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New graduate students in biology programs may lack the quantitative skills necessary for their research and professional careers. The acquisition of these skills may be impeded by teaching and mentoring experiences that decrease rather than increase students’ beliefs in their ability to learn and apply quantitative approaches. In this opinion piece, we argue that revising instructional experiences to ensure that both student confidence and quantitative skills are enhanced may improve both educational outcomes and professional success. A few studies suggest that explicitly addressing productive failure in an instructional setting and ensuring effective mentoring may be the most effective routes to simultaneously increasing both quantitative self-efficacy and quantitative skills. However, there is little work that specifically addresses graduate student needs, and more research is required to reach evidence-backed conclusions.

In response to the growing computational intensity of the healthcare industry, biomedical engineering (BME) undergraduate education is placing increased emphasis on computation. The presence of substantial gender disparities in many computationally intensive disciplines suggests that the adoption of computational instruction approaches that lack intentionality may exacerbate gender disparities. Educational research suggests that the development of an engineering and computational identity is one factor that can support students’ decisions to enter and persist in an engineering major. Discipline-based identity research is used as a lens to understand retention and persistence of students in engineering. Our specific purpose is to apply discipline-based identity research to define and explore the computational identities of undergraduate engineering students who engage in computational environments. This work will inform future studies regarding retention and persistence of students who engage in computational courses. Twenty-eight undergraduate engineering students (20 women, 8 men) from three engineering majors (biomedical engineering, agricultural engineering, and biological engineering) participated in semi-structured interviews. The students discussed their experiences in a computationally-intensive thermodynamics course offered jointly by the Biomedical Engineering and Agricultural & Biological Engineering departments. The transcribed interviews were analyzed through thematic coding. The gender stereotypes associated with computer programming also come part and parcel with computer programming, possibly threatening a student's sense of belonging in engineering. The majority of the participants reported that their computational identity was “in the making.” Students’ responses also suggested that their engineering identity and their computational identity were in congruence, while some incongruence is found between their engineering identity and a creative identity as well as between computational identity and perceived feminine norms. Responses also indicate that students associate specific skills with having a computational identity. This study's findings present an emergent thematic definition of a computational person constructed from student perceptions and experiences. Instructors can support students’ nascent computational identities through intentional mitigation of the gender stereotypes and biases, and by framing assignments to focus on developing specific skills associated with the computational modeling processes.

Research on learning communities has primarily focused on identifying institutional outcomes such as student achievement and retention. However, more research is needed on how the learning community experience impacts the motivation, beliefs, and perceptions associated with student success. This study investigates the psychosocial effects of participating in a residential research-oriented learning community regarding students’ interest and motivation in pursuing research-oriented careers, research and data self-efficacy beliefs, sense of belongingness with the learning community, and socialization levels and career awareness in research-oriented fields. This study also investigated the mediating effects of students’ initial research self-efficacy beliefs on differential gains regarding career awareness, motivation and interest, and sense of belongingness and socialization after one year of participating in a residential research-oriented learning community. Participants of the study consisted of five cohorts of the learning community, each composed of twenty students. Students in each cohort participated in a pretest-posttest design survey study. Findings suggest that alignment of student interest with the learning community discipline is a key mediator of student growth in their self-efficacy beliefs, sense of belongingness with the learning community and levels of socialization, and career awareness in the selected field. Implications include recommendations for the thoughtful design of learning communities that promote cognitive apprenticeships by orchestrating the content, method, sequencing, and sociology of the learning environment.

There is growing awareness of the need for mathematics and computing to quantitatively understand the complex dynamics and feedbacks in the life sciences. Although individual institutions and research groups are conducting pioneering multidisciplinary research, communication and education across fields remains a bottleneck. The opportunity is ripe for using education research principles to develop new mechanisms of cross-disciplinary training at the intersection of mathematics, computation and biology. In this paper we present a case study which describes the efforts of one computational biology lab to rapidly prototype, test, and refine a mentorship infrastructure for undergraduate research experiences in alignment with the computational apprenticeship theoretical framework. We describe the challenges, benefits, and lessons learned, as well as the utility of the computational apprenticeship framework in supporting computational/math students learning and contributing to biology, and biologists in learning computational methods. We also explore implications for undergraduate classroom instruction, and cross-disciplinary scientific communication.

In science and engineering education, the use of heuristics has been introduced as a way of understanding the world, and as a way to approach problem-solving and design. However, important consequences for the use of heuristics are that they do not always guarantee a correct solution. Learning by Design has been identified as a pedagogical strategy that can guide individuals to properly connect science learning via design challenges. Specifically, we focus on the effect of simulation-enabled Learning by Design learning experiences on student-generated heuristics that can lead to solutions to problems. A total of 318 middle school students were exposed to a lesson that integrated design practices in the context of energy consumption and energy conservation considerations when designing buildings using an educational CAD tool. The students were pre- and posttested before and after the 2-week long intervention. The data analysis procedures combined qualitative with quantitative methods along with machine learning approaches. Our analysis revealed two distinct groups of students based on their learning achievement: the naive developing heuristic group and semi-knowledgeable fixated heuristic group. Differences between the groups are discussed in terms of performance, as well as implications for the use of computer simulations to improve student learning.

Pattern formation by bone morphogenetic proteins (BMPs) demonstrates remarkable plasticity and utility in several contexts, such as early embryonic development, tissue patterning and the maintenance of stem cell niches. BMPs pattern tissues over many temporal and spatial scales: BMP gradients as short as 1-2 cell diameters maintain the stem cell niche of the Drosophila germarium over a 24-h cycle, and BMP gradients of several hundred microns establish dorsal-ventral tissue specification in Drosophila, zebrafish and Xenopus embryos in timescales between 30 min and several hours. The mechanisms that shape BMP signaling gradients are also incredibly diverse. Although ligand diffusion plays a dominant role in forming the gradient, a cast of diffusible and non-diffusible regulators modulate gradient formation and confer robustness, including scale invariance and adaptability to perturbations in gene expression and growth. In this Review, we document the diverse ways that BMP gradients are formed and refined, and we identify the core principles that they share to achieve reliable performance., Summary: This Review looks at BMP morphogen gradient patterning in diverse developmental contexts including in Tribolium, Drosophila, Xenopus and zebrafish early embryos, as well as the Drosophila wing imaginal disc and germarium.

Numerous stages of organismal development rely on the cellular interpretation of gradients of secreted morphogens including members of the Bone Morphogenetic Protein (BMP) family through transmembrane receptors. Early gradients of BMPs drive dorsal/ventral patterning throughout the animal kingdom in both vertebrates and invertebrates. Growing evidence in Drosophila, zebrafish, murine and other systems suggests that BMP ligand heterodimers are the primary BMP signaling ligand, even in systems in which mixtures of BMP homodimers and heterodimers are present. Signaling by heterodimers occurs through a hetero-tetrameric receptor complex comprising of two distinct type one BMP receptors and two type II receptors. To understand the system dynamics and determine whether kinetic assembly of heterodimer-heterotetramer BMP complexes is favored, as compared to other plausible BMP ligand-receptor configurations, we developed a kinetic model for BMP tetramer formation based on current measurements for binding rates and affinities. We find that contrary to a common hypothesis, heterodimer-heterotetramer formation is not kinetically favored over the formation of homodimer-tetramer complexes under physiological conditions of receptor and ligand concentrations and therefore other mechanisms, potentially including differential kinase activities of the formed heterotetramer complexes, must be the cause of heterodimer-heterotetramer signaling primacy. Further, although BMP complex assembly favors homodimer and homomeric complex formation over a wide range of parameters, ignoring these signals and instead relying on the heterodimer improves the range of morphogen interpretation in a broad set of conditions, suggesting a performance advantage for heterodimer signaling in patterning multiple cell types in a gradient., Author summary TGF-β signaling is an important cell signaling system through which cells respond to external information. In the TGF-β system, signaling is initiated when a ligand dimer pair binds to a receptor tetramer. Interestingly, in numerous developmental contexts, TGF-β signaling has a greater response to heterodimeric ligands (dimers of multiple ligands), as compared to homomeric ligands (dimers made of two molecules of a single ligand). However, neither the cause of heterodimer signaling primacy, nor the systemic effects of heterodimeric vs homomeric signaling are understood. We use a biophysically-informed computational modeling approach to investigate the system dynamics of heterodimer-heterotetramer BMP signaling, to understand the cause and consequence of the requirement for Bmp2/7-mediated signaling in dorsoventral patterning in zebrafish development. Using our model, we demonstrate that BMP heterodimer signaling complex formation is not kinetically favored over homodimer signaling complexes, suggesting subfunctionalization of BMP receptors may be required to explain heterodimer signaling. Additionally, we show that heterodimer signaling provides a performance advantage via increased range of morphogen interpretation. Our findings provide insight into the systems principles involved in developmental signaling.

In this Work In Progress in the Research Category we present a qualitative study that explores how computing instruction experiences may mediate the progression of social and cognitive factors associated with career development in community college engineering students. The rapidly evolving technological landscape has created an increased need for an engineering workforce with computing skills. Traditionally, policymakers, educators and researchers have focused on K-12 and four-year secondary institutions as the primary arena for addressing our workforce development needs. However, community colleges, which enroll over one-third of U.S. undergraduates, represent an important, and not yet fully utilized resource for training future engineers. However, there is a dearth of engineering education research that seeks to critically understand the experiences of community college engineering students in learning computational skills. To address this gap, our study includes semi-structured interviews with first- and second-year students enrolled in an engineering program at a public two-year institution in the midwestern United States. Our work is informed by a social cognitive career theory (SCCT) perspective from which we examine how engineering course learning experiences involving integrated computing instruction influence students’ self-efficacy beliefs and outcome expectations. In alignment with SCCT, our analysis will aim to identify personal attributes and external environmental factors that mediate students’ differential responses to computational instruction. This pilot study is the first part of a larger research effort directed towards learning how to support students as they navigate the community college pathway to engineering.

This Work in Progress paper in the Research category studies undergraduate students use of higher order metacognitive skills while engaging in computational modeling engineering research. Policymakers, universities and other key stakeholders have promoted ‘authentic learning experiences’ including undergraduate research experiences as a vehicle for the cognitive and metacognitive development of undergraduates. Indeed, undergraduate research experiences in STEM fields have been demonstrated to have positive effects including enhanced technical skills development and greater persistence in STEM degrees. However, specific research is needed to understand how metacognitive skills are engaged during undergraduate research experiences. Further, work on undergraduate research experiences has typically focused on science research, and relatively little work has been done to understand student development during research experiences in engineering and computational fields. To address this gap, we have initiated a qualitative study of undergraduate researchers within a computational modeling engineering research group at a large midwestern university. Here, we share preliminary results from semi-structured interviews of undergraduate student researchers and their supervisors. The research and implications of our work are grounded within a cognitive apprenticeship framework and will provide insight into how best to support the cognitive and metacognitive development of undergraduate engineering researchers.

This research study presents our work focused on studying the development of introductory computational thinking in undergraduate biomedical engineering students. In response to the growing computational intensity of the healthcare industry, biomedical engineering (BME) undergraduate education is starting to emphasize computation and computational thinking. Computational thinking is a way of thinking that uses concepts and methodologies of computing to solve problems in interdisciplinary and multidisciplinary subjects. In broader terms, computational thinking is not only associated with using computational tools but also with the thought process of solving a problem by data representation, problem decomposition, and algorithm design. Despite being so important, there is little research work or information available on the development of computational thinking in BME undergraduate students. Our research focuses on how BME undergraduate students develop computational thinking skills while performing group activities related to problem-solving. In order to conduct this study, we incorporate a teaching methodology that prompts computational thinking in a thermodynamics course being taught at a public mid-western university to approximately 120 sophomore students. We observe classroom activities involving analytical problem solving followed by pseudo code generation for computational coding. In order to investigate computational thinking, we collect classroom observations of small groups of students as they come up with a solution to an analytical problem with each other. We complement the observation notes of the classroom activities with follow up semi structured interviews with individual students from five groups. Thematic analysis of the student interviews is used in order to analyze student responses towards the incorporation of computation intensive teaching methodology. This Work in Progress helps us expand our understanding of computational thinking development and the challenges involved in performing computational thinking activity in BME undergraduate students.

This study explores interactions between computational thinking, gender and engineering identity among biomedical engineering undergraduate students. Biomedical engineering enjoys higher rates of women’s enrollment than other engineering disciplines, but nevertheless has gender disparities in persistence within the field. Additionally, trends towards greater incorporation of computation into biomedical engineering have the potential to recreate the gender inequities seen in more computationally intensive engineering disciplines. Recently, ‘engineering identity’ has emerged as a powerful analytic lens to understand persistence in engineering, particularly for underrepresented groups such as women. However, there is limited work examining how experiences using computational methods influences engineering identity formation in undergraduate biomedical engineers. Further, it remains unclear to what extent gender differentially mediates the effects of computational practice on engineering identity formation. In order to explore the intersection of these issues, we study a thermodynamics course in the biomedical engineering department of a large Midwestern public research institution in the United States. The thermodynamics course includes in-class computational modeling group activities and has an enrollment of more than 120, primarily sophomore year, undergraduate students. We use a qualitative study approach that includes gathering data through classroom observation and detailed semi-structured interviews. We analyze classroom observation data to try to understand student experiences of learning and participation during in-class computational modeling exercises. Specifically, we look for evidence of gendered differences in task sorting and engagement with the exercise. Classroom data is complemented by semi-structured interviews. Thematic analysis of semi-structured interviews gains student’s perspectives on how gender has influenced their learning experience and their identity as engineers.

This Work-in-Progress paper in the Research Category explores the unique challenges and opportunities of interdisciplinary education in computational modeling for life sciences student researchers at emerging research institutions (ERIs), specifically in predominantly undergraduate institutions (PUIs), and minority serving institutions (MSIs). Engineering approaches such as computational modeling have underappreciated potential for capacity building for the biomedical research enterprises of ERIs. We perform a bibliometric analysis to assess the prevailing use of computational modeling in life sciences research at MSIs, and PUIs. Additionally, we apply Social and Cognitive Theory to identify unique attitudinal, social and structural barriers for student researchers in learning and using computational modeling approaches at each of these types of institutions. Specifically, we use quantitative retrospective pre- and post-survey data and qualitative interviews of students who have attended a short-format computational modeling training course. We supplement these data with qualitative interviews of the students’ faculty sponsors. Upon completion, this study will provide deeper understanding of issues related to computer science and engineering education at non-Research I institutions.

This Work-in-Progress paper in the Research Category uses a retrospective mixed-methods study to better understand the factors that mediate learning of computational modeling by life scientists. Key stakeholders, including leading scientists, universities and funding agencies, have promoted computational modeling to enable life sciences research and improve the translation of genetic and molecular biology high-throughput data into clinical results. Software platforms to facilitate computational modeling by biologists who lack advanced mathematical or programming skills have had some success, but none has achieved widespread use among life scientists. Because computational modeling is a core engineering skill of value to other STEM fields, it is critical for engineering and computer science educators to consider how we help students from across STEM disciplines learn computational modeling. Currently we lack sufficient research on how best to help life scientists learn computational modeling.To address this gap, in 2017, we observed a short-format summer course designed for life scientists to learn computational modeling. The course used a simulation environment designed to lower programming barriers. We used semi-structured interviews to understand students’ experiences while taking the course and in applying computational modeling after the course. We conducted interviews with graduate students and post-doctoral researchers who had completed the course. We also interviewed students who took the course between 2010 and 2013. Among these past attendees, we selected equal numbers of interview subjects who had and had not successfully published journal articles that incorporated computational modeling. This Work-in-Progress paper applies social cognitive theory to analyze the motivations of life scientists who seek training in computational modeling and their attitudes towards computational modeling. Additionally, we identify important social and environmental variables that influence successful application of computational modeling after course completion. The findings from this study may therefore help us educate biomedical and biological engineering students more effectively.Although this study focuses on life scientists, its findings can inform engineering and computer science education more broadly. Insights from this study may be especially useful in aiding incoming engineering and computer science students who do not have advanced mathematical or programming skills and in preparing undergraduate engineering students for collaborative work with life scientists.

Integrins regulate cell-cell and cell-matrix adhesion and thereby play critical roles in tumor progression and metastasis. Although work in preclinical models suggests that β1 integrins may stimulate metastasis of a number of cancers, expression of the β1 subunit alone has not been shown to be a useful prognostic indicator in human cancer patients. Here we have demonstrated that the α2β1 integrin suppresses metastasis in a clinically relevant spontaneous mouse model of breast cancer. These data are consistent with previous studies indicating high expression of α2β1 integrin in normal breast epithelium and loss of α2β1 in poorly differentiated breast cancer. They are also consistent with our systematic analysis of microarray databases of human breast and prostate cancer, which revealed that decreased expression of the gene encoding α2 integrin, but not genes encoding α1, α3, or β1 integrin, was predictive of metastatic dissemination and decreased survival. The predictive value of α2 expression persisted within both good-risk and poor-risk cohorts defined by estrogen receptor and lymph node status. Thus, the α2β1 integrin functionally inhibits breast tumor metastasis, and α2 expression may serve as an important biomarker of metastatic potential and patient survival.

Phosphoinositide 3-kinase (PI(3)K) is a unique enzyme characterized by both lipid and protein kinase activities. Here, we demonstrate a requirement for the protein kinase activity of PI(3)K in agonist-dependent beta-adrenergic receptor (betaAR) internalization. Using PI(3)K mutants with either protein or lipid phosphorylation activity, we identify the cytoskeletal protein non-muscle tropomyosin as a substrate of PI(3)K, which is phosphorylated in a wortmannin-sensitive manner on residue Ser 61. A constitutively dephosphorylated (S61A) tropomyosin mutant blocks agonist-dependent betaAR internalization, whereas a tropomyosin mutant that mimics constitutive phosphorylation (S61D) complements the PI(3)K mutant, with only lipid phosphorylation activity reversing the defective betaAR internalization. Notably, knocking down endogenous tropomyosin expression using siRNAs that target different regions if tropomyosin resulted in complete inhibition of betaAR endocytosis, showing that non-muscle tropomyosin is essential for agonist-mediated receptor internalization. These studies demonstrate a previously unknown role for the protein phosphorylation activity of PI(3)K in betaAR internalization and identify non-muscle tropomyosin as a cellular substrate for protein kinase activity of PI(3)K.

The α2β1 integrin, also known as VLA-2, GPIa-IIa, CD49b, was first identified as an extracellular matrix receptor for collagens and/or laminins [55, 56]. It is now recognized that the α2β1 integrin serves as a receptor for many matrix and nonmatrix molecules [35, 79, 128]. Extensive analyses have clearly elucidated the α2 I domain structural motifs required for ligand binding, and also defined distinct conformations that lead to inactive, partially active or highly active ligand binding [3, 37, 66, 123, 136, 137, 140]. The mechanisms by which the α2β1 integrin plays a critical role in platelet function and homeostasis have been carefully defined via in vitro and in vivo experiments [76, 104, 117, 125]. Genetic and epidemiologic studies have confirmed human physiology and disease states mediated by this receptor in immunity, cancer, and development [6, 20, 21, 32, 43, 90]. The role of the α2β1 integrin in these multiple complex biologic processes will be discussed in the chapter.

The α2β1 integrin plays an important but complex role in angiogenesis and vasculopathies. Published GWAS studies established a correlation between genetic polymorphisms of the α2β1 integrin gene and incidence of diabetic retinopathy. Recent studies indicated that α2-null mice demonstrate superior vascularization in both the wound and diabetic microenvironments. The goal of this study was to determine whether the vasculoprotective effects of α2-integrin deficiency extended to the retina, using the oxygen-induced retinopathy (OIR) model for retinopathy of prematurity (ROP).In the OIR model, wild-type (WT) and α2-null mice were exposed to 75% oxygen for 5 days (postnatal day [P] 7 to P12) and subsequently returned to room air for 6 days (P12-P18). Retinas were collected at postnatal day 7, day 13, and day 18 and examined via hematoxylin and eosin and Lectin staining. Retinas were analyzed for retinal vascular area, neovascularization, VEGF expression, and Müller cell activation. Primary Müller cell cultures from WT and α2-null mice were isolated and analyzed for hypoxia-induced VEGF-A expression.In the retina, the α2β1 integrin was minimally expressed in endothelial cells and strongly expressed in activated Müller cells. Isolated α2-null primary Müller cells demonstrated decreased hypoxia-induced VEGF-A expression. In the OIR model, α2-null mice displayed reduced hyperoxia-induced vaso-attenuation, reduced pathological retinal neovascularization, and decreased VEGF expression as compared to WT counterparts.Our data suggest that the α2β1 integrin contributes to the pathogenesis of retinopathy. We describe a newly identified role for α2β1 integrin in mediating hypoxia-induced Müller cell VEGF-A production.

Airway smooth muscle (ASM) from infant guinea pigs has less spontaneous relaxation during stimulation than ASM from adults. Inhibition of cyclooxygenase (COX), which catalyzes the production of prostanoids, increases this relaxation in infant ASM and abolishes age differences, thus suggesting that prostanoids reduce relaxation in infant ASM. In this study, we investigated whether leukotrienes are also involved in reducing spontaneous relaxation; whether the two COX isoforms, COX-1 and COX-2, differentially regulate spontaneous relaxation; and whether prostanoid release is developmentally regulated in guinea pig ASM. In different age groups, we measured relaxation during and after electrical stimulation in tracheal strips as well as prostanoid release from tracheal segments. Relaxation was studied in the absence and in the presence of a lipoxygenase inhibitor, a cysteinyl leukotriene receptor-1 antagonist, a COX-1 inhibitor, or a COX-2 inhibitor. We found that inhibition of lipoxygenase or cysteinyl leukotriene receptor-1 antagonism did not increase spontaneous relaxation at any age, thus excluding a role for leukotrienes in this phenomenon. Inhibition of COX-2, but not COX-1, promoted spontaneous relaxation. The basal release of prostanoids was more abundant in tissue from infant animals and decreased significantly with age. Thromboxane B2 was the most abundant metabolite released at all ages. Electrical stimulation and epithelium removal did not affect the age difference in prostanoid release. We conclude that increased basal prostanoid release contributes to the reduced spontaneous relaxation in immature guinea pig ASM compared with older animals. By regulating ASM relaxation, prostanoids may play a role in the airway hyperresponsiveness at a young age.

Attempting to understand the gene-environment interactions that lead to disease is the basis of modern molecular medicine. DNA microarray technology has provided vast quantities of new data for building up these models. Unfortunately the vast majority of studies using this technology consist of samples from populations of European ancestry. To understand the gene-environment interactions that contribute to racial and ethnic health disparities data from studies with samples from diverse populations must be analyzed. Currently, this data is limited and hard to access. The few studies that use samples from diverse populations are lost among the millions of published microarray datasets. To address this issue we have developed Disparitome-Miner, a microarray database and web-based data-mining platform that will serve as a tool for facilitating discovery from published transcriptomic datasets. To date, Disparitome-Miner contains 18 microarray datasets consisting of samples from diverse patient populations. Differential expression analyses comparing tissue samples from healthy and disease states in multiple ancestry backgrounds are provided. Transcriptomic microarray data is analyzed and visualized interactively through Shiny Server, an open-source package for web-based R applications. Our hope is that Disparitome-Miner allows life scientists without advanced statistical training to evaluate their gene-of-interest for a role in the gene-environment interactions that contribute to racial and ethnic health disparities. This web-app can provide help in hypothesis-generation and facilitate further investigation into health disparities. Citation Format: Aasakiran Madamanchi, David Cappel, Chaitanya Madamanchi, Roman Covarrubias, John Micheal Thomson. Disparitome-Miner: A data visualization web-application for ‘gene-of-interest’ in health disparities. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr C03. doi:10.1158/1538-7755.DISP13-C03

Angiogenesis expands the vascular network during normal development and in response to angiogenic stress. Dysregulation of this dynamic process contributes to tumor progression and to the pathogenesis of many diseases. Evidence suggests that the alpha2beta1 integrin, a collagen and laminin receptor, plays an important role in angiogenesis. In the wound-healing and tumor microenvironment, deletion of the alpha2beta1 integrin has been reported to increase neoangiogenesis. In contrast, small molecule inhibitor (SMI) targeting of the alpha2 integrin blocks sprouting angiogenesis. To reconcile these divergent findings and gain a fuller understanding of alpha2beta1 integrin's role in angiogenesis we turned to the retina. The retinal model is uniquely suited for angiogenesis investigations as the retinal vasculature develops postnatally in a 2-dimensional plane in a well-characterized manner. Evaluation of the alpha2-null retina reveals a constellation of defects and delays in vascular development, including delayed vessel outgrowth, and increased vessel irregularity and decreased plexus density at the vascular front. Additionally we determined that alpha2 integrin-deletion has a protective effect in an oxygen-induced retinopathy model of retinopathy of prematurity (ROP) in mice by inhibiting both hyperoxia-induced vaso-obliteration and hypoxia-induced pathologic neovascularization. Confirming this result, our analysis of human microarray data shows, for the first time, that preterm infants with lower ITGA2 expression are less likely to suffer from ROP. This work clarifies the role of alpha2beta1 integrin in sprouting angiogenesis and raises the intriguing possibility of alpha2 integrin targeted therapies for prevention of ROP. These changes are reminiscent of changes observed in other models with dysregulated notch signaling. Recent studies reported that the alpha2beta1 integrin regulates sprouting angiogenesis by inducing DLL4 in ‘tip cells’. We show, for the first time, notch induced downregulation of alpha2beta1 integrin expression in ‘stalk cells’. Together these results suggest that the alpha2beta1 integrin coordinates endothelial notch signaling by stabilizing tip-stalk status. The apparent discrepancy between the effects of the alpha2 integrin inhibition and integrin-deletion may reflect differences between acute and chronic upregulation of notch signaling. We propose that synergistic use of notch and alpha2 integrin targeted therapies may provide enhanced anti-tumor angiogenesis. Citation Format: Aasakiran Madamanchi, Megan Capozzi, Ling Geng, Zhengzhi Li, Zhonghua Zhang, Richard Friedman, Kent Dickeson, John Penn, Mary Zutter. Alpha2beta1 integrin regulation of endothelial notch signaling in the retina. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3900. doi:10.1158/1538-7445.AM2013-3900