Physics-based in silico modelling of microvascular pulmonary perfusion in COVID-19.

Due to its ability to induce heterogenous, patient-specific damage in pulmonary alveoli and capillaries, COVID-19 poses challenges in defining a uniform profile to elucidate infection across all patients. Computational models that integrate changes in ventilation and perfusion with heterogeneous damage profiles offer valuable insights into the impact of COVID-19 on pulmonary health. This study aims to develop an in silico hypothesis-testing platform specifically focused on studying microvascular pulmonary perfusion in COVID-19-infected lungs. Through this platform, we explore the effects of various acinar-level pulmonary perfusion abnormalities on global lung function. Our modelling approach simulates changes in pulmonary perfusion and the resulting mismatch of ventilation and perfusion in COVID-19-afflicted lungs. Using this coupled modelling platform, we conducted multiple simulations to assess different scenarios of perfusion abnormalities in COVID-19-infected lungs. The simulation results showed an overall decrease in ventilation-perfusion (V/Q) ratio with inclusion of various types of perfusion abnormalities such as hypoperfusion with and without microangiopathy. This model serves as a foundation for comprehending and comparing the spectrum of findings associated with COVID-19 in the lung, paving the way for patient-specific modelling of microscale lung damage in emerging pulmonary pathologies like COVID-19.

NSF DARE-transforming modeling in neurorehabilitation: perspectives and opportunities from US funding agencies.

In recognition of the importance and timeliness of computational models for accelerating progress in neurorehabilitation, the U.S. National Science Foundation (NSF) and the National Institutes of Health (NIH) sponsored a conference in March 2023 at the University of Southern California that drew global participation from engineers, scientists, clinicians, and trainees. This commentary highlights promising applications of computational models to understand neurorehabilitation ("Using computational models to understand complex mechanisms in neurorehabilitation" section), improve rehabilitation care in the context of digital twin frameworks ("Using computational models to improve delivery and implementation of rehabilitation care" section), and empower future interdisciplinary workforces to deliver higher-quality clinical care using computational models ("Using computational models in neurorehabilitation requires an interdisciplinary workforce" section). The authors describe near-term gaps and opportunities, all of which encourage interdisciplinary team science. Four major opportunities were identified including (1) deciphering the relationship between engineering figures of merit-a term commonly used by engineers to objectively quantify the performance of a device, system, method, or material relative to existing state of the art-and clinical outcome measures, (2) validating computational models from engineering and patient perspectives, (3) creating and curating datasets that are made publicly accessible, and (4) developing new transdisciplinary frameworks, theories, and models that incorporate the complexities of the nervous and musculoskeletal systems. This commentary summarizes U.S. funding opportunities by two Federal agencies that support computational research in neurorehabilitation. The NSF has funding programs that support high-risk/high-reward research proposals on computational methods in neurorehabilitation informed by theory- and data-driven approaches. The NIH supports the development of new interventions and therapies for a wide range of nervous system injuries and impairments informed by the field of computational modeling. The conference materials can be found at https://dare2023.usc.edu/ .

Spatial predictions of tree density and tree height across Mexico forests using ensemble learning and forest inventory data.

The National Forestry Commission of Mexico continuously monitors forest structure within the country's continental territory by the implementation of the National Forest and Soils Inventory (INFyS). Due to the challenges involved in collecting data exclusively from field surveys, there are spatial information gaps for important forest attributes. This can produce bias or increase uncertainty when generating estimates required to support forest management decisions. Our objective is to predict the spatial distribution of tree height and tree density in all Mexican forests. We performed wall-to-wall spatial predictions of both attributes in 1-km grids, using ensemble machine learning across each forest type in Mexico. Predictor variables include remote sensing imagery and other geospatial data (e.g., mean precipitation, surface temperature, canopy cover). Training data is from the 2009 to 2014 cycle (n > 26,000 sampling plots). Spatial cross validation suggested that the model had a better performance when predicting tree height r 2 = .35 [.12, .51] (mean [min, max]) than for tree density r 2 = .23 [.05, .42]. The best predictive performance when mapping tree height was for broadleaf and coniferous-broadleaf forests (model explained ~50% of variance). The best predictive performance when mapping tree density was for tropical forest (model explained ~40% of variance). Although most forests had relatively low uncertainty for tree height predictions, e.g., values <60%, arid and semiarid ecosystems had high uncertainty, e.g., values >80%. Uncertainty values for tree density predictions were >80% in most forests. The applied open science approach we present is easily replicable and scalable, thus it is helpful to assist in the decision-making and future of the National Forest and Soils Inventory. This work highlights the need for analytical tools that help us exploit the full potential of the Mexican forest inventory datasets.

Methods for analyzing infant heart rate variability: A preliminary study.

Heart rate (HR) and heart rate variability (HRV) reflect autonomic development in infants. To better understand the autonomic response in infants, reliable HRV recordings are vital, yet no protocol exists. The purpose of this paper is to present reliability of a common procedure for analysis from two different file types. In the procedure, continuous electrocardiograph recordings of 5-10 min are obtained at rest in infants at 1 month of age by using a Hexoskin Shirt-Junior's (Carre Technologies Inc., Montreal, QC, Canada). Electrocardiograph (ECG; .wav) and R-R interval (RRi; .csv) files are extracted. The RRi of the ECG signal is generated by VivoSense (Great Lakes NeuroTechnologies, Independence, OH). Two MATLAB (The MathWorks, Inc., Natick, MA) scripts converted files for analysis with Kubios HRV Premium (Kubios Oy, Kuopio, Finland). A comparison was made between RRi and ECG files for HR and HRV parameters, and then tested with t tests and correlations via SPSS. There are significant differences in root mean squared successive differences between recording types, with only HR and low-frequency measures significantly correlated together. Recording with Hexoskin and analysis with MATLAB and Kubios enable infant HRV analysis. Differences in outcomes exist between procedures, and standard methodology for infant HR analysis is needed.

Rapid-cycle designs to adapt interventions for COVID-19 in safety-net healthcare systems.

Racial/ethnic minority, low socioeconomic status, and rural populations are disproportionately affected by COVID-19. Developing and evaluating interventions to address COVID-19 testing and vaccination among these populations are crucial to improving health inequities. The purpose of this paper is to describe the application of a rapid-cycle design and adaptation process from an ongoing trial to address COVID-19 among safety-net healthcare system patients. The rapid-cycle design and adaptation process included: (a) assessing context and determining relevant models/frameworks; (b) determining core and modifiable components of interventions; and (c) conducting iterative adaptations using Plan-Do-Study-Act (PDSA) cycles. PDSA cycles included: Plan. Gather information from potential adopters/implementers (e.g., Community Health Center [CHC] staff/patients) and design initial interventions; Do. Implement interventions in single CHC or patient cohort; Study. Examine process, outcome, and context data (e.g., infection rates); and, Act. If necessary, refine interventions based on process and outcome data, then disseminate interventions to other CHCs and patient cohorts. Seven CHC systems with 26 clinics participated in the trial. Rapid-cycle, PDSA-based adaptations were made to adapt to evolving COVID-19-related needs. Near real-time data used for adaptation included data on infection hot spots, CHC capacity, stakeholder priorities, local/national policies, and testing/vaccine availability. Adaptations included those to study design, intervention content, and intervention cohorts. Decision-making included multiple stakeholders (e.g., State Department of Health, Primary Care Association, CHCs, patients, researchers). Rapid-cycle designs may improve the relevance and timeliness of interventions for CHCs and other settings that provide care to populations experiencing health inequities, and for rapidly evolving healthcare challenges such as COVID-19.

Racial/ethnic minority, low socioeconomic status, and rural populations experience a disproportionate burden of COVID-19. Finding ways to address COVID-19 among these populations is crucial to improving health inequities. The purpose of this paper is to describe the rapid-cycle design process for a research project to address COVID-19 testing and vaccination among safety-net healthcare system patients. The project used real-time information on changes in COVID-19 policy (e.g., vaccination authorization), local case rates, and the capacity of safety-net healthcare systems to iteratively change interventions to ensure interventions were relevant and timely for patients. Key changes that were made to interventions included a change to the study design to include vaccination as a focus of the interventions after the vaccine was authorized; change in intervention content according to the capacity of local Community Health Centers to provide testing to patients; and changes to intervention cohorts such that priority groups of patients were selected for intervention based on characteristics including age, residency in an infection "hot spot," or race/ethnicity. Iteratively improving interventions based on real-time data collection may increase intervention relevance and timeliness, and rapid-cycle adaptions can be successfully implemented in resource constrained settings like safety-net healthcare systems.

Systematic Review of Active Travel to School Surveillance in the United States and Canada.

Active travel to school is one way youths can incorporate physical activity into their daily schedule. It is unclear the extent to which active travel to school is systematically monitored at local, state, or national levels. To determine the scope of active travel to school surveillance in the US and Canada and catalog the types of measures captured, we conducted a systematic review of peer-reviewed literature documenting active travel to school surveillance published from 2004 to February 2018. A study was included if it addressed children's school travel mode across two or more time periods in the US or Canada. Criteria were applied to determine whether a data source was considered an active travel to school surveillance system. We identified 15 unique data sources; 4 of these met our surveillance system criteria. One system is conducted in the US, is nationally representative, and occurs every 5-8 years. Three are conducted in Canada, are limited geographically to regions and provinces, and are administered with greater frequency (e.g., 2-year cycles). School travel mode was the primary measure assessed, most commonly through parent report. None of the systems collected data on school policies or program supports related to active travel to school. We concluded that incorporating questions related to active travel to school behaviors into existing surveillance systems, as well as maintaining them over time, would enable more consistent monitoring. Concurrently capturing behavioral information along with related environmental, policy, and program supports may inform efforts to promote active travel to school.

Improving active travel to school and its surveillance: an overlooked opportunity in health promotion and chronic disease prevention.

Increasing active travel to school (ATS) could reduce the deficit in youth physical activity participation; however, surveillance of ATS is limited. Given that ATS contributes to our understanding of children's physical activity patterns nationwide, is influenced by local contexts and state laws, and occurs within communities, surveillance could be informative at the national, state, and local levels. Following a National Collaborative on Childhood Obesity Research workshop, this commentary offers insights into strengthening surveillance and data collection of ATS behavior as well as ATS environmental, policy, and program supports.

Impact of Maternal Health Behaviours and Social Conditions on Infant Diet at Age 1-Year: Results from a Prospective Indigenous Birth Cohort in Ontario, Canada.

Background: Understanding the impact of maternal health behaviours and social conditions on childhood nutrition is important to inform strategies to promote health during childhood. Objective: To describe how maternal health sociodemographic factors (e.g., socioeconomic status, education), health behaviours (e.g., diet), and traditional health care use during pregnancy impact infant diet at age 1-year. Methods: Data were collected from the Indigenous Birth Cohort (ABC) study, a prospective birth cohort formed in partnership with an Indigenous community-based Birthing Centre in southwestern Ontario, Canada. 110 mother-infant dyads are included in the study and were enrolled between 2012 and 2017. Multiple linear regression analyses were performed to understand factors associated with infant diet scores at age 1-year, with a higher score indicating a diet with more healthy foods. Results: The mean age of women enrolled during pregnancy was 27.3 (5.9) years. Eighty percent of mothers had low or moderate social disadvantage, 47.3% completed more than high school education, and 70% were cared for by a midwife during their pregnancy. The pre-pregnancy body mass index (BMI) was <25 in 34.5% of women, 15.5% of mothers smoked during pregnancy, and 14.5% of mothers had gestational diabetes. Being cared for by an Indigenous midwife was associated with a 0.9-point higher infant diet score (p = 0.001) at age 1-year, and lower maternal social disadvantage was associated with a 0.17-point higher infant diet quality score (p = 0.04). Conclusion: This study highlights the positive impact of health care provision by Indigenous midwives and confirms that higher maternal social advantage has a positive impact on child nutrition.

Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19.

Physics-based multi-scale in silico models offer an excellent opportunity to study the effects of heterogeneous tissue damage on airflow and pressure distributions in COVID-19-afflicted lungs. The main objective of this study is to develop a computational modeling workflow, coupling airflow and tissue mechanics as the first step towards a virtual hypothesis-testing platform for studying injury mechanics of COVID-19-afflicted lungs. We developed a CT-based modeling approach to simulate the regional changes in lung dynamics associated with heterogeneous subject-specific COVID-19-induced damage patterns in the parenchyma. Furthermore, we investigated the effect of various levels of inflammation in a meso-scale acinar mechanics model on global lung dynamics. Our simulation results showed that as the severity of damage in the patient's right lower, left lower, and to some extent in the right upper lobe increased, ventilation was redistributed to the least injured right middle and left upper lobes. Furthermore, our multi-scale model reasonably simulated a decrease in overall tidal volume as the level of tissue injury and surfactant loss in the meso-scale acinar mechanics model was increased. This study presents a major step towards multi-scale computational modeling workflows capable of simulating the effect of subject-specific heterogenous COVID-19-induced lung damage on ventilation dynamics.

In silicomodeling of tibial fatigue life in physically active males and females during different exercise protocols.

Preventing bone stress injuries (BSI) requires a deep understanding of the condition's underlying causes and risk factors. Subject-specific computer modeling studies of gait mechanics, including the effect of changes in running speed, stride length, and landing patterns on tibial stress injury formation can provide essential insights into BSI prevention. This study aimed to computationally examine the effect of different exercise protocols on tibial fatigue life in male and female runners during prolonged walking and running at three different speeds. To achieve these aims, we combined subject-specific magnetic resonance imaging (MRI), gait data, finite element analysis, and a fatigue life prediction algorithm, including repair and adaptation's influence. The algorithm predicted a steep increase in the likelihood of developing a BSI within the first 40 days of activity. In five of the six subjects simulated, faster running speeds corresponded with higher tibial strains and higher probability of failure. Our simulations also showed that female subjects had a higher mean peak probability of failure in all four gait conditions than the male subjects studied. The approach used in this study could lay the groundwork for studies in larger populations and patient-specific clinical tools and decision support systems to reduce BSIs in athletes, military personnel, and other active individuals.

The Relationship Between Perceived Confidence, Gender, and Writing in a Biomedical Engineering Research Experience for Undergraduates Site.

Women frequently feel alienated in science, technology, engineering, and mathematics (STEM) environments due to gender biases, ultimately leading them to feel less competent or leave the field altogether. This study utilizes personal statements from a subset of participants from a National Science Foundation (NSF) funded Research Experiences for Undergraduates (REU) Site: Biomedical Engineering in Simulations, Imaging, and Modeling (BME-SIM) to investigate how confidence is shown by participants and how confidence is perceived by faculty reviewers in personal statements. This study compares feedback from faculty reviewers to perceived and self-reported confidence using lexical (i.e., word choices and use) and syntactic (i.e., structures of language segments such as sentences, phrases, and organization of words) features of these personal statements. Women received more negative feedback related to confidence compared to their male counterparts, notably in relation to modesty. Few differences were found between writing styles of genders in their pre- and post-program statements. Overall, writing styles did not seem to correlate with the genders' perceived or self-reported confidence; however, perception of confidence suggested a relationship between genders' pre- and post-program statements when examined by noun and adjective variation. A similar relationship was found between self-reported confidence and noun variation in men and women participants. Findings suggest that writing style perceptions and practices may be influenced by gender norms; however, without looking at the specific diction and content of personal statements, these conclusions cannot be fully established.

Novel Application of Nutritional Biomarkers From a Controlled Feeding Study and an Observational Study to Characterization of Dietary Patterns in Postmenopausal Women.

Dietary guidance emphasizes healthy dietary patterns, but supporting evidence comes from self-reported dietary data, which are prone to measurement error. We explored whether nutritional biomarkers from the Women's Health Initiative Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) (n = 153; 2010-2014) and the Women's Health Initiative Nutrition and Physical Activity Assessment Study Observational Study (NPAAS-OS) (n = 450; 2006-2009) could identify biomarker signatures of dietary patterns for development of corresponding regression calibration equations to help mitigate measurement error. Fasting blood samples were assayed for a specific panel of vitamins, carotenoids, and phospholipid fatty acids; 24-hour urine samples were assayed for nitrogen, sodium, and potassium levels. Intake records from the NPAAS-FS were used to calculate Healthy Eating Index 2010 (HEI-2010), Alternative Healthy Eating Index 2010 (AHEI-2010), alternative Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) scores. Scores were regressed on blood and urine nutritional measures for discovery of dietary pattern biomarkers using a cross-validated model R2 ≥ 36% criterion (stage 1). Next, stepwise models (P ≤ 0.10 for entry/removal) using NPAAS-OS data were used to regress stage 1 dietary pattern biomarkers on NPAAS-OS self-reported dietary pattern scores using a food frequency questionnaire, a 4-day food record, and a 24-hour recall (stage 2). HEI-2010 and aMED analyses met the cross-validated R2 ≥ 36% criterion in stage 1, while AHEI-2010 and DASH analyses did not. The R2 values for HEI-2010 stage 2 calibration equations were as follows: food frequency questionnaire, 63.5%; 4-day food record, 83.1%; and 24-hour recall, 77.8%. Stage 2 aMED R2 values were 34.9%-46.8%. Dietary pattern biomarkers have potential for calibrating self-reports to enhance studies of diet-disease associations.

The immune response is a critical regulator of zebrafish retinal pigment epithelium regeneration.

Loss of the retinal pigment epithelium (RPE) because of dysfunction or disease can lead to blindness in humans. Harnessing the intrinsic ability of the RPE to self-repair is an attractive therapeutic strategy; however, mammalian RPE is limited in its regenerative capacity. Zebrafish possess tremendous intrinsic regenerative potential in ocular tissues, including the RPE, but little is known about the mechanisms driving RPE regeneration. Here, utilizing transgenic and mutant zebrafish lines, pharmacological manipulations, transcriptomics, and imaging analyses, we identified elements of the immune response as critical mediators of intrinsic RPE regeneration. After genetic ablation, the RPE express immune-related genes, including leukocyte recruitment factors such as interleukin 34 We demonstrate that macrophage/microglia cells are responsive to RPE damage and that their function is required for the timely progression of the regenerative response. These data identify the molecular and cellular underpinnings of RPE regeneration and hold significant potential for translational approaches aimed toward promoting a pro-regenerative environment in mammalian RPE.

Self-reported symptoms of arm lymphedema and health-related quality of life among female breast cancer survivors.

We examined cross-sectional associations between arm lymphedema symptoms and health-related quality of life (HRQoL) in the Health, Eating, Activity and Lifestyle (HEAL) Study. 499 women diagnosed with localized or regional breast cancer at ages 35-64 years completed a survey, on average 40 months after diagnosis, querying presence of lymphedema, nine lymphedema-related symptoms, e.g., tension, burning pain, mobility loss, and warmth/redness, and HRQoL. Analysis of covariance models were used to assess HRQoL scores in relation to presence of lymphedema and lymphedema-related symptoms. Lymphedema was self-reported by 137 women, of whom 98 were experiencing lymphedema at the time of the assessment. The most common symptoms were heaviness (52%), numbness (47%), and tightness (45%). Perceived physical health was worse for women reporting past or current lymphedema than those reporting no lymphedema (P-value < 0.0001). No difference was observed for perceived mental health (P-value = 0.31). Perceived physical health, stress, and lymphedema-specific HRQoL scores worsened as number of symptoms increased (P-values ≤ 0.01). Women reporting tension in the arm had lower physical health (P-value = 0.01), and those experiencing burning pain, tension, heaviness, or warmth/redness in the arm had lower lymphedema-specific HRQoL (P-values < 0.05). Treatment targeting specific lymphedema-related symptoms in addition to size/volume reduction may improve some aspects of HRQoL among affected women.

The retinal pigment epithelium: Development, injury responses, and regenerative potential in mammalian and non-mammalian systems.

Diseases that result in retinal pigment epithelium (RPE) degeneration, such as age-related macular degeneration (AMD), are among the leading causes of blindness worldwide. Atrophic (dry) AMD is the most prevalent form of AMD and there are currently no effective therapies to prevent RPE cell death or restore RPE cells lost from AMD. An intriguing approach to treat AMD and other RPE degenerative diseases is to develop therapies focused on stimulating endogenous RPE regeneration. For this to become feasible, a deeper understanding of the mechanisms underlying RPE development, injury responses and regenerative potential is needed. In mammals, RPE regeneration is extremely limited; small lesions can be repaired by the expansion of adjacent RPE cells, but large lesions cannot be repaired as remaining RPE cells are unable to functionally replace lost RPE tissue. In some injury paradigms, RPE cells proliferate but do not regenerate a morphologically normal monolayer, while in others, proliferation is pathogenic and results in further disruption to the retina. This is in contrast to non-mammalian vertebrates, which possess tremendous RPE regenerative potential. Here, we discuss what is known about RPE formation during development in mammalian and non-mammalian vertebrates, we detail the processes by which RPE cells respond to injury, and we describe examples of RPE-to-retina and RPE-to-RPE regeneration in non-mammalian vertebrates. Finally, we outline barriers to RPE-dependent regeneration in mammals that could potentially be overcome to stimulate a regenerative response from the RPE.

Implications of microscale lung damage for COVID-19 pulmonary ventilation dynamics: A narrative review.

The COVID-19 pandemic surges on as vast research is produced to study the novel SARS-CoV-2 virus and the disease state it induces. Still, little is known about the impact of COVID-19-induced microscale damage in the lung on global lung dynamics. This review summarizes the key histological features of SARS-CoV-2 infected alveoli and links the findings to structural tissue changes and surfactant dysfunction affecting tissue mechanical behavior similar to changes seen in other lung injury. Along with typical findings of diffuse alveolar damage affecting the interstitium of the alveolar walls and blood-gas barrier in the alveolar airspace, COVID-19 can cause extensive microangiopathy in alveolar capillaries that further contribute to mechanical changes in the tissues and may differentiate it from previously studied infectious lung injury. Understanding microlevel damage impact on tissue mechanics allows for better understanding of macroscale respiratory dynamics. Knowledge gained from studies into the relationship between microscale and macroscale lung mechanics can allow for optimized treatments to improve patient outcomes in case of COVID-19 and future respiratory-spread pandemics.

Systematic Review of Active Travel to School Surveillance in the United States and Canada.

Active travel to school is one way youths can incorporate physical activity into their daily schedule. It is unclear the extent to which active travel to school is systematically monitored at local, state, or national levels. To determine the scope of active travel to school surveillance in the US and Canada and catalog the types of measures captured, we conducted a systematic review of peer-reviewed literature documenting active travel to school surveillance published from 2004 to February 2018. A study was included if it addressed children's school travel mode across two or more time periods in the US or Canada. Criteria were applied to determine whether a data source was considered an active travel to school surveillance system. We identified 15 unique data sources; 4 of these met our surveillance system criteria. One system is conducted in the US, is nationally representative, and occurs every 5-8 years. Three are conducted in Canada, are limited geographically to regions and provinces, and are administered with greater frequency (e.g., 2-year cycles). School travel mode was the primary measure assessed, most commonly through parent report. None of the systems collected data on school policies or program supports related to active travel to school. We concluded that incorporating questions related to active travel to school behaviors into existing surveillance systems, as well as maintaining them over time, would enable more consistent monitoring. Concurrently capturing behavioral information along with related environmental, policy, and program supports may inform efforts to promote active travel to school.

Alignment of Dietary Patterns With the Dietary Guidelines for Americans 2015-2020 and Risk of All-Cause and Cause-Specific Mortality in the Women's Health Initiative Observational Study.

Poor diet quality is a leading risk factor for death in the United States. We examined the association between Healthy Eating Index-2015 (HEI-2015) scores and death from all causes, cardiovascular disease (CVD), cancer, Alzheimer disease, and dementia not otherwise specified (NOS) among postmenopausal women in the Women's Health Initiative Observational Study (1993-2017). This analysis included 59,388 participants who completed a food frequency questionnaire and were free of cancer, CVD, and diabetes at enrollment. Stratified Cox proportional hazards models were fit using person-years from enrollment as the underlying time metric. We estimated multivariable adjusted hazard ratios and 95% confidence intervals for risk of death associated with HEI-2015 quintiles, with higher scores reflecting more optimal diet quality. Over a median of 18.2 years, 9,679 total deaths 3,303 cancer deaths, 2,362 CVD deaths, and 488 deaths from Alzheimer disease and dementia NOS occurred. Compared with those with lower scores, women with higher HEI-2015 scores had an 18% lower risk of all-cause death and 21% lower risk of cancer death. HEI-2015 scores were not associated with death due to CVD, Alzheimer disease, and dementia NOS. Consuming a diet aligned with 2015-2020 US dietary guidelines may have beneficial impacts for preventing overall causes of death and death from cancer.

A Six-Year Review of the Biomedical Engineering in Simulations, Imaging, and Modeling Undergraduate Research Experience.

Undergraduate research continues to serve as an effective strategy for mitigating the effects of a leaky pipeline. Significant funding from institutions and government agencies has increased the number of students participating in undergraduate research. In this paper, we report on the six-year experience of a National Science Foundation funded Research Experiences for Undergraduates (REU) Site: Biomedical Engineering in Simulations, Imaging, and Modeling (BME-SIM). The operation and evaluation of the program are both described. We report on the results from 55 students over six summers from 2014 to 2019. Our program was successful in attracting a diverse group of participants including 46% under-represented minority students and 53% women. Based on evaluation results, students reported significant gains in technical skills, communication skills, and knowledge of graduate school. Our findings indicate baseline gender differences for several learning outcomes, where women and nonbinary students report lower levels of mastery. These gaps are closed by the end of the program except for confidence in skills, which is still significantly lower than those reported by male counterparts. The impact of the experience on ultimate career path is difficult to determine due to underlying biases and other motivating factors; however, 67.6% of graduates have entered graduate programs. Finally, we have provided lessons learned for those who are interested in building a summer research program. In conclusion, we have described the successful implementation of an REU site and the positive learning outcomes of the student participants.