Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 19 entries
Sorted by: Best Match Show Resources per page
Transcriptome-metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism.

Toxicology reports

Roede JR, Uppal K, Park Y, Tran V, Jones DP.
PMID: 27722094
Toxicol Rep. 2014;1:435-444. doi: 10.1016/j.toxrep.2014.07.006. Epub 2014 Jul 24.

A combination of the herbicide paraquat (PQ) and fungicide maneb (MB) has been linked to Parkinson's disease. Previous studies show that this involves an additive toxicity with at least two different mechanisms. However, detailed understanding of mixtures is often...

Cite
Roede JR, Uppal K, Park Y, et al. Transcriptome-metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism. Toxicol Rep. 2014;1:435-444doi: 10.1016/j.toxrep.2014.07.006.
Roede, J. R., Uppal, K., Park, Y., Tran, V., & Jones, D. P. (2014). Transcriptome-metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism. Toxicology reports, 1435-444. https://doi.org/10.1016/j.toxrep.2014.07.006
Roede, James R, et al. "Transcriptome-metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism." Toxicology reports vol. 1 (2014): 435-444. doi: https://doi.org/10.1016/j.toxrep.2014.07.006
Roede JR, Uppal K, Park Y, Tran V, Jones DP. Transcriptome-metabolome wide association study (TMWAS) of maneb and paraquat neurotoxicity reveals network level interactions in toxicologic mechanism. Toxicol Rep. 2014;1:435-444. doi: 10.1016/j.toxrep.2014.07.006. Epub 2014 Jul 24. PMID: 27722094; PMCID: PMC5053767.
Copy Download .nbib Format: NLM
A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS.

The annals of applied statistics

Zhao Y, Kang J, Yu T.
PMID: 25984253
Ann Appl Stat. 2014 Jun;8(2):999-1021. doi: 10.1214/14-AOAS719.

It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with...

Cite
Zhao Y, Kang J, Yu T. A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS. Ann Appl Stat. 2014;8(2):999-1021doi: 10.1214/14-AOAS719.
Zhao, Y., Kang, J., & Yu, T. (2014). A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS. The annals of applied statistics, 8(2), 999-1021. https://doi.org/10.1214/14-AOAS719
Zhao, Yize, et al. "A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS." The annals of applied statistics vol. 8,2 (2014): 999-1021. doi: https://doi.org/10.1214/14-AOAS719
Zhao Y, Kang J, Yu T. A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS. Ann Appl Stat. 2014 Jun;8(2):999-1021. doi: 10.1214/14-AOAS719. PMID: 25984253; PMCID: PMC4433170.
Copy Download .nbib Format: NLM
Restoration of Monotonicity Respecting in Dynamic Regression.

Journal of the American Statistical Association

Huang Y.
PMID: 29430068
J Am Stat Assoc. 2017;112(518):613-622. doi: 10.1080/01621459.2016.1149070. Epub 2017 Mar 30.

Dynamic regression models, including the quantile regression model and Aalen's additive hazards model, are widely adopted to investigate evolving covariate effects. Yet lack of monotonicity respecting with standard estimation procedures remains an outstanding issue. Advances have recently been made,...

Cite
Huang Y. Restoration of Monotonicity Respecting in Dynamic Regression. J Am Stat Assoc. 2017;112(518):613-622doi: 10.1080/01621459.2016.1149070.
Huang, Y. (2017). Restoration of Monotonicity Respecting in Dynamic Regression. Journal of the American Statistical Association, 112(518), 613-622. https://doi.org/10.1080/01621459.2016.1149070
Huang, Yijian. "Restoration of Monotonicity Respecting in Dynamic Regression." Journal of the American Statistical Association vol. 112,518 (2017): 613-622. doi: https://doi.org/10.1080/01621459.2016.1149070
Huang Y. Restoration of Monotonicity Respecting in Dynamic Regression. J Am Stat Assoc. 2017;112(518):613-622. doi: 10.1080/01621459.2016.1149070. Epub 2017 Mar 30. PMID: 29430068; PMCID: PMC5800531.
Copy Download .nbib Format: NLM
Circulating Progenitor Cells in Patients With Coronary Artery Disease and Renal Insufficiency.

JACC. Basic to translational science

Mehta A, Tahhan AS, Liu C, Dhindsa DS, Nayak A, Hooda A, Moazzami K, Islam SJ, Rogers SC, Almuwaqqat Z, Mokhtari A, Hesaroieh I, Ko YA, Waller EK, Quyyumi AA.
PMID: 32875168
JACC Basic Transl Sci. 2020 Aug 12;5(8):770-782. doi: 10.1016/j.jacbts.2020.06.006. eCollection 2020 Aug.

Patients with coronary artery disease and renal insufficiency (RI) (estimated glomerular filtration rate 

Cite
Mehta A, Tahhan AS, Liu C, et al. Circulating Progenitor Cells in Patients With Coronary Artery Disease and Renal Insufficiency. JACC Basic Transl Sci. 2020;5(8):770-782doi: 10.1016/j.jacbts.2020.06.006.
Mehta, A., Tahhan, A. S., Liu, C., Dhindsa, D. S., Nayak, A., Hooda, A., Moazzami, K., Islam, S. J., Rogers, S. C., Almuwaqqat, Z., Mokhtari, A., Hesaroieh, I., Ko, Y. A., Waller, E. K., & Quyyumi, A. A. (2020). Circulating Progenitor Cells in Patients With Coronary Artery Disease and Renal Insufficiency. JACC. Basic to translational science, 5(8), 770-782. https://doi.org/10.1016/j.jacbts.2020.06.006
Mehta, Anurag, et al. "Circulating Progenitor Cells in Patients With Coronary Artery Disease and Renal Insufficiency." JACC. Basic to translational science vol. 5,8 (2020): 770-782. doi: https://doi.org/10.1016/j.jacbts.2020.06.006
Mehta A, Tahhan AS, Liu C, Dhindsa DS, Nayak A, Hooda A, Moazzami K, Islam SJ, Rogers SC, Almuwaqqat Z, Mokhtari A, Hesaroieh I, Ko YA, Waller EK, Quyyumi AA. Circulating Progenitor Cells in Patients With Coronary Artery Disease and Renal Insufficiency. JACC Basic Transl Sci. 2020 Aug 12;5(8):770-782. doi: 10.1016/j.jacbts.2020.06.006. eCollection 2020 Aug. PMID: 32875168; PMCID: PMC7452291.
Copy Download .nbib Format: NLM
Progenitor Cell Therapy to Treat Acute Myocardial Infarction: The Promise of High-Dose Autologous CD34(+) Bone Marrow Mononuclear Cells.

Stem cells international

Poole JC, Quyyumi AA.
PMID: 23737803
Stem Cells Int. 2013;2013:658480. doi: 10.1155/2013/658480. Epub 2013 Apr 28.

ST elevation myocardial infarction (STEMI) is associated with an increased risk for congestive heart failure and long-term mortality despite the widespread use of thrombolysis and catheter-based revascularization. The need for improved post-STEMI therapies has led to a surge of...

Cite
Poole JC, Quyyumi AA. Progenitor Cell Therapy to Treat Acute Myocardial Infarction: The Promise of High-Dose Autologous CD34(+) Bone Marrow Mononuclear Cells. Stem Cells Int. 2013;2013:658480doi: 10.1155/2013/658480.
Poole, J. C., & Quyyumi, A. A. (2013). Progenitor Cell Therapy to Treat Acute Myocardial Infarction: The Promise of High-Dose Autologous CD34(+) Bone Marrow Mononuclear Cells. Stem cells international, 2013658480. https://doi.org/10.1155/2013/658480
Poole, Joseph C, and Quyyumi, Arshed A. "Progenitor Cell Therapy to Treat Acute Myocardial Infarction: The Promise of High-Dose Autologous CD34(+) Bone Marrow Mononuclear Cells." Stem cells international vol. 2013 (2013): 658480. doi: https://doi.org/10.1155/2013/658480
Poole JC, Quyyumi AA. Progenitor Cell Therapy to Treat Acute Myocardial Infarction: The Promise of High-Dose Autologous CD34(+) Bone Marrow Mononuclear Cells. Stem Cells Int. 2013;2013:658480. doi: 10.1155/2013/658480. Epub 2013 Apr 28. PMID: 23737803; PMCID: PMC3655659.
Copy Download .nbib Format: NLM
Bootstrap for the case-cohort design.

Biometrika

Huang Y.
PMID: 25170175
Biometrika. 2014 Jun;101(2):465-476. doi: 10.1093/biomet/asu004.

The case-cohort design facilitates economical investigation of risk factors in a large survival study, with covariate data collected only from the cases and a simple random subset of the full cohort. Methods that accommodate the design have been developed...

Cite
Huang Y. Bootstrap for the case-cohort design. Biometrika. 2014;101(2):465-476doi: 10.1093/biomet/asu004.
Huang, Y. (2014). Bootstrap for the case-cohort design. Biometrika, 101(2), 465-476. https://doi.org/10.1093/biomet/asu004
Huang, Yijian. "Bootstrap for the case-cohort design." Biometrika vol. 101,2 (2014): 465-476. doi: https://doi.org/10.1093/biomet/asu004
Huang Y. Bootstrap for the case-cohort design. Biometrika. 2014 Jun;101(2):465-476. doi: 10.1093/biomet/asu004. PMID: 25170175; PMCID: PMC4143157.
Copy Download .nbib Format: NLM
Cardiovascular Disease Biomarkers and suPAR in Predicting Decline in Renal Function: A Prospective Cohort Study.

Kidney international reports

Hayek SS, Ko YA, Awad M, Ahmed H, Gray B, Hosny KM, Aida H, Tracy MJ, Wei C, Sever S, Reiser J, Quyyumi AA.
PMID: 29142970
Kidney Int Rep. 2017 Feb 09;2(3):425-432. doi: 10.1016/j.ekir.2017.02.001. eCollection 2017 May.

INTRODUCTION: Soluble urokinase-type plasminogen activator receptor (suPAR) strongly predicts outcomes and incident chronic kidney disease (CKD) in patients with cardiovascular disease (CVD). Whether the association between suPAR and CKD is a reflection of its overall association with chronic inflammation...

Cite
Hayek SS, Ko YA, Awad M, et al. Cardiovascular Disease Biomarkers and suPAR in Predicting Decline in Renal Function: A Prospective Cohort Study. Kidney Int Rep. 2017;2(3):425-432doi: 10.1016/j.ekir.2017.02.001.
Hayek, S. S., Ko, Y. A., Awad, M., Ahmed, H., Gray, B., Hosny, K. M., Aida, H., Tracy, M. J., Wei, C., Sever, S., Reiser, J., & Quyyumi, A. A. (2017). Cardiovascular Disease Biomarkers and suPAR in Predicting Decline in Renal Function: A Prospective Cohort Study. Kidney international reports, 2(3), 425-432. https://doi.org/10.1016/j.ekir.2017.02.001
Hayek, Salim S, et al. "Cardiovascular Disease Biomarkers and suPAR in Predicting Decline in Renal Function: A Prospective Cohort Study." Kidney international reports vol. 2,3 (2017): 425-432. doi: https://doi.org/10.1016/j.ekir.2017.02.001
Hayek SS, Ko YA, Awad M, Ahmed H, Gray B, Hosny KM, Aida H, Tracy MJ, Wei C, Sever S, Reiser J, Quyyumi AA. Cardiovascular Disease Biomarkers and suPAR in Predicting Decline in Renal Function: A Prospective Cohort Study. Kidney Int Rep. 2017 Feb 09;2(3):425-432. doi: 10.1016/j.ekir.2017.02.001. eCollection 2017 May. PMID: 29142970; PMCID: PMC5678674.
Copy Download .nbib Format: NLM
Pilot randomized controlled trial of a Mediterranean diet or diet supplemented with fish oil, walnuts, and grape juice in overweight or obese US adults.

BMC nutrition

Jaacks LM, Sher S, Staercke C, Porkert M, Alexander WR, Jones DP, Vaccarino V, Ziegler TR, Quyyumi AA.
PMID: 30271610
BMC Nutr. 2018;4:26. doi: 10.1186/s40795-018-0234-y. Epub 2018 May 31.

BACKGROUND: The 2015-2020 Dietary Guidelines for Americans recommend a Mediterranean-type diet as one of three healthful eating patterns. However, only one previous trial has evaluated the effects of a Mediterranean diet intervention in a US sample population.METHODS: To address...

Cite
Jaacks LM, Sher S, Staercke C, et al. Pilot randomized controlled trial of a Mediterranean diet or diet supplemented with fish oil, walnuts, and grape juice in overweight or obese US adults. BMC Nutr. 2018;4:26doi: 10.1186/s40795-018-0234-y.
Jaacks, L. M., Sher, S., Staercke, C., Porkert, M., Alexander, W. R., Jones, D. P., Vaccarino, V., Ziegler, T. R., & Quyyumi, A. A. (2018). Pilot randomized controlled trial of a Mediterranean diet or diet supplemented with fish oil, walnuts, and grape juice in overweight or obese US adults. BMC nutrition, 426. https://doi.org/10.1186/s40795-018-0234-y
Jaacks, Lindsay M, et al. "Pilot randomized controlled trial of a Mediterranean diet or diet supplemented with fish oil, walnuts, and grape juice in overweight or obese US adults." BMC nutrition vol. 4 (2018): 26. doi: https://doi.org/10.1186/s40795-018-0234-y
Jaacks LM, Sher S, Staercke C, Porkert M, Alexander WR, Jones DP, Vaccarino V, Ziegler TR, Quyyumi AA. Pilot randomized controlled trial of a Mediterranean diet or diet supplemented with fish oil, walnuts, and grape juice in overweight or obese US adults. BMC Nutr. 2018;4:26. doi: 10.1186/s40795-018-0234-y. Epub 2018 May 31. PMID: 30271610; PMCID: PMC6159217.
Copy Download .nbib Format: NLM
Development of immortalized mouse aortic endothelial cell lines.

Vascular cell

Ni CW, Kumar S, Ankeny CJ, Jo H.
PMID: 24690145
Vasc Cell. 2014 Apr 01;6(1):7. doi: 10.1186/2045-824X-6-7.

BACKGROUND: The understanding of endothelial cell biology has been facilitated by the availability of primary endothelial cell cultures from a variety of sites and species; however, the isolation and maintenance of primary mouse aortic endothelial cells (MAECs) remain a...

Cite
Ni CW, Kumar S, Ankeny CJ, et al. Development of immortalized mouse aortic endothelial cell lines. Vasc Cell. 2014;6(1):7doi: 10.1186/2045-824X-6-7.
Ni, C. W., Kumar, S., Ankeny, C. J., & Jo, H. (2014). Development of immortalized mouse aortic endothelial cell lines. Vascular cell, 6(1), 7. https://doi.org/10.1186/2045-824X-6-7
Ni, Chih-Wen, et al. "Development of immortalized mouse aortic endothelial cell lines." Vascular cell vol. 6,1 (2014): 7. doi: https://doi.org/10.1186/2045-824X-6-7
Ni CW, Kumar S, Ankeny CJ, Jo H. Development of immortalized mouse aortic endothelial cell lines. Vasc Cell. 2014 Apr 01;6(1):7. doi: 10.1186/2045-824X-6-7. PMID: 24690145; PMCID: PMC4230636.
Copy Download .nbib Format: NLM
Blood transcriptomics and metabolomics for personalized medicine.

Computational and structural biotechnology journal

Li S, Todor A, Luo R.
PMID: 26702339
Comput Struct Biotechnol J. 2015 Oct 31;14:1-7. doi: 10.1016/j.csbj.2015.10.005. eCollection 2016.

Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from...

Cite
Li S, Todor A, Luo R. Blood transcriptomics and metabolomics for personalized medicine. Comput Struct Biotechnol J. 2015;14:1-7doi: 10.1016/j.csbj.2015.10.005.
Li, S., Todor, A., & Luo, R. (2016). Blood transcriptomics and metabolomics for personalized medicine. Computational and structural biotechnology journal, 141-7. https://doi.org/10.1016/j.csbj.2015.10.005
Li, Shuzhao, et al. "Blood transcriptomics and metabolomics for personalized medicine." Computational and structural biotechnology journal vol. 14 (2016): 1-7. doi: https://doi.org/10.1016/j.csbj.2015.10.005
Li S, Todor A, Luo R. Blood transcriptomics and metabolomics for personalized medicine. Comput Struct Biotechnol J. 2015 Oct 31;14:1-7. doi: 10.1016/j.csbj.2015.10.005. eCollection 2016. PMID: 26702339; PMCID: PMC4669660.
Copy Download .nbib Format: NLM
Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events.

Journal of the American Statistical Association

Sun X, Peng L, Huang Y, Lai HJ.
PMID: 27212738
J Am Stat Assoc. 2016;111(513):145-156. doi: 10.1080/01621459.2014.995795. Epub 2016 May 05.

In survival analysis, quantile regression has become a useful approach to account for covariate effects on the distribution of an event time of interest. In this paper, we discuss how quantile regression can be extended to model counting processes,...

Cite
Sun X, Peng L, Huang Y, et al. Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events. J Am Stat Assoc. 2016;111(513):145-156doi: 10.1080/01621459.2014.995795.
Sun, X., Peng, L., Huang, Y., & Lai, H. J. (2016). Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events. Journal of the American Statistical Association, 111(513), 145-156. https://doi.org/10.1080/01621459.2014.995795
Sun, Xiaoyan, et al. "Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events." Journal of the American Statistical Association vol. 111,513 (2016): 145-156. doi: https://doi.org/10.1080/01621459.2014.995795
Sun X, Peng L, Huang Y, Lai HJ. Generalizing Quantile Regression for Counting Processes with Applications to Recurrent Events. J Am Stat Assoc. 2016;111(513):145-156. doi: 10.1080/01621459.2014.995795. Epub 2016 May 05. PMID: 27212738; PMCID: PMC4872875.
Copy Download .nbib Format: NLM
Sequencing the exposome: A call to action.

Toxicology reports

Jones DP.
PMID: 26722641
Toxicol Rep. 2016;3:29-45. doi: 10.1016/j.toxrep.2015.11.009.

The exposome is a complement to the genome that includes non-genetic causes of disease. Multiple definitions are available, with salient points being global inclusion of exposures and behaviors, and cumulative integration of associated biologic responses. As such, the concept...

Cite
Jones DP. Sequencing the exposome: A call to action. Toxicol Rep. 2016;3:29-45doi: 10.1016/j.toxrep.2015.11.009.
Jones, D. P. (2016). Sequencing the exposome: A call to action. Toxicology reports, 329-45. https://doi.org/10.1016/j.toxrep.2015.11.009
Jones, Dean P. "Sequencing the exposome: A call to action." Toxicology reports vol. 3 (2016): 29-45. doi: https://doi.org/10.1016/j.toxrep.2015.11.009
Jones DP. Sequencing the exposome: A call to action. Toxicol Rep. 2016;3:29-45. doi: 10.1016/j.toxrep.2015.11.009. PMID: 26722641; PMCID: PMC4692045.
Copy Download .nbib Format: NLM
Showing 1 to 12 of 19 entries