University Of Massachusetts Amherst

NSF Awards · FY 2024 · 2024-09

Ni-based superalloys were developed in the 1940s and have been continuously improved ever since, culminating in the current single-crystal jet turbine blades made by directional solidification. However, the cost of such turbine blades exceeds $15,000 and replacement costs when a jet engine is overhauled can be hundreds of thousands to millions of dollars. Thus, a cost-effective method of producing Ni-based superalloy turbine blades is imperative. This award supports research into methods to produce columnar-grained structures or single crystals of nickel alloys by directional recrystallization (DR), a solid-state process, of additively manufactured (AM) material, in which the complex structures are built layer-by-layer by powder fusion. The goal is to investigate if production of a single crystal Ni-based superalloy turbine blade is feasible via the integrated route of AM and DR, and to understand the physics underlying such a processing route. The technology, although focused on Ni alloys, is nonspecific and could be used for other materials, and easily scaled up. The project will train undergraduates and Ph.D. students. In addition, undergraduates from Smith College and from the University of Massachusetts will undertake an annual workshop on AM technology. To gain a fundamental understanding of DR processing of AM materials, the project will use several printing strategies to make different AM microstructures using laser powder bed fusion and laser directed energy deposition of Ni-Al alloys, and the microstructures before and after DR processing will be characterized. The project will build a new DR system specifically for this purpose. Several scientific questions will be addressed: (1) Are carbides or similar insoluble particles necessary to prevent equiaxed grain growth and thus enable columnar-grained structures to grow? (2) Are the columnar structures produced by primary recrystallization or secondary recrystallization? (3) Can this technology grow columnar grains or single crystals at high hot-zone velocities? Previous work has indicated that the upper hot zone velocity to propagate columnar grains is substantially higher than that required to nucleate them. (4) Can this technology use a spiral growth selector built into an AM sample to provide grain selection during DR to produce single crystals? (5) Can single crystals or columnar-grained structures with complex geometries, such as hollow components used for air-cooled Ni-based superalloy turbine blades, be produced by the integrated approach of AM and DR? If successful, this project can generate new understanding in the manufacturing of high-performance alloys, which will advance aerospace industries and alloy manufacturing. 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 · 2024-09

This project is a collaboration amongst the University of Florida (Gainesville), the University of Georgia (Athens), and the University of Massachusetts (Amherst). Schistosomiasis, a disease caused by parasitic worms and transmitted through contact with contaminated freshwater, poses a significant public health threat in many developing regions. Hence, designing effective intervention strategies to mitigate the disease’s impact is timely and critical. This project aims to advance our understanding of schistosomiasis transmission dynamics and control. Specifically focusing on schistosomiasis in Zanzibar and Ethiopia, this research will create and use innovative mathematical modeling tools to understand how various factors like human movement and environmental changes influence disease transmission. This will help to identify the best strategies to control and eventually eliminate schistosomiasis as a public health problem. The project is not only scientifically important but also has significant public health, educational, and societal implications. The educational and societal impacts include training a diverse group of students (including students from underrepresented groups) and fostering interdisciplinary and collaborative research skills. The project will provide novel analytic tools for efficient resource management and inform evidence-based policies for sustainable elimination of schistosomiasis, thereby significantly impacting global health. A workshop in Zanzibar will further help building workforce in quantitative public health and disseminating scientific knowledge. The proposed project seeks to develop advanced mathematical models to improve our understanding and management of schistosomiasis transmission dynamics, especially during the transition from high to low transmission phases towards elimination. Current models often fail to adequately capture low transmission environments, where random events, spatial and temporal heterogeneities, as well as environmental factors significantly impact transmission persistence. The project aims to develop a novel and robust hybrid deterministic-agent-based modeling framework integrating snail population dynamics (an aspect hither to overlooked in many schistosomiases transmission models) and environmental factors, using data for Schistosoma haematobium from Zanzibar and Schistosoma mansoni from Ethiopia. This innovative dual-phase framework will capture complexities in both high and low transmission settings, incorporating human movement, hydrological networks, and parasite gene flow. The project will assess persistence drivers under low-level transmission, identify transmission breakpoints, and optimize intervention strategies, offering new insights into transmission dynamics and control strategies that lead to impactful public health policies.  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 · 2024-09

The resilience and robustness of autonomous robotic systems in dynamic, unpredictable, and ever-changing environments are central concerns of the robotics community. To address these challenges, this research project introduces a novel "introspective counterfactual reasoning" capability to empower robots with lifelong autonomy. While counterfactual thinking—considering the implications of changes in the world that could have happened, but didn’t—is a foundational cognitive function in human beings, its application in robotics remains largely underexplored. This project aims to bridge this knowledge gap by enabling robots to answer and learn from "what if" questions regarding both their surroundings and themselves, better preparing them for unforeseen events, potential hazards, and evolving contexts. This project introduces two different yet interleaved forms of counterfactual reasoning: Contextual Physical Rehearsal and Introspection Adaptation. Contextual Physical Rehearsal allows the robot to model the physical world and forecast the outcomes of actions without actual execution. Introspection Adaptation focuses on predicting and enhancing the robot's capacity to perform tasks in unfamiliar environments and unexpected situations. The strategy involves designing these capabilities, integrating them into diverse autonomy platforms as interconnected modules, and validating their efficacy in real-world tasks. The framework will be validated in a rigorous procedure from modular simulation testing to integration and deployment on real ground vehicles under challenging conditions. The project will create new interfaces that allow developing courses on field robotics and simulation and provide immersive and engaging programming activities for K-12 students. 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 · 2024-09

Vortices are persistent circulating flow patterns that arise in diverse physical contexts, ranging from classical hydrodynamics and superfluids to condensed matter physics and nonlinear optics. They are ubiquitous physical phenomena in the world around us and can be observed at very different scales, from microscopic vortex lines in superfluid liquid helium, to dust devils and tornadoes, and even to Jupiter's Great Red Spot. Bose-Einstein condensates of ultracold atoms (BECs) provide a pristine and controllable environment where numerous aspects of the fascinating realm of nonlinear vortex dynamics can be explored not just in theory but also through direct experiments. In addition to their intrinsic fundamental interest, these systems also exhibit localized solutions with potential practical applications: for example, it has been suggested that solitary waves could be used for unprecedented, improved sensitivity in interferometric and force-sensing devices. On the other hand, vortical structures, which are the focus of this proposal, also hold promise for other intriguing applications. For instance, they can provide an instance of 'analogue gravity' as a proxy to study the behavior of spinning black holes. It has also been proposed that BEC vortices could collapse in a manner akin to supermassive black holes and that supersonic expansion in BECs can replicate properties of an expanding universe in laboratory settings. Through a bijective collaboration with experiments, this proposal aims to advance the current understanding of topological structures in BECs. Being based on universal models of modulated waves in nonlinear media, the underlying physical setting represents a fundamental playground to study topologically charged excitations that are, in turn, at the heart of an extremely wide variety of physical contexts in atomic, optical, wave physics, and beyond. The project will address the existence, stability, manipulation, and dynamics of vortex configurations in 2D and 3D settings from a novel and broad perspective. The PIs' plan is to develop effective lower dimensional, reduced evolution equations to gain novel insights on the properties of these coherent structures in the original, high-dimensional, models and to compare the theoretical results therefrom with numerical computations and circling all the way back to direct observations from atomic and polariton BEC experiments. The main goals of this proposal are multi-fold and include the following themes: the creation, removal, and interactions of vortices and soliton filaments and experimentally tailored external potentials by leveraging effective lower-dimensional dynamical models for the evolution of soliton filaments coupled with point-vortex models including the relevant case of open quantum systems in the presence of driving and damping for polariton condensates. Also, in close synergy with experimental collaborators, the study of the timely theme of synthetic magnetic monopoles and the elusive so-called Alice ring in spinor (chiefly F=2) BECs. The project aims to shed light on this highly complex, topological pattern forming system and, in particular, on the recent collaborator experiments where they observed that monopole instabilities give rise to topological patterns reminiscent of Alice rings. 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 · 2024-09

Cardiac diseases are the leading cause of human morbidity and mortality. Drugs also need to be verified to not cause side effect in heart before they can be used clinically. It is inconvenient to study cardiac diseases or test drug effects by using living animals for multiple reasons, including that an animal heart is not that close to a human heart. A convenient strategy is to use heart-mimic tissue outside of the living body made from human-derived cells, which bypasses the use of living life but retains human information for relevant studies. Since the heart beating is coordinated by an electrical signal, it is often desirable to monitor both the mechanical beating and electrical signal together for better assessment of the tissue state involved in various studies. However, current sensing technologies are limited in achieving that—particularly deep inside the tissue—without causing perturbation to the tissue function or health. This project aims to tackle this challenge by developing cell-sized electronic sensors that can simultaneously detect the electrical and mechanical activities in cardiac tissue, incorporating these sensors on small ribbon threads having the lateral width still smaller than a cell, and embedding these threaded sensors into the cardiac tissue for real-time monitoring. For the small form factors in both the sensors and ribbon threads, the system is expected to introduce minimal invasiveness or perturbation to tissue function. Therefore, it will not only acquire enriched signals from both mechanical and electrical activities but also long-term stable monitoring, fundamentally improving the assessment of tissue state involved in cardiac disease studies and drug tests. Eventually, the research contributes to the improvement of cardiac disease remedy and alleviation of healthcare burden. To meet the overall goal, this project will accomplish the following key objectives: 1) A scalable assembly strategy will be developed to fabricate an array of three-dimensional sensor structures using planar semiconducting graphene material. The sensor structure is designed to be able to detect both electrical and mechanical stimuli. 2) These sensor devices will be evaluated for their multifunctional sensing capabilities by culturing planar cardiac tissue on them. 3) A scalable integration method will be developed to integrate these three-dimensional sensors on an ultra-flexible and porous mesh scaffold consisting of individual thin ribbons. 4) The sensor-integrated mesh system will be embedded into three-dimensional cardiac organoids for functional validation and tissue-state evaluation. Success in the research can lead to transformative biomedical devices and cardiac tissue models that have much improved feedback quantifications for various studies. It can also have the long-term potential to translate to implantable biomedical devices for heart monitoring and early disease prediction. The research will also be integrated into education for broadening the participation in science and engineering. 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 · 2024-09

This award funds the research activities of Professors John Donoghue, Ben Heidenreich, and Lorenzo Sorbo at the University of Massachusetts, Amherst. One of the most pressing questions in theoretical physics concerns the search for a theory (or theories) that can unite quantum mechanics and gravity, as well as strategies to probe its validity. Professor Donoghue's and Professor Heidenreich’s research use different techniques to explore the theoretical aspects of quantum gravity: Professor Donoghue, by studying its implications at relatively low energies, and Professor Heidenreich, by determining general properties that any theory of quantum gravity should satisfy. Professor Sorbo studies how such a theory (as well as other theories) might have left observable effects during the early evolution of the Universe. This project will also have important broader impacts. Graduate students will be involved in this research, so that junior physicists can be trained to do research in this field. Profs. Donoghue, Heidenreich and Sorbo will also create online pedagogical material, organize workshops and provide outreach to grade school audiences. More technically, Professor Donoghue will investigate novel aspects of the effective field theory treatment of quantum general relativity. Professor Heidenreich will investigate quantum gravity through the swampland program, with a focus on stringent tests of foundational ideas such as the absence of global symmetries and constraints on the spectrum of particles and branes, and on the properties of moduli space. Professor Sorbo will explore various aspects of inflationary phenomenology, with a focus on processes of particle creation during inflation, especially in the regime where the created particles strongly affect the background. 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 · 2024-09

Computer science education is increasingly critical for preparing well-trained professionals for the national economy and building a competitive workforce of the future. The emergence of generative AI provides an opportunity to improve computer science education by adapting the learning process to the needs and knowledge of individual learners. University of Pittsburgh, Carnegie-Mellon University, University of Massachusetts, and North Carolina State University will develop and evaluate a comprehensive personalized programming practice environment (C-3PE) that utilizes artificial intelligence (AI ) to enhance learning experiences. This project capitalizes on the power of generative AI and progress in learning science research to provide personalized learning experiences for computer science students. C-3PE recommends the most suitable learning activities for each student according to their current knowledge level and offers personalized feedback to support their progress. By conducting long-term classroom studies, the project team will assess the impact of AI-based personalization approaches and identify the most effective types of learning activities and feedback messages for students with different competency levels. Leveraging advances in AI-driven learning technologies and theoretical frameworks in learning sciences, C-3PE will deliver engaging computer science learning experiences. It will provide personalized practice support and detailed feedback for individual learners based on their practice history and current knowledge state. C-3PE will dynamically model the state of learner knowledge using context-aware deep-learning knowledge tracing models. Furthermore, the project team will develop a nested personalization approach with an outer loop and an inner loop. For the outer loop, the project will develop new, large language model (LLM)-powered adaptive testing algorithms that select the most informative next practice question/worked example for each student. For the inner loop, they will use preference optimization to align LLM-driven feedback generation with student learning outcomes. A sequence of experiments will lead to a better understanding of the kinds of practice opportunities (i.e., worked examples vs problems) and types of feedback messages that are most effective to each student. Utilizing an iterative design process to integrate insights from studies into the learning environment, the project will evaluate C-3PE in various introductory programming classrooms across diverse institutions. The project will enhance education through personalized recommendations and feedback, disseminating findings and tools through academic conferences and platforms, and sharing C-3PE via a GitHub repository for computer science instructors. This project is funded by the Research on Innovative Technologies for Enhanced Learning (RITEL) program that supports early-stage exploratory research in emerging technologies for teaching and learning. 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 · 2024-09

Catalysis is a key technology that enables the production of fuels and chemicals from carbon-containing resources such as petroleum, biomass, or waste polymers. In an ideal scenario, a catalyst has an infinite lifetime: it assists a chemical transformation while remaining unaltered itself. However, the real-world conditions in industrial processes lead to catalyst deactivation, often by deposits on the surface of the catalyst. As a result, the processes become less efficient, and catalysts need to be regenerated or replaced, all of which adds to energy consumption, waste generation, and cost. Researchers at the University of Massachusetts Amherst (US), the L.V. Pisarzhevsky Institute of Physical Chemistry of the National Academy of Sciences of Ukraine in Kyiv (Ukraine), and the National Institute of Chemical Physics and Biophysics in Tallinn (Estonia) combine their expertise and devise new approaches to catalyst regeneration that will prolong the service life of catalysts. The objective of the project is to test the concept of a “companion catalyst” that will be integrated into a reactor and make the regeneration process itself catalytic. It is hypothesized that catalytic regeneration is milder and more efficient than non-catalytic regeneration. Three target reactions with a variety of reactants (hydrocarbon or oxygenate) and a range of operating temperatures will be explored to generate deposits of different composition. Companion catalysts will be designed to oxidize or hydrogenate the deposits to volatile compounds. To avoid interference of a companion catalyst with the target catalyst, it will have low intrinsic reactivity, be passivated, or be inaccessible to the reactants. Experiments will be conducted to assess the role of transport of the activated regenerant across the surface or grains. The group in Kyiv will synthesize and characterize catalysts; the group in Tallinn will apply NMR to characterize catalysts and carbon-containing deposits; and the group in Amherst will deactivate catalysts and monitor their regeneration by operando spectroscopy and thermal analysis. The concept of a companion catalyst, if proven to be viable, has potential for the many processes in which deactivation is caused by deposits. The project will provide basic and advanced training in catalysis and kinetics, cutting-edge methods of materials synthesis and characterization, and in situ and operando techniques for all participants, including students in all three locations. Efforts to enhance the participation of underrepresented groups will be made when recruiting students and through contributions to the UMass College of Engineering RISE program. The results of this project will be widely disseminated, within the scientific community through publication in peer-reviewed international journals or presentation at conferences, and to a broader audience via news items on institutional webpages. This IMPRESS-U project is jointly funded by NSF, Estonian Research Council (ETAG), US National Academy of Sciences, and Office of Naval Research Global (DoD). The research will be performed in a multilateral international partnership that unites University of Massachusetts Amherst (US), National Institute of Chemical Physics and Biophysics, Tallinn (Estonia), and Institute of Physical Chemistry, National Academy of Sciences of Ukraine, Kyiv (Ukraine). US portion of the collaborative effort will be co-funded by NSF OISE/OD and ENG/CBET programs. 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 · 2024-09

Quantum information processing is at the threshold of having a significant impact on technology and society in the form of providing unbreakable security, ultra-high-precision distributed sensing, and potentially exponential speed up on many computing applications. Most of these applications rely on what is termed shared entanglement between pairs and groups of users that gives rise to Albert Einstein referred to as “spooky action at a distance”. A critical component needed to pass this threshold is a distributed infrastructure in the form of a world-wide quantum network to distribute entanglement to users. Our research project is focused on enabling such an infrastructure. It focuses on challenges that arise due to the need to share a quantum network among different users and the need to protect the network against loss and noise that is present in the environment. Its goal is to develop algorithms and protocols that allow efficient and fair sharing of the network among users, and that protects against noise inherent in the network. The goal of the project is a fully informed study of the design and operation of quantum networks combining physical-layer device noise models with the ground-up development of higher-layer network protocols. Our project will: (i) develop new path selection and link-level entanglement allocation algorithms for flows; (ii) develop resource allocation protocols optimized for device quality metrics, such as quantum memory coherence times; and (iii)develop strategies for masking the effects of and reducing the amount of classical communication required by quantum networking protocols. Another goal is to inspire undergraduate and graduate students from underrepresented groups to study and perform research in quantum information topics. 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 Despite potential lifelong consequences of gut microbiome dysbiosis, little is known about environmental factors that influence its diversity and composition, including windows of susceptibility to exposure. The gut microbiome performs essential functions for human health, and is related to neurobehavioral development via the gut-brain axis. While a few studies have examined the infant/adult microbiome in the context environmental epidemiology, the adolescent microbiome has not received attention, even though it occurs in a period of rapid development when the hormonal milieu is changing, and internalizing behaviors often emerge. The proposed project aims to address these gaps by examining the relations between exposure to triclosan—an antimicrobial and endocrine disrupting compound—pubertal hormones, the adolescent microbiome, and neurobehavior. This work will leverage the Health Outcomes and Measures of the Environment Study, a longitudinal birth cohort with rich data collection including quantification of urinary triclosan at 10 visits from early gestation through 12Y, pubertal hormones, the serum metabolome, and behavior. Crucial to this project, participants provided stools at 12Y. During the K99 phase, fecal DNA will be sequenced to profile microbial communities, which will be used to identify windows of susceptibility to triclosan (Aim 1). Dr. Laue will assess the role of hormones in shaping the microbiome, including whether they mediate or modify the triclosan-microbiome association (Aim 2), and examine the relationship between the adolescent microbiome and behavior (Aim 3a). During the R00 phase, microbiome and behavioral assessment at 18Y to inform our understanding of the longitudinal association between the microbiome and behavior (Aim 3b). Dr. Laue will characterize the role of the serum metabolome in the microbiome-behavior association (Aim 4) and will determine whether bacterial features mediate or modify the association between triclosan and adolescent behavior (Exploratory Aim 5). To complete this research, Dr. Laue will complement her expertise in environmental epidemiology and the infant microbiome with extensive training under the guidance of her mentorship team (Dr. Margaret Karagas— primary mentor, Dr. Joseph Braun—co-mentor, Dr. Juliette Madan—advisor, Dr. Abby Fleisch—advisor, Dr. Amy Willis—advisor). Dr. Laue will learn from coursework, workshops, and individualized trainings in 1) processing microbiome data and microbiome measurement error, 2) multiple informant modeling and other methods for identifying windows of susceptibility, 3) causal mediation, 4) pediatric endocrinology, and 5) neurobehavior. This award will prepare Dr. Laue to be an independent researcher specializing in environmental epidemiology and the adolescent microbiome. Dr. Laue’s research will fill a critical gap in the environmental epidemiological literature, namely what role the adolescent microbiome and metabolome play in the relationship between a ubiquitous environmental toxicant (triclosan) and neurobehavior.

NSF Awards · FY 2024 · 2024-08

The propulsion of floating objects via self-generated surface tension nonuniformities, also known as Marangoni surfing, represents a fascinating phenomenon observed in the world of living organisms while also bearing promising potential for robotic applications. For example, in nature, this mode of locomotion is employed by water-walking insects for speedy movement in emergency situations and by certain bacterial swarms for rapid interfacial migration toward nutrient-rich regions for further colonization. In recent years, Marangoni surfers of various sizes have been engineered to perform a wide array of tasks, including environmental sensing and monitoring, microfluidic manipulation, and interfacial self-assembly. The goal of this project is to investigate the motion of Marangoni surfers at spherical interfaces, which are difficult to generate on Earth but achievable in zero gravity aboard the International Space Station (ISS). The propulsion of these interfacial surfers will be studied, with a specific focus on the importance of both the global interfacial curvature of the spherical water droplet and the local interface curvature around the surfers. Additionally, this project will have broader societal impacts through its integrated educational initiatives, which include outreach to underrepresented middle and high school students, research mentorship of community college and graduate students, and curriculum development. The principal objective of this project is to investigate the individual and collective hydrodynamics of Marangoni surfers that self-propel on spherical interfaces. This research aims to generate new knowledge by establishing a computational-experimental framework that includes both ISS- and ground-based measurements. The framework is designed to capture the complex interactions between the motion of active particles, the transport of released species, and the effects of interface curvature and confinement. Notably, performing experiments on a levitating spherical drop in microgravity allows us to probe the importance of interface curvature on particle motion and assembly while simultaneously eliminating the local gravitationally-induced interface curvature effects from around the active particle that have been shown to play an oversized role in inter-particle interactions. The insights gained from this project are expected to define the foundational principles for designing self-propelled surfers optimized for curved interfaces, potentially leading to transformative advancements in robotics and microfluidics. Also, the results of this research will enhance our understanding of self-assembly processes, facilitating the rapid production of small-scale structured materials. Moreover, this study will shed light on the role of Marangoni stresses in the colonization of antibiotic-resistant bacteria at fluidic interfaces, offering new strategies for tackling infectious diseases by elucidating bacterial colonization and survival mechanisms in adverse conditions. 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 · 2024-08

Humans use language to talk about the causal relations between situations and events in the world. In English, periphrastic causative expressions such as, “made,” as in “The girl made the boy go to the store” are examples of such a relationship. Humans also use language to talk about possible things and their possible relations that don’t exist in the here and now and that don’t correspond to reality. This kind of language is modal language, and examples in English are expressions such as, “should, can, might, have to,” e.g., “The girl has to go to the store.” Although seemingly unrelated, a longstanding debate in the fields of formal semantics, cognitive science, and philosophy is whether causal expressions as in the first example are best understood as involving modality or not. This doctoral dissertation project is an experimental investigation into the relationship between modal and causative expressions in natural language by exploring their processing similarities and differences using a classic tool in cognitive psychology known as the priming effect, which is used to investigate structures with shared features. This dissertation project makes novel methodological achievements by testing whether two semantically similar linguistic expressions can prime the production of each other, irrespective of their syntactic dissimilarity. If a priming effect occurs, it provides evidence that the two expressions share abstract semantic representations. This project also contributes to the societal achievement of underrepresented groups in the empirical sciences as it is spearheaded by the Co-PI, who is a member of one such underrepresented group. Using behavioral methods, this dissertation project answers the following questions with three case studies each of which focuses on a different kind of modal expression and its relation to causative expressions: Do causatives and modal expressions share components of their semantics? Can priming be used to provide evidence of this shared meaning by targeting their abstract semantic representations? To answer these questions the project assumes that the relationship between causatives and modals is a close one and that if two linguistic expressions share abstract semantic representations, then they will be processed similarly. This dissertation project extends our understanding of priming’s potential as a methodology by using it to target the semantics of modal language. The results of the project’s experiments will support novel theoretical claims about the relationship between causatives and modals in language, and they will support novel methodological claims about the role of meaning in sentence production with evidence that semantic priming effects can occur between syntactically dissimilar expressions. With this in mind, an overarching goal of this doctoral dissertation project is to show how particular apt psychological methodology is for answering semantic research questions. 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 · 2024-08

Galaxies transform gas into stars in a process known as star formation. Stars are most often born in clusters. Stellar Clusters can contain thousands of stars and are the main product of star formation in galaxies. The process of forming stars can last for millions of years. The investigators will observe a large number Stellar Clusters in nearby galaxies, with the goal of accurately estimating the time it takes for these Clusters to form. By comparing the environments of star formation with the estimated times of formation, the team will better explain the key physical mechanisms of star formation. To achieve this goal, the team will analyze data of nearby galaxies from the Atacama Large Millimeter Array and from the James Webb Space Telescope. The team will also integrate research experiences for teachers from local schools into the project. The teachers will be guided in creating science educational modules, which they will bring back to their classrooms. The aim is to inspire students from minority-dominated school districts into pursuing STEM careers. Molecular gas maps from ALMA and multi-wavelength images from JWST will yield thousands of gas clouds and dusty young star clusters, with their physical parameters, for a sample of 13 galaxies within the local 12 Mpc. A new Artificial Intelligence framework, “AI with Humans in the Loop”, will be employed to search for and label the young clusters, decreasing the effort for these tasks by 50-fold, thus providing a game-changing capability. The large collections of clouds and star clusters will be used to measure the timescales for clearing the natal gas and establish the nature of the feedback mechanism mostly responsible for the clearing. The range of physical parameters probed will enable the team to determine whether the timescales, and their physical origin, depend on cluster mass and/or gas pressure. The results from this project will inform models and simulations of galaxy evolution, of the interplay between galaxies and their surrounding medium, and of the conditions that enable galaxies to leak ionizing photons into the interstellar and intergalactic media. 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 · 2024-08

PROJECT SUMMARY Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis (TB) is one of the leading causes of death globally by a single infectious agent. There continues to be an urgent and unmet need for new drugs, diagnostics, vaccines, and host-directed therapies for TB. Two critical events that occur early after Mtb aerosol transmission are the confinement of the initial inoculum into alveolar macrophages (AM), the first cells infected in the lung, and the slow establishment of T cell priming and the adaptive immune response. These two features highlight the importance of early recognition by the host in affecting the course of TB disease and the significant role of lung-resident AM in initiating the host immune response. As innate airway sentinels, AM must recognize Mtb bacilli and respond quickly in order to recruit other innate cells to the site of infection, including cells that will transport bacteria to the draining lymph node for T cell priming. We have previously shown that upon infection with Mtb in vivo, AM mount an Nrf2-dependent cell-protective, rather than pro-inflammatory, response that impedes an effective host response and contributes to early Mtb replication. However, the AM response to Mtb also has plasticity. We observed that mycobacterial exposure, either through BCG vaccination or a contained Mtb infection, leads to AM cell-intrinsic and durable remodeling, including up-regulation of Interferon Response Genes and a robust pro-inflammatory response to Mtb, that is associated with an accelerated host response and enhanced bacterial control after Mtb challenge. The objective of this proposal is to evaluate mechanisms that restrain or enhance AM responses to Mtb to better understand the regulation of the early events during infection. In Aim 1, we will categorize AM sensing abilities and defects using both ex vivo and in vivo delivery of Mtb- related Pathogen Associated Molecular Patterns (PAMPs), and screen for novel negative regulators of AM innate sensing using a CRISPR-Cas9 knockout library. In Aim 2, we will determine how Type I and II Interferons regulate AM innate responses using in vitro models and in vivo cell transfer approaches. In Aim 3, we will evaluate how alterations in AM sensing by Type I and II Interferons impact downstream events in Mtb infection by measuring changes to innate cell recruitment, transfer of bacteria to the draining lymph node, T cell priming, and AM antigen presentation in murine aerosol Mtb infection and a macrophage-T cell co-culture system. The studies are motivated by the hypothesis that the hypo-inflammatory response of AM during Mtb infection is a result of the reliance on AM as the initial Mtb sentinel, a function for which they are impaired, and the absence of early systemic signals such as Type I and II Interferons, for which AM are highly sensitive. A better understanding of the regulation of AM during Mtb infection will inform development of new vaccines and host-directed therapies.

NSF Awards · FY 2024 · 2024-08

Monitoring the health of living plants holds critical significance across various domains, such as precision agriculture, horticulture, and environmental conservation. Effective plant monitoring aids decision-making in agriculture related to irrigation, fertilization, pest control, and harvesting. In urban settings like parks and gardens, it improves residents’ quality of life as healthy plants improve air quality, provide shade, and contribute to aesthetics and well-being. In forestry, it allows early detection of tree stress or disease, helping prevent large-scale die-offs and promoting forest health. However, existing solutions are bulky and high maintenance and often fail to capture essential health signals like nutrient and water levels. The project’s novelties are the development of zero-maintenance, intelligent, and robust computer systems that use biocompatible sensor arrays implanted in the plant’s xylem to continuously monitor and wirelessly report water and nutrient uptake in real-time, enhancing water management and irrigation practices based on plant needs and environmental conditions. The project's broader significance and importance are demonstrated through its commitment to publicly sharing research materials online via open-source hardware and software libraries, tutorials, talks, publications, and datasets, along with the integration of sustainable computing into curriculum development, mentoring for graduate students, research experiences for undergraduates, and a summer event focused on a wind-based, battery-free coding competition. This project seeks to develop a swarm of ultra-long-lasting and zero-maintenance intelligent devices to monitor the full life cycle of a plant and provide insights into critical biological aspects such as timing and coordination of nutrient uptake and metabolism. The developed system provides real-time, highly synchronized data from which robust calibration learning models can be developed to predict water and nutrient levels to guide the water’s application, fertilizers, and chemicals. This project creates a biocompatible, ion-sensitive sensor array and installation method, develops energy-harvesting techniques for remote data transmission, and builds AI-powered calibration models to enhance sensor accuracy. The project involves designing, implementing, and testing these innovations through both in-lab and in-the-field experiments to improve plant health monitoring and inform practical applications in agriculture and environmental management. 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 · 2024-08

Understanding how the ocean and climate influence each other is important for understanding weather and climate change. Measurements of ocean and air temperature have shown that there are regional climate patterns around the North Atlantic and the Arctic. An important pattern is called Atlantic Multidecadal Variability (AMV), which refers to up-and-down periods of warming and cooling in the North Atlantic Ocean lasting decades. AMV influences regional ocean temperature and marine ecosystems, as well as air temperature and precipitation across the Atlantic Arctic and nearby land areas including eastern North America. Natural patterns of warming and cooling are important because they affect regional weather, and they can strengthen or weaken human-made climate change from greenhouse gases. The general goal of this research is to identify and understand how the ocean and climate interact, through studying regional patterns of climate and how they may change through many centuries. To do this, we will use many different sources of information, including (1) temperature measurements that go back about a century, (2) historical observations that go back a century or two, and (3) longer-term climate records from tree growth rings, mud sediments from lakes and the ocean floor, remains from sea creatures, as well as glacial ice from Greenland, Canada and Svalbard in the high Arctic. We can combine these very different types of information to reconstruct patterns of regional climate through past several centuries or longer. We can then use mathematics to detect any repeating patterns and changes in the behavior of the ocean and climate over the years. One research focus is to identify patterns that last about 20 to 30 years and others that last much longer, about 50 to 90 years. Another focus is to investigate how combining data from different sources, such as precipitation records from Svalbard and ice from Greenland, along with tree rings from Northern Scandinavia, can help us reconstruct changes in extreme weather patterns in the Atlantic Arctic region. We want to figure out how these patterns have changed over the past few hundred years, a time period with both natural and human-made climate changes. This project is not just about science research to learn new things; it is also about teaching others. University students will be involved in this project, receiving training and experience in doing science, and learning about using mathematics to study the climate. Further, we will involve the public through popular science activities. Understanding how the ocean and atmosphere influence each other is crucial for understanding climate change. Natural modes of variability and teleconnections are regional patterns of climate variations, which are important to understand as they can amplify or dampen anthropogenic climate change. An important mode is Atlantic Multidecadal Variability (AMV), which refers to alternating periods of warming and cooling in the North Atlantic Ocean lasting decades. AMV influences sea ice, ocean temperature and marine ecosystems, as well as air temperature and precipitation across the Atlantic Arctic and adjacent land areas including eastern North America. The overarching goal of this empirical research is to quantitatively constrain and understand modes of variability in the climate system in the Atlantic Arctic and Subarctic, in a long-term paleo perspective. This project will study these patterns by using various complementary sources of data, including: (1) meteorological and oceanographic measurements, (2) historical observations, and (3) climate proxy data from tree rings, sediments from lakes and the ocean floor, remains of sea organisms, as well as glacial ice from Greenland, Canada and Svalbard in the high Arctic. By integrating and statistically analyzing data from these different types of natural archives, we aim to reconstruct patterns in regional climate variability over the past several centuries. One key focus is to test the general hypothesis that robust and persistent signals of interdecadal (approximately 20 to 30 years) and multidecadal (approximately 50 to 90 years) variability exist, and can be extracted using advanced statistical techniques applied to a spatial network of data records. Specific hypotheses are: (1) an interdecadal signal will be found primarily in records from the northwestern North Atlantic / Nordic Seas, and may arise from subsurface/surface ocean variability associated with the atmospheric circulation; and (2) a multidecadal signal will be found in marine and terrestrial records across the subarctic–arctic Atlantic, possibly linked to ocean variability such as the AMV and exchange processes between the Atlantic and Arctic. Another key focus is to investigate how combining data from different sources such as precipitation records from Svalbard and ice proxies from Greenland, along with tree rings from Northern Scandinavia, can help us understand changes in extreme weather patterns in the Atlantic Arctic region. Specific hypotheses are: (1) combining these proxies can be used to reconstruct shifts in so-called Scandinavian Blocking teleconnection pattern over the last several centuries; and (2) important shifts in this mode occurred during major climate transitions in the past. Beyond scientific advancements, this work will support a graduate student who will receive training and participate in the research, and also aims to educate students about climate science and statistics, as well as including popular science outreach. 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 · 2024-08

Cellular processes are governed by highly organized networks including a large number of protein–protein interactions (PPIs). These diverse PPIs exist throughout the life span of cells, including their growth, survival, and differentiation. However, the cellular functions for the majority of these interactions remain elusive and barely understood. In particular, cell membrane PPI networks are crucial for molecular recognition and signal transduction, which determine the efficiency of cellular communication with the environment. For example, at least 58 receptor tyrosine kinases and ~800 transmembrane G protein-coupled receptors have been identified in the human genome as essential modulators of cellular communications. The membrane dimerization of these protein receptors likely play important roles in regulating cellular ligand binding, receptor maturation and internalization, and are coupled with various downstream signaling outcomes. While numerous ligands have been identified to selectively recognize cellular proteins, targeted modulators for a given interaction between two specific proteins are still rare. Most PPIs remain unstudied as the the current ability to regulate selective PPIs of interest remains limited. This has greatly hindered the study of celluar networks that govern critical aspects of cellular properties and functions in both physiology and disease processes. The Broader Impacts of this project include its intrinsic merit as the development of tools to measure and control a wide range of cell membrane protein interactions will be useful to a breadth of studies in many labs. Additional activities involve middle school students, along with the interdisciplinary training of undergraduate and graduate students and a post-doctoral fellow. The goal of this project is to develop a general approach to rapidly modulate different target PPIs on living cell membranes with high specificity, controllability, and precision. Membrane PPIs play critical roles in cell signaling networks and are essential regulators of cell functions. However, it remains a major challenge to control specific interactions between target proteins, especially in situ, in real time, and in living systems. In this project, a DNA-based toolbox is proposed to fill this gap, counting on the fact that a large number of antibodies and other ligands have been identified to target specific cell membrane proteins, which can be potentially used for guided labeling of these proteins with DNA barcodes of designed sequences. By further linking individual DNA barcodes together via programmable DNA hybridizations, targeted stabilization of specific cell membrane PPIs can be achieved in a modular and precise manner. Specifically, this project will first establish a modular antibody- and aptamer-directed proximity labeling approach for targeted DNA barcoding of cell membrane proteins, especially the human receptor tyrosine kinases. A kinetic model for understanding and prediction of the correlations between DNA design and their membrane hybridization affinities and kinetics will also be built. The precise modulation of specific PPI pairs will then be accomplished on living cell membranes to evaluate their correlation with the selection of signaling pathways and modulation of cellular ligand binding, receptor maturation, and proliferation. These efforts of developing innovative DNA-based PPI modulation tools will also be integrated with scientific education and outreach. 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 2026 · 2024-08

PROJECT SUMMARY With aging of the U.S. population, the burden of osteoporotic fractures will increase well beyond the current estimate of 2 million per year and $17 billion cost. The 10-year absolute risk of fracture for those aged 75-84 is 24% in women and 14% in men. PFAS are chemicals that are stable in the environment and can bioaccumulate in human tissue. Biomonitoring studies document PFAS exposure in >98% of the U.S. population, with up to 200 million Americans exposed to PFAS through their drinking water. PFAS have been isolated in human bone and may be linked to osteoporosis and increased risk of fracture; these concerning findings need to be verified in additional cohorts. Rigorous epidemiologic studies are critically needed to understand the impact of PFAS on bone health, especially those that include racially diverse populations. Our overarching hypothesis is that PFAS concentrations are associated with increased bone loss and fracture risk. We will leverage existing samples and data from the two largest prospective US osteoporosis cohort studies to perform an in-depth study of serum PFAS, bone loss, and fractures that will include long-term follow-up of up to 20 years using: 1) The Osteoporotic Fractures in Men (MrOS) Study and 2) the Study of Osteoporotic Fractures (SOF). Additionally, we will confirm findings in the Health Aging and Body Composition Study (HABC), a racially diverse cohort of older adults. Aim 1: Using efficient case-cohort study designs, investigate the prospective association between serum PFAS and incident fractures in 1321 MrOS men and 1578 SOF women who will be sex matched with 1500 randomly selected persons from each respective cohort. PFAS will be analyzed in serum. We will confirm findings in a third case-cohort selected from the racially diverse HABC study (479 incident fractures and a sex- and race- matched cohort of 480 randomly selected participants). Aim 2: Evaluate the prospective association between serum PFAS and rate of loss of total hip bone mineral density (BMD) separately in men and women from the three subcohorts. Aim 3: Utilize markers of bone metabolism and structure to provide novel insights into the cellular and structural mechanisms by which PFAS may adversely affect bone. #3a: Evaluate the association between serum PFAS and markers of bone formation (PINP) and bone resorption (CTX) separately in men and women from the cohorts. #3b: In a substudy using data already available in MrOS, evaluate the association between serum PFAS and bone structure (HR-pQCT). #3c: Also, in an exploratory sub-Aim, apply mediation analyses using a counterfactual framework-based approach to estimate the extent to which PFAS’s influence on bone loss might be mediated via biomarkers of bone metabolism (serum PINP, CTX). Aim 4: Leverage rich data on urine Cd exposure in this study population to investigate mixtures of PFAS and Cd in the preceding analyses. We have an excellent opportunity to capitalize on pre-existing data and biospecimens to conduct a rigorous evaluation of the associations between PFAS and fracture risk, bone mineral density, and bone turnover in a diverse study population.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Bone metastasis is a major cause of morbidity and mortality in cancer survivors. It is closely linked to advanced skeletal aging, which is driven by the accumulation of aged (senescent) cells that secrete proinflammatory molecules. Pharmacologically delaying bone aging remains the most effective preventive strategy against bone metastasis. Osteoporosis drugs effectively impede bone aging and metastasis, but their benefits are transient. Senolytic drugs are a new class of drugs that have shown compelling preclinical evidence in delaying skeletal aging. However, their clinical adoption has been slow due to the heterogeneous cellular senescence and tissue- specific efficacy. This proposal aims to develop and validate demineralized bone paper (DBP)-based human bone metabolic and senolytic assays that support bone-targeting drug discovery and treatment regimens. DBP is an osteoid-inspired thin slice of demineralized compact bone matrix that preserves the intrinsic collagen structure of bone while remaining accessible for microscopic imaging. DBP can be produced in large quantities and attach stably to tissue culture plastic. This feature effectively enables DBP to receive mechanical stress transmitted via vibration. Attaching DBP in a standard 96-well plate provides a unique opportunity to develop standardized, functional, and analytical human bone models and phenotypic assays. In Aim 1, we will develop humanized bone metabolic assays. We will humanize DBP-based bone models with human bone marrow-derived mesenchymal stem cells and human CD14+ monocytes, mimicking bone remodeling cycles. Next, we will create anabolic and catabolic assays using the models and validate with known agents. Finally, we will test whether the models can recapitulate osteoporosis treatment outcomes using Denosumab and Zoledronate. In Aim 2, we will develop humanized bone senolytic assays. We will first introduce pre-senescent osteoblasts and co-culture with human CD14+ monocytes to create an aged bone model. Next, we will validate that senescent models increase osteoclast differentiation and mineral resorption. We will then test a model senolytic drug therapy (Dasatinib and Quercetin) to mitigate negative impacts. Finally, we will investigate whether vibrational mechanoculture affects senolytic drug responses. The proposed DBP-based models will provide predictive bone assays for drug screening, which could significantly impact the field by accelerating the identification of new anti-bone-aging drugs and improved treatment strategies. Overall, this proposal is a significant contribution to the field of bone research and has the potential to make a major impact on the lives of cancer survivors.

NSF Awards · FY 2024 · 2024-08

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Igor Kaltashov and his group at the University of Massachusetts-Amherst are developing novel approaches for studying water-soluble metal oxide nanostructures (frequently referred to as polyoxometalates, or POMs). POMs are viewed as the missing link between the single-molecule and the nanoparticular (or indeed the bulk material) scales. Metal oxide nanoparticles have many important uses in the biomedical field, catalysis and energy storage. One factor that remains a major impediment vis-à-vis wider utilization of these entities in modern technology is the lack of robust and versatile analytical tools that can be used to characterize their structure and behavior at the atomic level. This gap proved difficult to address due to the dramatic increase in size and complexity upon transitioning from the single-molecule scale to the nano-objects. Professor Kaltashov and his team target metal oxide molecular entities that are sufficiently large to resemble nanoparticles and share many of their traits, and at the same time are sufficiently small to be chemically defined. The structure and stability of these objects are probed with a new technique that uses stable isotope exchange and state-of-the-art spectroscopic tools. The project also provides opportunities for undergraduate students to (i) be involved in research focusing on the role of metal oxide-based materials in fighting the H. pylori infection, and (ii) increase the awareness of this frequently asymptomatic disease within the communities that are particularly hard-hit by it and its consequences. The new experimental tool will utilize stable isotope exchange in solution followed by mass spectrometric (MS) detection to probe the structure and dynamic behavior of both chemically defined metal oxide particles (such as POMs) and the macroscopic objects (such as metal oxide surfaces). At the initial stage, oxygen exchange (18O/16O) in solution will be used to detect and characterize transient dynamic events affecting decavanadate, a paradigmatic member of the POM family. This will be followed by developing SIX(n) - Simultaneous Isotope eXchange in solution (e.g., 18O/16O, 17O/16O and 15N/14N) with high-resolution MS detection - to study transient dynamic events affecting the structure of POM-based nanocages and elucidate their role in the cargo capture/release processes. Further modification of this experimental strategy shall expand the scope of inquiry to include dynamic processes at the surface of metal oxide materials. Successful development of these novel experimental tools will undoubtedly catalyze progress in many branches of material science where the metal oxides behavior is one of the major contributors to the materials quality. 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 · 2024-07

PROJECT SUMMARY Background: Gap closure is a critical step in wound healing and the maintenance of tissue homeostasis during embryogenesis. Current studies of gap closure focus on epithelial cells with strong adhesion strength and junctional actin cytoskeletons and have identified lamellipodia-mediated cell crawling and “purse-string”-like contractile actin rings as two major mechanisms for gap closure. At the molecular level, ERK and p53 activations are known to regulate the migration and proliferation of tissues. Recent new findings, including our own data, suggest that tissue fluidity, the tissue mechanical property that reflects the frequency of cell intercalations, plays a major role in gap closure. It is still unclear how tissue fluidity is patterned spatiotemporally during gap closure, how it is regulated within the cells and by the microenvironment, and what are its molecular regulators. We have discovered that by introducing epithelial-mesenchymal transition (EMT) to epithelial cells and generating a meso- scale gap in the order of magnitude of millimeter, tissues with partial EMT status demonstrate a coordinated collective migration pattern that is distinct from both random cell crawling and purse-string-like contraction. This coordinated gap closure will serve as a novel model system to study the fundamental mechanisms for gap closure from biophysics, cell and molecular biology perspectives. Recent Progress by the PI: In the past 7 years, the PI has established his lab and built a productive research team at UMass Amherst. Since joining UMass, the PI’s group has published 26 journal articles and engaged 8 graduate students, 2 postdoctoral fellows, and more than 20 undergraduate researchers with diverse backgrounds, including bioengineering, molecular and cell biology, neuroscience, and biophysics. With strong collaborations with cell biologists, biophysicists, and bioinformatic experts, the PI’s lab has developed several bioengineering tools to define cell microenvironment, including micropatterning, traction force microscopy, DNA- based fluorescence sensors for intercellular force measuring, mechanical strain gradient generation device, and single cell RNA sequencing expertise. Leveraging those tools, the PI’s lab has investigated how mechanical cues such as geometrical confinement, substrate mechanics, and external mechanical strains regulate cell rearrangement and migration. Overview of Future Research Plans: To fully understand the mechanism of this novel gap closure process, our first goal is to track and rigorously characterize cell kinematics, proliferation/growth pattern, force distribution, and tissue fluidity during the gap closure of tissues undergoing EMT. We will study how force and tissue fluidity patterns are regulated by environmental factors such as gap geometry, 3D curvature, extracellular matrix properties, and external mechanical strains. Further, we aim to combine spatial transcriptomics and molecular biology techniques to identify the molecular mechanisms for coordinated gap closure and molecular regulators of tissue fluidity. Together, those fundamental studies will deepen our understanding of the wound healing process and guide the design of novel medical devices to accelerate the wound healing process.

NSF Awards · FY 2024 · 2024-07

Efficient remediation strategies to capture and remove forever chemicals such as polyfluoroalkyl substances (PFAS) are crucial to mitigate their detrimental health and environmental impacts. However, current technologies are ineffective- strategies degrading PFAS often lead to still-toxic intermediates, and membrane technologies have poor efficiency. In this project, a potential solution to remove PFAS from wastewater will be pursued. Since PFAS molecules are negatively charged and concentrate at oil-water interfaces, particles will be specifically engineered to pin to the interface between oil and water, adsorb PFAS due to opposite charge interactions, and be removed from the interface to isolate PFAS and recycle the particles. This project will advance the fundamental science of utilizing rationally engineered particles for interfacial materials processing, with the long term goal of helping society via environmental remediation strategies. In addition, educational and outreach activities are integrated into this project, including the development of active learning workshops for middle and high school students to expand awareness of the chemistry and impacts of PFAS molecules on the environment and how engineering solutions involving multiphase materials are being pursued. The proposed project will investigate how particle surface roughness dictates the capillary pinning and interfacial mechanics of spherical and ellipsoidal polymer microparticles. This work is motivated by the potential to use colloids pinned to fluid interfaces to adsorb environmental pollutants, namely PFAS, de-pin from the interface, and successfully be sequestered. However, the behavior of rough particles, which afford increased surface area for adsorption and tunable pinning energetics, at fluid interfaces is poorly understood. The central hypothesis is that adsorption of PFAS molecules will alter the interfacial contact angle of pinned microparticles, causing emulsions to destabilize once sufficient molecules are adsorbed. To realize this vision, novel synthetic techniques to control the roughness and chemistry of polymer spheres and ellipsoids will be applied such that tunable interactions with PFAS molecules are achieved. Mirau interferometry will quantify, in situ, the resultant interfacial pinning, which will be related to corresponding experiments examining the interfacial monolayer viscoelasticity. By linking particle characteristics (size, shape, chemistry, roughness) with interfacial properties, we will be able to identify design principles for engineering emulsions with selective response to environmental stimuli. This work will provide fundamental understanding of how manipulating interfacial pinning via colloidal roughness dictates the interfacial mechanics of particulate monolayers. By accomplishing these aims, a scalable and versatile strategy to use colloidal particles to perform environmental remediation will be established. 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 · 2024-07

Social media platforms see a surge of user-created polls, known as social polls, which gauge social media users’ opinions for various societal issues. These polls are not scientific and often exhibit biases favoring particular poll responses. Such polls can mislead the public into believing these biased outcomes reflect true public opinion. Every month, well over a million social polls are created on social media. However, these biased polls can give a misleading impression about what the public believes. Given the rising popularity of social media polls, it is crucial to address their potential to distort people’s perception of public opinion. This project aims to investigate and mitigate the harmful effects of biased social polls by identifying the biases, studying their prevalence and dissemination, examining potential harms, and developing corrective measures. These efforts will help maintain the integrity of public opinion perception. This project is pursuing three key goals. First, the project is identifying publicly visible social polls that misrepresent public opinion and evaluating the level of bias reflected in those polls by analyzing the demographic characteristics of social media users engaging with them. Second, the project is examining the prevalence and uses of such polls. Third, the project is developing a novel algorithmic method for correcting demographic biases in social polls via regression and post-stratification based on inferred attributes of users interacting with the polls. Finally, the project is experimentally assessing the effects of exposure to biased and bias-corrected poll outcomes on public opinion perception. To achieve these goals, the project is analyzing data from polls published publicly on social media, comparing the results of this analysis with the results of traditional polls, and conducting survey experiments to assess the impact of social polls on individuals. The project will significantly contribute to understanding and mitigating the impact of biased social polls on the public. 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 2026 · 2024-07

ABSTRACT Sepsis is a rapid-developing and life-threatening condition and is one of the most common causes of death in hospitalized patients in the US. Sepsis is generally caused by bacterial, fungal, or viral infection. For well over half a century, blood culture has been the main diagnostic method, but can only inform us of the presence of microorganism growth. Although empirical antibiotic treatments are usually started as soon as patients presenting with signs of severe sepsis, gaps remain in our ability to rapidly identify sepsis-causing pathogens to guide treatment with higher precision. Studies have shown significant risks to septic patients associated with delayed results and inappropriate therapy, with each hour of delay in administration of appropriate antibiotics associated with increased mortality. Although molecular diagnostic technologies are available to improve identification accuracy, they still rely on a positive blood culture result which may take 12 to 48 h or even longer if the initial culture is unsuccessful. In this MIRA R35 project, we propose to develop novel nanopore- and click- chemistry-based approaches for accurate detection of sepsis-causing pathogen independent of blood culture in about 2 hours to support the early administration of source-directed antibiotics. To fit in the clinical sepsis treatment procedure, we will employ rapid automatic sample preparation and assay methods. Our methodology will target proteomic biomarkers, such as outer membrane proteins and virulence factors released into circulation, as they are less prone to interference of blood components compared to bacterial genomic materials, and are only secreted by viable microorganisms. The PI will accomplish the proposed goal by engineering nanopore biosensors meet clinical needs of sepsis causing pathogen detection and developing multiplex click chemistry amplified nanopore sensing for sepsis causing microorganism detection and prognosis. The scientific and clinical promises of our research lie in the innovative biosensing mechanism with unprecedented sensitivity for detecting sepsis causing pathogen protein biomarkers directly in blood; the user-friendly device prototype readily applicable in clinical settings; and the discovery of potential prognosis value of virulence factors. In the past years, the PI has established a successful research trajectory by mentoring a postdoctoral fellow and six PhD students, publishing high-impact research papers, and securing competitive research grants. We will utilize our group’s diverse expertise on biochemistry, proteomics, nanotechnology, and microelectronics in conjunction with our collaborators’ expertise on high specificity high affinity binding ligands and sepsis clinical diagnosis and treatment to ensure the success of proposed research. The nanopore biosensing platform resulting from this project will also benefit the general in vitro diagnostics field by offering a sensitive, user-friendly, cost-effective, and robust method for assaying protein biomarkers in biological samples.

NIH Research Projects · FY 2026 · 2024-07

PPROJECT SUMMARY (See instructions): mRNA in cells contains base modifications, strategically (and dynamically) placed at specific position in the RNA. For fundamental research, RNA containing site-specific modifications can be generated by chemical synthesis, but only at very short lengths. The proposed research aims to build on recent advances in co-immobilized flow transcription to develop an enzymatic system to incorporate (multiple and different) modified bases site-specifically. Such a system would enable more detailed studies of translation and alternative splicing, for example, where base modifications are known to play key roles. Synthesis of RNA with position-specific substitutions will also facilitate studies of RNA structure and dynamics, where fluorescent probes for FRET/environment studies or stable isotopes for NMR measurements are essential. A better understanding of the roles of specific base modifications will ultimately inform future RNA therapeutics.