Graduate Research Fellowship Research Articles

ACS congratulates NSF Graduate Research Fellowship awardees

The American Chemical Society extends its congratulations to three recent US National Science Foundation (NSF) Graduate Research Fellowship awardees who were previously involved with the ACS Bridge Project or the ACS Scholars Program—initiatives that provide support for students from groups underrepresented in the chemical sciences. The three awardees are Esteban Bautista at the University of California, Irvine, Stephanie Oliveras Santos at the University of Wisconsin–Madison, and Kala Youngblood at the University of North Carolina at Greensboro. Since 1952, NSF has awarded over 50,000 Graduate Research Fellowships to students from a pool of more than 500,000 applicants. Forty-two of these fellows have become Nobel laureates and more than 450 have joined the National Academy of Sciences.

Contributing Authors

Say Burgin is assistant professor of history at Dickinson College. Her publications have appeared in the Women's History Review, Journal of American Studies, Journal of International Women's Studies, The Nation, and elsewhere. Her first book project examines the myth that Black Power was “antiwhite” and the white fight for Black Power in Detroit. Say was a regular contributor to Black Perspectives, the blog of the African American Intellectual History Society. She also co-created the educational website Rosa Parks's Biography: A Resource for Teaching Rosa Parks (https://rosaparksbiography.org/). Follow her on Twitter @sayburgin.Robert T. Chase is associate professor of history at Stony Brook University. His research and teaching interests include the history of mass incarceration and the construction of what historians call “the carceral state.” He is also the co-director of the national organization Historians Against Slavery (HAS). He is an expert in social justice, Latino/a, and civil rights movements, and political and African American history. He is the editor of the book Caging Borders and Carceral States: Incarcerations, Immigration Detentions, and Resistance (2019). His book We are Not Slaves won the Best Book Award from the Division of Critical Criminology and Social Justice, American Society of Criminology; the Hank Lacayo Best Labor-Themed Award from the International Latino Book Award; and honorable mention for the Betty and Alfred Lee McClung Award from the Association for Humanist Sociology.Simon Hall is professor of modern history at the University of Leeds, where his research and teaching focus on the civil rights–Black Power movements, the student radicalism of the long 1960s, and global protest during the Cold War. His previous books include 1956: The World in Revolt (2016) and Peace and Freedom: The Civil Rights and Antiwar Movements in the 1960s (2005).Brandon James Render is a PhD candidate in the History Department at the University of Texas at Austin. His research interests include twentieth-century United States social and intellectual history, post-1945 social movements and “the culture wars,” and public policy. His dissertation, “Colorblind University,” traces the intellectual genealogy of race-neutral policies and practices in higher education through admissions policies, departmental structure, and curriculum design. In addition to service as a graduate research fellow at the Center for the Study of Race and Democracy in 2018–19, he is the 2021-22 Mitchem Dissertation Fellow at Marquette University.

ACS members awarded NSF Graduate Research Fellowships

ACS members awarded NSF Graduate Research Fellowships

IgM anti-ACE2 autoantibodies in severe COVID-19 activate complement and perturb vascular endothelial function.

BackgroundSome clinical features of severe COVID-19 represent blood vessel damage induced by activation of host immune responses initiated by the coronavirus SARS-CoV-2. We hypothesized autoantibodies against angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 receptor expressed on vascular endothelium, are generated during COVID-19 and are of mechanistic importance.MethodsIn an opportunity sample of 118 COVID-19 inpatients, autoantibodies recognizing ACE2 were detected by ELISA. Binding properties of anti-ACE2 IgM were analyzed via biolayer interferometry. Effects of anti-ACE2 IgM on complement activation and endothelial function were demonstrated in a tissue-engineered pulmonary microvessel model.ResultsAnti-ACE2 IgM (not IgG) autoantibodies were associated with severe COVID-19 and found in 18/66 (27.2%) patients with severe disease compared with 2/52 (3.8%) of patients with moderate disease (OR 9.38, 95% CI 2.38–42.0; P = 0.0009). Anti-ACE2 IgM autoantibodies were rare (2/50) in non-COVID-19 ventilated patients with acute respiratory distress syndrome. Unexpectedly, ACE2-reactive IgM autoantibodies in COVID-19 did not undergo class-switching to IgG and had apparent KD values of 5.6–21.7 nM, indicating they are T cell independent. Anti-ACE2 IgMs activated complement and initiated complement-binding and functional changes in endothelial cells in microvessels, suggesting they contribute to the angiocentric pathology of COVID-19.ConclusionWe identify anti-ACE2 IgM as a mechanism-based biomarker strongly associated with severe clinical outcomes in SARS-CoV-2 infection, which has therapeutic implications.FUNDINGBill & Melinda Gates Foundation, Gates Philanthropy Partners, Donald B. and Dorothy L. Stabler Foundation, and Jerome L. Greene Foundation; NIH R01 AR073208, R01 AR069569, Institutional Research and Academic Career Development Award (5K12GM123914-03), National Heart, Lung, and Blood Institute R21HL145216, and Division of Intramural Research, National Institute of Allergy and Infectious Diseases; National Science Foundation Graduate Research Fellowship (DGE1746891)

TRM and mucosal tissue sites are protected from age-associated phenotypic changes in secondary lymphoid organs

Abstract The persistence and maintenance of immunological memory is critical for long-term immunity generated in response to infection and vaccination. Aging of memory T cells in humans has predominantly been studied in the peripheral blood, and considerably less is known about the aging of memory T cells within tissues. Using tissues obtained from human organ donors, we investigated how tissue localization, expression of the CD103 integrin, and age influence the phenotype of tissue resident memory T cells (TRM). Using multi-parameter flow cytometry, we characterized diverse tissue sites from donors ages 9 to 93 years old and demonstrate that age-associated changes in the T cell compartment exhibit tissue- and subset- specific dynamics. CD8 T cells in blood-rich tissues spleen and lung have elevated expression of replicative senescence markers CD57 and KLRG1 relative to lung-associated lymph nodes (LLN), jejunum, and mesenteric lymph nodes (MLN). CD103+ TRM have the lowest expression of CD57 and KLRG1 across all tissue sites relative to both CD103− TRM and circulating TEM. CD8 T cells in lymphoid tissues spleen, LLN, and MLN exhibit the largest age-associated increases in expression of CD57, KLRG1, CD244, and PD-1. Together, these results demonstrate that age-associated phenotypic changes are most prominent in secondary lymphoid organs, while TRM and mucosal sites exhibit few senescent changes. Supported by the National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) and grants from NIH (P01 AI106697, U19 AI057266)

Cell type-specific differential expression in Alzheimer’s disease and cancer using spatial transcriptomics

Abstract Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. The detection of genes that are differentially expressed across tissue context for cell types of interest is an essential challenge for dissecting pathological mechanisms. However, changes in cell type composition across space and measurement contamination from other cell types introduce complex statistical challenges. Here, we introduce a statistical method, Generalized Linear Admixture Models for Differential Expression (GLAMDE), that estimates cell type-specific patterns of differential gene expression while accounting for localization of other cell types. By modeling spatial transcriptomics gene expression as an additive mixture, across cell types, of generalized log-linear functions, we provide a unified framework for identifying gene expression changes for a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Our approach enables statistical inference across multiple samples and replicates. We demonstrate, through simulations and validation experiments on Slide-seq and MERFISH data, that our approach accurately identifies cell type-specific differential gene expression with valid uncertainty quantification. Lastly, we apply GLAMDE to characterize spatially-localized tissue changes in the context of disease. In an Alzheimer’s mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. GLAMDE is available within the spacexr R package. D.C. was supported by a Fannie and John Hertz Foundation Fellowship and an NSF Graduate Research Fellowship. This work was supported by an NIH Early Independence Award (DP5, 1DP5OD024583 to F.C.), the NHGRI (R01, R01HG010647 to F.C.), as well as the Burroughs Wellcome Fund, the Searle Scholars Award, and the Merkin Institute to F.C.. R.A.I. was supported by NIH grants R35GM131802 and R01HG005220.

The National Science Foundation Graduate Research Fellowship Program

The purpose of the National Science Foundation Graduate Research Fellowship Program (NSF-GRFP) is to help ensure the quality, vitality, and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students in NSF-supported STEM disciplines who are pursuing research-based master's and doctoral degrees in any of the eligible fields and subfields at accredited US institutions. The five-year fellowship includes three years of financial support including an annual stipend of $34,000 and a cost of education allowance of $12,000 to the institution. NSF has a strong commitment to diversity and actively encourages women, persons who are members of groups historically underrepresented in STEM, persons with disabilities, veterans, and undergraduate seniors to apply. This session will provide the audience a brief overview of the NSF-GRFP, such as its goal, eligibility requirements, application process, and timeline. Additionally, the session will include information on the NSF-GRFP's efforts to increase representation of women and members of groups historically underrepresented in STEM with a follow-up discussion on how the audience can encourage women and members of groups historically underrepresented in STEM to apply for the program or become reviewers. The last part of the session will be reserved for Q & A. We strongly encourage interaction among the audience and presenters.

The ZFP36 family of RNA-binding proteins regulate homeostatic and autoreactive T cell responses

Abstract The zinc finger 36 (ZFP36) family of RNA-binding proteins, consisting of ZFP36, ZFP36L1, and ZFP36L2, is known to negatively regulate mRNA stability and/or inhibit translation of many transcripts, including cytokines. While there are reports of all three family members regulating T cell cytokine production, delineating the functions of these genes is challenging due to spontaneous phenotypes upon global deletion of single genes and potential redundancy in their functions. To overcome this, we generated Cd4-Cre+ Zfp36fl/fl Zfp36l1fl/fl Zfp36l2fl/fl mice. Only upon triple deletion, but not individual or paired deletions, do mice spontaneously develop an inflammatory disease characterized by early lethality, hypercytokinemia, and immune cell infiltration into some peripheral organs, including the central nervous system. As SNPs in human ZFP36L1 and ZFP36L2 have been linked to susceptibility for multiple sclerosis, we tested ZFP36 family member individual and paired T cell-deficient mice in experimental autoimmune encephalomyelitis (EAE). To our surprise, Cd4-Cre+ Zfp36l1fl/fl Zfp36l2fl/fl mice were markedly protected from EAE clinical disease, while no change in disease severity was seen with any deletion strains involving Zfp36. There was a severe impairment in generating antigen-specific CD4+ T cells in Cd4-Cre+ Zfp36l1fl/fl Zfp36l2fl/fl mice during EAE priming. Our findings demonstrate a novel redundancy of the ZFP family members in regulating T cell homeostasis and a shared role for ZFP36L1 and ZFP36L2 to promote clonal expansion. Understanding the individual and shared functions of the ZFP36 family members may lead to opportunities to target them to suppress T cell-driven autoimmunity. M.E.C. supported by the National Science Foundation Graduate Research Fellowship program (DGE-1745038) and by grant 5T32AI007163 from the NIAID. B.T.E. supported by the NIAID (R01 AI113118).

Managing Self-Confidence: Theory and Experimental Evidence

We use a series of experiments to understand whether and how people’s beliefs about their own abilities are biased relative to the Bayesian benchmark and how these beliefs then affect behavior. We find that subjects systematically and substantially overweight positive feedback relative to negative (asymmetry) and also update too little overall (conservatism). These biases are substantially less pronounced in an ego-free control experiment. Updating does retain enough of the structure of Bayes’ rule to let us model it coherently in an optimizing framework, in which, interestingly, asymmetry and conservatism emerge as complementary biases. We also find that exogenous changes in beliefs affect subjects’ decisions to enter into a competition and do so similarly for more and less biased subjects, suggesting that people cannot “undo” their biases when the time comes to decide. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: Financial support from the National Science Foundation (NSF), Harvard University, and Wesleyan University is gratefully acknowledged. P. Niehaus received financial support from an NSF Graduate Research Fellowship. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2021.4294 .

The NSF Graduate Fellowship Program: An Analysis of Awards in the Ocean Sciences by Gender and Career Stage, 1996–2021

The information published annually by the National Science Foundation on its Graduate Research Fellowship Program (GRFP) awardees was used to create an Awardees in Ocean Sciences (AOS) data set. This data set shows that women have been successful in receiving the fellowship award in the ocean sciences, receiving an overall 69% of the awards from 1996 through 2021 (458 women among 659 awardees). Women comprised at least 50% of awardees in the six ocean sciences disciplines listed as GRFP subfields of study. The highest percentages of awards to women (72%) were in biological oceanography and marine geology/geophysics, followed by marine biology and chemical oceanography (69%), physical oceanography (67%), and ocean engineering (61%). Women were successful both as undergraduate applicants (69% of undergraduate awardees) and as graduate applicants (71% of graduate awardees). We estimate that GRFP women awardees made up 17.8% of the women obtaining doctoral degrees in oceanography from 2017 to 2021, compared with GRFP men awardees comprising 8.5% of the male doctoral recipients for the same period. Our analysis suggests future directions for study of GRFP awardees and highlights the need for data that would help inform community outreach to underserved student populations.

Using the NSF Graduate Research Fellowship Proposal to Train Original Scientific Writing Skills in First-Year Graduate Students: A Demonstrated Project at the University of Iowa

Advanced scientific communication skills are highly desired for academic and nonacademic career professionals but are insufficiently developed in many graduate students. Because students with under...

Functionalized Metal-Organic Framework Toward Colorimetric CO2 Sensing in Indoor Air Environment

Carbon dioxide (CO2) has been shown to contribute to human health consequences indoors, such as shortness of breath, nasal and optic irritation, dizziness, and nausea. Given these precarious conditions for human health, various efforts have emerged toward development of CO2 monitors for indoor deployment. The chief problem in gas sensing is the design of a sensor that is highly-sensitive and selective to targeted species, energy-efficient, inexpensive to fabricate, stable, and convenient for users. One of the most popular CO2 sensors in commercial operations is the nondispersive infrared (NDIR) CO2 sensor. While boasting high accuracy and longevity, the CO2 NDIR sensor has traditionally been challenged by power consumption, cost, and bulky dimensions. In contrast to the NDIR sensing technology, colorimetric sensing retains several advantages, including easy preparation, user convenience, and obvious responses detectable by the human eye.In this work, we situate metal–organic frameworks (MOFs) as highly-porous, crystalline sorbents for sensitive colorimetric CO2 detection. In particular, a zeolitic imidazolate framework (ZIF) is chosen as the sorptive material due to its chemical stability and tunable CO2 affinity. The colorimetric gas sensor is developed by incorporating a CO2-affinative basic function and a pH indicator into the ZIF. The developed colorimetric CO2 sensor exhibits an obvious response to a wide range of CO2 levels of interest to indoor air detection (with a lower limit of detection below 1,000 ppm CO2). Powder X-ray diffraction confirms its chemical stability over one month in ambient conditions. Ultraviolet-visible spectroscopy reveals quantitative differences in colorimetric responses across a span of CO2 concentrations (700 – 7,500 ppm CO2). The color response is attributed to a two-step reaction mechanism whereby the pH indicator deprotonates the reaction intermediate between the adsorbed CO2 reacting with the basic function, shifting the pH and inducing a color change. Given its simple fabrication, rapid and obvious response, and stability in ambient environment, the ZIF-based colorimetric sensor provides a promising route for an improved indoor air quality monitoring. Acknowledgements We would like to thank the National Science Foundation for support in the form of a Graduate Research Fellowship (GRF) and Grant # 1903188, as well as the Bakar Fellows Program.

Deep learning evaluation of biomarkers from echocardiogram videos.

BackgroundLaboratory testing is routinely used to assay blood biomarkers to provide information on physiologic state beyond what clinicians can evaluate from interpreting medical imaging. We hypothesized that deep learning interpretation of echocardiogram videos can provide additional value in understanding disease states and can evaluate common biomarkers results.MethodsWe developed EchoNet-Labs, a video-based deep learning algorithm to detect evidence of anemia, elevated B-type natriuretic peptide (BNP), troponin I, and blood urea nitrogen (BUN), as well as values of ten additional lab tests directly from echocardiograms. We included patients (n = 39,460) aged 18 years or older with one or more apical-4-chamber echocardiogram videos (n = 70,066) from Stanford Healthcare for training and internal testing of EchoNet-Lab's performance in estimating the most proximal biomarker result. Without fine-tuning, the performance of EchoNet-Labs was further evaluated on an additional external test dataset (n = 1,301) from Cedars-Sinai Medical Center. We calculated the area under the curve (AUC) of the receiver operating characteristic curve for the internal and external test datasets.FindingsOn the held-out test set of Stanford patients not previously seen during model training, EchoNet-Labs achieved an AUC of 0.80 (0.79-0.81) in detecting anemia (low hemoglobin), 0.86 (0.85-0.88) in detecting elevated BNP, 0.75 (0.73-0.78) in detecting elevated troponin I, and 0.74 (0.72-0.76) in detecting elevated BUN. On the external test dataset from Cedars-Sinai, EchoNet-Labs achieved an AUC of 0.80 (0.77-0.82) in detecting anemia, of 0.82 (0.79-0.84) in detecting elevated BNP, of 0.75 (0.72-0.78) in detecting elevated troponin I, and of 0.69 (0.66-0.71) in detecting elevated BUN. We further demonstrate the utility of the model in detecting abnormalities in 10 additional lab tests. We investigate the features necessary for EchoNet-Labs to make successful detection and identify potential mechanisms for each biomarker using well-known and novel explainability techniques.InterpretationThese results show that deep learning applied to diagnostic imaging can provide additional clinical value and identify phenotypic information beyond current imaging interpretation methods.FundingJ.W.H. and B.H. are supported by the NSF Graduate Research Fellowship. D.O. is supported by NIH K99 HL157421-01. J.Y.Z. is supported by NSF CAREER 1942926, NIH R21 MD012867-01, NIH P30AG059307 and by a Chan-Zuckerberg Biohub Fellowship.

Contributing Authors

Dr. Mary Frances Berry, professor of history and Geraldine R. Segal Professor of American Social Thought at the University of Pennsylvania, is the author of twelve books, including History Teaches Us to Resist (2018). From 1980 to 2004, she was a member of the U.S. Commission on Civil Rights and from 1993–2004 served as chair. Between 1977 and 1980, Dr. Berry served as the assistant secretary for education in the U.S. Department of Health, Education, and Welfare. She has also served as provost of the University of Maryland and chancellor of the University of Colorado at Boulder. In recognition of her scholarship and public service, Professor Berry has received 35 honorary doctoral degrees and many awards.Brandon James Render is a PhD candidate in the History Department at the University of Texas at Austin. His research interests include twentieth-century United States social and intellectual history, post-1945 social movements and “the culture wars,” and public policy. His dissertation, “Colorblind University,” traces the intellectual genealogy of race-neutral policies and practices in higher education through admissions policies, departmental structure, and curriculum design. In addition to service as a graduate research fellow at the Center for the Study of Race and Democracy in 2018–19, he is the 2021–22 Mitchem Dissertation Fellow at Marquette University.Lee Sartain is a senior lecturer in American history at the University of Portsmouth, England. His research focuses primarily on the NAACP and civil rights activism from the 1910s to the 1970s. His first book, Invisible Activists: Women of the Louisiana NAACP and the Struggle for Civil Rights, 1915–1945 (2007) won the Landry Prize for best book on a southern topic. He has also published Borders of Equality: The NAACP and the Baltimore Civil Rights Struggle, 1914–1970 (2013) and coedited Long Is the Way: One Hundred Years of the NAACP (2009). Recent articles have focused on the NAACP and the Great War and on youth movements and the NAACP in New Mexico. He has also written various encyclopedia entries on the NAACP. He is a member of the Royal Historical Society.Matthew Shannon is associate professor of history at Emory & Henry College. He is the author of Losing Hearts and Minds: American–Iranian Relations and International Education during the Cold War (2017). Dr. Shannon's research has been published in Iranian Studies, Diplomatic History, International History Review, and The Sixties. He is the editor of American–Iranian Dialogues: From Constitution to White Revolution, c. 1890s–1960s (2021), and the coeditor of 9/11 and the Academy: Responses in the Liberal Arts and the 21st-Century World (2019).Quito Swan is professor of African American and African diaspora studies at Indiana University Bloomington. A historian of Black internationalism, he is the author of Pauulu's Diaspora: Black Internationalism and Environmental Justice (2021), Black Power in Bermuda (2010), and the forthcoming Pasifika Black: Black Internationalism in Oceania. Swan has garnered several major awards for his research, including fellowships from the National Endowment for the Humanities, Harvard University's Radcliffe Institute, Australia's University of Queensland, and, most recently, Pennsylvania State's Humanities Institute.Dr. Rhonda Y. Williams, professor and John L. Seigenthaler Chair in American History at Vanderbilt University, is the author of the award-winning The Politics of Public Housing: Black Women's Struggles against Urban Inequality (2004) and Concrete Demands: The Search for Black Power in the 20th Century (2005). She is also the coeditor of the award-winning book series “Justice, Power, and Politics” from the University of North Carolina Press. During her tenure at Case Western Reserve University, she founded and directed the Social Justice Institute, as well as the postdoctoral fellowship in African American studies.

Effect of architecture and process on the ultrasonic mapping of hybrid additively manufactured materials

Hybrid additive manufacturing enables the creation of materials with functional microstructure and mechanical property patterns. While samples with functional patterns provide unique advantages in the overall performance of the material, they present a challenge for nondestructive evaluation. In particular, the nondestructive mapping of the properties imparted by hybrid AM processes is critical. In this work, hybrid 316 stainless steel samples are created using laser powder bed fusion (LPBF) with varying hybrid architectures and with a variety of hybrid processes. The ultrasonic responses of these samples, in terms of wave speed, attenuation, and backscatter amplitude, are evaluated for each architecture and process combination. These responses are compared with those from conventionally manufactured samples and traditional AM samples. This evaluation provides information on the sensitivity of ultrasonic responses to hybrid architecture and process, highlighting the potential of ultrasonic nondestructive methods for the characterization of hybrid AM components. [This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1610400. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.]

Redox-Active Polymers Designed for the Circular Economy of Energy Storage Devices

A.G. and A.S. acknowledge funding from the TomKat Center for Sustainable Energy at Stanford University and the StorageX initiative. A.S. and S.T.M.T. gratefully acknowledge support from the National Science Foundation Award CBET #1804915. T.J.Q. and G.L. acknowledge support from the NSF Graduate Research Fellowship Program under grant DGE-1656518. Part of this work was performed at the Stanford Nanofabrication Facilities (SNF) and Stanford Nano Shared Facilities (SNSF), supported by the National Science Foundation as part of the National Nanotechnology Coordinated Infrastructure under award ECCS-1542152. The authors acknowledge financial support from KAUST, including the Office of Sponsored Research (OSR) award nos. OSR-2018-CRG/CCF-3079, OSR-2019-CRG8-4086, and OSR-2018-CRG7-3749. The authors acknowledge funding from an ERC Synergy Grant SC2 (610115). Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-76SF00515.

Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future. History: This article was accepted for the Decision Analysis Special Issue on Emerging Topics in Health. Funding: The first two authors’ efforts were supported by the National Natural Science Foundation of China [Grants 71971217 and 71671189], the Key Project of Natural Science Foundation of China [Grants 71790615 and 91846301], and the Independent Exploration of Innovation Project for Postgraduate of Central South University [Grant 2019zzts843]. The third author’s effort was partially supported by the U.S. National Science Foundation Graduate Research Fellowship Program [Grant 2043091].

The Outcomes of Interprofessional Experiential Learning for Underrepresented Racial/Ethnic Minority Students to Address Latino Childhood Obesity

Addressing Latino childhood obesity requires effective health promotion programs and culturally resonant health professionals. The current profiles of public health professionals and registered dietitians point to the need to increase the number of Latino students trained in community-based participatory research and engagement of underserved populations. To address this workforce gap, the Center for Latino Community Health, Evaluation, and Leadership Training developed the Sanos y Fuertes: Healthy & Strong Graduate Research Fellowship to provide Latino graduate students with research training, professional development, and mentorship. Five cohorts of seven graduate students participated in a yearlong experiential learning program. Graduate research fellows received monthly research and professional development training from faculty, staff, and community health workers. Furthermore, fellows engaged in mentored research through the development and implementation of a Latino childhood obesity prevention curriculum and intervention. A mixed-method evaluation approach was used to assess the effectiveness of the program. Fellows completed baseline, posttraining, and follow-up assessments. Assessment surveys measured training experiences (e.g., research methods, community engagement), confidence (e.g., research methods, health education), and knowledge and skills (e.g., community health program skills). The training resulted in significant increases in skills and confidence between pre- and postassessments that were sustained at follow-up. Based on these findings, we recommend that student training programs include research as experiential learning with multidisciplinary, interprofessional teams and that community-based, community-engaged, or translational research teams include community health workers as integral members for research with marginalized, underserved populations.

Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world.

Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Abstract 299: Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment

Abstract Traditional treatment methods for glioblastoma multiforme (GBM) including resection, radiation, and chemotherapy have been largely unsuccessful, with a current 5-year survival rate of 5.6%. In this project we examine the potential of nanosized self-assembling peptide hydrogels to locally deliver and convert temozolomide (TMZ), an FDA-approved pH-sensitive prodrug, for GBM treatment. The peptide hydrogel is designed to load TMZ into the hydrophobic regions of the hydrogels, and during hydrogel degradation in vivo, convert TMZ into its active form. Hydrogel characterization, drug loading and conversion, and cellular uptake and viability are examined to determine the in vitro efficacy of this delivery method. A combination of dynamic light scattering (DLS), scanning electron microscopy (SEM), and circular dichroism (CD) are used to characterize size and structure of the hydrogels. Loading and conversion of TMZ are quantified using UV-Vis spectroscopy. Fluorescent imaging and cell viability assays are used to determine uptake and anti-cancer effects of the drug-loaded hydrogels on glioblastoma cells. Our results show high uptake in drug-resistant T98G and non-resistant LN-18 glioblastoma cell lines using several of our tunable peptide formulations. CD has shown that all peptide formulations form mostly beta-sheet and random structures during self-assembly. SEM and DLS show that peptide hydrogels formed in a water solvent are more polydisperse than hydrogels in a PBS solvent. Using a pH-meter, we have shown that as the peptides in PBS degrade, there is an increase in local pH. Additionally, TMZ conversion is observed to occur more quickly in drug-loaded hydrogels than TMZ alone. Preliminary cell viability studies have shown that unassembled peptides are not cytotoxic; some of the assembled peptide hydrogels are cytotoxic while others maintain greater than 80% viability when compared to untreated cells. Future studies for the project will include cell viability assays with the most promising peptide formulations loaded with TMZ to determine efficacy of the delivery and conversion system. Finally, this project will culminate in an in vivo study to confirm the overall anti-cancer effect of the drug-loaded peptide hydrogels in a tumor model of GBM. Acknowledgements: This research was supported in part by the National Science Foundation EPSCoR Program under NSF Award # OIA-1655740, the National Institute of Health Award # P30GM131959, and National Science Foundation's Graduate Research Fellowship Program. Citation Format: Megan Pitz, Alexandra Nukovic, Margaret Elpers, Sarah Wilde, Angela Alexander-Bryant. Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 299.