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1.
Cell ; 157(2): 499-513, 2014 Apr 10.
Article in English | MEDLINE | ID: mdl-24725414

ABSTRACT

A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires the collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination. Peripheral blood mononuclear cell transcriptomes, serum titers, cell subpopulation frequencies, and B cell responses were assessed in 63 individuals before and after vaccination and were used to develop a systematic framework to dissect inter- and intra-individual variation and build predictive models of postvaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time points. Most of the parameters contributing to prediction delineated temporally stable baseline differences across individuals, raising the prospect of immune monitoring before intervention.


Subject(s)
B-Lymphocytes/metabolism , Influenza Vaccines/administration & dosage , Influenza Vaccines/immunology , Leukocytes, Mononuclear/metabolism , Adult , Antibody Formation , B-Lymphocytes/immunology , Female , Humans , Leukocytes, Mononuclear/immunology , Male , Middle Aged , Transcriptome , Young Adult
2.
JAMA ; 297(22): 2496-501, 2007 Jun 13.
Article in English | MEDLINE | ID: mdl-17565084

ABSTRACT

CONTEXT: Although concerns have persisted for decades about the production of new physician clinical scientists and their success in receiving and sustaining research supported by the National Institutes of Health (NIH), no comprehensive analysis documents the experiences of first-time investigators with an MD over a long period. OBJECTIVE: To ascertain the perseverance and comparative success of physician-scientists competing for NIH research (R01) grants awarded over 40 years. DESIGN, SETTING, AND PARTICIPANTS: A longitudinal, comparative study of all first-time applicants and recipients of NIH R01 grants between 1964 and 2004 stratified by the principal investigators' major degrees (MD, PhD, or MD and PhD) and their proposed involvement in research of humans or human tissues. MAIN OUTCOME MEASURES: Number of first- and second-time NIH R01 grant applicants and recipients by academic degree and by research type (clinical vs nonclinical). RESULTS: The annual number of first-time investigators with an MD only as NIH R01 grant applicants remained remarkably stable over 4 decades (41-year mean of 707 [range, 537-983] applicants). Among first-time applicants, those with an MD consistently had less success in obtaining funding (mean annual percentage [MAP], 28%) than either investigators with a PhD (MAP, 31%; P = .03 vs MD only) or both an MD and a PhD (MAP, 34%; P<.001 vs MD only and P = .002 vs PhD only). Among investigators who obtained a first R01 grant, those with an MD were consistently less likely (MAP, 70%) than those with a PhD (MAP, 73%; P = .04 vs MD only) or those with an MD and a PhD (MAP, 78%; P<.001 vs MD only and P = .007 vs PhD only) to obtain a subsequent R01 grant. First-time applicants with an MD were much more likely to propose clinical research (MAP, 67%) than applicants with an MD and a PhD (MAP, 43%) and applicants with a PhD only (39%). First-time applicants with an MD only who proposed clinical research were funded at lower rates than their MD-only counterparts proposing nonclinical research (23% vs 29%, respectively; P<.001). CONCLUSIONS: From 1964-2004, the number of physician-investigators applying for first R01 grants showed little net change. Physician-investigators consistently experienced higher rates of attrition and failure, even after receiving a first R01 grant, and those proposing clinical research were less successful in obtaining funding than physicians proposing nonclinical research.


Subject(s)
Biomedical Research/statistics & numerical data , National Institutes of Health (U.S.)/statistics & numerical data , Physicians/statistics & numerical data , Research Personnel/statistics & numerical data , Research Support as Topic/statistics & numerical data , Longitudinal Studies , United States
5.
Ann N Y Acad Sci ; 1285: 133-47, 2013 May.
Article in English | MEDLINE | ID: mdl-23692568

ABSTRACT

The Center for Human Immunology, Autoimmunity, and Inflammation (CHI) is an exciting initiative of the NIH intramural program begun in 2009. It is uniquely trans-NIH in support (multiple institutes) and leadership (senior scientists from several institutes who donate their time). Its goal is an in-depth assessment of the human immune system using high-throughput multiplex technologies for examination of immune cells and their products, the genome, gene expression, and epigenetic modulation obtained from individuals both before and after interventions, adding information from in-depth clinical phenotyping, and then applying advanced biostatistical and computer modeling methods for mining these diverse data. The aim is to develop a comprehensive picture of the human "immunome" in health and disease, elucidate common pathogenic pathways in various diseases, identify and validate biomarkers that predict disease progression and responses to new interventions, and identify potential targets for new therapeutic modalities. Challenges, opportunities, and progress are detailed.


Subject(s)
Allergy and Immunology , Autoimmune Diseases , National Institutes of Health (U.S.) , Allergy and Immunology/history , Autoimmune Diseases/history , Autoimmune Diseases/pathology , History, 21st Century , Humans , Inflammation/history , Inflammation/pathology , Influenza Vaccines/history , National Institutes of Health (U.S.)/history , National Institutes of Health (U.S.)/organization & administration , United States , Vaccination/history
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