University Of Rochester

NSF Awards · FY 2024 · 2024-11

The broader impact of this I-Corps project is based on the development of a solution to address challenges faced by regional supply chains at major companies that experience financial losses due to counterfeit goods and theft. Traditional 2-dimensional barcodes, such as QR codes, are currently used for tracking but lack the data capacity required for detailed tracking while adhering to common global standards. This new barcode technology, utilizing dual modulation, offers enhanced packaging barcodes that enable more efficient tracking and verification of goods without disrupting existing workflows. This improvement could lead to significant reductions in counterfeit products and better supply chain management. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of two-dimensional (2D) barcode technologies that exploit the high spatial resolution and color capabilities of modern smart mobile devices. By encoding a 2D barcode in each color channel (red, green, and blue) of an image, these channel-wise color barcodes provide a three-fold increase in data capacity over monochrome barcodes. The technology further improves traditional 2D barcode designs by using dual-modulated barcodes, where the conventional black squares are replaced with black elliptical dots whose orientation is modulated to embed additional data. This innovative design allows for secure data communication at close distances and is particularly useful for transmitting private information in public settings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

The Collaborative Research to Yield Stimulating Transnational Activities in Lattice Dynamics (CRYSTAL Dynamics) project, led by the University of Rochester, will provide students with invaluable international experiences while performing cutting-edge research in materials chemistry. In this IRES program, undergraduate and graduate students will have the opportunity to travel to prestigious Italian institutions, including the University of Turin and the University of Modena and Reggio Emilia, to undertake interdisciplinary research on advanced materials with important technological applications, from drug development to molecular semiconductors. This initiative is crucial for developing the next generation of scientists who are globally aware and culturally fluent, addressing the national need for a diverse and well-prepared STEM workforce that has experience working on an international and interdisciplinary research team. The project prioritizes recruiting students with no previous international experience, students from primarily undergraduate institutions, and those from underrepresented communities, and provides them with unique opportunities to perform world-class research while building an extensive international collaborative network, thus enhancing their educational experiences and future career prospects. By promoting the progress of science and fostering an inclusive educational environment, this program aligns with national priorities related to STEM education. CRYSTAL Dynamics focuses on the study of lattice dynamics to generate a comprehensive understanding of the relationship between atomic structure, lattice dynamics, and bulk material properties. The project is structured around three main research thrusts: understanding forces related to solid-state phase transformations, creating dynamic molecular crystals using green chemistry methods, and utilizing quantum mechanical simulations to inform experimental work. Students will form two cohorts, one experimental and one theoretical, and will engage in interdisciplinary research projects, such as synthesizing and characterizing dynamic crystals and developing computational tools for predicting material behaviors. The collaborative effort involves internationally-recognized researchers from the University of Rochester, the University of Turin, and the University of Modena and Reggio Emilia, and provides students with access to advanced research facilities and mentorship from leading scientists who have deep international experience. This research aims to uncover the fundamental forces that underpin bulk material phenomena, with applications in materials chemistry, semiconductor engineering, and the pharmaceutical industry. The program will also enhance the practical skills, cultural fluency, and professional development of the students, contributing to the broader goal of preparing a diverse, globally-competent STEM workforce. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This project aims to serve the national need of alleviating the shortage of highly qualified STEM teachers for high-need schools. In particular, over the five years of the project, the investigators will recruit and prepare twenty-one (21) computer science, mathematics, and other STEM prospective teachers, who will promote the national goal of making STEM education more accessible and effective for all students. These new teachers will be prepared to teach in high-need schools, and to support the implementation of the state of New York Computer Science and Digital Fluency Learning Standards across the curriculum. The new teachers developed from the program will contribute to the nation’s economic competitiveness by better preparing the next generation of students. Insights gained from the implementation of this program will also contribute new knowledge about how to best prepare future STEM teachers, especially in the areas of computer science and digital fluency. This project is housed at the University of Rochester and will leverage long-term partnerships with the College of Computing and Information Sciences at the Rochester Institute of Technology, East Irondequoit Central School District, and East High School within the Rochester City School District. The project features two underlying goals. First, the project will provide twenty-one (21) scholarships to a diverse set of graduates from STEM majors, to enable them to complete a rigorous 14-month graduate teacher preparation program leading to New York State teacher certification in computer science, mathematics, biology, chemistry, physics, or earth science. A second underlying goal is to prepare the new teachers to integrate the recently established New York State Computer Science and Digital Fluency Learning Standards into their STEM teaching. Other goals include preparing project participants to: teach in high-need schools; be equipped with culturally responsive pedagogies that promote social justice, equity, and inclusion; and be able to create a classroom culture in which all students experience a sense of STEM belonging and are prepared to succeed. The project is supported by formative and summative project evaluation focused on determining the impact, efficacy, and value of project activities. In addition, it is expected that new knowledge will be generated in the areas of preparing teachers to incorporate computer science and digital fluency learning, especially as it relates to the New York State standards. Proactive dissemination of the project's findings related to these issues will take place in several STEM education venues, particularly to engage stakeholders in New York. This Track 1: Scholarships and Stipends project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the effectiveness and retention of K-12 STEM teachers in high-need school districts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Learning is a central psychological construct that has been studied primarily in individuals. However, humans and other social animals often learn with others, yielding outcomes that are often superior to those obtained by learning alone—a phenomenon known as collective learning. This project investigates the extent to which fundamental principles of associative learning, which operate at the level of individual organisms, contribute to collective learning. Just as individuals learn about correlations in the environment (e.g., rain typically follows dark clouds), they may also learn about correlations between stimuli in the environment and the actions of other individuals (e.g., rain typically follows if you see people carrying umbrellas). The investigators will test a mathematical model that postulates how associative learning in individuals contributes to collective learning using animal model systems. The specific animal models are selected because (a) like humans, they are highly social and learn collectively, (b) they afford the necessary level of experimental control under laboratory conditions to test the proposed mathematical model, and (c) the evolutionary distance between them is large enough to identify general mechanisms of collective learning. The basic rules of collective learning found in these animal groups can be leveraged to promote advantageous aspects of collective learning and to anticipate its detrimental consequences. This project aims to identify fundamental processes of collective learning. A series of associative-learning experiments will test which form of training—individual or collective—results in faster and more durable learning that is resilient to interference from uninformative cues. For each experiment, a prediction will be made based on a simple computational model that assumes that the behavior of other group members can be learned as an informative cue. The generality of the proposed model will be tested on nest-seeking behavior in social insects and food-seeking behavior in social mammals. Aside from their sociality and convenience, specific species were selected as animal models because they lack the higher cognitive sophistication of humans. This makes it easier to uncover the basic associative mechanisms underlying collective learning, without having to control for potential interference by cognitively complex non-associative processes, such as verbal communication. Nonetheless, aspects of the model that are validated with different parameters are expected to generalize to human learning and can be the basis of further examination in humans. These findings will, therefore, aid in determining the factors that can promote or impede collective intelligence when humans or machines (e.g., artificial intelligence) perform tasks as a group. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Contamination in child maltreatment research occurs when members of a comparison condition are exposed to child maltreatment prior to enrolling in a study or during longitudinal follow-up. This phenomenon presents a serious scientific concern, as contamination minimizes real differences in the risk for adverse child development between child maltreatment and comparison conditions. The current project addresses this concern by testing different methods for detecting and controlling contamination bias in child maltreatment research. Specifically, investigators will access existing data from independent prospective cohort studies and examine the performance of five different statistical modeling approaches to determine which has the optimal control of contamination. Two bias reduction modeling approaches, propensity score and augmented synthetic control models, will be executed with results compared against three conventional approaches: no control of contamination, controlling contamination by removing identified participants from the statistical model, and controlling contamination by testing it as a covariate or moderator of risk estimates. Investigators will then use data simulations to model the performance of these five methods across different research conditions, including variations in contamination prevalence, sample size, statistical power, and effect size magnitude. Ultimately, the best performing methods for detecting and controlling contamination in child maltreatment research will be disseminated to scientists so that future risk estimates are more accurate, something that can better inform child welfare policy through more reliable scientific data. While tested within child maltreatment research, results from the statistical models evaluated in this project will be available to any scientist conducting observational research on exposure variables, enhancing the reliability of scientific results across STEM domains. Finally, knowledge on how to use these methods will be incorporated into STEM education at the University-level by educating undergraduate, graduate, and post-doctoral fellows on how to control contamination in prospective cohort studies within and outside the area of child maltreatment. Contamination, when subjects recruited to a non-exposure comparison condition have been exposed to the event under investigation, is a methodological phenomenon in observational research that downwardly biases effect size estimates by minimizing group differences, thereby increasing replication and reproducibility failures. The current project will evaluate the performance of multiple strategies for detecting and controlling contamination bias in prospective cohort research with the child maltreatment population. This will be achieved through secondary analysis of existing data from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN; N=1354) and the National Survey of Child and Adolescent Well-being-II (NSCAWII; N=5873) cohorts, each of which are multi-wave, prospective cohort studies of child maltreatment from birth through age eighteen. A multi-method approach of official case reports, self-report, and caregiver-report assessments obtained across child development will be used to maximize sensitivity for detecting contamination and establishing its prevalence in these cohorts. Two innovative methods for controlling bias in observational research, doubly robust propensity score and augmented synthetic controls, will be used to control contamination bias in each of these cohorts. Results from these two models will be evaluated against alternative models that: 1) ignore contamination, 2) control contamination by removing subjects from statistical analysis, and 3) control contamination by estimating it as a covariate/moderator of child maltreatment effects. Following statistical efficiency principles, the performance of all five models will be benchmarked with respect to needed sample size, impact on statistical power, and extent of bias reduction in effect size estimates. Given the ultimate goal to identify which methods provide the most accurate estimates under different empirical conditions, this project will also evaluate results from all five models using simulations that both mimic the data structures of LONGSCAN and NSCAW-II and extend out to conditions commonly encountered in prospective cohort studies, including variations in contamination prevalence, sample size, and effect size magnitude. These results will have broader scientific and public impacts by: disseminating results to scientists outside the area of child maltreatment who conduct research where contamination is present, training the next generation of STEM scientists in the optimal methods for detecting and controlling contamination, and providing more accurate estimates of the risks associated with child maltreatment to better inform child welfare policy in the U.S. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

This application addresses the CDC SIP-24-013 ‘Understanding the potential of schools in promoting non- mandated childhood vaccinations.’ Influenza results in thousands of deaths and millions of illnesses in the US each year. Children under age 4, those with high-risk conditions, and individuals over age 65 are most likely to be hospitalized due to influenza, and healthy school-aged children and adolescents often spread influenza to their more vulnerable family members. Influenza vaccine provides 68% protection against pediatric hospitalization, but only half of children receive the vaccine (rates are lower for rural and Black children). Each year in the U.S., ≥20,000 women and 15,000 men develop HPV-related cancers. Almost all cases of cervical cancer and ~70% of oropharyngeal cancer are caused by HPV. Fortunately, if given prior to exposure, HPV vaccine is nearly 100% effective, so the vaccine series is recommended to start at ages 9-12. Schools play a role in making sure students receive those vaccines that are mandated by law, but also have the potential to promote influenza and HPV vaccination. Increasing confidence in the safety and efficacy of vaccines and building trust are crucial to enhance vaccine uptake. School-based trusted messengers, including school nurses, school physicians and health teachers, as well as administrators, have the potential to act as trusted messengers for vaccine information. In addition, schools communicate with parents by email and messaging apps, where vaccine reminders can be sent. Our novel ‘Theater for Vaccine Hesitancy’ (TVH) training, based in social determination theory, trains trusted messengers in productive conversations with vaccine hesitant patients. It will be combined with education and resources about influenza and HPV vaccination, as well as direct parent messaging from school, to encourage vaccination. Specifically, we will: 1) Modify existing vaccine promotion toolkits and interactive TVH workshops to focus on trusted school messengers supporting influenza and HPV vaccination, 2) Measure the effect of the revised educational toolkit + TVH on influenza vaccination rates in urban and rural schools. Assess intervention feasibility, acceptability, and cost, and 3) Measure the effect of the intervention on HPV vaccination (any dose) in schools randomized in Aim 2. Assess intervention feasibility, acceptability, and cost. At the conclusion of the interventions, we will have a model and revised toolkit to implement a parent focused school-based education/reminder program to increase rates of non-mandated recommended vaccines in rural and urban schools.

NIH Research Projects · FY 2025 · 2024-09

Deaf sign language users and people with hearing loss comprise health disparity populations overlooked by most public health research, surveillance and programs. The mission of the Rochester Prevention Research Center (RPRC) is to promote health and prevent disease with populations of Deaf American Sign Language (ASL) users and people with hearing loss through community-based participatory research (CBPR). These two populations differ in many aspects, including language, culture, and lived experience. Three similarities are risk for health inequities, barriers to healthcare communication, and limited engagement with public health. One RPRC goal is to eliminate health disparities and inequities experienced by populations of Deaf ASL-users and people with hearing loss. RPRC will work to achieve the mission and goal through three overarching aims. Overarching Center Aim: To administer, maintain and grow RPRC to continue to address disparities and inequities, and to reach new populations of Deaf ASL-users and people with hearing loss to promote health. Overarching Research Aim: To conduct one community-engaged dissemination and implementation core research project with Deaf Weight Wise (DWW), an evidence-based intervention shown to improve health, wellness, and social connection among Deaf adult ASL-users. The research is designed to identify the facilitators and barriers to the successful implementation of DWW with diverse partners across the USA, and the approaches and strategies that lead to the successful translation of DWW into a health program available to those who would benefit. Overarching PRC Network Aim: To continue RPRC's active engagement with the PRC Network and program, and to explore additional opportunities to partner with other PRCs to collaboratively adapt their evidence-based interventions to be communication accessible and appropriate for use with people with hearing loss or Deaf ASL-users. This research is responsive to Deaf community priorities in that it focuses on: 1) inequities in access to health promotion programs, 2) implementation and the request that RPRC translate DWW from research into a health program that is available to those who would benefit, and 3) scalability and the request that the benefits of RPRC research extend to Deaf communities outside of Western/Central NYS. This proposal is responsive to the NOFO with our emphasis on health and wellness of older adults (category #1), with RPRC's specific focus on underserved subpopulations of older adults who are Deaf ASL-users. RPRC accomplishments at the end of this funding period will include: enhanced capacity for CBPR with communities of Deaf ASL-users and people with hearing loss; data to inform implementation strategies and scale to connect DWW programs with Deaf communities; expanded RPRC reach, with stronger and new partnerships with Deaf communities and other implementation partners outside of Western/Central NYS; communications and products, in English and American Sign Language, to inform communities, researchers, the PRC Network, and other stakeholders of RPRC methods, results, programs, and services.

NIH Research Projects · FY 2025 · 2024-09

The goal of this research program is to develop robust and flexible dual-duration, multi- wavelength fiber sources of light for nonlinear and multimodal imaging with orders of magnitude signal enhancement over the state of the art. Nonlinear imaging enables label-free, deep, and diffraction-limited imaging in living tissue through a variety of nonlinear interactions that are each sensitive to specific molecules, symmetries, and structures, including two-photon excitation fluorescence (2PEF), second- and third-harmonic generation (SHG and THG), and Raman- sensitive techniques such as coherent anti-Raman scattering (CARS). Moreover, combining these largely orthogonal modalities yields a rich combination of molecular, structural, and functional information which has been demonstrated for diagnosing atherosclerosis, neurological diseases, and cancer, including revealing new biomarkers and clinically relevant signatures absent even from histologically processed tissue. However, each imaging modality requires specific and incompatible pulse parameters that cannot be achieved with current ultrashort pulse technology without sacrificing orders of magnitude in imaging signal strength. This proposal will establish a new suite of technologies for ultra-short pulse generation that no longer rely on traditional mode-locked laser-based systems. Building from recent proof-of-concept demonstrations from the PIs, this research targets flexible and efficient fiber sources of inherently synchronized multi-wavelength picosecond and femtosecond pulses specific for each nonlinear imaging modality, with the ability to generate them simultaneously for multimodal imaging. The research program is based on three Aims: (1) Developing diode-laser driven fiber time-lens picosecond sources that are efficiently wavelength shifted with fiber parametric amplification for flexible, multiwavelength picosecond sources; (2) Developing Kerr resonators for femtosecond pulse generation with high efficiencies and the energy and wavelength flexibility ideal for nonlinear imaging; and (3) Establishing dual-duration multi-wavelength sources adapted for background suppressed CARS imaging and 2PEF, SHG, and THG, and demonstrating these sources for multimodal imaging with unprecedented speeds and contrast using existing multiphoton microscopes and a commercial microscope system to demonstrate the potential for widespread adaptation. Our aim is to enable a significant advance for nonlinear and multimodal imaging contrast and depth at real-time frame rates with a novel source that is low-cost and more accessible than previous technologies. Successful completion of this program will have major impact for biomedical research as well as clinical applications of ultrashort-pulse imaging.

NIH Research Projects · FY 2024 · 2024-09

The older adult population (OAs; e.g., ≥65 years old) is projected to almost double between 2012 and 2050 in the United States. This population already disproportionately utilizes surgical services and this is projected to increase with this increase in the OA population. OAs have higher rates of complications after major colorectal surgery, particularly those who are frail. In addition, pre-existing functional and cognitive decline can also amplify the consequences of surgical complications. Finally, changes to bowel, urinary or sexual function are common in OAs after major colorectal surgery and can significantly impact quality of life. Thus, surgical shared decision- making (SDM) in this population is more complex. SDM is an approach well suited to manage complex decision making, such as high risk surgery in frail OAs. However SDM is not often successfully done prior to surgery, particularly in the OA population. SDM tools have been utilized to promote and improve SDM, but there is a gap in SDM tools specific to the frail OA population considering major colorectal surgery. A scoping review of existing provider facing tools for SDM show that most are risk calculators intended for elective surgical risk assessment but few addressed patient-centered domains such as assessment of patient goals, postoperative expectations such as changes to physical or cognitive function or independence, anticipated changes to quality of life, and long-term risks. As the population of the US continues to age, it will place greater demands on surgical services and is important that the medical community meet these growing demands and ensure high quality care for OA surgical patients, particularly those who are frail and most vulnerable within this population. The American College of Surgeons Geriatric Surgery Verification Program has recognized improvement of the surgical SDM process as an important standard of care in this patient population. There is a critical need to improve the SDM process in this population that is particularly vulnerable, growing in size, and with unique needs to improve outcomes, ensure high quality care, and inform decision making with patients and their families. This proposal will help develop a user-friendly SDM tool for surgeons, specific to the needs of frail older adults considering major colorectal surgery, to improve communication in the surgical SDM process. This will be achieved through a Delphi process of clinical experts and patient representatives to adapt an existing SDM to be specific for the proposed population utilizing the RAND/UCLA Appropriateness Methodology. This tool will then be pilot tested amongst providers to examine implementation outcomes (e.g., feasibility, barriers to use, utility of the tool) using the Consolidated Framework for Implementation Research (CFIR) and explore quality of SDM among patients. This proposal will adapt an existing tool for SDM in the frail OA population considering major colorectal surgery and pilot the tool to inform larger scale testing and multi-site implementation to evaluate its effects on the quality of surgical SDM through a later R01.

NIH Research Projects · FY 2026 · 2024-09

PROJECT SUMMARY Of the nearly 68 million Latinos who reside in the U.S., over 5.4 million (8.0%) currently smoke cigarettes, and most do not meet the recommended levels of physical activity (at least 150 minutes of moderate to vigorous physical activity per week). Addressing smoking and insufficient physical activity – behaviors associated with increased morbidity and mortality – among Latinos requires innovative, effective, accessible, and communityengaged interventions. Over the past eight years, in partnership with a Community Advisory Board (CAB), we developed Decídetexto, a smoking cessation text messaging intervention for Latinos (available in English and Spanish). Our recently completed randomized controlled trial (RCT; n=457) demonstrated that Latinos receiving the Decídetexto intervention were significantly more likely than those receiving standard of care (smoking cessation printed materials) to self-report abstinence at Month 6 (34.1% vs 20.6%; p<0.001). Despite the proven efficacy of Decídetexto among Latinos, we did not address the fact that 75% of participants did not meet the recommended levels of physical activity [at least 150 minutes of moderate to vigorous physical activity (MVPA) per week]. Moreover, we did not leverage the potential role of physical activity in enhancing cessation rates despite evidence suggesting that MVPA may enhance cessation rates. Thus, we developed Actívatexto, an innovative mobile intervention that incorporates physical activity into the Decídetexto intervention. Specifically, Actívatexto integrates four components: 1) a text messaging program that promotes both smoking cessation and physical activity, 2) wearable devices to monitor physical activity, 3) smoking cessation pharmacotherapy (i.e., nicotine replacement therapies), and 4) an online dashboard where the research team manages participants’ incoming and outgoing data from both the text messaging program and wearable devices. Pilot tested among Latinos who smoke and do not meet the recommended levels of physical activity (n=20), Actívatexto generated high satisfaction, increased minutes of MVPA per week, and resulted in noteworthy cessation rates (70% of participants were smoking abstinent at Month 3). We will use a hybrid type I effectiveness- implementation research design to assess the efficacy of Actívatexto and the barriers and facilitators of its implementation. Specific aims are: Aim 1. Assess the efficacy of Actívatexto, a mobile intervention that promotes both smoking cessation and physical activity, compared to a mobile intervention that solely promotes smoking cessation, on smoking abstinence at Month 6 among Latinos. Aim 2. Assess physical activity, self-efficacy, and perceived stress as mediators of the presumed treatment effect on cotinine-verified 7- day point prevalence abstinence at Month 6 among Latinos. Aim 3. Examine the barriers and facilitators to implement Actívatexto among Latinos.

NIH Research Projects · FY 2025 · 2024-09

Our study will address the goals of RFA-AG-24-025 by elucidating how the pathways by which key aspects of social connectedness in social networks (SNs)—structural characteristics, functional aspects, and quality of relationships—interact and are associated with clinically significant health behaviors of older adults with advanced cancer. We focus on older adults with advanced cancer with an estimated survival of less than 12 months because our research shows that a) they rely heavily on social networks (SNs) for instrumental and emotional support, b) their health behaviors are complicated by poor disease understanding, c) aging-related conditions and treatment-related toxicities adversely affect their quality of life (QoL) and survival, d) their interpersonal emotional processes and social determinants influence discretionary utilization (e.g., chemotherapy) at the end of life (i.e., DIALs), and e) serious illness conversations and advance care planning with SN members promote appropriate use of palliative care. In this proposal, we focus on three behaviors known to improve outcomes at the end of life (EoL): initiating and participating in serious illness conversations about preferences for EoL care, completing advance care planning, and engaging with palliative care. We will examine how structural characteristics of patients’ SNs (e.g., density; size and composition of inner circle), their functional aspects for provision of social support, and the quality of relationships (perceptions of belonging, interpersonal emotional processes) influence these health behaviors. We will also examine SN resilience: how SNs evolve to continue to provide support for patient behaviors in the face of cancer progression and network disruptions. We will assess interactions among structure, function, and quality of relationships of SNs using Mixed Methods Social Network Analysis (MMSNA) to integrate structural analysis with qualitative assessment of network characteristics, and evaluate associations with health behaviors at the EoL. At study entry, we will survey 300 patients with advanced cancer (age >65 years, with a life expectancy <12 months) to assess their SN structures. Then, we will use criterion-based emergent sampling to purposively select up to 70 patients and one key influential member of their SNs for in-depth semi-structured interviews to characterize how SN members influence health behaviors of older patients with advanced cancer at the EoL. Our aims are (1) To assess the interrelationships between SN structure, function, and quality of relationships; (2) To analyze how SN structure, function, and quality of relationships relate to key health behaviors, including engagement in serious illness conversations about EoL preferences, advance care planning, and palliative care; and (3) To describe thematic pathways of network resilience (i.e, how the structure, function, quality of relationships evolve) in response to cancer progression and SN stressors over 6 months. Our findings will help develop SN interventions, informed by and adapted to network structures and interpersonal processes of behavior change, to improve EoL care in older patients with advanced cancer.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY This is an application for a K23 Mentored Career Development Award for Dr. Ashley Jenkins, a dually trained Internal Medicine and Pediatrics (Med-Peds) hospitalist. Dr. Jenkins career goal is to become an independent researcher who uses patient-engaged approaches and implementation science to improve hospital care and promote health equity for patients with sickle cell disease (SCD). Over 100,000 people in the US live with SCD, the majority of whom are people of color and living in poverty. People with SCD experience extremely painful vaso-occlusive episodes (VOE). VOE can be fatal, yet patients avoid hospitalization for severe VOE for the same reasons they avoid ED visits: clinicians lack SCD knowledge, disease stigma, racial bias, and complications of health system complexity like long wait times. Care delays for severe VOE add to the risk of death. Hence, improving VOE inpatient care may not only mitigate negative healthcare experiences for patients with SCD, but also decrease their risk of death. The NHLBI recommends use of patient-specific protocols, or individualized care plans (ICPs), for acute VOE care. ICPs include patient-specific recommendations for VOE care like pain medications. When tested in the ED setting, ICPs resulted in improved patient experience and reduced need for hospitalization. Yet, a critical knowledge gap remains regarding how to adapt and implement ICPs tested in the emergency department for inpatient care settings. The overall objective of this K23 proposal is to use implementation strategies to adapt and preliminarily test an ICP prototype specific for inpatient VOE care. In Aim 1, Dr. Jenkins will develop an ICP prototype adapted from the emergency department setting for inpatient SCD care with a patient-inclusive multistakeholder team. In Aim 2, she will test the feasibility of implementing and evaluating ICPs for inpatient VOE care at both a community and university-based hospital. Dr. Jenkins’s career development plan includes formal coursework, intensive mentorship, and experiential training in 1) implementation research, 2) intervention adaptation, 3) delivering high quality SCD inpatient care, and 4) the successful conduct of multisite collaborative research. Dr. Jenkins will be supported by the extensive resources of the University of Rochester Medical Center and Clinical and Translational Science Institute. She has also identified expert mentors in these disciplines with outstanding track records in training independent investigators and securing protected time for this work. This award addresses a significant gap in SCD and hospital-based research while affording the education and mentored research experience critical to Dr. Jenkins and her career goal of becoming an independently funded physician-scientist.

NIH Research Projects · FY 2025 · 2024-09

Project summary: Today, assisted living communities (ALs) are a popular choice for older adults who can no longer maintain an independent lifestyle at home. However, ALs generally do not offer medical services on- site. This may be challenging, especially for the more than 40% of AL residents with ADRD, who often have complex health conditions and require regular outpatient primary and specialty services (e.g., mental health) to manage their health needs. Accessing and arranging transportation for these necessary services may be difficult and burdensome for these residents due to their physical and cognitive impairments, and due to the limited availability of some services. Telemedicine, which has expanded greatly since the pandemic, may provide an opportunity to improve access to care for AL residents with ADRD. However, the impact of the telemedicine policy may vary across ALs and be influenced by market- and state-level factors. Effective telemedicine utilization may require resources, such as infrastructure (e.g., high-speed internet) and a sufficient and well-trained workforce. Direct care workers (DCWs) are the main care providers in ALs and play a crucial role in supporting residents with ADRD. Several factors, including AL-level resources, market-level direct care workforce, and state AL regulations, may affect AL infrastructure, staffing and training, and, consequently, effective telemedicine use in ALs. To date, there is very limited empirical evidence on the potential impact of the CMS’ telemedicine policy on AL residents. Thus, the objective of this study is to use a mixed-method approach to understand multi-level factors at AL- (SA1), market- (SA2), and state-level (SA3) that may influence the impact of telemedicine policy on AL residents with ADRD. By using 2018-2024 data, we will examine telemedicine and all visits (including in-person) for different types of outpatient services (e.g., mental health, primary care), as well as the use of other health services (e.g., hospitalizations and long-term nursing home [NH] placement) that may be affected by regular outpatient services. We hypothesize that residents with ADRD in ALs with fewer resources, in markets with lower wages of DCWs, or in states with less specific regulations are less likely to “benefit” from the policy - that is, they are less likely to use telemedicine outpatient services and more likely to have hospitalization, emergency room visits, and NH placement, accounting for the differences in these events before the pandemic. We will also collect primary data (through interviews) to explore how key AL, staff, and resident/family characteristics vary in ALs and their potential associations with telemedicine use (SA4). The study is innovative because it will be the first to address the proposed research objectives. This study is significant because it will provide important findings on potential benefits/challenges to telemedicine use in ALs for residents with ADRD. Findings will also shed light on regulatory policies that may create barriers to and exacerbate disparities in receiving appropriate care in this population. This study will provide important and timely insights into the CMS’ telemedicine policy decisions.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY or ABSTRACT Over the past 25 years, the United States (US) has witnessed a fourfold increase in its prison and jail population, There is a glaring lack of data on their surgical care, and what is known is deeply troubling. This study, titled 'Validating Methodologies and Evaluating Surgical Care for Incarcerated Individuals,' seeks to deepen our understanding of the healthcare of incarcerated individuals and ultimately describe mortality and timely surgical care. Incarcerated individuals possess the unique constitutional right to healthcare, yet the extent, quality, and outcomes after surgery are unknown. The reasons for this knowledge gap are complex, none the least of which is the difficulty of identifying these patients in healthcare databases. Identifying incarcerated individuals in healthcare databases relies on the International Classification of Diseases 10th edition codes, Z65.1 ("imprisonment and other incarceration") and Y92.14x ("prison as the place of occurrence of the external cause") or the Agency for Healthcare Research and Quality admission source code. These codes are used ubiquitously in healthcare databases, but their validity is unestablished. To address these critical gaps in the surgical care of incarcerated individuals, our study has two aims. In Aim 1, we will validate methods for identifying incarcerated patients in electronic medical records (EMR) and claims databases. The accuracy of these codes is crucial for gaining insights into healthcare delivery for incarcerated individuals requiring surgery and in-hospital medical care. In Aim 2, we will evaluate the timeliness of surgical care and outcomes (morbidity, mortality) of incarcerated patients in New York State undergoing inpatient surgery using validated codes. This study introduces an innovative method for identifying incarcerated patients in healthcare databases, serving as an invaluable model for future research. Our multidisciplinary investigator team and Expert Advisory Panel have expertise in the healthcare of incarcerated individuals, health outcomes, surgical care, , and policy evaluations which ensures the validity of the study. In essence, this research addresses pressing issues in incarcerated healthcare and provides a methodological framework to inform future studies, facilitating informed policy decisions and improved healthcare practices for all.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY (ABSTRACT) As genetic and disease-modifying interventions emerge, there is an urgent need for early and accurate assessment of disease-specific motor impairments in people with Huntington’s disease (HD). Traditional measures are subjective and episodic and have a limited ability to capture early, subtle motor features. Digital measures have the potential to remotely quantify disease-specific impairments in individuals with HD. A key next step is to evaluate the most promising digital measures in the early stages of HD. Gait impairments and involuntary choreic movements are clinical hallmarks of HD and two of the earliest motor signs. Chorea, which is characterized by involuntary writhing movements, can affect gait characteristics and make conventional approaches to quantifying gait using wearable sensors inaccurate in HD. Our pilot work has shown that wearable sensors can evaluate the quantity and quality of daily living gait in people with HD, even in the presence of chorea, with the aid of tailored machine learning. Exciting initial findings also suggest that chorea severity can be captured using digital health technologies (DHTs) like wearable sensors. Daily physical activity, heart rate variability, and sleep also differ in individuals with HD and healthy controls. All of these measures have the potential to be meaningful endpoints in HD clinical trials, but critical gaps first need to be addressed. We aim to demonstrate the reliability, validity, and meaningfulness of two key digital measures, daily living mobility (gait) and chorea, captured remotely and continuously using wearable sensors. We will also explore daily physical activity, heart rate variability, and sleep. In this remote, cross-sectional study, 40 individuals with early HD (HD Integrated Staging System, HD-ISS Stage 2, and early Stage 3) and 20 control participants will wear two sensors (trunk and wrist) for 1 and 2 weeks, respectively, and will complete telehealth assessments and interviews. Our long-term objective is to fully establish these digital measures as drug development tools and treatment response endpoints in early HD. Our two specific aims are: 1) demonstrate the construct validity and test-retest reliability of a) real-world gait and chorea and b) daily living physical activity, heart rate variability, and sleep quality using wrist-worn wearable sensors in people with early-stage HD; and 2) a) to map personally bothersome and important symptoms/impacts of HD and assess relevance of selected digital measures and b) to evaluate the relationship between the digital measures and patient-reported outcomes. The proposed work will be the first time that our innovative symptom mapping approach is applied to HD, the first time that DHTs are connected to patient-reported meaningfulness in HD, and the first time that real- world study of gait and chorea in HD is assessed as a function of the recently developed HD-ISS staging. This will also be the first study that brings together recently developed HD functional scales, patient symptom mapping, and novel digital measures. The study will inform larger-scale validation efforts and clinical endpoint studies in HD and other, more common diseases with involuntary movements (e.g. Parkinson’s disease).

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT: Maternal mortality (MM) and severe maternal morbidity (SMM) have been on the rise, and racial disparities are widening. Rochester is the city with the highest Black MM/SMM rates in the state of New York, and Black women are 2 to 3 times more likely to die and to have severe morbidities associated with pregnancy. Researchers continue work towards assessing these disparities and identifying modifiable structural and social factors to improve pregnancy outcomes for Black women and birthing persons, while communities are called to action to address disparities in MM/SMM. Our local community efforts include the initiatives of the Consortium to End Black Maternal Mortality, created in 2019 (PCORI funded project) to engage multiple stakeholders in the quest to understand local disparities and create a research agenda to inform local programs. Our initial project consisted of conducting listening sessions with Black women in Rochester to understand their experiences with the perinatal care system (Alio et al, 2022). Mothers identified their partners/infants’ fathers’ support as an important factor influencing their experiences with perinatal care. In the literature, the emotional, physical and financial support of fathers during pregnancy has been associated with improved birth outcomes, especially among Black women. However, little is known about the role of fathers in helping to reduce MMM/SMM. Fathers/partners are an untapped source of emotional and logistical support during perinatal care, and their involvement may have indirect impact on MM/SMM, and longer-term benefits for the family. Furthermore, fathers can serve as advocates for their birthing partner, and allies in the care of women during the perinatal period. We build upon the work of our community Consortium to continue our efforts to understand the experiences of Black parents and identify specific areas for intervention. Supplementing our data on Black women, this study aims to explore Black fathers’ experiences with perinatal care, and their potential role in mitigating these dire outcomes. Like our study with Black women (N=44), we will conduct listening sessions with 40 Black fathers and individual interviews with 20 Black fathers in Rochester, NY, to explore their group and individual experiences with perinatal care and understand their potential role as advocates for mothers and allies in perinatal care (AIM 1). We will then merge results of LS with existing data from Black women for an integrated, group dyadic analysis (AIM 2). Additionally, we will compare data from LS with fathers with results from induvial interviews to assess differences in themes from the two methods. Findings will provide a comprehensive picture of Black parents’/co-parents’ experiences with perinatal care. The socio ecological model will guide the identification of multi-level elements of Black fathers’ experiences and allow for comparisons with women’s data, and for assessing couple’s experiences. The patient experience framework will guide analysis of themes from both groups. Results will inform local efforts to identify and address specific elements of perinatal care to increase equitable care for Black women and to reduce MM /SMM.

NIH Research Projects · FY 2024 · 2024-09

Current HIV/STI prevention interventions for female-male couples in the US require an in-person modality and focus on specific subgroups. Digital health interventions may provide one solution to expand access to tailored, couples-based HIV/STI prevention-care interventions that appeal to male-female couples in the U.S. with varying vulnerabilities to HIV and other STIs. One couples-based digital health intervention has reduced male couples’ susceptibility to HIV and other STIs. The intervention used a hybrid format with individuals first completing a sequence of pre-determined modules (i.e., HIV/STI education, instructional videos, a searchable sexual health resources database, activities including an agreement builder) followed by completing the sequence jointly with their partner, and then ending with a finalized, comprehensive sexual agreement containing HIV/STI prevention items. To examine the acceptability of this theoretically-driven, couples-based digital health intervention for HIV/STI prevention, we conducted a multi-method pilot project with 28 female-male couples in New York State. Couples in this pilot reported high intervention acceptability (96%), and qualitative dyadic content and thematic analysis revealed explicit recommendations to enhance intervention relevancy for adapting the digital health intervention to meet their specific relationship and sexual health needs. Given these preliminary findings, we propose to conduct a novel, 3-year mixed method study guided by the Couples Interdependence Theory and the Assessment, Decision, Adaptation, Production, Topical experts, Integration, Training, and Testing model to adapt and pilot-test this digital health intervention to meet the needs of female-male couples. Dyadic data will be collected via: a) quantitative assessments at baseline, month 3 and 6; b) HIV/STI screening at baseline and month 6; c) 7 different paradata outputs (intervention use); d) individual exit interviews at month 6. Our specific aims are: (1) Adapt the intervention for couples using the proposed model with human-centered design. (2) Conduct a 6-month pilot RCT with 60 couples using a 2:2 block random allocation approach (intervention vs. 3-month, waitlist control), stratified by dyad HIV serostatus. Feasibility will measure enrollment and retention rates. Acceptability will leverage mixed methods from 3 data sources: qualitative - to contextualize intervention engagement; paradata - to describe intervention use over time; quantitative - to assess usability, sexual health behavior and general wellness. (3) Examine preliminary intervention impact: a) primary outcomes (mutual HIV/STI awareness; creation/adherence to a tailored relationship agreement, uptake/adherence of evidence- based biomedical strategies); b) secondary outcomes (Improvements in relationship dynamics including communication). Impact will be assessed via couples’ outcomes over time, between trial arms, and for all couples. This study has high public health significance complemented with rigor and scientific premise to address a critical gap in couples-based interventions.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The National Youth Tobacco Survey showed the prevalence of e-cigarette use among high school students has skyrocketed from 12% in 2017 to 28% in 2019 and remains high at 14.1% in 2022. While different regulatory policies (such as the FDA e-cigarette flavor enforcement and Tobacco 21) are currently in place trying to alleviate this vaping epidemic among youth and young adults, there is an urgent need to effectively communicate with the public about the risks of e-cigarette use and nicotine addiction. However, how to engage the public with the e- cigarette prevention messages is particularly challenging. Social media platforms such as Twitter/X, Instagram, TikTok, and YouTube are very popular in the United States, especially among youth and young adults. Previous studies have found that social media platforms are widely used to promote e-cigarette products by vape shops and companies but are under-used by public health authorities for educating the community about the health risks of e-cigarette use. Social media marketing of e-cigarettes as healthier alternatives to conventional cigarettes resulted in the common perception among youth that vaping is a harmless activity. Social media exposure to e-cigarette-related content could affect e-cigarette use (vaping) behavior, with vaping promotion content leading to more vaping and vaping prevention content leading to reduced vaping. Therefore, social media provides a rich and natural data resource about vaping-related messages in different formats (text, image, and video). The purpose of the proposed study is to identify key features of e-cigarette-related social media (Twitter/X, Instagram, TikTok, and YouTube) posts (especially vaping prevention posts) associated with high social media user engagement (such as the number of likes) by applying advanced artificial intelligence and statistical modeling techniques, and further validate them using the combination of an online survey study and a semi-structured interview study. To achieve our goal, we will characterize key features of Twitter/X posts (tweets) related to e-cigarettes associated with high social media user engagement, such as the number of retweets and favorites, using natural language processing, machine learning, and statistical modeling techniques (Aim 1). We will characterize key features of e-cigarette-related Instagram posts associated with high social media user engagement through deep-learning algorithms and statistical models (Aim 2). We will characterize key features of e-cigarette-related TikTok and YouTube videos with high social media user engagement using artificial intelligence techniques (Aim 3). We will validate the key features selected from social media posts through a cross-sectional anonymous online survey study and a semi-structured interview study (Aim 4). Results from the proposed study will provide valuable guidance in designing effective vaping prevention messages for future public health campaigns to help with the effective communication of risks associated with e-cigarette use, which will help prevent the initiation and counter-uptake of e-cigarettes by youth and young adults.

NIH Research Projects · FY 2025 · 2024-09

Lewy-body dementia (LBD) is a neurodegenerative illness and the most common of a spectrum of Parkinsonian disorders called Parkinson’s and related disorders (PDRD). Notably, Lewy-body dementia has been specifically named by NIH as an Alzheimer’s and Related disorder (ADRD) and an area of high priority research. LBD includes Dementia with Lewy bodies, an illness characterized by early dementia, hallucinations and parkinsonism, and Parkinson’s Disease Dementia, an occurrence that affects over 75% of people with Parkinson’s and the leading cause of carepartner distress in this population. Despite this, carepartner support for LBD is not routinely addressed in current models of care, even when compared to other ADRDs. When it is addressed, the focus is on carepartner burden reduction. Support is likely to be incomplete, and possibly even harmful, when provided solely through a burden lens especially as carepartners themselves believe that there are positive aspects of caregiving and that it can be fulfilling. Providing adequate carepartner support is challenging without knowledge of carepartners’ views on caregiving and what matters to them. Stakeholder engagement research methods offer an important way to address this knowledge gap. The long-term goal is to use stakeholder engagement research methods to partner with carepartners and multidisciplinary teams and develop, test, and promote interventions and programs that promote balanced and carepartner-driven approaches to carepartner support. This proposal’s research objectives are to identify the dimensions and positive and negative aspects of LBD caregiving, adapt and co-design a peer-led intervention for this population, and conduct a pilot clinical trial. An intervention developed with LBD carepartners that goes beyond burden can improve carepartner preparedness, and wellbeing, and decrease social isolation. This is based on evidence from peer-led interventions in other diseases that have channeled the experiences and motivation of former carepartners to successfully address current carepartner concerns. This proposal has three specific aims: (1) Identify dimensions of LBD caregiving by collaborating with key stakeholders, (2) Adapt & design a peer-led pilot intervention for and with LBD carepartners, and (3) Assess feasibility and acceptability of the pilot intervention. The approach is innovative as it is the first within the field of Neurology to (a) identify what matters most to carepartners, (b) use stakeholder engagement research methods from design to delivery of an intervention, and (c) utilize a user centered design framework. The training objectives of this proposal will build on the applicant’s prior research experiences to learn new skills related to (1) Stakeholder Engagement Methods, (2) Intervention Adaptation and co-design, and (3) Design of Clinical Trials.

NSF Awards · FY 2024 · 2024-09

Plastics have been found in all aquatic realms, from groundwater to the most remote areas of the global ocean, but estimates of their abundance, depth variability, longevity, and impact on marine biogeochemical cycles are unknown. The goal of this project is to determine how the presence of microplastics in the ocean may impact the distribution of naturally-occurring radioactive isotopes. These isotopes are commonly used to track processes associated with natural particles like sediments and biological materials. Plastics have different chemical and physical properties than natural particles. These differences may affect how isotopes “stick” to particles, and change how oceanographers use the isotopes to calculate things like how fast particles sink through the ocean. The team will use a combination of laboratory experiments and field work to investigate these questions. The project will facilitate the training of graduate and undergraduate researchers from the University of Rochester and incorporate unique educational experiences for undergraduates and local high school students. One graduate student’s PhD work and two undergraduate senior theses will focus on aspects of this project. The investigators will also engage with high school students from Rochester City School District (RCSD) in two workshops focused on “the radioactivity around us” and how radioisotopes are used to answer big questions in earth sciences and beyond. The workshops will be offered through the Upward Bound program, which has a proven track record of increasing college admission rates for RCSD students. Persistent, buoyant, and metals-scavenging plastics have the potential to impact tracer distributions, especially for longer-lived isotopes, as a lateral source and/or as a standing stock at depths could obscure or contribute to natural variations. While the ultimate goal is to know what tracers stick to (i.e., to plastics or to associated biochemical materials), the most pressing question is to what degree do particle-reactive radioisotopes associate with microplastics (MPs) in the marine environment and does this behavior differ from the typical associations observed for the average ocean particle? Specifically, do MPs have comparable partition coefficients (Kds) to bulk particles for key radioisotope tracers, and how different are Kds with location or varying biogeochemical conditions? The project will address three objectives. Objective 1 is to quantify the association (Kds) of select particle-reactive radioisotopes with plastics in controlled environments through laboratory experiments. Objective 2 is to quantify the association (relative Kds) of select particle-reactive radioisotopes with plastics at a coastal and open ocean location to determine whether a gradient could exist. Finally, Objective 3 is to assess whether there is a potential for ‘inherited’ radioisotope signals to come from plastics with terrestrial origins or introductions, through collection of sediment cores from beaches and estuaries. If the proposed work shows that MPs have some potential for impacting radioisotope distributions (hypothesis 1: plastics Kds ≥ typical particle Kds) or that MPs have the greatest potential for impacting radioisotope distributions (hypothesis 2: plastics Kds ≥ typical particle Kds and observed gradients suggest inherited tracer signals could be transported in a manner unique to plastics), observational radiochemists and modelers will have a baseline to account for the ‘plastics effect’. Collectively, the field of chemical oceanography can begin to study the significance of plastics for various elemental cycles and incorporate the ‘plastics effect’ into future efforts focused on key marine tracers. Currently, this type of proposal, and marine plastics studies in general, sit on the edge of several existing programs. The proposed work can be used directly for future decision making on paired plastics-radioisotopes and general tracer studies by NSF Chemical Oceanography and other agencies. If, after the proposed work is carried out, there is little to no predicted impact of microplastics on radioisotope tracer distribution in the oceans (the ‘null’ hypothesis), the ongoing debate of the effect of plastics will be closed but radioisotopes will be established as tracers of plastics. In this case, the proposed measurements will produce upper ocean plastics fluxes and residence times. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Abstract Hip osteoarthritis (OA) affects one in four people by the age of 85, and it is linked to abnormal hip morphology including Cam-type femoroacetabular impingement (FAI). Hence, symptomatic FAI represents an ideal condition to identify key regulators in hip OA progression. To this end, we performed RNA sequencing (RNA- seq) comparing FAI and hip OA cartilage, revealing that WNT16 expression is negatively correlated with OA severity. We also showed that WNT16 is decreased during cartilage cell (i.e., chondrocyte) hypertrophy (a hallmark of OA) and that WNT16 is up-regulated in chondrocytes under mechanical loading. As Transient Receptor Potential Vanilloid 4 (TRPV4), a Ca2+-permeable ion channel, is an essential mechanosensor in chondrocytes, our results suggest a novel link between TRPV4, WNT16, and chondrocyte mechanobiology. Our preliminary data predict that WNT16 in chondrocytes is potentially regulated by TRPV4-mediated signaling pathways, and WNT16 inhibits chondrocyte hypertrophy via G protein-associated signal transduction. Thus, to elucidate the functional role of WNT16 in hip OA pathogenesis and develop novel therapies, we propose the following aims: Specific Aim 1: To determine the genetic and epigenetic mechanism(s) of mechanoinduction of WNT16 in chondrocytes. Agarose constructs encapsulating human stem cell-derived chondrocytes and hip primary chondrocytes will be subjected to loading in combination of TRPV4 activator/inhibitor, and their effects on WNT16 will be assessed. We will use novel next-generation sequencing to identify genetic and epigenetic factors that regulate WNT16 expression in chondrocytes. Specific Aim 2: To determine the effects of WNT16 gain- and loss-of-function on chondrocyte specification, hypertrophy, and hip OA development. We will investigate if cartilage-specific Wnt16 knockout mice exhibit enhanced hip OA compared to control mice. We will measure OA severity, synovitis, and bone remodeling. We will also quantify behavioral changes and pain responses, as well as determine the association of these measurements with hip OA severity. We will use human hip primary chondrocytes with WNT16 modulation to investigate its effects on hypertrophy. Specific Aim 3: To elucidate altered chondrocyte cell-cell crosstalk in hip healthy/FAI/OA cartilage and to determine if WNT16 mRNA delivery can mitigate hip OA by restoring normal WNT signaling among chondrocyte crosstalk. We will fully characterize distinct chondrocyte phenotypes in human healthy, FAI, and OA hip cartilage by integrating scRNA/Spatial-seq datasets. We will determine if WNT16 mRNA delivery using nanoparticles to hip FAI/OA cartilage explants is sufficient to mitigate hip OA progression. Impact: A mechanistic understanding of the role of WNT16 in hip cartilage homeostasis and FAI/OA will provide insights into the development of therapeutic interventions for hip OA by targeting WNT16 signaling.

NSF Awards · FY 2024 · 2024-09

Machine-learning technology enables web searching, social networks, e-commerce, and consumer products and is expected to become more and more prevalent in modern society. While incredibly effective, large neural networks are incompatible with traditional computers for which Moore’s law has hit physical limits, and memory accessing adds significant lag. Specialized dense-data-optimized processors such as GPUs and TPUs now surpass these bottlenecks. However, current data centers based on these technologies are incredibly power hungry and scaling much larger presents a major challenge for the industry. Optics, which has already demonstrated superiority for interconnection tasks, is a potentially great fit for today’s incredible computing demands due to its low-loss propagation, high bandwidth, and lack of interference between neighboring channels. While recent spatially extended optical neural network approaches have already demonstrated useful fast and efficient calculations for small neural networks, scaling size by several orders of magnitude to meet current demand appears to be an insurmountable technical challenge. Here we propose to leverage the low-loss and high-speed benefits of light to process information in time and space with massively time-multiplexed ultrashort optical pulses. In this way >billion-scale model sizes can be processed in real-time with few spatial elements, bypassing the limits of current optical computing architectures with slow reconfigurability and poor spatial scaling. Beyond technological impact, this project will train two PhD students in an area of large technological importance at the interface of machine learning, ultrafast nonlinear optics and advanced optical technologies, and the PIs will integrate this important platform into the regular curriculum as well as into the extra-curricular optics summer-school program at the University of Rochester. Technical description Optics is being recognized as a potential solution for today’s incredible artificial neural network (ANN) computing demands due to its low-loss propagation, high speeds, and lack of interference, enabling parallel, efficient and fast information processing. In the last few years, several approaches to optical ANNs have been demonstrated. ANNs require linear matrix vector multiplications as well as nonlinear thresholding of the products. Optical thresholding is achieved through modulators, lasers, detectors and several other techniques and the linear weight matrix vector calculations are processed commonly using micro-ring resonator arrays, Mach Zehnder interferometer arrays, and diffractive optics networks. These systems are challenging, however, because they are complex, highly calibrated nano-photonic devices with a limited number of input vector elements. The research proposed here leverages the high speed, high bandwidth, and low loss properties of light by multiplexing information in the time domain, in addition to the spatial domain. In this way >billion-scale model sizes can be processed in real-time with few spatial elements, bypassing the limits of current optical computing architectures with slow reconfigurability and poor spatial scaling. Through this approach, vector values coded in the amplitude of the electric field of a pulse are effectively processed with a novel matrix scaling algorithm, two in-memory all-optical accumulators, and a single nonlinear activation unit, without requiring intermediate electronics that limit the speed and efficiency of other time domain platforms. Finally, this system has unique advantages for extremely sparse matrices unavailable with prior techniques. Beyond technological impact, this project will train two PhD students in an area of large technological importance at the interface of machine learning, ultrafast nonlinear optics and advanced optical technologies, and the PIs will integrate this important platform into the regular curriculum as well as into the extra-curricular optics summer-school program at the University of Rochester. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary and Abstract This award will support Azmeer Sharipol, M.S., long-term goal of developing the expertise and skills needed to become an independent investigator exploring the role of polypharmacy and microenvironmental dysregulation in acute myeloid leukemia (AML) using an applied microphysiological systems (MPS) approach. The standard daunorubicin and cytarabine (DNR) chemotherapy for AML result in a 5-year survival rate of less than 30%. 70% of patients >60 years old succumb to the disease after 1-year of diagnosis. Polypharmacy, which is the use of ³5 drugs to treat comorbidities, is common in vulnerable patients. However, it remains unclear whether polypharmacy has an impact on AML chemotherapy. AML studies mostly focused on finding the intrinsic mutations within the hematopoietic stem cell lineage that give rise to dysfunctional AML cells. However, the role of the bone marrow microenvironment (BMME) is often overlooked. Studies using in vivo models showed that AML cells can dysregulate the BMME through cell-cell interaction and chemokine signaling. Azmeer’s sponsor, Dr Benjamin Frisch, showed that AML cells inhibit osteoblastic cell function via C-C motif chemokine ligand 3 (CCL3) in a clinically relevant murine AML model. However, it is challenging to prove the AML-BMME signaling in human cases due to the lack of reliable in vitro model of the human BMME. Azmeer Sharipol will address these gaps in research through an innovative research plan that leverages his background in applied MPS. For the F99 phase, Azmeer will develop an in vitro human BMME-chip model using Emulate Chip-S1™ microfluidics systems and fibrin-hydrogel encapsulation containing osteoblastic, endothelial, and stromal cells compartments that are important regulator of stem cell maintenance and differentiation. Using the BMME-chip, he will elucidate the role of CCL3 in the dysregulation of the human BMME and investigate the targeting of CCL3 receptors, CCR1 and CCR5, using small molecule inhibitors to rescue BMME dysregulation in AML- BMME-chip. For the K00 phase, Azmeer will explore the effects of polypharmacy from common comorbidity drugs including metformin and captopril in addition to standard chemotherapies on the BMME function using the AML-BMME-chip, and in vivo models of AML. Azmeer Sharipol has worked closely with his sponsors to develop a training plan that emphasized on building new knowledge and methodological skills to prepare him a smooth transition into an independent research career path. The training plan includes improving knowledge in cancer biology, cancer cell signaling, clinical pharmacology, and bioinformatics analysis. Azmeer and his mentors also developed a plan for identifying a postdoctoral mentor. Together, the proposed research and training plan provide optimal opportunities and structure for Azmeer to develop new skills and progress toward cancer researcher.

NIH Research Projects · FY 2025 · 2024-09

People who are deaf or hard of hearing experience many barriers when trying to enter STEM graduate programs, health science professions, and research environments. Increasing such individuals in the scientific workforce is a recognized priority for both the National Institutes of Health (NIH) and the National Cancer Institute (NCI). The dropout rate among deaf undergraduate STEM majors is alarming, with an average of 83% leaving their programs before graduation. This issue is primarily due to unwelcoming research environments, inadequate services, and mentors who are not sufficiently prepared to support these students. To address this challenge, the University of Rochester's James P. Wilmot Cancer Institute (Wilmot) has proposed the Future Deaf Scientists (FDS) program. This mentored research training initiative builds upon a successful summer internship program developed through a partnership between Wilmot and the Rochester School for the Deaf (RSD), a bilingual institution founded in 1876 that provides instruction in American Sign Language (ASL) and English. The FDS program aims to increase the participation of deaf students in cancer research and improve the mentorship environment for young deaf scientists. The program includes deaf competency training for mentors and ASL interpreter training focused on advanced STEM topics. Moreover, the FDS initiative seeks to establish a linguistically appropriate STEM and cancer research curriculum for deaf high school students, which could also be implemented nationwide. This innovative and tailored approach serves as a critical first step in strengthening the Deaf Scientist Training pipeline in Rochester, NY, while also advancing cancer research in STEM across the country. Ultimately, FDS students will acquire the skills and confidence necessary to succeed in post-secondary education and pursue careers in STEM, health professions, and cancer research.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Myocardial infarction (MI) causes localized cardiomyocyte (CM) death which predisposes the adult mammalian heart to persistent fibrosis and subsequent complications such as heart failure. Border zone (BZ) CMs are a phenotypically distinct population of cells adjacent to the ischemic region, and their response may impact the course of heart recovery. Adult BZ CMs become hypocontractile and may be susceptible to continued cell death, which can lead to scar expansion and exacerbate pathologic remodeling. In contrast, neonatal BZ CMs may activate programs promoting cell survival, dedifferentiation, and proliferation that can contribute to scarless heart repair via cardiac regeneration. Therefore, it is imperative to study how BZ CMs respond under different conditions, as this will improve our understanding of regenerative versus non-regenerative cardiac repair. Neonatal mouse CMs retain some proliferative capacity through the first week of life, making the neonatal heart an excellent model to study the differences between BZ CM phenotypes. Using RNA-Sequencing and spatial transcriptomics, we identified that small proline-rich protein 1A (Sprr1a) is transiently upregulated following cardiac insult and is predominantly expressed in BZ CMs. To investigate BZ CM function, we made a knock- in/knockout mouse by replacing the Sprr1a locus with a GFP expression cassette (Sprr1aGFP). Importantly, we verified that GFP recapitulates endogenous SPRR1A expression after cardiac insult. The aims of this proposal are to determine the role of Sprr1a during cardiac injury and characterize the BZ CM response to cardiac insult in regenerative versus non-regenerative cardiac repair. Aim 1 will investigate how Sprr1a deletion impacts neonatal heart regeneration in response to cryoinjury and/or apical resection. Aim 2 will explore how SPRR1A may regulate BZ CM survival via predicted interactions with cIAP1/2. Aim 3 will characterize the transcriptomic profile of GFP+ BZ CMs isolated from hearts injured within the proliferative window (P1) versus post-mitotic stage (P7) in control and SPRR1A KO hearts. These findings will characterize the phenotypic response of BZ CMs in regenerative versus non-regenerative cardiac repair and define the role of Sprr1a in this process. The discovery of additional markers within this sub-population will be beneficial for translational research as this may facilitate the design of targeted therapies to enhance CM cell survival or proliferation post-MI.