2019 Publications

Rhonda Bacher, Ph.D.

  • Bacher, R., Leng N., Chu, L., Ni, Z., Thomson, J.A., Kendziorski, C., & Stewart, R. (2018). Trendy: segnmented regression analysis of expression dynamics in high-throughput ordered profiling experiments. BMC bioinformatics, 19(1), 380.
  • Bacher, R. (2019). Normalization for Single-Cell RNA-Seq Data Analysis. In Computational Methods for Single-Cell Data Analysis (pp.11-23). Humana Press, New York, NY.

Babette Brumback, PhD.

  • Alrwisan A, Antonelli PJ, Brumback BA, Wei Y-J, Winterstein AG (2018). Azithromycin and sensorineural hearing loss in adults: A retrospective cohort study. Otoglogy & Neurotology, 39(8):957-963.
  • Choi Y, Staley B, Henriksen C, Xu D, Lopori G, Brumback B, Winterstein A (2018). A dynamic risk model for inpatient falls. American Journal of Health-System Pharmacy, 75(17):1293-1303.
  • Gardner AK, Ghita GL, Wang Z, Ozrazgat-Baslanti T, Raymond SL, Mankowski RT, Brumback BA, Efron PA, Bihorac A, Moore FA, Anton SD, Brakenridge SC (2019). The development of chronic critical illness determines physical function, quality of life, and long-term survival among early survivors of sepsis in surgical ICUs.  Critical Care Medicine, 47(4): 566-673.
  • Harle CA, Golembiewski EH, Rahmanian KP, Brumback B, Krieger JL, Goodman KW, Mainous AG, Moseley RE (2019). Does an interactive trust-enhanced electronic consent improve patient experiences when asked to share their health records for research? A randomized trial.  Journal of the American Medical Informatics Association, 26(7): 620-629.
  • Wang Z*, Brumback BA, Alrwisan AA, Winterstein AG (2019). Model-based standardization using an outcome model with random effects.  Statistics in Medicine, 38(18): 3378-3394.
  • Wiggins ME, Tanner J, Schwab N, Crowley SJ, Schmalfuss I, Brumback B, Libon DJ, Heilman K, Price C (2018). Regional leukoariosis and cognition in non-demented older adults.  Brain Imaging and Behavior, https://doi.org/10.1007/s11682-018-9938-5.
  • Wijayabahu AT, Zhou Z, Cook RL, Brumback B, Ennis N, Yaghjyan L (2019). Healthy behavioral choices and cancer screening in persons living with HIV/AIDS are different by sex and years since HIV diagnosis. Cancer Causes & Control, 30(3): 281-290.

Yueh-Yun Chi, PhD.

  • Daw, N. C., Chi, Y. Y., Kim, Y., Mullen, E. A., Kalapurakal, J. A., Tian, J., … & Warwick, A. B. (2019). Treatment of stage I anaplastic Wilms’ tumour: a report from the Children’s Oncology Group AREN0321 study. European Journal of Cancer, 118, 58-66.
  • Spunt, S. L., Francotte, N., De Salvo, G. L., Chi, Y. Y., Zanetti, I., Hayes “Jordan, A., … & van Noesel, M. M. (2019). Clinical features and outcomes of young patients with epithelioid sarcoma: an analysis from the Children’s Oncology Group and the European paediatric soft tissue Sarcoma Study Group prospective clinical trials. European Journal of Cancer, 112, 98-106.
  • von Versen-Hoynck, F., Schaub, A. M., Chi, Y. Y., Chiu, K. H., Liu, J., Lingis, M., … & Zhang, W. (2019). Increased preeclampsia risk and reduced aortic compliance with in vitro fertilization cycles in the absence of a corpus luteum. Hypertension, 73(3), 640-649.
  • von Versen-Hoynck, F., Strauch, N. K., Liu, J., Chi, Y.-Y., Keller-Woods, M., Conrad, K. P., & Baker, V. L. (2019). Effect of Mode of Conception on Maternal Serum Relaxin, Creatinine, and Sodium Concentrations in an Infertile Population. Reproductive Sciences, 26(3), 412 “419. https://doi.org/10.1177/1933719118776792

Somnath Datta, PhD.

  • Chen, Y. and Datta, S. Adjustments of multi-Sample U-statistics to right censored data and confounding covariates. Computational Statistics and Data Analysis, 135, 1-14 (2019)
  • Dutta, S. and Datta, S. Rank based inference for covariate and group effects in clustered data in presence of informative intra-cluster group size. Statistics in Medicine, 37, 4807-4822 (2018).
  • Gregg, M., Datta, S., and Lorenz, D. A log-rank test for clustered data with informative within-cluster group size. Statistics in Medicine, 37, 4071 “4082 (2018).
  • Grimes, T., Potter, S. S., and Datta, S. Integrating gene regulatory pathways into differential network analysis of gene expression data. Scientific Reports – Nature, 9: 5479 (2019)
  • Satten, G., Kong, M., and Datta, S. Multisample adjusted U-Statistics that account for confounding covariates. Statistics in Medicine, 37, 3357 “3372 (2018).
  • Vahabi, N., Kazemnejad, A., and Li, G. F., Zheng, Q. S., Yu, Y., Zhong, W., Zhou, H. H., Qiu, F., … & Derendorf, H. (2019). Impact of Ethnicity-Specific Hepatic Microsomal Scaling Factor, Liver Weight, and Cytochrome P450 (CYP) 1A2 Content on Physiologically Based Prediction of CYP1A2-Mediated Pharmacokinetics in Young and Elderly Chinese Adults. Clinical pharmacokinetics, 58(7), 927-941.. A joint overdispersed marginalized random effects model for analyzing two or more longitudinal ordinal responses. Statistical Methods in Medical Research, 28, 50-69 (2019).
  • Yan, X., Abdia, Y., Datta, S., Kulasekera, K. B., Ugiliweneza, B., Boakye, M., Kong, M. Estimation of average treatment effects among multiple treatment groups by using an ensemble approach. Statistics in Medicine, 38, 2828-2846 (2019).

Susmita Datta, PhD.

  • Mishra, S.; Crowley, P.; Wright, K.; Palmer, S.; Walker, A.; Datta, S.; Brady, L. J. (2019) Membrane proteomic analysis reveals overlapping and independent functions of Streptococcus mutans Ffh, YidC1, and YidC2. Mol Oral Microbiol. Aug;34(4):131-152. PMC6625898.
  • Porter M, Agana DF, Hatch R, Datta S, Carek PJ. (2019) Medical Schools, Primary Care, and Family Medicine: Clerkship directors ‘ perceptions of the current environment. Family Practice 2019, 1-5. doi.org/10.1093/fampra/cmz015.
  • Sekula, M., Gaskins, J., Datta, S. (2018) Detection of differentially expressed genes in discrete single cell RNA. Accepted in Biometrics, April 22, 2019. DOI: 10.1111/biom.13074

Natalie Dean, PhD.

  • Bellan, S. E., Eggo, R. M., Gsell, P. S., Kucharski, A. J., Dean, N. E., Donohue, R., Zook, M., Edmunds, W. J., Odhiambo, F., Longini, I. M., Brisson, M., Mahon, B. E., Henao-Restrepo, A.M. (2019). An online decision tree for vaccine efficacy trial design during infectious disease epidemics: The InterVax-Tool. Vaccine, 37(31): 4376-4381.3.24
  • Dean, N. E., Gsell, P. S., Brookmeyer, R., De Gruttola, V., Donnelly, C .A., Halloran, M. E., Jasseh, M., Nason, M., Riveros, X., Watson, C. H., Henao-Restrepo, A. M. & Longini, I. M. (2019). Design of vaccine efficacy trials during public health emergencies. Science Translational Medicine, 11(499), eaat0360.16.80
  • Ding, A. A., Wu, S. S., Dean, N. E., & Zahigian, R. S. (2019). Two-stage adaptive enrichment design for testing an active factor. Journal of Biopharmaceutical Statistics, DOI: 10.1080/10543406.2019.1609015
  • Hunt, G. M., Ledwaba, J., Kalimashe, M., Salimo, A., Cibane, S., Singh, B., Puren, A., Dean, N.E., Morris, L. & Jordan, M. R. (2019). Provincial and national prevalence estimates of transmitted HIV-1 drug resistance in South Africa measured using two WHO-recommended methods. Antiviral Therapy. doi: 10.3851/IMP3294
  • Sun, K., Zhang, Q., Pastore-Piontti, A., Chinazzi, M., Mistry, D., Dean, N.E., Rojas, D.P., Merler, S., Poletti, P., Rossi, L., Halloran, M.E., Longini, I.M. & Vespignani, A. (2018). Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015 “2016 ZIKV epidemic. BMC Medicine, 16(1), 195.

Subharup Guha, PhD.

  • Drusbosky, L. M., Singh, N. K., Hawkins, K. E., Salan, C., Turcotte, M., Wise, E. A., Meacham, A., Vijay, V., Anderson, G. G., Kim, C. C., Radhakrishnan, S., Ullal, Y., Talawdekar, A., Sikora, H., Nair, P., Khanna-Gupta, A., Abbasi, T., Vali, S., Guha, S., Farhadfar, N., Murthy, H. S., Horn, B. N., Leather, H. L., Castillo, P., Tucker, C., Cline, C., Pettiford, L., Lamba, J. K., Moreb, J. S., Brown, R. A., Norkin, M., Hiemenz, J. W., Hsu, J. W., Slayton, W. B., Wingard, J. R., & Cogle, C. R. (2019). A genomics-informed computational biology platform prospectively predicts treatment responses in AML and MDS patients. Blood Advances, 3(12), 1837-1847. Accessed July 22, 2019. https://doi.org/10.1182/bloodadvances.2018028316.

Zhiguang Huo, PhD.

  • Han, S., Huo, Z., Nguyen, K., Zhu, F., Underwood, P. W., Basso, K. B. G., … & Hughes, S. J. (2019). The Proteome of Pancreatic Cancer Derived Exosomes Reveals Signatures Rich in Key Signaling Pathways. Proteomics, 1800394.
  • Huo, Z., Song, C., & Tseng, G. (2019). Bayesian latent hierarchical model for transcriptomic meta-analysis to detect biomarkers with clustered meta-patterns of differential expression signals. The annals of applied statistics, 13(1), 340.
  • Huo, Z., Zhu, L., Ma, T., Liu, H., Han, S., Liao, D., … & Tseng, G. (2019). Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery. Statistics in Biosciences, 1-22.
  • Huo, Z., Zhu, Y., Yu, L., Yang, J., De Jager, P., Bennett, D. A., & Zhao, J. (2019). DNA methylation variability in Alzheimer’s disease. Neurobiology of aging, 76, 35-44.
  • Ma, T., Huo, Z., Kuo, A., Zhu, L., Fang, Z., Zeng, X., … & Rahman, T. (2019). MetaOmics: analysis pipeline and browser-based software suite for transcriptomic meta-analysis. Bioinformatics.
  • Shaikh, N., Martin, J. M., Hoberman, A., Skae, M., Milkovich, L., Nowalk, A., … & Shalaby-Rana, E. (2019). Host and Bacterial Markers that Differ in Children with Cystitis and Pyelonephritis. The Journal of pediatrics.

John Kairalla, PhD.

  • Buford TW, Manini TM, Kairalla JA, McDermott MM, Vaz Fragoso CA, Chen H, Fielding RA, King AC, Newman AB, Tranah GJ (2018). Mitochondrial DNA sequence variants associated with blood pressure among two cohorts of older adults. Journal of the American Heart Association, 7(18), 1-11.
  • Manini TM, Buford TW, Kairalla JA, McDermott MM, Vas Fragoso CA, Fielding RA, Hsu FC, Johannsen N, Kritchevsky S, Harris TB, Newman AB, Cummings SR, King AC, Pahor M, Santanasto AJ, Tranah GJ (2018). Meta-analysis identifies mitochondrial DNA sequence variants associated with walking speed. GeroScience, 40(5-6), 497-511. https://doi.org/10.1007/s11357-018-0043-x
  • Sia I, Crary M, Kairalla JA, Carnaby G, Sheplak M, Mcculloch TM (2019). Derivation and Measurement Consistency of a Novel Biofluid Dynamics Measure of Deglutitive Bolus-Driving Function – Pharyngeal Swallowing Power. Neurogastroenterology and Motility, 31(1), e13465. PMC6296874
  • Sia I, Crary MA, Kairalla J, Carnaby GD, Sheplak M, Mcculloch T (2018). Bolus Volume and Viscosity Effects on Pharyngeal Swallowing Power “ How Physiological Bolus Accommodation Affects Bolus Dynamics. Neurogastroenterology and Motility, 30(12), e13481. https://doi.org/10.1111/nmo.13481
  • Vaz Fragoso CA, Manini TM, Kairalla JA, Buford TW, Hsu FC, Gill TM, Kritchevsky SB, McDermott MM, Sanders JL, Cummings SB, Tranah GJ (2019). Mitochondrial DNA variants and pulmonary function in older persons. Experimental Gerontology, 115, 96-103. doi:10.1016/j.exger.2018.11.023

Ji-Hyun Lee, Dr PH

  • Dashner-Titus, E. J., Hoover, J., Li, L., Lee, J. H., Du, R., Liu, K. J., … & Hudson, L. G. (2018). Metal exposure and oxidative stress markers in pregnant Navajo Birth Cohort Study participants. Free Radical Biology and Medicine, 124, 484-492.
  • Hatch, E. W., Geeze, M. B., Martin, C., Salama, M. E., Hartmann, K., Eisenwort, G., … & Chen, L. (2018). Variability of PD-L1 expression in mastocytosis. Blood advances, 2(3), 189-199.
  • Kinney, A. Y., Howell, R., Ruckman, R., McDougall, J. A., Boyce, T. W., Vicuña, B., … & Gallegos, K. M. (2018). Promoting guideline-based cancer genetic risk assessment for hereditary breast and ovarian cancer in ethnically and geographically diverse cancer survivors: Rationale and design of a 3-arm randomized controlled trial. Contemporary clinical trials, 73, 123-135.
  • Luo, L., Hudson, L. G., Lewis, J., & Lee, J. H. (2019). Two-step approach for assessing the health effects of environmental chemical mixtures: application to simulated datasets and real data from the Navajo Birth Cohort Study. Environmental Health, 18(1), 46.
  • Shi, Y., & Lee, J. H. (2018). Sample size calculations for group randomized trials with unequal group sizes through Monte Carlo simulations. Statistical methods in medical research, 27(9), 2569-2580.
  • Shi, Y., Wang, M., Shi, W., Lee, J.H., Kang, H., & Jiang, H. (2019). Accurate and efficient estimation of small P-values with the cross-entropy method: applications in genomic data analysis. arXiv preprint arXiv:1803.03373. Bioinformatics. 35, 2442-2248.

Zhigang Li, PhD

  • Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data. Statistics in Biosciences
  • Patient-Clinician Discordance in Perceptions of Treatment Risks and Benefits in Older Patients with AML. The Oncologist
  • Prenatal arsenic exposure alters the placental expression of multiple epigenetic regulators in a sex-dependent manner.
    Environmental Research
  • Prenatal exposure to mercury in relation to infant infections and respiratory symptoms in the New Hampshire Birth Cohort Study. Environmental Research
  • Sex-specific gut microbiome impacts of infant arsenic exposure in a US population. Scientific Reports

Ira Longini, PhD.

  • Dean N, Gsell PS, Brookmeyer R, De Gruttola V, Donnelly CA, Halloran ME, Jasseh M, Nason M, Riveros X, Watson C, Henao-Restrepo AM, Longini IM: Considerations for the design of vaccine efficacy trials during public health emergencies. Science Translational Medicine 2019: Vol. 11, Issue 499, eaat0360, DOI: 10.1126/scitranslmed.aat0360
  • Pavia-Ruz N, Barrera-Fuentes GA, Villanueva-Jorge S, Che-Mendoza A, Campuzano JC, Manrique-Saide P, Rojas DP, Vazquez-Prokopec GM, Halloran ME, Longini IM, Gomez-Dantés H: Dengue seroprevalence in a cohort of schoolchildren and their siblings in Yucatan, Mexico (2015-2016). PloS Neglected Tropical Diseases https://doi.org/10.1371/journal.pntd.0006748 (2018) PMCID: PMC6248890
  • Robert A, Edmunds WJ, Watson CH, Henao-Restrepo AM, Gsell P-S, Williamson E, Longini IM, Sakoba K, Kucharski AJ, Touré A, Nadlaou SD, Diallo B, Barry MS, Fofana TO, Camara L, Kaba IL, Sylla L, Diaby ML, Soumah O, Diallo A, Niare A, Diallo A, Eggo RM. Determinants of transmission risk during the late stage of the West African Ebola epidemic. American Journal of Epidemiology https://doi.org/10.1093/aje/kwz090 (2019) PMID: 30941398
  • Rojas DP, Barrera-Fuentes GA, Pavia-Ruz N, Salgado-Rodriguez M, Che-Mendoza A, Manrique-Saide P, Vazquez-Prokopec GM, Halloran ME, Longini IM, Gomez-Dantes HJ: Epidemiology of dengue and other arboviruses in a cohort of school children and their families in Yucatan, Mexico: Baseline and first year follow-up, PLoS Neglected Tropical Diseases. https://doi.org/10.1371/journal.pntd.0006847 . PMCID: PMC6248893
  • Tsang T, Chen T, Longini IM, Halloran ME, Yang Y: Transmissibility of Norovirus in Urban vs. Rural Households: Observations from a Large Community Outbreak in China. Epidemiology (2018 May 29. doi: 10.1097/EDE.0000000000000855. PMID: 29847497.
  • Tsang TK, Ghebremariam SL, Gresh L, Gordon A, Halloran ME, Leah C. Katzelnick LC, Rojas DP, Kuan G, Balmaseda A, Sugimoto J, Harris E, Longini IM, Yang Y: Effects of infection history on dengue virus infection and pathogenicity. Nature Communications 10, https://doi.org/10.1038/s41467-019-09193-y (2019) PMCID: PMC6423047

Arlene Naranjo, PhD.

  • Alexander, N., Marrano, P., Thorner, P., Naranjo, A., Van Ryn, C., Martinez, D., Batra, V., Zhang, L., Irwin, M.S., & Baruchel, S. (2019). Prevalence and Clinical Correlations of Somatostatin Receptor-2 (SSTR2) Expression in Neuroblastoma. Journal of Pediatric Hematology/Oncology, 41(3), 222-7. DOI: 10.1097/MPH.0000000000001326.
  • Pinto, N., Naranjo, A., Hibbitts, E., Kreissman, S.G., Granger, M.M., Irwin, M.S., Bagatell, R., London, W.B., Greengard, E.G., Park, J.R., & DuBois, S.G. (2019). Predictors of Differential Response to Induction Chemotherapy in High-Risk Neuroblastoma: A Report from the Children ‘s Oncology Group (COG). European Journal of Cancer 112: 66-79. DOI: 10.1016/j.ejca.2019.02.003.
  • Twist, C. J., Naranjo, A., Schmidt, M. L., Tenney, S. C., Cohn, S. L., Meany, H. J., Mattei, P., Adkins, E.S., Shimada, H., London, W.B., Park, J.R., Matthay, K.K., & Park, J. R. (2019). Defining Risk Factors for Chemotherapeutic Intervention in Infants with stage 4S Neuroblastoma: A Report from Children ‘s Oncology Group. Journal of Clinical Oncology, 37(2), 115-24. DOI: 10.1200/JCO.18.00419.

Robert Parker, PhD.

  • Parker, R., & Rosalsky, A. (2019). Strong Laws of Large Numbers for Double Sums of Banach Space Valued Random Elements. Acta Mathematica Sinica, English Series, 35(5), 583-596.

Qinglin Pei, PhD.

  • Cole, P. D., McCarten, K. M., Pei, Q., Spira, M., Metzger, M. L., Drachtman, R. A., … & Kelly, K. M. (2018). Brentuximab vedotin with gemcitabine for paediatric and young adult patients with relapsed or refractory Hodgkin’s lymphoma (AHOD1221): a Children’s Oncology Group, multicentre single-arm, phase 1 “2 trial. The Lancet Oncology, 19(9), 1229-1238.
  • Kelly, K. M., Cole, P. D., Pei, Q., Bush, R., Roberts, K. B., Hodgson, D. C., … & Schwartz, C. (2019). Response adapted therapy for the treatment of children with newly diagnosed high risk Hodgkin lymphoma (AHOD0831): a report from the Children ‘s Oncology Group. British journal of haematology.
  • Marks, L. J., McCarten, K. M., Pei, Q., Friedman, D. L., Schwartz, C. L., & Kelly, K. M. (2018). Pericardial effusion in Hodgkin lymphoma: a report from the Children ‘s Oncology Group AHOD0031 protocol. Blood, 132(11), 1208-1211.
  • Marks, L. J., Pei, Q., Bush, R., Buxton, A., Appel, B., Kelly, K. M., … & Friedman, D. L. (2018). Outcomes in intermediate risk pediatric lymphocyte predominant Hodgkin lymphoma: A report from the Children’s Oncology Group. Pediatric blood & cancer, 65(12), e27375.
  • McCarten, K. M., Metzger, M. L., Drachtman, R. A., Pei, Q., Friedman, D. L., Schwartz, C. L., & Kelly, K. M. (2018). Significance of pleural effusion at diagnosis in pediatric Hodgkin lymphoma: a report from Children ‘s Oncology Group protocol AHOD0031. Pediatric radiology, 1-9.

Peihua Qiu, PhD.

  • Feng, L., and Qiu, P. (2018), Difference Detection Between Two Images for Image Monitoring, Technometrics, 60, 345-359.
  • Iqbal, A., Sakharuk, I., Goldstein, L., Tan, S.A., Qiu, P., Li, Z., Hughes, S.J. (2018), Readmission after ileostomy creation in colorectal surgery patients is predictable, Journal of the Society of Laparoendscopic Surgeons, 22, 1 “8.
  • Kang, Y., Gong, X., Gao, J., and Qiu, P. (2019), Error-in-Variables Jump Regression Using Local Clustering,  Statistics in Medicine, 38, 3642 “3655.
  • Kang, Y., Mukherjee, P.S., and Qiu, P. (2018), Efficient Blind Image Deblurring Using Nonparametric Regression And Local Pixel Clustering,  Technometrics, 60, 522 “531.
  • Qiu, P. (2018), Peter Hall: My Mentor, Collaborator, and Friend,  Statistica Sinica, 28, 2249 “2259.
  • Qiu, P., and You, L. (2018), Recent Research in Dynamic Screening System for Sequential Process Monitoring,  In Proceedings of the Pacific Rim Statistical Conference for Production Engineering (Choi et al. ed.), 85 “93, Springer.
  • Qiu, P., He, Z., and Wang, Z. (2019), Nonparametric Monitoring of Multiple Count Data,  IISE Transactions, 51, 972 “984.
  • Qiu, P., Zi, X., and Zou, C. (2018), Nonparametric Dynamic Curve Monitoring, Technometrics, 60, 386 “397.
  • Song, H., and Qiu, P. (2018), Three-dimensional Image Registration Using Distributed Parallel Computing,  IET Image Processing, 12, 1713 “1720.
  • Wang, Z., and Qiu, P. (2018), Count data monitoring: parametric or nonparametric? Quality and Reliability Engineering International, 34, 1763 “1774.
  • You, L., and Qiu, P. (2019), Fast Computing For Dynamic Screening Systems When Analyzing Correlated Data,  Journal of Statistical Computation and Simulation, 89, 379 “394.
  • Zang, Y., and Qiu, P. (2018), Phase II Monitoring of Free-Form Surfaces: An Application to 3D Printing,  Journal of Quality Technology, 50, 379 “390.

Samuel Wu, PhD.

  • Borsa PA, Parr JJ, Wallace MR, Wu SS, Dai Y, Fillingim RF, George SZ. (2018). Genetic and Psychological Factors Interact to Predict Physical Impairment Phenotypes Following Exercise-Induced Shoulder Injury. Journal of Pain Research. 11:2497-2508. (PMID: 30425562)
  • Dahodwala N, Shah K, He Y, Wu SS, Schmidt P, Cubillos F, Willis AW. (2018). Sex disparities in access to caregiving in Parkinson disease. Neurology. 90(1):e48-e54. (PMID: 29196580)
  • Ding AA, {\bf Wu SS}, Dean NE, Zahigian RS. (2019).
    Two-stage adaptive enrichment design for testing an active factor.
    J Biopharm Stat.} May 28:1-13. (PMID: 31135263)
  • Margoliusa A, Cubillosb F, He Y, Wu S, Schmidt PN, and Simunia T on behalf of the NPF QII Investigators. (2018). Predictors of Clinically Meaningful Change in PDQ-39 in Parkinson ‘s Disease. Parkinsonism & Related Disorders. 56:93-97. (PMID: 30056039)
  • Parashos SA, Bloem BR, Browner NM, Giladi N, Gurevich T, Hausdorff JM, He Y, Lyons KE, Mari Z, Morgan JC, Post B, Schmidt PN, Wielinski CL, and Wu SS. (2018). What predicts falls in Parkinson disease? Observations from the Parkinson Foundation Registry. Neurology: Clinical Practice. 8(3):214-222. (PMID: 30105161)

Yang Yang, PhD.

  • Cheng X-J, Tan L-H, Gao Y-Y, Yang Y, Schwebel DC and Hu G-Q. A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate. PLoS One. 2019; doi.org/10.1371/journal.pone.0216613.
  • Kim YY, Lew JF, Keith B, Telisma T, Nelson EJ, Brantly AC, Chavannes S, Anilis G, Yang Y, Liu M-J, Alam MT, Rashid MH, Morris JG, Madsen VE and De Rochars B. Acute Respiratory Illness in Rural Haiti. International Journal of Infectious Diseases. 2019; 81:176-183. doi.org/10.1016/j.ijid.2019.02.003
  • Ma MJ, Yang Y, Fang LQ. Highly Pathogenic Avian H7N9 Influenza Viruses: Recent Challenges. Trends in Microbiol 2019; 27:93-5.
  • Ning P-S, Gao D-Y, Cheng P-X, Schwebel D, Wei X, Tan L-H, Xiao W-X, He J-Y, Fu Y-H, Chen B, Yang Y, Deng J, Wu Y, Yu R-H, Li S-K, Hu G-Q. Framework for developing an app-based parenting intervention for unintentional injury among caregivers of Chinese children ages 0-6 years: a mixed-method study. J. Med. Internet Research. 2019; 7(4):e11957. doi.org/10.2196/11957
  • Porter M, Quillen D, Agana DF, Chacko L, Lynch K, Bielick L, Fu X-Q, Yang Y and Carek PJ. Are Patients Frequently Readmitted to the Hospital Different from the Other Admitted Patients? Journal of American Board of Family Medicine. 2019; 32(1):58-64. DOI: 10.3122/jabfm.2019.01.180052 Revision submitted 9/12/2018
  • Tsang KL, Ghebremariam S, Gresh L, Gordon A, Halloran ME, Katzelnick LC, Rojas DP, Kuan G, Balmaseda A, Sugimoto J, Harris E, Longini IM, Yang Y. Effects of Infection History on Dengue Virus Infection and Pathogenicity. Nature Communications. 2019; 10:Article #1246. (Corresponding author)

Yichao Yu, PhD.

  • Hinderling, P. H., & Yu, Y. (2019). Quantitative Assessment of the Effect of Chronic Kidney Disease on the Nonrenal Clearance of 10 Drugs After Intravenous Administration. Clinical pharmacology in drug development, 8(2), 138-151.
  • Li, G. F., Zheng, Q. S., Yu, Y., Zhong, W., Zhou, H. H., Qiu, F., … & Derendorf, H. (2019). Impact of Ethnicity-Specific Hepatic Microsomal Scaling Factor, Liver Weight, and Cytochrome P450 (CYP) 1A2 Content on Physiologically Based Prediction of CYP1A2-Mediated Pharmacokinetics in Young and Elderly Chinese Adults. Clinical pharmacokinetics, 58(7), 927-941.