasma metabolomics and lung cancer risk among never-smoking women in the prospective Shanghai Women’s Health Study". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 6056. http://dx.doi.org/10.1158/1538-7445.am2023-6056.

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Abstract Background: The etiology of lung cancer among never-smokers is unclear despite 15% of cases in men and 53% in women worldwide are not smoking-related. Metabolomics provides a snapshot of dynamic biochemical activities, including those found to be driving tumor formation and progression. This study used untargeted metabolomics with network analysis to agnostically identify network modules and independent metabolites in pre-diagnostic blood samples among never-smokers to further understand the pathogenesis of lung cancer. Methods: Within the prospective Shanghai Women’s Health Study, we conducted a nested case-control study of 395 never-smoking incident lung cancer cases and 395 never-smoking controls matched on age. We performed liquid chromatography high-resolution mass spectrometry to quantify 20,348 unique metabolic features in plasma. Because metabolic features are expected to be highly correlated and more likely to be involved in biological processes as a network of intertwined features than individually, we agnostically constructed 28 network modules using a weighted correlation network analysis approach. The associations between metabolite network modules and individual metabolites with lung cancer were assessed using conditional logistic regression models, adjusting for age, body mass index, and exposure to environmental tobacco smoke. We accounted for multiple testing using a false discovery rate (FDR) < 0.20. Results: We identified a network module of 122 metabolic features enriched in lysophosphatidylethanolamines that was associated with all lung cancer combined (p = 0.001, FDR = 0.028) and lung adenocarcinoma (p = 0.002, FDR = 0.056) and another network module of 440 metabolic features that was associated with lung adenocarcinoma (p = 0.014, FDR = 0.196). Metabolic features were enriched in pathways associated with cell growth and proliferation, including oxidative stress, bile acid biosynthesis, and metabolism of nucleic acids, carbohydrates, and amino acids, including 1-carbon compounds. Conclusions: Our prospective study suggests that untargeted plasma metabolomics in pre-diagnostic samples could provide new insights into the etiology of lung cancer in never-smokers. Replication and further characterization of these associations are warranted. Citation Format: Mohammad L. Rahman, Xiao-Ou Shu, Douglas Walker, Dean P. Jones, Wei Hu, Bu-tian Ji, Batel Blechter, Jason YY Wong, Qiuyin Cai, Gong Yang, Tu-Tang Gao, Wei Zheng, Nathaniel Rothman, Qing Lan. A nested case-control study of untargeted plasma metabolomics and lung cancer risk among never-smoking women in the prospective Shanghai Women’s Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6056.
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Rahman, Mohammad L., Charles E. Breeze, Xiao-Ou Shu, Jason YY Wong, Andres Cardenas, Xuting Wang, Bu-Tian Ji et al. "Abstract 3483: Epigenome-wide association study of lung cancer among never-smokers in two prospective cohorts in Shanghai". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 3483. http://dx.doi.org/10.1158/1538-7445.am2023-3483.

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Abstract Background: The etiology of lung cancer among never-smokers has not been adequately elucidated despite that globally15% of lung cancer cases in men and 53% in women are not smoking-related. Epigenetic modifications, including changes in DNA methylation (DNAm), have been suggested as possible underlying mechanisms. However, only a few prospective epigenome-wide association studies (EWAS) of lung cancer incidence have been conducted, all exclusively focused on DNAm in peripheral blood cells and included a minimal number of never-smokers. We aimed to investigate genome-wide DNAm associations and epigenetic age acceleration with future risk of lung cancer among never-smokers using pre-diagnostic oral rinse samples. Methods: We conducted a case-control study of 80 never-smoking incident lung cancer cases and 83 comparable never-smoking controls nested in two large prospective cohorts: the Shanghai Women’s Health Study and Shanghai Men’s Health Study. DNAm was measured using the Illumina EPIC array. The top 50 differentially methylated positions (DMPs) were identified from a discovery sample and tested for replication in a validation sample using robust linear regression models. We also conducted an EWAS in the pooled sample. We examined functional overlap enrichment across chromatin states and histone mark broadPeaks for the top 1000 DMPs using eFORGE and constructed enrichment biological pathways analyses. Results: Across discovery and pooled EWAS, we identified four DMPs associated with lung cancer at the epigenome-wide significance level of P<8.0x10-8 (cg01411366: SLC9A10, P=7.23x10-08; cg00811020: NAA30, P=3.95x10-08; cg05658193: EIF2A, SERP1, P=5.02x10-08; and cg09198866: unannotated, P=5.39x10-09). The top 1000 DMPs were significantly enriched in epithelial regulatory regions and were associated with small GTPase-mediated signal transduction pathways. Furthermore, epigenetic age acceleration, measured by the GrimAge clock was prospectively associated with an increased risk of lung cancer (OR=1.19 per year of acceleration; 95% CI: 1.06-1.34) in logistic regression models. Conclusions: To our knowledge, this is the first prospective EWAS of lung cancer among never-smokers using oral rinse samples. Our results show that DNAm in pre-diagnostic oral rinse samples can provide new insights into lung cancer etiology and risk factors. Citation Format: Mohammad L. Rahman, Charles E. Breeze, Xiao-Ou Shu, Jason YY Wong, Andres Cardenas, Xuting Wang, Bu-Tian Ji, Wei Hu, Batel Blechter, Qiuyin Cai, H Dean Hosgood, Gong Yang, Jianxin Shi, Jirong Long, Yu-Tang Gao, Douglas Bell, Wei Zheng, Qing Lan, Nathaniel Rothman. Epigenome-wide association study of lung cancer among never-smokers in two prospective cohorts in Shanghai [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3483.
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Blechter, Batel, Parichoy Pal Choudhury, Xiao-ou Shu, Wei Zheng, Qiuyin Cai, Gong Yang, Jason Y. Y. Wong et al. "Abstract 2254: Risk models for lung cancer in never-smoking women in Shanghai with implications for screening". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 2254. http://dx.doi.org/10.1158/1538-7445.am2022-2254.

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Abstract Background: The majority of female lung cancer cases in Asia are never-smokers with distinct risk factor profiles. Given the high burden of disease in this population, there is an increasing need to improve the understanding of lung cancer. Current risk models for lung cancer focus on active smokers and individuals of European ancestry. Therefore, we developed statistical models by integrating genetic and environmental risk factors to estimate absolute and population attribute risk of lung cancer among never-smoking women in Asia. Methods: We built absolute risk models for lung cancer among never-smoking women using data from 71,300 women (760 incident cases) in the Shanghai Women’s Health Study (SWHS), a population-based prospective cohort study. Relative risks were estimated using a multivariable Cox regression model with questionnaire-based risk factors. To account for missing genetic data for some subjects, we simulated genotypes for 10 common single nucleotide polymorphisms (SNP) using information on minor allele frequencies (MAF) and odds ratio estimates from previous genome-wide association studies (GWAS), conditional on family history of lung cancer. We used the iCARE tool to build two models for predicting lifetime (40 years) and 6-year absolute risk of lung cancer using age-specific lung cancer incidence rates, age-specific competing mortality rates, and risk factor distribution with: 1) questionnaire-based risk factors only and 2) questionnaire and genetic data. We then used the full absolute risk model to estimate the population attributable risk (PAR) due to modifiable risk factors, namely coal use and exposure to environmental tobacco smoke (ETS). Results: The questionnaire-based only model included family history of lung cancer, coal use, exposure to ETS, and body mass index (BMI). The full model also included data on 10 lung cancer related SNPs from our previous GWAS and had a wider spread in distribution of absolute lifetime risk (median=2.41%; range=0.43-12.36) compared to the questionnaire-based only model (median=2.72%; range=1.93-4.87). We used the full model to estimate the PAR and found that 1.74% and 6.33% of lung cancer cases could be prevented if never-smoking women in Shanghai did not use coal and were not exposed to ETS, respectively. Furthermore, we found that the full model estimated that 2.5% of the study population had a 6-year absolute risk of lung cancer higher than 1.51%, which is the suggested risk threshold for screening by existing risk models. Conclusion: We built risk models for never-smoking Asian women and estimated the contribution of coal use and ETS to the burden of lung cancer in Shanghai. This initial work shows promise for expanding and validating risk models in this population with potential translational implications, such as providing insight to identifying high risk individuals that may be eligible for lung cancer screening and primary prevention efforts. Citation Format: Batel Blechter, Parichoy Pal Choudhury, Xiao-ou Shu, Wei Zheng, Qiuyin Cai, Gong Yang, Jason Y.Y. Wong, Bu-Tian Ji, Wei Hu, Anne Rositch, Nilanjan Chatterjee, Nathaniel Rothman, Qing Lan. Risk models for lung cancer in never-smoking women in Shanghai with implications for screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2254.
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Wang, Bu Hai, Cai Yue Chen, Xian Zhang, Yu Xiang Huang, Yi Chun Zeng, Lei Li, Mao Qi Wang et al. "Abstract 5091: The early change of serum interleukin 14α levels predicts the response to anti-PD-1 therapy in cancer". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 5091. http://dx.doi.org/10.1158/1538-7445.am2022-5091.

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Abstract Background: Targeting programmed cell death-1 (PD-1) or programmed cell death ligand-1 (PD-L1) has been shown improved clinical efficacy in a wide range of tumor types. We evaluated serum interleukin 14α (IL14α) as a biomarker to predict the response of anti- PD-1 therapy. Patients and methods: Thirty advanced cancer patients treated with PD-1 inhibitor were enrolled in this study. Serum levels of IL-14α were tested at baseline and after 2 cycles of treatment. Result: Among these 30 patients, the mean expression level of IL14α before treatment was 2.1±1.21, whereas the mean level of IL14α after 2 cycles was 1.99±0.82. There were no association between the expression levels of IL14α and clinical outcome. Early change of IL14α after 2-cycles of anti-PD-1 therapy was calculated as delta IL14α % change = (IL14α level after 2 cycles - IL14α level before treatment)/IL14α level before treatment*100%. Receiver operating characteristic (ROC) was analyzed to get a cutoff point of delta IL14α % change as 2.46% (Sensitivity 85.71%, Specificity 62.5%; AUC=0.7277, P=0.034). Using this cutoff to subgroup the patients, we found higher delta IL14α % change was significantly associated with superior overall response to anit-PD-1 therapy (p=0.0072) and had a better progression free survival (p=0.0039). Conclusion: Early changes of serum IL14α level may be a useful predicting factor in advanced cancer patients with anti-PD-1 therapy. Keywords: IL14α, serum biomarker, anti-PD-1 therapy response, cancer Citation Format: Bu Hai Wang, Cai Yue Chen, Xian Zhang, Yu Xiang Huang, Yi Chun Zeng, Lei Li, Mao Qi Wang, Jing Liang Guo, Qiu Xian Li, Long Shen, Juan J. Gu, Yi Chen Liang. The early change of serum interleukin 14α levels predicts the response to anti-PD-1 therapy in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5091.
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Itelman, E., M. Perelman, D. Kent, N. Bibar, G. Segal, L. Negru e A. Dagan. "POS0784 LOW COMPLEMENT LEVELS ARE ASSOCIATED WITH HIGHER MORTALITY IN HOSPITALIZED PATIENTS WITH POSITIVE ANTIPHOSPHOLIPID ANTIBODIES". Annals of the Rheumatic Diseases 81, Suppl 1 (23 de maio de 2022): 679.1–679. http://dx.doi.org/10.1136/annrheumdis-2022-eular.4815.

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BackgroundAntiphospholipid Syndrome is an autoimmune disease characterized by increased risk for vascular thrombosis (arterial and/or venous) thrombosis and/or pregnancy morbidity in the presence of antiphospholipid antibodies. The mechanisms by which aPLs induce thrombosis are unclear; several have been suggested, among them complement activation.(1-2) The complement system is a system of enzymes and regulatory proteins of the innate immune system that play a crucial role in the inflammatory response to various pathogenic stimuli. The complement and coagulation pathways are interconnected, and expanding evidence indicates that complement may be activated in patients with antiphospholipid syndrome (3-5).ObjectivesOur study was intended to better characterize the complicated relations between antiphospholipid antibodies and complement activation among hospitalized patients with antiphospholipid syndrome and its impact on short- and long-term prognosisMethodsA retrospective cohort studies. Clinical and prognostic data of hospitalized patients with antiphospholipid syndrome and a measurement of complement levels (C3 or C4) were obtained. Rates of long-term mortality, one-year mortality, deep vein thrombosis (DVT), and pulmonary emboli (PE) were compared between patients with low complement levels and patients with normal complement levels. Low complement was defined as C3 < 90 mg/dl or C4 < 10 mg/dl. A multivariate analysis was performed to control for Anticardiolipin levels, β₂ macroglobulin levels and RVVT ratio.ResultsComplete data was available for 6,599 patients, of which 712 (11%) had low complement levels. The median age of the cohort was 47.7, and most of the patients were females (56%). Patients with low complement levels had significantly higher mortality rates 30% vs. 18%, p < 0.001 for long-term mortality (Figure 1) and 15% vs. 5%, p < 0.001 for 1 year mortality when compared to patients with normal complement levels. DVT and PE rates were similar (4% vs 3.8%, P = 0.78 and 4% vs 2.4%, P = 0.13 respectively). Results of the multivariate analysis (Table 1) were consistent and showed that patients with low complement levels had 111% higher mortality rates (CI 1.52-2.90, P < 0.001).Table 1.Multivariate Analysis for long term mortalityMultivariate AnalysisOR (CI)pLow Complement2.11 [1.52, 2.90]<0.001Anticardiolipin IGG1.00 [1.00, 1.01]0.243Anticardiolipin IGM0.99 [0.98, 1.00]0.084β₂ IGM1.01 [1.00, 1.01]0.017β₂ IGG1.00 [0.99, 1.00]0.663RVVT Ratio0.99 [0.63, 1.52]0.954Figure 1.Cumulative 10-Year survivalConclusionIn hospitalized patients with high aPLs, low complement levels are associated with significantly higher mortality rates. This finding is in correlation with recent literature, suggesting an important role for complement activation in APS.References[1]Chaturvedi S, Brodsky RA, McCrae KR. Complement in the pathophysiology of the antiphospholipid syndrome. Front Immunol. 2019 Mar 14;10:449.[2]Bu C, Gao L, Xie W, Zhang J, He Y, Cai G, et al. beta2-glycoprotein i is a cofactor for tissue plasminogen activator-mediated plasminogen activation. Arthritis Rheum. 2009 Feb;60(2):559–568.[3]Tedesco F, Borghi MO, Gerosa M, Chighizola CB, Macor P, Lonati PA, et al. Pathogenic role of complement in antiphospholipid syndrome and therapeutic implications. Front Immunol. 2018 Jun 19;9:1388.[4]Oku K, Nakamura H, Kono M, Ohmura K, Kato M, Bohgaki T, et al. Complement and thrombosis in the antiphospholipid syndrome. Autoimmun Rev. 2016 Oct;15(10):1001–1004.[5]Salmon JE, Girardi G, Holers VM. Complement activation as a mediator of antiphospholipid antibody induced pregnancy loss and thrombosis. Ann Rheum Dis. 2002 Nov;61 Suppl 2:ii46–50.Disclosure of InterestsNone declared
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Teses / dissertações sobre o assunto "Cai zheng bu"

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Zhang, Shifei. "Shanghai ai zheng zi zhu zu zhi yan jiu zu yuan can yu, she hui zhi chi he she hui xue xi de zeng quan xiao guo /". online access from Digital dissertation consortium, 2001. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3025931.

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So, Yiu Cheong. "Dang dai Zhongguo de zu qun zheng zhi : cong "min zu wen xue" dao "xi bu wen xue" /". View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?HUMA%202007%20SO.

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Zhang, Jieneng. "Jin shi liu nian (1989-2005) Xianggang Zhong yao bu liang fan ying shi gu de fen xi yan jiu /". click here to view the abstract and table of contents, 2006. http://net3.hkbu.edu.hk/~libres/cgi-bin/thesisab.pl?pdf=b1998697xa.pdf.

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4

Poon, Hon-fong. "A critical study of Chunqiu Zuoshizhuan Buzhu of Shen Qinhan (1775-1832) = Shen Qinhan (1775-1832) "Chun qiu Zuo shi zhuan bu zhu" jiao zheng /". Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23339639.

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Livros sobre o assunto "Cai zheng bu"

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Mianchi Xian (China). Cai zheng ju. Mianchi Xian cai zheng zhi: Nei bu zi liao. Sanmenxia Shi: Mianchi Xian cai zheng ju cai zheng zhi bian xie zu, 1986.

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2

Xun, Lu. Cai wei ben yue: "A Q zheng zhuan" san bu qu. Xinbei Shi: Pu tian chu ban she, 2015.

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3

Xintai Shi (China). Cai zheng ju. Cai zheng zhi bian wei hui. Shandong Sheng Xintai Shi cai zheng zhi (nei bu zi liao). [China]: [Publisher not identified], 1988.

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4

Zhong yang cai jing da xue. Tu shu guan. Qing mo Minguo cai zheng shi liao ji kan bu bian. Beijing: Guo jia tu shu guan chu ban she, 2008.

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5

Zhizhong, Wu, ed. Jiao Cai zhong lang ji shu zheng: [10 juan, wai ji 1 juan] ; Cai zhong lang wen ji bu : [1 juan]. Shanghai: Shanghai gu ji chu ban she, 2002.

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6

Hengshan, Zhang. Dang zheng gan bu fa zhi jiao cheng. Beijing: Zhong guo ren min da xue chu ban she, 2017.

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7

Ling, Wenchao. Zoumalou Wu jian cai ji bu shu zheng li yu yan jiu. Guilin Shi: Guangxi shi fan da xue chu ban she, 2015.

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8

ping, Yang xiao. Yong bao qing zheng lian jie de zheng zhi ben se. Bei jing: Ren min chu ban she, 2015.

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9

Zhong xuan bu xuan chuan jiao yu ju. Gong wu yuan yi fa xing zheng du ben. Bei jing: Zhong guo zheng fa ta xue chu ban she, 2001.

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10

Zheng quan zhuan ye zi ge kao shi ming ti yan jiu zu. Fa bu zheng quan yan jiu bao gao ye wu. Chengdou: Xi nan cai jing da xue chu ban she, 2016.

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