Michael Cole - US grants

The activation of cellular oncogenes appears to play a central role in the transformation of normal cells to a neoplastic phenotype. The c-myc oncogene has been implicated in a wide range of tumor cells, especially in B cell neoplasia, and hence is particularly important to study in terms of regulation and function. We have recently found that, when linked to viral promoters, the c-myc gene induces fibroblast cell lines to become tumorigenic in nude mice. This study will be extended to determine if alteration of the c-myc promoter is required for oncogenic activation of the gene, and if there is a threshold level of c-myc expression that is necessary for tumorigenesis. A second study will focus on the influence of c-myc on the expression of other genes, in particular whether c-myc can induce transcription from genes which lack enhancers. A third study will examine the effect of constitutive c-myc expression on the in vitro differentiation of the human promyelocytic leukemia line, HL-60. These experiments will explore the relationship between activated cellular oncogenes and their block in differentiation and continued proliferation of tumor cells. Finally, the biological activity of c-myc retrovirus will be studied, especially the transforming potential in vivo and the effect on primary cells in vitro. A novel DHFR-myc retrovirus that can be amplified in "normal" cells will also be constructed to attempt to identify cellular genes that are influenced by overexpression of c-myc. All of these studies are designed to further our understanding of the c-myc oncogene in cell transformation. (X)

The goal of this research is to understand the activation of cellular oncogenes by chromosomal translocation, with particular emphasis on the c-myc oncogene in mouse plasmacytomas. Previous work from this laboratory has demonstrated that the first c-myc intron is transcriptionally activated by translocation and that constitutively expressed c-myc genes induce immortalized fibroblast lines to become transformed (tumorigenic). Studies will continue to explore the mechanism by which c-myc is transcribed after translocation, using gene transfer of breakpoint-linked marker genes into plasmacytoma cells. The influence of c-myc activation on primary B cells will be studied by injection of spleen or bone marrow cells with a c-myc retrovirus. These experiments will attempt to determine if c-myc activation is sufficient either to transform primary cells, to extend their growth potential, or to reduce their dependence on exogenous growth factors. We will also test the stability of c-myc mRNAs that are produced before and after translocation. We suspect that the removal of the untranslated first exon of the c-myc gene may extend the mRNA half-life and thus produce more c-myc protein with only a low rate of transcription. Ultimately, we hope to examine other types of tumors for DNA rearrangements that affect cellular oncogenes and contribute to neoplastic transformation. (M)

DNA rearrangements have been found to occur near cellular oncogene loci in tumor cells, activating the oncogenes and inducing a deregulation in cellular growth control. The major goal of this project will be to understand the chromosomal translocation that occurs at the c-myc locus in mouse plasmacytomas, linking the oncogene to the immunoglobulin locus. The Ig gene region will be tested for the presence of transcriptional enhancing sequences. The c-myc intron sequences that function as a bidirectional promoter after translocation will also be studied for enhancing activity and for their ability to substitute for an essential, transcription factor binding domain in the SV40 promoter. Finally, the chromatin structure surrounding the translocated c-myc gene will be analyzed for nuclease sensitivity and the presence of hypersensitive sites. In a related study, the c-myc gene has been used to detect and clone novel mouse cellular sequences that promise to be members of a family of myc-related cellular genes. The mouse genes will be cloned and sequenced to determine their relationship to the previously identified c- and N-myc oncogenes. These genes will be studied for their regulation in development and in the cell cycle, and used to screen for DNA rearrangements in human tumors. Finally, a series of fibroblast clones that have been selected for spontaneous anchorage-independent growth will be studied for the presence of oncogene DNA rearrangements. The frequency at which these variants arise and their relatively stable phenotype suggest that they have suffered a heritable genetic change. Particular emphasis will be placed on detecting gene amplification, a frequent mechanism by which myc oncogenes are activated. Each of these studies is designed to understand cellular oncogenes and the molecular mechanisms by which they are activated in cancer cells.

The goal of this proposal is to determine the effect of IgA1 protease on secretory IgA antibody activity. Secretory IgA (SIgA) is the principal immunoglobulin isotype in the mucosal secretions of the body. SIgA is thought to play a major role in host defense at mucosal surfaces by inhibiting the colonization of potentially pathogenic microorganisms. A number of mucosal pathogens produce a protease that specifically cleaves the IgA1 subclass at the hinge region to produce Fab and Fc fragments. Despite the potential importance of IgA1 protease as a microbial virulence factor in host-parasite interactions at mucosal surfaces virtually nothing is known concerning the effect of cleavage on the antibody function of SIgA. Comparisons of antibody activity before and after cleavage with IgA1 protease cannot be readily achieved because (1) it is difficult to obtain high titer specific naturally occurring SIgA antibody from normal human serum or secretions and (2) IgA1 proteases synthesized by human mucosal pathogens have extraordinary specificity for only human, gorilla and chimpanzee IgA and will not cleave IgA from other animal species. The chimpanzee has been selected in the current proposal because (1) the chimpanzee can be immunized to induce high levels of specific SIgA antibody in breast milk and, (2) chimpanzee IgA is susceptible to cleavage by IgA1 proteases derived from human mucosal pathogens. The objective of this proposal is to determine whether IgA1 protease can interfere with the functional activity of SIgA antibody in the oral cavity. Accordingly, it is proposed to (1) determine the effect of IgA1 protease on the ability of SIgA antibody to bind to the cariogen, Streptococcus mutans. This will be accomplished by comparing the binding of anti-S. mutans SIgA antibody before and after treatment with IgA1 protease in an enzyme-linked immunosorbent assay. The effect of protease on SIgA antibody, before and after binding to S. mutans will be examined (2) determine the effect of IgA1 protease and the ability of SIgA antibody to agglutinate S. mutans. This will be accomplished by use of an agglutination assay in which the endpoint titer of the SIgA antibody will be compard before and after protease treatment and (3) determine the effect of IgA1 protease on the adherence inhibiting activity of SIgA antibody. This will be accomplished by comparing the effect of protease on the adherence of S. mutans to hydroxyapatite (HA) in the presence of SIgA antibody bound to bacteria or HA.

This proposal is for exploratory small grant funding for the collation and summary of telecommunications-in-education research applicable to the use of large-scale wide-area networks in the science classroom and the prompt dissemination of that information to the facilitators of state and national education networks. The purpose of this project is to facilitate future research in educational telecommunications, and to collate and provide information useful to the initial phases of state-wide and national telecommunications-in-education networks. Several states, and several commercial organizations are already offering or are about to offer from September 1991 or September 1992 access to large scale telecommunications facilities to schools. Though a considerable amount of research has been done on individual small scale networks and on small group components of large-scale networks, this research is neither easily accessible nor wholly relevant to the large-scale situation. As yet,l we have very little information on the effects of scaling up from the base of research-oriented prototype networks. Also, the creation of these new telecommunications applications and new network communities in education is taking place extremely quickly. If these developments are to be constructive advances in teaching and learning strategies it is imperative that these new efforts should be informed by prior experience and research. In order to establish a baseline of relevant information in a timely fashion, it is proposed that NSF should fund a limited research initiative between April 1, 1991 and September 1,l 1991. The initiative will have three components - the collation of existing research, a demonstration study of an academic network, and a demonstration study of a global-scale K-12 network.

DESCRIPTION (Adapted from applicant's abstract): DNA rearrangements that alter the myc family of proto-oncogenes have been more frequently linked to human and mouse cancers than any oncogene except ras. Chromosomal translocation, retrovirus insertion and gene amplification lead to deregulated or elevated expression of the myc protein and complex changes in cellular growth properties. Yet the mechanism by which deregulated myc expression disrupts cell growth remains unknown. The goal of this proposal is to determine how DNA rearrangements disrupt myc gene expression, and how deregulated expression contributes to the transformation of mouse lymphoid cells and causes plasmacytomas. The first goal of this project will be to determine the mechanism of c-myc mRNA turnover. An important feature of c-myc gene regulation is the very short half-life of the mRNA (less than 30 min). Chromosomal translocations usually displace the first exon of c-myc and induce mRNA stabilization. The cis-acting determinants of RNA turnover and the basic mechanism by which c-myc mRNA is degraded will be investigated. A related goal will be to determine the cis-acting determinants that mediate the differential regulation of c-myc and granulocyte-macrophages-CSF mRNA stability. The second goal of this project is to identify the secondary mutations that cause B cell lymphomas in a unique mouse transgenic model in which an immunoglobulin enhancer-linked N-myc transgene induces tumors with long latency (greater than one year). Retrovirus infection of these mice potentiates rapid (four mo) B cell lymphomas, suggesting that the retrovirus integration site will identify the secondary genetic lesions that collaborate with myc. The pathology of tumor progression will also be investigated to better understand the role that individual mutations play in the disease. The third goal of the project will be to understand the molecular basis of the c-myc promoter suppression in tumor cells. Specifically, the c-myc gene will be studied for suppression after microinjection into mouse embryos, or transfer of the extended chromosomal domain into cells by YAC cloning. Proper gene regulation may be dependent on either distant flanking sequences or developmental factors that are not reproduced in cultured cells. DNA rearrangements may primarily act by overriding the normal suppression of the c-myc gene so an understanding of the basic mechanism of gene suppression is critical to understanding malignant transformation.

The cellular oncogene, c-myc, has been found to be activated in a wide range of cancer cells by chromosomal translocation, gene amplification and proviral integration. The focus of this proposal will be to understand the function of the c-myc protein in controlling normal and tumor cell growth. The specific goals of the proposal are as follows: 1. The c-myc protein complex isolated from normal and myc-transformed cells will be investigated to characterize associated proteins. 2. The role of phosphorlylation in controlling the DNA binding activity and/or specificity of Max and Myc will be investigated through structure function studies. In particular, we will analyze a domain of Max which inhibits homodimer but not heterodimer DNA binding activity. 3. We will develop assays to determine the function of the N-terminal portion of the c-Myc protein, which is hypothesized to function in the enhancement of transcription. Conserved domains of Myc will be used to screen expression libraries and for affinity column, both of which will be used to isolate and then characterize the cellular factors that mediate Myc function. 4. We will continue our studies of myc-regulated cellular promoters to identify the key cellular targets through which myc transforms cells.

Candida albicans is a member of the normal flora of mucosal surfaces that usually exists in a commensal relationship with the host unless the flora is perturbed or the immune system compromised when this fungus an become opportunistically pathogenic. Immunosuppression resulting from infection with the human immunodeficiency virus (HIV) leads to oral and vaginal candidiasis in over 90% of patients with AIDS. Mucosal defense is mediated principally by secretory immunoglobulin A (SIgA) antibodies which inhibit adherence of C. albicans. HIV infection results in the progressive depletion of CD4+ T lymphocytes and disruption of the follicular dendritic cell network in germinal centers. 60% of all lymphocytes are found in the mucosal-associated lymphoid tissues that are the inductive sites for SigA antibody responses and memory. The objective of this application is to define the salivary and vaginal secretory immune responses to C. albicans in men and women with AIDS. Sequential samples of saliva and vaginal secretions and isolates of C. albicans will be obtained from HIV+ men and women and healthy controls during a four year longitudinal study. Data will be analyzed to test the following hypotheses: (1) The susceptibility of AIDS patients to oral and vaginal candidiasis results from impaired SigA antibody responses due to disregulation of the immune system; (2) Strains of C. albicans colonizing AIDS patients are more virulent, genetically less diverse than those in healthy subjects, show tropism for the mouth or vagina and persist in these habitats. The Specific Aims are: Aim 1A. Determine the levels of total SigA, SigA1 and SigA2 subclasses in saliva and vaginal secretions of AIDS patients. Total SigA,SigA1 and SigA2 will be quantitated using an enzyme-linked immunosorbent assay (ELISA) specific for exocrine IgA to test the hypothesis that progressive AIDS results in reduced concentrations of SigA and its subclasses in saliva and vaginal secretions. Aim 1B. Analyze the quantity and specificity of total SigA, SigA1 and SigA2 antibodies reactive with C. albicans in saliva and vaginal secretions. The specificity and quantity of antibodies will be analyzed by Western blotting and by ELISA to test the hypotheses that the quantity and specificity of antibodies changes throughout the progression of AIDS. Aim 1C. Analyze the avidity of total SigA, SigA1 and SigA2 antibodies reactive with C. albicans in saliva and vaginal secretions. Chaotrope dissociation ELKISA and immunoblots will be used to test the hypothesis that progressive AIDS results in the production of low avidity antibodies that do not exhibit affinity maturation and are ineffective in immune elimination of this fungus. Aim 2. Compare the SigA proteinase activity of C. albicans isolates from the mouth and vagina and t he levels of proteinase in saliva and vaginal secretions. SigA-degrading enzymes will be detected by a radial diffusion assay and by ELISA using proteinase-specific antibody to test the hypothesis that these enzymes contribute to the virulence of this fungus by destroying SigA antibodies. Aim 3: Compare the genetic diversity of C. albicans isolates obtained from the mouth and vagina. DNA fingerprinting will be used to test the hypotheses that in AIDS patients there is; (a) limited genetic heterogeneity within the strains of this species isolated from the mouth and vagina; (b) different genotypes of Candida in the mouth compared with the vagina and (c) genotypes of this fungus are stable in these habitats over time.

DESCRIPTION: Functional studies have demonstrated that two specific domains of the c-Myc protein are essential for cell transformation: the C- terminal 100 amino acids which encompass the DNA binding basic/helix-loop- helix/leucine zipper region (B/HLH/LZ), and a small 20 amino acid segment from the N-terminus (called Myc homology box II of MbII) that is conserved in all members of the Myc family of proteins. This project will address the function of MbII domain of c-Myc through an analysis of the nuclear proteins that bind to this region and which are also essential for the transforming activity of the oncoprotein. Previous studies have showed that dominant interfering alleles of the c-Myc protein form protein complex that are dependent on the integrity of MbII and hence correlate with nuclear factors that may be essential for c-Myc function. The specific aims are as follows: I. Analyze the function of a novel protein called TR-AP that binds to the essential MBII region of the c-Myc oncoprotein in vivo. Genetic evidence suggests that TR-AP is required for the transforming activity of c-Myc and hence is a critical effector of c-Myc function. It is hypothesized that the c-Myc/Max heterodimer recruits TR-AP to specific chromosomal sites to alter gene expression and/or chromatin structure. II. Analyze the function of the yeast homologue of human TR-AP (called TRA1) to determine the essential role that this gene plays in growth. Yeast strains deficient in TRA1 will then be used to conduct a genetic screen to identify human and yeast genes that can complement a loss-of- function mutation in TR-AP. These experiments offer a novel genetic approach toward an understanding of c-Myc function. III. Purify and clone a nuclear protein that can bind tightly to the N-Myc oncoprotein and which appear to bind specifically to N-Myc but not c-Myc. He will also conduct a systematic mapping of the functional domains of the N-Myc protein to correlate important regions with nuclear factor interactions.

The indigenous microbiota of the mouth and other mucosal surfaces exists in homeostasis with the host except when perturbed, the mucosal surface damaged or the immune system compromised. Then, commensal bacteria are capable of causing severe opportunistic infections. Adaptive humoral immunity at mucosal surfaces principally is effected by secretory immunoglobulin A (SIgA) that is thought to play a role in the regulation of commensal bacteria. However, despite the fact that saliva contains SIgA antibodies reactive with commensal bacteria, these microorganisms colonize and persist on mucosal and tooth surfaces. This suggests that indigenous oral bacteria are unaffected by, not subjected to, or are able to avoid immune elimination by mucosal antibodies. This assertion is supported by data published by others showing that the acquisition and composition of the oral and intestinal indigenous microbiota of mice lacking mucosal SIgA and their litter mates do not differ, and that colonization of mice by commensal enteric bacteria appears to generate a self-limiting mucosal immune response resulting in a state of chronic hypo-responsiveness. During the previous funding period we have demonstrated, in a longitudinal study of human infants from birth to two years of age, that the commensal oral bacterium, S. mitis biovar 1, induces a limited antibody response in saliva with salivary SIgA antibodies reactive with this bacterium showing a significant decline from birth to two years of age. Furthermore, this bacterium demonstrated extensive genetic diversity and evidence of clonal replacement. Concomitantly, Western blots of envelope antigens of type strains of this bacterium showed a similar high degree of variability. In this competing continuation, the hypothesis to be tested is that commensal bacteria persist in the mouth by inducing a limited salivary SIgA antibody response due to antigenic variation mediated via clonal replacement. Employing a longitudinal study of infants from birth to 12 months, the Specific Aims are to (1) analyze the clonal diversity of S. mitis biovar 1 obtained from shedding surfaces within the infants' mouth and (2) analyze the diversity of SIgA antibodies in each infants' saliva reactive with their own S. mitis biovar 1 isolates. This work should provide important information concerning colonization of the human mouth by pioneer bacteria and may demonstrate the ability of SIgA to influence the presence of specific bacterial clones.

This planning grant is designed to serve as the foundation for a full-scale proposal to the IERI. During planning grant the project will run a pilot study which begins to integrate the existing activities in order to collect preliminary data on barriers to vertical integration, and will work with a second geographical location as a site for studying the replication of the vertical integration model system.

The major goal of the long term research project is to identify the institutional and social arrangements necessary for the successful vertical integration of proven after-school educational K-12 programs. Currently, these programs operate independently at the pre-school, elementary school, middle and high school levels. Our goal is to bring together an interdisciplinary team to design a vertically integrated system of such activities and to develop a set of methodological tools which will be useful for studying and integrating after-school programs more generally. This vertical integration will constitute an effective pipeline for educational achievement in SMET. Such integration is necessary for the development of individual students, for the mutual support of after-school and school activities, and for sustaining these design efforts.

Typically when a teacher wants to probe a student's understanding of a concept, she asks him to write about it. In science students write lab reports, in reading they write book reports; even in math, students often have to write how they solved the math problem. Unfortunately, many students do not enjoy writing and therefore do not necessarily give the teacher the insight she is looking for. In currently funded NSF work at Tufts University, researchers are developing a software toolset that allows students to build stop action movies (SAM) as a means for representing ideas about math and science. SAM is not meant to replace the standard reporting methods, but rather to augment them. Tufts investigators, looking at how students learn differently as a result of the difference in reporting mechanism, are finding that animation can even motivate and drive the learning (because students want to improve their movies). This ongoing work has reached the halfway point, and is starting to show preliminary successes in the classroom. Changing the reporting methodology has resulted in students being excited about coming to class. They willingly stay after class to complete their "reports", and will actively discuss the science they are learning with each other and with the teacher. This exploratory grant will allow the PI to join the Tufts team, as it were, so that the project can branch out into other learning environments while still in the development stage. The PI will extend the research to non-school-based learning environments, with particular concentration on reaching out to African-American and Latino communities. The timing of this work is critical for both institutions, and the results will be mutually beneficial. Outcomes of this exploratory project will enable Tufts to improve the user interface while their SAM software is still in development, and thereby potentially open up a new learning market. UCSD, on the other hand, will acquire new tools to teach logical thinking and elementary programming to disadvantaged populations, exploiting the substantial infrastructure and expertise they already have in place.

Broader Impacts: This research will extend the SAM approach into non-traditional educational settings (e.g., the after-school learning environment) for disadvantaged students, and will further help our understanding in general of how kids learn in different environments.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Recently developed diffusion weighted imaging (DWI) technology provides an unprecedented view of anatomical connectivity in the living human brain. The most popular DWI modeling method is diffusion tensor imaging (DTI). Unfortunately, this method is severely limited in its ability to resolve white matter tract crossings, which occur quite often in the human brain (Alexander et al., 2002). We will use advanced DWI modeling methods, such as PAS-MRI, Q-Ball, and probabilistic tractography, to more accurately resolve white matter tract crossings and anatomical connectivity between brain regions. We plan to use supercomputing resources mostly for the computationally intensive PAS-MRI algorithm (based on maximum-entropy spherical deconvolution;Jansons et al., 2003 and Alexander et al., 2005). Resolving white matter tract crossings with this algorithm takes one minute per voxel on modern desktop computers. With 786432 voxels (128 X 128 in-plane, and 48 slices) it would take 546 days to compute just one subjects white matter tractography. We hope using supercomputing resources will make this a more practical endeavor.

DESCRIPTION (provided by applicant): The goal of this Pathway to Independence Award (K99/R00) application is to obtain training in the cognitive neuroscience of flexible cognitive control and brain network analysis from expert researchers in preparation for independence, where this training will be used to start a laboratory that investigates the network mechanisms of flexible control. Flexible control - a capacity supporting adaptive, goal-directed behavior important in daily life - is affected in a variety of mental illnesses, markedly reducing quality o life. Critically, the mechanisms underlying flexible control remain poorly understood at both cognitive and neural levels. A large body of evidence suggests that flexible control is implemented across a variety of situations by a set of fronto-parietal brain regions sometimes referred to as the cognitive control network (CCN). We recently found that CCN regions have among the highest global brain connectivity (GBC) in the human brain and, more importantly, that GBC in a lateral prefrontal CCN region strongly predicts fluid reasoning - suggesting flexible control is linked to the global connectivity properties of specific brain regions. Based on these findings, we postulate the flexible hub hypothesis: that some CCN regions are able to use their extensive connectivity to flexibly reconfigure currently active connections (with task-relevant sensory, semantic, and motor regions) according to task demands. We will investigate the hypothesis that flexible hubs are a key neural mechanism underlying flexible control by determining the neural network and cognitive properties underlying the relationship between flexible hubs and flexible control. During the mentored (K99) phase I will receive training in graph theory from Dr. Steve Petersen (co-mentor), Dr. Olaf Sporns (collaborator), and Dr. Deanna Barch (collaborator) to enable the development of more quantitatively precise network property indicators that can identify and define flexible hubs in the human brain. Further, trainin in individual differences approaches from Dr. Todd Braver (mentor) and Dr. Randall Engle (collaborator) will enable the development of more quantitatively precise cognitive measures of flexible control. During the independent (R00) phase we will then build upon this research and training to determine how dynamic (across-task) flexible hub connectivity changes are related to stable network properties and flexible control abilities. This rigorous characterization of the lin between flexible hubs and flexible control will enable a more comprehensive understanding of the flexible control impairments present in a variety of mental illnesses. Training will take place at Washington University in St. Louis, which has extensive intellectual and equipment resources for conducting studies of executive functions involving individual differences and functional connectivity magnetic resonance imaging (fcMRI). Dr. Braver is a world expert in cognitive control research and has extensive experience using individual differences methodology with functional MRI, which makes him an excellent mentor for the proposed training plan. Dr. Petersen is a world expert in developing graph theory fcMRI methods and applying them to cognitive control research, makes him an excellent co-mentor for the proposed training plan. Importantly, several well-established collaborators will also supplement my training and evaluation during the K99 phase and the transition into the independent R00 phase. I have pursued my interest in researching the cognitive neuroscience of executive functions since I was an undergraduate in Mark D'Esposito's laboratory at UC Berkeley. I subsequently went to graduate school in Walter Schneider's laboratory at the University of Pittsburgh and received a Ph.D. in Neuroscience. My graduate research led to multiple first-authored publications based on innovative research approaches driven by my strong independent research interests. Specifically, these interests led me to focus primarily on two lines of research: rapid instructed task learning (RITL) and GBC. The first, RITL, investigates the executive functions underlying flexible, adaptive human behavior (i.e., flexible cognitive control). This is important and timely research as it remains a mystery how healthy individuals are able to rapidly (i.e., in a single tril) learn a virtually infinite variety of possible tasks (and how this ability can become impaired in mental illnesses). For instance, this ability is used the first time an individual uses a cell phon (in order to adapt to differences from 'landline' phones), or any new technology. The second line of research, GBC, is focused on characterizing the brain's most connected regions. My time as a postdoctoral fellow in Dr. Braver's lab has been highly productive, as I have learned new advanced fMRI methods such as multivariate pattern analysis (MVPA), developed a new RITL cognitive paradigm, and published a paper investigating GBC deficits in schizophrenia, among other accomplishment. Critically, the proposed research plan will combine - and benefit from synergy between - the RITL and GBC lines of research in preparation for forming my own independent laboratory. I plan to develop my laboratory primarily at the confluence of these two lines of research: investigating the ways in which brain network connectivity specifies the dynamics underlying flexible cognitive control. The training and research outlined in this K99/R00 proposal are essential components of my career development plans as I transition to becoming a successful independent researcher.

? DESCRIPTION (provided by applicant): The objective of the project is to characterize the potential role of DNA methylation patterns in Sjögren's Syndrome (SS) disease etiology and mechanism. A growing body of evidence indicates that epigenetic changes, in particular, altered patterns of DNA methylation, contribute to the development of autoimmune disease and can mediate genetic risk factors. To date, aberrant DNA methylation has been associated with several human autoimmune diseases, including rheumatoid arthritis and systemic lupus erythematosus. My proposal focuses on the identification of unique epigenetic profiles in SS, focusing primarily on T cells, B cells, and salivary gland tissue, a primary site of the inflammatory disease. An understanding of these profiles in the context of genetic background, publicly available genomic data (RNA, ChIP-seq, WGBS) and annotation data (TF binding motifs, genomic QTLs), and cell types have the potential to significantly transform our understanding of SS etiology, particularly given the well-established heterogeneity in clinical manifestations. Further, these DNA methylation profiles could become useful clinical biomarkers for determining risk and prognosis in SS, especially if their biological relevance can be validated in future functional studies. The overall hypothesis of this project is that DNA methylation changes in key genomic regions are associated with SS status and phenotype. The project will use genome-wide SNP data, epigenome-wide methylation array data, and clinical characteristics abstracted from 100 SS cases and 20 controls to address 3 related hypotheses: First, that epigenome-wide DNA methylation patterns in T cells, B cells (both derived from peripheral blood), and salivary gland biopsy tissue are associated with primary SS status after correcting for cell-type heterogeneity. Case-control differences will be tested using supervised machine learning algorithms, new region-discovery methods, and cell-mixture inference techniques. Publicly available data (listed above) will be used to infer biological relevance. Second, that epigenome-wide DNA methylation patterns in these samples are representative of SS sub-phenotypes. Cases (and initially controls) will be clustered using principal component analysis (PCA) applied to all relevant DNA methylation probes and subsets of probes measuring CpGs implicated in specific pathways relevant to SS. The reduced representations will be tested for association with specific clinical and serological profiles. Third, that risk alleles identifie by genome-wide association studies (GWAS) are directly or indirectly associated with SS-specific DNA methylation patterns. Allelic dosage and random forest selection frequency (RFSF) analyses will be used to identify novel methylation quantitative trait loci within SS-associated genes in cases and controls (separately), and we will test whether cell-proportion or eQTLs can explain SS-specific methylation patterns.

This Major Instrumentation Grant award supports the Acquisition of a GPU cluster to support interdisciplinary research in human learning, machine learning, and data science at Rutgers University--Newark, a Minority Serving Institution (MSI). It permits purchase of 3 Nvidia dual V100 GPUs to enable theoretical advances and practical applications in interdisciplinary understanding of learning. Rutgers-Newark is undertaking a multiyear effort to build strength in interdisciplinary computer science to support research training, and to address issues of diversity and representation within computer science and data science. These resources would: (1) enable the application of computationally-intensive methods in order to develop new theories and tools to understand human and machine learning; (2) support existing cross-disciplinary training efforts, such as graduate-level courses centered around deep learning and Deep Gaussian Processes; (3) enhance existing funded research by allowing the deployment of advanced data-analytic methods. The GPU cluster will provide a common computational resource for researchers from the Computer Science, Psychology, and Neuroscience departments through which they may collaborate to advance the state-of-the-art in each field. This purchase will complement the existing high-performance computing infrastructure already on campus as well as a recent NSF-supported purchase of a 1.2 petabyte storage system for cataloging the dynamics of human visual experience. Also, it will supplement an NSF-sponsored Mobile Maker Center for community-based data collection and fMRI research.

Humans remain the most powerful and impressive available models of learning, although the roots of these abilities are not fully understood. Although machine learning methods have become exceptionally powerful in recent years, they remain opaque in ways that human learning is not and still require vastly more data, energy and compute power than human learners. Both human and machine learning would benefit from the ability to more tightly connect and study the strengths of each. Gaussian processes provide one such unifying framework. They are an object of interest in machine learning, where they have dual interpretations as regression models and as neural networks, as well as in human learning where they have been proposed as models of cognition and perception. These multiple interpretations of Gaussian processes are key to their interest for bridging human and machine learning. From a theoretical perspective, Gaussian processes are equivalent to (a specific type of) neural network, but much more amenable to mathematical analysis, and can be stacked to obtain Deep Gaussian processes. This Deep learning framework may allow more systematic mathematical analysis than other Deep learning approaches---for example the ability to derive explanations for their inferences. The primary research goal of this project is to use the GPU cluster and the investigators' interdisciplinary expertise to draw deep connections between machine learning and human learning perspectives to advance the state of the art in both, while also improving data analytic capabilities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Polymer reinforced composites are materials that combine reinforcement materials such as carbon or glass fiber, or glass particles with a polymeric base material to produce a material with enhanced mechanical properties. Utilization of these materials has revolutionized industries involved in aerospace, automotive, and sporting goods manufacture. Increasingly, industry is turning to additive manufacturing, or 3D printing, to realize customized components with complex geometries. However, stereolithography, an additive manufacturing process that uses light to locally cure (harden) a liquid polymer resin in layers to build up a solid part, cannot successfully produce polymeric reinforced composites. Nor can the process easily incorporate material property gradients within a single build. This Grant Opportunities for Academic Liaison with Industry (GOALI) project seeks to overcome these limitations by understanding the material processing interactions occurring during a modified stereolithography printing process capable of combining polymers and nanoparticles to produce printed polymer composite materials. Success will advance the performance and range of polymeric materials that can be printed via stereolithography, and in doing so will realize the 3D printing of high performance, customizable, functionally graded components. This has the potential to advance the competitiveness of core US industries involved in the manufacture of aerospace, automotive, and medical components. As Align Technology, a manufacturer utilizing stereolithography in their custom-made orthodontics fabrication process, is a collaborator on this project the students involved in the project will not only be exposed to advanced material science and manufacturing technologies but will also gain an understanding of industrial challenges and drivers. Extended online courses will be made available to students and practicing engineers, providing flexible learning opportunities to keep informed of new developments in materials science and manufacturing.

The primary goal of this project is to elucidate the structure/property relationships of gradient composite polymers printed by gray scale stereolithography of a matrix polymer followed by swelling with a reactive filler containing nanoparticles. A secondary goal is to reduce, control or eliminate the large internal stresses caused by polymerization shrinkage and solvent swelling of stereolithographic parts. The latter will be achieved by employing covalent adaptable matrices, e.g. addition-fragmentation chain transfer backbones that rearrange to relax stress in the presence of radicals. To achieve these goals the following tasks will be conducted; 1) precise, macroscopic characterization of matrix monomer-to-polymer conversion as a function of processing conditions and how this partial conversion controls swelling of the filler, 2) validation of the macroscopic predictions on the micron scale via gray-scale stereolithography of the matrix followed by swelling and polymerization of the filler, 3) validation of the predicted viscoelastic behavior of inhomogeneous printed nanocomposites, and 4) demonstration that reversible addition-fragmentation chain transfer chemistry can be leveraged to provide local stress control in bulk composites. If successful the knowledge gained will be used to print and verify the predicted properties of a printed trinary nanocomposite with photo-induced plasticity.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This award provides a state of the art MRI scanners, such as the SIEMENS PRISMA magnetic resonance imager to the Rutgers University Newark. This model has ultra-fast collection times in 100s of milliseconds and sharp detail in (0.1mm) spatial resolution. The combination of these features and many other recent innovations in MRI will provide for novel research and fundamental breakthroughs in brain research, impacting on the characterization and basic understanding of mental health disease (e.g. Schziophrenia, Depression, Autism) as well as furthering more general understanding of areal connectivity within the human brain.

RUBIC is a core research center for all Rutgers campuses and a regional resource for institutions and research groups throughout the northeast corridor. Specific areas of research are immediately enabled by the PRISMA and other core areas are strengthened. These research areas include (1) Human connectome research and network neuroscience, (2) Decision science and reward learning (3). Basic research on Alzheimer's and characterization of various types of dementia. RUBIC has 25-30 PI researchers in any given research cycle, and has an active growing community of researchers at RUTGERS and in nearby institutions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This award to Rutgers University-Newark supports the acquisition and deployment of a High-Performance Computing (HPC) cluster (named PRICE) dedicated to research, teaching and societal outreach efforts. PRICE will have 60 general compute (CPU) nodes and one graphical processing unit (GPU) node as well as storage appropriate for the planned usage over the lifetime of the machine. The enabled research develops along three main directions: atomistic modeling, neuroscience, and data science. Some atomistic models enabled by PRICE will study the structure and dynamics of proteins to address questions related to diseases such as Alzheimer’s. New materials modeling and design is enabled both by PRICE and by the development of new quantum simulation methods. The enabled simulations will also regard new materials design by way of genetic algorithms. The enabled neuroscience research regards computational analysis of experimental data to understand brain function, connectivity, and human behavior. Enabled data science research includes the formulation of novel cooperative artificial intelligence (AI) algorithms that will improve the outcome of machine learning (ML) models of broad applicability. In addition to enabling new science, the project realizes several societal broader impacts including broadening HPC literacy of underrepresented minorities and training the future NJ workforce using HPC in the classroom and development of new undergraduate and graduate curricula.

PRICE will comprise 60 compute nodes (52 cores/node), 700 TB of redundant storage and one GPU node (4 GPUs/node) to be housed at Rutgers University-Newark. PRICE will enable several additional research projects carried out by the PI, co-PIs, and major users at Rutgers-Newark and NJIT. The GPU portion enables state-of-the-art molecular dynamics simulations that elucidate structure and dynamics of proteins for the understanding of diseases, such as Alzheimer’s. GPUs also enable the efficient and timely execution of cooperative AI algorithms aimed at improving predictivity. The CPU nodes will enable quantum simulations aimed at materials engineering through density-functional theory calculations. These simulations facilitate the development of quantum models based on density functional theory, its subsystem formulation (which parallelizes efficiently over PRICE’s low-latency network) as well as quantum mechanical frameworks based on the exact factorization of the Schrödinger equation for multicomponent systems. CPU and GPU nodes will enable data analysis associated with neuroscience experiments aimed at uncovering how the brain modulates behavior and vision-related tasks as well as the study of neuron connectivity to understand brain function. Data from these experiments is growing exponentially due to increased instrument data flow from new fMRI units and improved technology allowing recordings of local field potentials from hundreds on neurons. The project also enables new science as well as the realization of societal broader impacts, such as broadening high-performance computing literacy of underrepresented minorities, training the future NJ workforce and recruitment of new faculty.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Abstract for "Brain network mechanisms of task-general cognition" <br/><br/>What are the special properties of the human brain that make us intelligent? What is the brain circuitry underlying the intelligence of geniuses such as Leonardo da Vinci, Marie Curie, Albert Einstein and the neural basis for normal human intelligence, which surpasses machine and artificial intelligence in a broad spectrum of cognitive and social tasks? Understanding the neural basis of different varieties of human intelligence is one of the great challenges in neuroscience. In addition to the scientific quest to understand the nature of human cognition and intelligence, knowing what makes the human brain intelligent would have many useful applications. For example, this knowledge could potentially be used to guide brain stimulation to help those with learning disabilities. This knowledge could also help develop brain-computer interfaces and enhance artificial intelligence, with many applications in science, engineering, and business. This project will use brain imaging and brain stimulation to learn about some of the key brain network processes that make human intelligence possible.<br/><br/>Converging evidence indicates that general human intelligence is primarily implemented by activity and connectivity in subnetworks of the brain termed cognitive control networks (CCNs). However, there is a critical need to determine how CCN activity and connectivity together generate intelligent goal-directed behavior. The overall objective of this project is to determine how CCNs implement intelligent behavior across a wide variety of different tasks. Researchers will use brain activity flow models – a novel method for determining how activity and connectivity together generate brain function –to investigate how CCNs implement task-general cognition underlying intelligent behavior. The project will utilize brain imaging and brain stimulation to build and test activity flow models of intelligent human behavior. This combined experimental and computational approach will allow testing of the hypothesis that CCNs dynamically re-route activity flows between sensory inputs and motor outputs, implementing intelligent behavior via conjunctive activations as well as dynamic connectivity changes. In addition to scientific research, this project will enhance Outreach and increase participation of underrepresented groups in STEM via supporting continuation and expansion of participation in the NSF-funded nationwide LSAMP (Louis Stokes Alliance for Minority Participation) program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.