University of South Florida
  • Tampa, FL, United States
Recent publications
Circular RNAs (circRNAs) are a class of non-coding RNAs featuring a covalently closed ring structure formed through backsplicing. circRNAs are broadly expressed and contribute to biological processes through a variety of functions. Standard gain-of-function and loss-of-function approaches to study gene functions have significant limitations when studying circRNAs. Overexpression studies in particular suffer from the lack of efficient genetic tools. While mammalian expression plasmids enable transient circRNA overexpression in cultured cells, most cell biological studies require long-term ectopic expression. Here we report the development and characterization of genetic tools enabling stable circRNA overexpression in vitro and in vivo. We demonstrated that circRNA expression constructs can be delivered to cultured cells via transposons, whereas lentiviral vectors have limited utility for the delivery of circRNA constructs due to viral RNA splicing in virus-producing cells. We further demonstrated ectopic circRNA expression in a hepatocellular carcinoma mouse model upon circRNA transposon delivery via hydrodynamic tail vein injection. Furthermore, we generated genetically engineered mice harbouring circRNA expression constructs. We demonstrated that this approach enables constitutive, global circRNA overexpression as well as inducible circRNA expression directed specifically to melanocytes in a melanoma mouse model. These tools expand the genetic toolkit available for the functional characterization of circRNAs.
Germline-encoded pattern recognition receptors [PRRs] in mammalian cells function in the detection of molecular patterns associated with pathogen invasion or cellular damage. A PRR subset is activated by the atypical presence and location of double-stranded RNA [dsRNA] or its synthetic analogue polyinosinic-polycytidylic acid [poly(I:C)], triggering pro-inflammatory signalling and death in many cell types. Poly(I:C) has been tested as a sole or combination cancer therapy in preclinical studies and clinical trials. The purpose of this study was to evaluate the effects of poly(I:C) transfection via electroporation on cell lines from a cancer of epithelial origin, 4T1 mammary carcinoma, and a cancer of mesenchymal origin, WEHI 164 fibrosarcoma. The effects of the poly(I:C) delivery on cell metabolism implicate the induction of cell death. A pro-inflammatory response was demonstrated by mRNA upregulation and the secretion of Type I interferon and several cytokines and chemokines. The mRNAs of dsRNA sensor DExD/H-box helicase 58/retinoic acid-inducible gene I protein [Ddx58/RIG-I] and sensor/co-sensor DEAH-box helicase 9 [Dhx9] were not regulated, but the mRNAs of RNA sensors toll-like receptor 3 [TLR3], interferon-induced with helicase C domain 1/melanoma differentiation-associated protein 5 [Ifih1/MDA5] and Z-DNA binding protein 1 [Zbp1] and co-sensors DEAD (Asp-Glu-Ala-Asp) box polypeptide 60 [Ddx60] and interferon-inducible protein 204 [Ifi204] were upregulated in both cell lines. The mRNAs encoding signalling pathways components were present or upregulated in both cell types. These data demonstrate that RNA sensing effects can be amplified by electroporation delivery, potentially expanding the practicality of this immunotherapeutic approach.
Background: Participants' study satisfaction is important for both compliance with study protocols and retention, but research on parent study satisfaction is rare. This study sought to identify factors associated with parent study satisfaction in The Environmental Determinants of Diabetes in the Young (TEDDY) study, a longitudinal, multinational (US, Finland, Germany, Sweden) study of children at risk for type 1 diabetes. The role of staff consistency to parent study satisfaction was a particular focus. Methods: Parent study satisfaction was measured by questionnaire at child-age 15 months (5579 mothers, 4942 fathers) and child-age four years (4010 mothers, 3411 fathers). Multiple linear regression analyses were used to identify sociodemographic factors, parental characteristics, and study variables associated with parent study satisfaction at both time points. Results: Parent study satisfaction was highest in Sweden and the US, compared to Finland. Parents who had an accurate perception of their child's type 1 diabetes risk and those who believed they can do something to prevent type 1 diabetes were more satisfied. More educated parents and those with higher depression scores had lower study satisfaction scores. After adjusting for these factors, greater study staff change frequency was associated with lower study satisfaction in European parents (mothers at child-age 15 months: - 0.30,95% Cl - 0.36, - 0.24, p < 0.001; mothers at child-age four years: -0.41, 95% Cl - 0.53, - 0.29, p < 0.001; fathers at child-age 15 months: -0.28, 95% Cl - 0.34, - 0.21, p < 0.001; fathers at child-age four years: -0.35, 95% Cl - 0.48, - 0.21, p < 0.001). Staff consistency was not associated with parent study satisfaction in the US. However, the number of staff changes was markedly higher in the US compared to Europe. Conclusions: Sociodemographic factors, parental characteristics, and study-related variables were all related to parent study satisfaction. Those that are potentially modifiable are of particular interest as possible targets of future efforts to improve parent study satisfaction. Three such factors were identified: parent accuracy about the child's type 1 diabetes risk, parent beliefs that something can be done to reduce the child's risk, and study staff consistency. However, staff consistency was important only for European parents. Trial registration: NCT00279318 .
TP53 is a key tumor suppressor gene involved in fundamental biological processes of genomic stability and is recurrently mutated in a subgroup of myelodysplastic syndromes and acute myeloid leukemia. These patients have unique clinical and molecular features resulting in dismal outcomes despite standard cytotoxic chemotherapy, and long-term survival is seldom achieved with allogeneic stem cell transplant. Upfront use of hypomethylating agents with or without venetoclax has resulted in a favorable initial response over intensive cytotoxic chemotherapy, albeit responses are nondurable, and the median overall survival is typically less than 6 to 8 months. In this review, we examine the evidence of conventional treatments and focus on the emerging novel therapeutic options, including targeted molecular and immunotherapies for this challenging molecular subgroup. Together, there are still significant unmet needs to improve outcomes of patients with TP53 mutated myelodysplastic syndromes and acute myeloid leukemia, and enrollment in clinical trials should be highly favored whenever they are available.
Background Altered DNA methylation (DNAm) may be one pathway through which early-life adversity (ELA) contributes to adverse mental and physical health outcomes. This study investigated whether the presence versus absence of ELA experiences reflecting the dimensions of threat and deprivation were associated with epigenome-wide DNAm cross-sectionally and longitudinally in a community-based sample of children and adolescents. Methods In 113 youths aged 8–16 years with wide variability in ELA, we examined associations of abuse (physical, sexual, emotional; indicating threat-related experiences) and neglect (emotional, physical; indicating deprivation-related experiences) with DNAm assessed with the Illumina EPIC BeadChip array, with DNA derived from saliva. In cross-sectional epigenome-wide analyses, we investigated associations of lifetime abuse and neglect with DNAm at baseline. In longitudinal epigenome-wide analyses, we examined whether experiencing abuse and neglect over an approximately 2-year follow-up were each associated with change in DNAm from baseline to follow-up. Results In cross-sectional analyses adjusting for lifetime experience of neglect, lifetime experience of abuse was associated with DNAm for four cytosine-phosphodiester-guanine (CpG) sites (cg20241299: coefficient = 0.023, SE = 0.004; cg08671764: coefficient = 0.018, SE = 0.003; cg27152686: coefficient = − 0.069, SE = 0.012; cg24241897: coefficient = − 0.003, SE = 0.001; FDR < .05). In longitudinal analyses, experiencing neglect over follow-up was associated with an increase in DNAm for one CpG site, adjusting for abuse over follow-up (cg03135983: coefficient = 0.036, SE = 0.006; FDR < .05). Conclusions In this study, we identified examples of epigenetic patterns associated with ELA experiences of threat and deprivation that were already observable in youth. We provide novel evidence for change in DNAm over time in relation to ongoing adversity and that experiences reflecting distinct ELA dimensions may be characterized by unique epigenetic patterns.
Acute pericarditis is caused by the inflammation of the pericardium which can result in an effusion around the heart. Proton beam therapy causing radiation-induced pericarditis is not a well-known cause of pericarditis. We present a case of a patient with Li-Fraumeni Syndrome who developed acute onset pericarditis, presumed to be secondary to proton beam therapy.
Background The BIN1 locus contains the second-most significant genetic risk factor for late-onset Alzheimer’s disease. BIN1 undergoes alternate splicing to generate tissue- and cell-type-specific BIN1 isoforms, which regulate membrane dynamics in a range of crucial cellular processes. Whilst the expression of BIN1 in the brain has been characterized in neurons and oligodendrocytes in detail, information regarding microglial BIN1 expression is mainly limited to large-scale transcriptomic and proteomic data. Notably, BIN1 protein expression and its functional roles in microglia, a cell type most relevant to Alzheimer’s disease, have not been examined in depth. Methods Microglial BIN1 expression was analyzed by immunostaining mouse and human brain, as well as by immunoblot and RT-PCR assays of isolated microglia or human iPSC-derived microglial cells. Bin1 expression was ablated by siRNA knockdown in primary microglial cultures in vitro and Cre-lox mediated conditional deletion in adult mouse brain microglia in vivo. Regulation of neuroinflammatory microglial signatures by BIN1 in vitro and in vivo was characterized using NanoString gene panels and flow cytometry methods. The transcriptome data was explored by in silico pathway analysis and validated by complementary molecular approaches. Results Here, we characterized microglial BIN1 expression in vitro and in vivo and ascertained microglia expressed BIN1 isoforms. By silencing Bin1 expression in primary microglial cultures, we demonstrate that BIN1 regulates the activation of proinflammatory and disease-associated responses in microglia as measured by gene expression and cytokine production. Our transcriptomic profiling revealed key homeostatic and lipopolysaccharide (LPS)-induced inflammatory response pathways, as well as transcription factors PU.1 and IRF1 that are regulated by BIN1. Microglia-specific Bin1 conditional knockout in vivo revealed novel roles of BIN1 in regulating the expression of disease-associated genes while counteracting CX3CR1 signaling. The consensus from in vitro and in vivo findings showed that loss of Bin1 impaired the ability of microglia to mount type 1 interferon responses to proinflammatory challenge, particularly the upregulation of a critical type 1 immune response gene, Ifitm3 . Conclusions Our convergent findings provide novel insights into microglial BIN1 function and demonstrate an essential role of microglial BIN1 in regulating brain inflammatory response and microglial phenotypic changes. Moreover, for the first time, our study shows a regulatory relationship between Bin1 and Ifitm3 , two Alzheimer’s disease-related genes in microglia. The requirement for BIN1 to regulate Ifitm3 upregulation during inflammation has important implications for inflammatory responses during the pathogenesis and progression of many neurodegenerative diseases. Graphical Abstract
Background We reviewed the epidemiology, risk factors, pathophysiology, and clinical presentations of coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM), then discussed the importance of rapid diagnosis and treatment facilitated by multidisciplinary approach. Main body India has reported world’s highest number of CAM cases where Rhizopus arrhizus was the most predominant etiology. CAM caused by Rhizopus microsporus was the most common from the rest of the world. Multiple risk factors for CAM were identified including diabetes mellitus, inappropriate corticosteroid use, COVID-19-related hypoxia, and lung damage. Rhino-orbito-cerebral mucormycosis (ROCM) accounted for almost 90% of CAM in India while 64% of global cases were ROCM. Less than 10% of CAM from India were pulmonary while the rest of the world reported 21% of pulmonary CAM. CAM is diagnosed by confirmed SARS-CoV2 infection along with clinical, radiological, histopathological, and/or microbiological evidence of mucormycosis. In patients with risks of CAM and associated symptoms, CT or MRI are recommended. If ROCM is suspected, endoscopy and biopsy are recommended. If pulmonary CAM is suspected, tissue biopsies, nasal samples, or bronchoalveolar lavage is recommended with histopathological exams. Early diagnosis, surgical, and pharmaceutical interventions are key to treat mucormycosis. Upon diagnosis, antifungal therapy with liposomal amphotericin B (IV) is considered first-line of therapy. Alternatively, posaconazole (PO/IV) or isavuconazole (PO/IV) can be used. Conclusion Treating CAM requires a multidisciplinary approach for early diagnosis and prompt initiation of interventions to maximize patient’s chance of survival.
The integration of dissimilar materials into heterostructures has become a powerful tool for engineering interfaces and electronic structure. The advent of 2D materials has provided unprecedented opportunities for novel heterostructures in the form of van der Waals stacks, laterally stitched 2D layers and more complex layered and 3D architectures. This Primer provides an overview of state-of-the-art methodologies for producing such van der Waals heterostructures, focusing on the two fundamentally different strategies, top-down deterministic assembly and bottom-up synthesis. Successful techniques, advantages and limitations are discussed for both approaches. As important as the fabrication itself is the characterization of the resulting engineered materials, for which a range of analysis techniques covering structure, composition and emerging functionality are highlighted. Examples of the properties of artificial van der Waals structures include optoelectronics and plasmonics, twistronics and unique functionality arising from the generalization of van der Waals assembly from 2D to 3D crystalline components. Finally, current issues of reproducibility, limitations and opportunities for future breakthroughs in terms of enhanced homogeneity, interfacial purity, feature control and ultimately orders-of-magnitude increased complexity of van der Waals heterostructures are discussed. Van der Waals epitaxy provides numerous opportunities for materials integration in heterostructures. This Primer provides an overview of methodologies for producing van der Waals heterostructures, focusing on top-down assembly and bottom-up synthesis, and discusses future opportunities for their continued development.
Introduction Elderly undertriage rates are estimated up to 55% in the United States. This study examined risk factors for undertriage among hospitalized trauma patients in a state with high volumes of geriatric trauma patients. Materials and methods This is a population–based retrospective cohort study of 62,557 patients admitted to Florida hospitals between 2016 and 2018 from the Agency for Healthcare Administration database. Severely injured trauma patients were defined by American College of Surgeons definitions and an International Classification of Disease Injury Severity Score <0.85. Undertriage was defined as definitive care of these severely injured patients at any Florida hospital other than a state-designated trauma center (TC). Univariate analyses were used to identify risk factors associated with inpatient mortality and undertriage. Multiple variable regression was used to estimate risk-adjusted odds of mortality after admission to either a designated or nondesignated TC. Results Undertriaged patients were more likely to have isolated traumatic brain injuries, lower International Classification of Disease Injury Severity Scores, multiple comorbidities, and older age. Trauma patients aged 65 and older were more than twice as likely to be undertriaged (34% versus 15.7%, P < 0.0001). Undertriaged patients of all ages were also more likely to suffer from pneumonia, urinary tract infection, arrhythmias, and sepsis. After risk adjustment, severely injured trauma patients admitted to non-TC were also more likely to be at risk for mortality (adjusted odds ratio, 1.27; 95% confidence interval, 1.17-1.38). Conclusions Age and multiple comorbidities are significant predictors of mortality among undertriage of trauma patients. As a result, trauma triage guidelines should account for high-risk geriatric trauma patients who would benefit from definitive treatment at designated TCs.
Research that illuminates causes of urban forest storm damage is valuable for planning and management. However, logistical and safety concerns often delay post-storm surveys in urban areas; thus, surveys may include observations with unverified sources of damage. While this uncertainty is often ignored, it can make up a high proportion of the number of damaged trees. The goal of this research was to improve understanding of techniques for modeling storm damage in urban forests. Using urban forest storm damage inventories collected in Florida, post-Hurricane Irma (2017), we tested how different imputation methods, modeling procedures, and damage frequency levels could impact overall model results. We utilized machine learning algorithms Random Forest (RF) and k-Nearest Neighbors (KNN), and generalized linear models (GLM). We found that GLM and RF models gave overall unbiased predictions of damage across all methods and rarity levels, while KNN consistently under-predicted damage. Damage frequency influenced some measures of performance but did not impact variable significance. Imputation methods all identified consistent variables of most significance within each model procedure; however, there was variation among variables ranked moderately important. While both GLM and RF models identified plot tree basal area as highly significant damage predictors, they otherwise disagreed on individual variable importance. These findings suggest that while explanatory models for urban forest storm damage can be achieved by examining linear relationships, more complex relationships such as the ones identified by RF models can have equal explanatory power with different subsets of predictor variables.
In 1963, Corrádi and Hajnal proved that every graph with at least 3k vertices and minimum degree at least 2k contains a collection of k vertex-disjoint cycles. The sharpness examples for this theorem were characterized by Kierstead, Kostochka, and Yeager in 2017 and one consequence of this characterization is that when k≥3, every graph with n≥3k vertices, minimum degree at least 2k−1, and independence number at most n−2k−1 has k vertex-disjoint cycles. We extend this result by showing that there exists β>0 and t0 such that for every t≥t0, k≥25t and n≥4k+t, every graph on n vertices with minimum degree at least 2k−t and independence number at most n−2k−t+βtlogt contains a collection of k vertex-disjoint cycles. We also show that the condition on the independence number is sharp up to the constant β.
Background Most people who survive suicide attempts neither re-attempt suicide nor die by suicide. Research on suicide attempt survivors has primarily focused on negative endpoints (e.g., increased suicide risk) rather than positive outcomes. One important outcome is psychological well-being (PWB), defined as positive functioning across emotional, intrapersonal, and interpersonal domains. We compared PWB among US military veterans with (i.e., attempt survivors) and without (i.e., non-attempters) a history of suicide attempt(s) using data from three nationally representative cohorts. Methods Each US veteran cohort (Cohort1: N = 3148; Cohort2: N = 1474; Cohort3: N = 4042) completed measures of suicidality (e.g., attempt history), character strengths (e.g., curiosity, optimism), psychological symptoms (e.g., depression), and indicators of PWB (e.g., happiness). t-Tests were conducted to examine group differences in PWB; hierarchical regressions were conducted to examine suicide attempt status as a predictor of PWB controlling for symptoms and demographics. Multivariable regressions were conducted to identify predictors of PWB among attempt survivors. Results In each cohort, reported PWB was markedly lower among suicide attempt survivors than non-attempters (ds = 0.9–1.2), even after adjusting for mental health symptoms. Individual differences in PWB were observed, with a subset of suicide attempt survivors reporting higher PWB levels than non-attempters (1.4–7.4 %). Curiosity and optimism were positively associated with PWB among suicide attempt survivors (rs = 0.60–0.78). Limitations Data were cross-sectional, limiting inferences about causation and directionality of associations. Conclusions Findings highlight diminished PWB as an important and understudied concern among veteran attempt survivors. Collectively, our findings underscore the importance of considering PWB in the research, assessment, and treatment of suicidality.
Social capital is a critical glue for economic and social development in urban areas. Yet, to effectively guide research and practice, there is a need for careful measurement of social capital and how it links to important aspects of urban system functions. This study is aimed at examining the multi-dimensional nature of social capital and the relationship between these dimensions and travel behavior. Prior research has shown connections between stand-alone social capital concepts, such as resources gathered via social networks, with specific aspects of travel behavior. In this work, we expand the definition of social capital to cover separate dimensions, modeled via multiple indicators. Specifically, we make use of over 1400 observations from the Pew Internet Networks and Community Survey dataset to build a Structural Equation Model dividing social capital into two latent dimensions: bonding and bridging to examine the relationship of both these dimensions with discretionary urban activity participation diversity and frequency. Moreover, broader measures of neighborhood and community engagement are included in the model to explain how such engagement can help with the accumulation of social capital. Our results indicate a positive but differential relationship between both social capital dimensions and activity participation. Further, the results also suggest an absence of correlation between bonding and bridging capital, strengthening the hypothesis that social capital is multi-dimensional. In terms of explaining the social capital accrual, we find that while community engagement is positively correlated to bridging capital, no evidence was found for a relationship between community engagement and bonding capital. Further, neighborhood engagement was not found to be associated with any of the social capital dimensions. This suggests that individuals predominantly rely on close-knit and stronger relationships for social/emotional support, while instead, community engagement significantly helps in the accumulation of bridging capital. The result from the study can be used by policy makers to improve transportation planning, management, and community well-being.
Background Respiratory viruses remain a key cause of early childhood illness, hospitalization, and death globally. The recent pandemic has rekindled interest in the control of respiratory viruses among paediatric populations. We estimate the burden of such viruses among children <2 years. Methods Enrolled neonates were followed until two years of age. Weekly active symptom monitoring for the development of acute respiratory illnesses (ARI) defined as cough, rhinorrhoea, difficulty breathing, asthenia, anorexia, irritability, or vomiting was conducted. When the child had ARI and fever, nasopharyngeal swabbing was performed, and samples were tested through singleplex RT-PCR. Incidence of respiratory viruses was calculated by dividing the number of laboratory-confirmed detections by the person-time accrued during weeks when that virus was detectable through national surveillance then corrected for under-ascertainment among untested children. Findings During December 2014–November 2017, 1567 enrolled neonates contributed 2,186.9 person-years (py). Six in ten (64·4%) children developed ARI (total 2493 episodes). Among children <2 years, incidence of respiratory syncytial virus (RSV)-associated ARI episodes (21·0, 95%CI 19·3–22·8, per 100py) and rhinovirus-associated (20·5, 95%CI 20·4–20·7) were similar and higher than parainfluenza 1–3-associated (14·2, 95%CI 12·2–16·1), human metapneumovirus-associated (9·2, 95%CI 7·7–10·8), influenza-associated (5·9, 95%CI 4·4–7·5), and adenovirus-associated ARI episodes (5·1, 95%CI 5·0–5·2). Children aged <3 months had the highest rates of RSV ARI (49·1, 95%CI 44·0–54·1 per 100py) followed by children aged 3–5 (25·1, 95%CI 20·1–30·0), 6–11 (17·6, 95%CI 13·2–21·9), and 12–23 months (11·9, 95%CI 10·8–12·9). One in ten children with RSV was referred to the hospital (2·5, 95%CI 2·1–2·8, per 100py). Interpretation Children frequently developed viral ARI and a substantive proportion required hospital care. Such findings suggest the importance of exploring the value of new interventions and increasing uptake of existing prevention measures to mitigate burden of epidemic-prone respiratory viruses. Funding The study was supported by the Centers for Disease Control and Prevention.
This paper proposes a control strategy for a freeway merging bottleneck consisting of a Connected and Automated Vehicle (CAV) exclusive lane and a human-driven vehicle (HDV) lane, aiming to achieve fuel economy and increase traffic efficiency. The trajectories of CAVs are optimized to enable them to smoothly merge into the gaps in the HDV lane. We utilize a stochastic car-following model to incorporate the uncertainty of HDVs and adopt the concept of α-percentile trajectory proposed in our earlier work (Xiong and Jiang, 2021) to estimate the trajectories of HDVs. Based on these, an optimization model is constructed to optimize the merging sequence and the merging trajectories of CAVs simultaneously. We use dynamic programming to solve the optimization model. Dividing RECTangles algorithm and Hamiltonian analysis are imbedded as a subroutine to obtain the energy efficient merging trajectory of each CAV. Simulation results show that the proposed control strategy is capable of reducing average fuel consumption and travel time under a wide range of inflow rates. The benefits depend on the inflow rate and the trajectory percentile α. When the total inflow rate is low, the impact of α is insignificant. If the total inflow rate increases to a high level, the impact of α becomes remarkable and the maximum benefits would be achieved at an intermediate range of α. Moreover, the computation efficiency of the proposed system is fast enough and can be implemented in real-time in the near future.
Due to high perishability and poor distribution management, strawberry is one of the most frequently discarded fruits. The aim of this study was to develop a non-destructive system for accurate estimation of shelf-life of strawberries using hyperspectral imaging technology. Harvested strawberries were stored for 9 day at five different temperatures. Shelf-life was calculated based on subjective visual evaluation of appearance attributes (colour, shrivelling, and decay) using a rating scale. Hyperspectral images of strawberries were obtained during cold storage, using a novel handheld push broom line-scanning hyperspectral camera. The model developed by partial least square regression (PLSR) with selected spectra was used to predict appearance scores of strawberries with a coefficient of determination of prediction (R²p) of 0.97 and root mean square error of prediction (RMSEp) of 0.17. The appearance scores from the PLSR model were used to develop a model based on first-order kinetics and Arrhenius equations to predict the remaining shelf-life of the strawberries. The models predicted remaining shelf-life with R²p of 0.86 and RMSEp of 1.4 days. Prediction models were also developed for other quality attributes and biochemical properties (weight loss, ascorbic acid, and soluble solids). The results from this study support the development a non-destructive system for the accurate estimation of shelf-life of strawberries. A system that could potentially offer objective quality assessment as product moves through the supply chain, aiding decision making and facilitating proactive actions to be taken with the aim of minimising loss/waste; benefiting food supply chain stakeholders across the globe and supporting the drive for zero waste.
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14,678 members
Yonggang Liu
  • College of Marine Science
Ulla Uusitalo
  • Department of Pediatrics
Ismail Kazem
  • Department of Oncologic Sciences
Ricardo Izurieta
  • College of Public Health
W. Edwin Clark
  • Department of Mathematics & Statistics
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Head of institution
Steve Currall
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www.usf.edu
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