Carnegie-Mellon University

NIH Research Projects · FY 2026 · 2024-02

PROJECT SUMMARY Eye movements serve as the front-end of the visual system, sampling visual information to bridge low-level visual input and high-level visuo-cognitive processes. Smooth pursuit for tracking object motion, and saccades for fixating objects are particularly important for these functions. Oculomotor coordination of these movements requires a brain network spanning the cortex and subcortex, to provide input to the oculomotor muscles. While smooth pursuit and saccade circuitry overlaps, they have possibly different developmental trajectories. As such, disrupting these networks at different points in childhood may cause eye movement deficits, whose patterns may elucidate mechanisms of compensation and recovery of the circuits generating intact eye movements. While various brain lesions have resulted in ipsilesional smooth pursuit and contralesional saccade deficits in adults, oculomotor disruption has not been described after pediatric lesions. Up to 11% of pediatric epilepsy patients undergo pediatric epilepsy surgery to treat drug-resistant seizures, and surgery may involve resection of either or both smooth pursuit and saccade network areas. Studying eye movement patterns in these patients is crucial for delineating the recovery and limitations of oculomotor coordination and its role in cognitive processes when the brain is at maximal neuroplastic potential. This study combines behavior and imaging methods to investigate the integrity of smooth pursuit and saccades after pediatric cortical resection, and the postsurgical malleability of these circuits. Aim 1 of this proposal characterizes smooth pursuit and saccade profiles after pediatric hemispherectomy compared to controls. Hemispherectomies result in only one functional hemisphere and are usually performed in childhood. As such, this work will reveal the response of the oculomotor system at the limits of available functional cortex in humans, and while developmental plasticity is possibly at its peak. Aim 2 uses functional MRI to study the neural correlates of smooth pursuit and saccades after focal pediatric cortical resections in two major cortical oculomotor areas – frontal and parietotemporal– compared to controls. This aim will demonstrate how focal disruptions impact eye movement profiles, and whether unaffected neural circuitry adapts to support any intact or compensatory oculomotor function. Finally, Aim 3 examines the neuro-cognitive implications of oculomotor network disruption under more naturalistic conditions in fMRI. Visual search task performance will be correlated with neural activity after pediatric resections involving both oculomotor and attentional areas (frontal, parietal), relative to controls. Overall, this proposal will advance understanding of oculomotor disruption and its neural and cognitive correlates after pediatric epilepsy surgery. This work will inform an understanding of surgical risk, and future interventional investigations. My training plan leverages the expertise of my mentors and resources at Carnegie Mellon and University of Pittsburgh to develop skills in rigorous design and analysis of eye movement and neuroimaging data which I will apply, in future, to pediatric neurology populations.

NIH Research Projects · FY 2025 · 2023-12

Cells acquire their unique identities during development through the progressive emergence of distinct transcriptional programs. These transcriptional programs can be viewed as dynamic networks of interacting genes known as gene regulatory networks (GRNs). GRNs have been well studied for their positive role in activating the expression of genes that endow cells with their specialized properties; however, it is now apparent that an equally important function of these networks is to exclude other, potentially alternative, transcriptional programs. Repressive interactions of this kind play a widespread, fundamental role in determining cellular identities in organisms as diverse as invertebrates and mammals. They are also important in the context of regenerative medicine. The direct reprogramming of somatic cells by lineage-specific transcription factors (TFs) is accompanied by the comprehensive silencing of pre-existing transcriptional programs. Despite the pivotal role that repressive interactions between transcriptional networks play in both embryonic cell fate specification and somatic cell reprogramming, the underlying mechanisms are poorly understood. We will address this important problem using the sea urchin, a prominent experimental model for the analysis of developmental mechanisms and for GRN biology. One of the best characterized sea urchin GRNs underlies the development of cells that form the skeleton. A key component of this network is Alx1, a lineage- specific TF that provides direct, positive inputs into many genes that support skeletogenesis. In parallel with its positive role, Alx1 represses potential, alternative transcriptional programs that are ordinarily restricted to surrounding non-skeletogenic mesoderm (NSM) cells. Perturbation of Alx1 function in skeletogenic cells results in the ectopic deployment of NSM GRNs in these cells and causes them to adopt NSM fates. The repression of NSM GRNs by Alx1 thus provides an outstanding opportunity to uncover mechanisms by which transcriptional networks interact with one another, thereby ensuring the emergence of unique cellular identities. To dissect the mechanisms underlying this GRN interaction, I will begin by defining key spatial and temporal aspects of NSM GRN repression by Alx1, using both quantitative methods and spatial gene expression analysis to characterize changes in gene expression that occur after perturbing Alx1 function (Aim 1). Next, I will explore the hypothesis that Alx1 directly represses NSM genes by using fluorescent reporter constructs and transgenesis to dissect cis-regulatory elements of these genes (Aim 2). Finally, I will test the hypothesis that Alx1 controls a cell-autonomous unresponsiveness to Notch/Delta signaling, a pathway that drives NSM specification during normal development (Aim 3). These studies will shed light on the mechanisms by which Alx1 represses NSM GRNs. More broadly, they will lead to a better understanding of interactions between transcriptional networks that regulate cell identity.

NIH Research Projects · FY 2025 · 2023-09

Rationale: To understand the many disorders of the brain it is necessary to grapple with its complexity. Increasingly large and complicated data sets are being collected, but the tools for analyzing and modeling the data are not yet available. More researchers trained in computational neuroscience are desperately needed. This project supports interdisciplinary graduate training programs in computational neuroscience (TPCN) at both Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), and a summer school in computational neuroscience for undergraduates, which are available to students coming from colleges and universities throughout the United States. Carnegie Mellon University (CMU) is a world leader and innovator in quantitative fields such as machine learning, computer science, and artificial intelligence, and recently, neuroscience has emerged as a field for strategic growth at the university. The University of Pittsburgh is renowned for the strength of its clinical and biomedical research programs. The TPCN is set within a highly collegial, cross-disciplinary environment of our Center for the Neural Basis of Cognition (CNBC), which is operated jointly by CMU and Pitt. The CNBC was established in 1994 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 162 faculty having appointments in 32 departments. Goals: The goals of the TPCN are to: Support computational training of PhD students across the neurosciences, Support training of students from undergraduate institutions who may not have had research opportunities in the computational neuroscience field by augmenting an existing MS-to-PhD training program that prepares them for advanced graduate training in computational neuroscience, Expand computational training of undergraduate students through a formal academic minor in computational neuroscience, Support an undergraduate summer program that combines a two-week “boot-camp” overview of computational neuroscience with an 8-week research experience, and Create online materials that not only serve our own students but are publicly available on the web.

NIH Research Projects · FY 2025 · 2023-09

To understand the many disorders of the brain it is necessary to grapple with its complexity. Increasingly large and complicated data sets are being collected, but the tools for analyzing and modeling the data are not yet available. More researchers trained in computational neuroscience are desperately needed. This project supports interdisciplinary graduate training programs in computational neuroscience (TPCN) at both Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), and a summer school in computational neuroscience for undergraduates, which are available to students coming from colleges and universities throughout the United States. Carnegie Mellon University (CMU) is a world leader and innovator in quantitative fields such as machine learning, computer science, and artificial intelligence, and recently, neuroscience has emerged as a field for strategic growth at the university. The University of Pittsburgh is renowned for the strength of its clinical and biomedical research programs. The TPCN is set within a highly collegial, cross-disciplinary environment of our Center for the Neural Basis of Cognition (CNBC), which is operated jointly by CMU and Pitt. The CNBC was established in 1994 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 162 faculty having appointments in 32 departments. Goals: The goals of the TPCN are to, 1) Support computational training of PhD students across the neurosciences, 2) Support training of students from undergraduate institutions who may not have had research opportunities in the computational neuroscience field by augmenting an existing MS-to-PhD training program that prepares them for advanced graduate training in computational neuroscience, 3) Expand computational training of undergraduate students through a formal academic minor in computational neuroscience, 4) Support an undergraduate summer program that combines a two-week “boot-camp” overview of computational neuroscience with an 8-week research experience, and 5) Create online materials that not only serve our own students but are publicly available on the web.

NIH Research Projects · FY 2025 · 2023-09

Nearly all brain functions involve activity that is distributed across multiple areas. To understand these functions, it is critical to understand the flow of signals across this distributed network. To date approaches to understanding inter-areal signaling have been limited in several critical ways. First, they often focus on single neurons or a few voxels to summarize an area’s activity—an impoverished sample of the intricate neuronal population activity patterns that are known to represent and transmit information. Second, prior approaches often consider only pairwise inter-areal interactions, though the relevant network of areas is often much larger. Third, they rarely consider the concurrent flow of signals both from and to any given node in the network. In this project, we aim to overcome all three of these limitations. In Aim 1, we will develop and validate statistical methods that allow us to assess the directed, multi-dimensional flow of neuronal population signals among multiple (more than two) brain areas. We will identify directed interactions based on if the activation of a population activity pattern in one brain area tends to reliably precede the activation of a population activity pattern in another brain area with a consistent time delay. In Aim 2, we will refine and deploy the methods we develop to assess signal flow across multiple stages of the macaque visual system, an ideal testbed given a great deal of prior work on the anatomical and functional properties of the sampled areas. Specifically, we will record hundreds of neurons distributed across different layers of primary visual cortex (V1), V2, and V3. We will determine how columnar interactions within each area interact with feedforward and feedback processes, at a laminar level. Our project aims to provide insights that will strongly advance understanding of fundamental aspects of cortical function—how neuronal populations communicate with each other and how that communication relates to cortical processing. We expect the understanding we gain, and the analytic and conceptual tools we develop, will be broadly applicable across different brain systems. Our ambitious goals will be accomplished by pooling complementary expertise of three PIs, building on a successful collaboration that has extended over many years.

NIH Research Projects · FY 2025 · 2023-09

Project Summary/Abstract Bacteria undergo dramatic cellular re-organizations in different environments. Understanding the non-genetic, reversible plasticity of cellular organization is crucial to unraveling the whole-cell level algorithm of survival, growth, adaptation, and infection of bacteria, with biomedical significance in combating pathogens that can adapt to various niches and tolerate antibiotics in the human body. Cellular space is incredibly crowded with biomolecules yet well-organized. However, we still lack a precise understanding of how cellular space is organized to dictate cellular scale behaviors, physiology, and fitness. The long-term goal of my lab is to delineate basic principles of how life at the cellular scale emerges from biomolecules and their interactions. In the next five years, we will pursue this goal by gauging how key features of cellular organizations interconnect with physiological states and fitness in bacterial cells, in model organisms such as E. coli, and human pathogens such as P. aeruginosa. The organization of the cell connects to its physiological state via a combination of physical, chemical, and biological processes. We will try to disentangle this complexity by testing two fundamental hypotheses suggested by our preliminary observations: (1) the membrane real-estate hypothesis – the cytoplasmic membrane is so packed with proteins that the cell needs to fine-tune the density, composition, and organization of the membrane proteins for optimizing cell fitness, and (2) the cellular surplus hypothesis – the core biosynthetic machines have an excess amount that does not benefit steady-state growth, but rather is beneficial for adaptation to a new environment. To better test these ideas, we will quantify and manipulate the density, composition, and spatial organization of membrane proteins and the abundance of core biosynthetic machines and examine their effects on physiological states such as growth, adaptation, and cell death. We will use these results to test physical models that render possible optimality principles by collaborating with theorists in membrane physics and operations physics. These tasks require expertise in both quantitative experiments and modeling. Our lab’s experience in biophysics, bioengineering, and molecular biology will set us in a unique position to perform the research and foster cross-field collaborations and interactions. We also plan to publish and share new tools and datasets to be yielded throughout the research with the scientific community, such as microfluidic devices, image analysis software, and databases of protein physical properties. Whether these hypotheses will be verified, outcomes from these projects can help us bridge cellular organization and physiology and understand better cellular adaptation, a branch of knowledge that can be extended to studying other higher organisms.

NIH Research Projects · FY 2026 · 2023-07

The mammalian brain is particularly well suited for managing streams of (often noisy) evidence, both internally and externally generated, to converge to a decision. This evidence accumulation process can adapt to changing environments and reward opportunities, mediated by cortico-basal-ganglia-thalamic (CBGT) circuits that both contribute to action selection and use feedback signals to modify future decisions. Dysfunction in how these pathways use feedback to guide future decisions is a primary mechanism for many addictive behaviors (e.g., opioid addiction, obesity). Our prior work has identified subsystems, which we call control ensembles, within the CBGT pathways that regulate dimensions of the evidence accumulation process, leading to various neural states with differing receptivity to the evidence streams that drive decisions, encapsulated in a particular decision policy. We propose a series of empirical and theoretical investigations that bridge across levels of analysis to understand the flow of information through CBGT circuits during the decision-making process. On the theory side we will use our models to understand the low-dimensional representational space of CBGT circuits throughout the decision-making process, using energy landscape models coupled with dimensionality reduction. Using computational models we will model decision trajectories through CBGT networks by applying entropy based analyses to the network behavior and building predictions of observed dynamics in both discrete and continuous actions (Specific Aim 1). Empirically, we will test predictions emerging from our network model and provide new observations to support model refinement using experiments in rodents (optogenetics, electrophysiology) as they perform both tasks with dynamic reward contingencies featuring either discrete choices or continuous motor control (Specific Aim 2). Our theoretical and empirical work will evolve in a mutual-development cycle, with theoretical experiments being used to derive novel behavioral and neural predictions and empirical experimental results being used to revise and update the generative model properties that lead to subsequent predictions.

NIH Research Projects · FY 2026 · 2023-06

Project Summary The goal of this project is to develop and validate a novel electrophysiological source imaging (ESI) approach based on biophysically constrained deep neural networks (BioDNN), to significantly improve surgical planning in drug resistant focal epilepsy patients. Epilepsy affects about 70 million people worldwide. For approximately 33% of the 3.4 million Americans with epilepsy, seizures are not controlled by medications alone. Epilepsy surgery is the most viable option for curing drug resistant focal epilepsy, only if seizure sources can be accurately localized and safely removed. There is a clinical need to innovate technological tools for better surgical planning of focal epilepsy. We propose in this project a novel ESI technology based on biophysically constrained deep neural network (BioDNN) to provide accurate, robust, and objective spatio-temporal estimates of the underlying epileptogenic zone (EZ). Of innovation is that the trained neural network, is capable of imaging brain sources without the need to tune the model’s hyper-parameters by an operator for every new instance of data, thus making the technique objective and easy-to-use in clinical settings. Our specific aims are: Aim 1. Establishing and Validating the BioDNN for Imaging Epileptogenic Tissue from EEG Inter-ictal Epileptiform Discharges (IEDs) of Focal Epilepsy Patients. We will establish, optimize and validate the proposed BioDNN for imaging EZ from IEDs in EEG in 200 focal drug resistant epilepsy (DRE) patients, in comparison to clinical “ground truth". Aim 2. Developing and Validating the BioDNN Model for Imaging Epileptogenic Tissue from MEG Inter-ictal Epileptiform Discharges of Focal Epilepsy Patients. We will develop and optimize the BioDNN model for imaging EZ from MEG IEDs and validate the MEG-BioDNN model and compare with the EEG-BioDNN model in 80 focal DRE patients in comparison to clinical “ground truth. Aim 3. Developing and Validating the BioDNN Model for Imaging Epileptogenic Tissue from Ictal EEG of Focal Epilepsy Patients. We will develop the BioDNN for imaging the SOZ from scalp ictal EEG and validate it from high density ictal EEG recordings in 120 focal DRE patients, in comparison to clinical “ground truth”. The successful completion of the proposed research will establish a novel machine learning technology to non-invasively localize and image underlying epileptogenic tissue from interictal and ictal electrophysiological biomarkers. The establishment of such a novel technology promises to significantly improve the precision of intracranial EEG electrodes implantation and aid surgical planning, leading to significant improvement in surgical outcomes, and benefiting numerous drug resistant epilepsy patients. 1

NIH Research Projects · FY 2026 · 2023-05

Project Summary The external segment of the globus pallidus (GPe) is a neuronally diverse and highly interconnected nucleus within the basal ganglia. Under conditions of low dopamine, plasticity in the GPe promotes the emergence of pathological firing patterns that contribute to widespread basal ganglia dysfunction. In Parkinson’s disease (PD), deep brain stimulation (DBS) in the GPe can alleviate motor symptoms, suggesting there is a mechanistic link between neuronal dysfunction in the GPe and motor symptoms of PD. Using optogenetics to target neuronal subpopulations in the GPe, we discovered that persistent behavioral rescue could be induced by interventions that excited parvalbumin-expressing GPe neurons (PV-GPe) and inhibited Lim homeobox 6-expressing GPe neurons (Lhhx6-GPe). Differences in the synaptic inputs onto these neuronal subpopulations enabled us to develop a human-translatable electrical DBS protocol that could achieve the same cell-type specificity of optogenetics. In parkinsonian mice, these circuit-inspired burst DBS protocols provided superior therapeutic benefit over conventional protocols, extending the therapeutic duration for hours beyond the period of active stimulation. We are now collaborating with neurosurgeons at Allegheny General in Pittsburgh to test the therapeutic efficacy of circuit-inspired DBS protocols in humans. Results from in vivo physiological recordings revealed that GPe interventions reverse parkinsonian pathophysiology in the basal ganglia for hours following stimulation, raising the intriguing possibility that GPe interventions induce therapeutic plasticity that restores circuit function in disease. This would represent a transformative advance in PD therapeutics. But a number of questions still remain about how transient interventions in the GPe translate into long-lasting therapeutic effects at the behavioral level. This proposal will use electrophysiological, optogenetic, and behavioral approaches to identify the therapeutic mechanisms of persistent behavioral rescue by achieving three main goals: (1) We will map the neural pathways required for persistent behavioral rescue, including testing an innovative hypothesis that both motor and arousal circuits are involved (2) We will identify short-term and long-term effects of GPe interventions on basal ganglia physiology, testing the hypothesis that GPe interventions drive therapeutic plasticity in dopamine depleted mice, and (3) We will assess the therapeutic efficacy of GPe interventions delivered at different stages of dopamine depletion on both motor and non-motor symptoms to further study the neural circuits involved, as well as to advance preclinical testing of GPe interventions for continued therapeutic development. These studies will advance the development of circuit-inspired approaches that repair, rather than mask circuit dysfunction for long-term recovery of brain function in disease.

NIH Research Projects · FY 2026 · 2023-04

Project Summary Movements are influenced by motivation. Consider a basketball player shooting a free-throw. Depending on the stakes of the outcome of the shot, performance can vary greatly. Top athletes rise to the challenge, and perform better during a game than they do during practice. But when the stakes are inordinately high, like when the game is on the line, even skilled players can “choke under pressure”, and under-perform right when it matters the most. What are the neural mechanisms whereby motivation affects motor performance? Here we propose a targeted set of experiments to dissect the neural mechanisms of motivated movement. Our work is guided by a conceptual model that is premised on decades of research into the function of the dopamine system. Put simply, we posit that dopamine modulates the activity of populations of neurons in the primary motor cortex. The level of dopamine is determined by the size of the expected reward. Neurons in motor cortex are activated by dopamine, as well as by volitional motor commands. We hypothesize that dopamine interacts with the ongoing neural control of behavior: Moderate amounts of dopamine improve the fidelity of movement-related signals in the motor cortex, but unusually high levels of dopamine actually interfere with neural activity patterns in motor cortex, perhaps by making them too variable or poorly-formed to trigger a successful movement. If we can show that this picture (or something like it) is true, then we can, for the first time, establish a direct link between motivation and motor control, mediated by whole-brain circuits involved in the performance of a skilled movement. Our approach relies on our recently established animal model: Rhesus monkeys exhibit the same behavioral performance profile that humans do. That is, they show improved performance as motivation increases, but then when the stakes get unusually high, they also choke under pressure. To our knowledge, this effect has never been demonstrated in a nonhuman animal, which makes monkeys the ideal model system in which we can begin to understand the neurophysiological mechanisms whereby motivation and movement mix in the human brain. Here, using this unique model, we first study how reward modulates the motor cortical control of movement, and test several hypotheses regarding how reward might mediate neural noise and behavioral variability. Second, we test how these reward-related modulations influence the planning, initiation, and execution of reach. Third, we record from midbrain dopaminergic reward processing circuits, to establish moment-by-moment links between dopamine activity and ongoing motor performance, and probe causal effects of cortical dopamine. Our studies stand to unveil the neural mechanisms of reward-based changes in motor control, with several clinical implications: (1) In Parkinson’s disease, the death of dopaminergic neurons results both in a loss of movement vigor and also a degradation in the quality of movement. This study will be among the first that will show a direct link between dopamine activity and both motivation and motor performance. (2) In stroke, rehabilitation can be a tedious and frustrating experience. Our work can show how the right motivational structure can improve motor performance and perhaps learning. (3) Our work also has relevance for brain-computer interfaces (BCI), through the design of systems that can extract stable motor-control signals despite shifts in motivation.

Fonds de recherche du Québec – Nature et technologies · FY 2023-2024 · 2023-04

Volet: Renouvellement - Bourses de recherche postdoctorale; Domaine: Non disponible

NIH Research Projects · FY 2025 · 2023-01

PROJECT SUMMARY/ABSTRACT In ecological listening environments, individuals must direct attention toward a specific source (e.g., the voice of a friend) while ignoring simultaneous background noise (e.g., other patrons in a café). Moreover, listeners must direct attention toward specific dimensions within an auditory source (e.g., frequencies useful for distinguishing between different speech sounds). A widely held but untested assumption is that these source-based and dimension-based forms of auditory selective attention are supported by common mechanisms. Human studies have historically focused on source-based attention using speech stimuli, while nonhuman animal studies have primarily investigated dimension-based attention with non-speech stimuli; there is thus an empirical gap between these literatures, making it unclear how well the animal studies can model human behavior. More generally, the mechanisms that support auditory selective attention remain underspecified. For instance, extant research suggests that selective attention involves enhancing representations of key information, but it is unclear whether selective attention also involves actively suppressing irrelevant information. Thus, the goal of the proposed project is to clarify the cognitive and neural mechanisms that support auditory selective attention. The first aim is to determine whether auditory selective attention involves suppression of irrelevant information. The key scientific premise is to use training as a tool for triangulating mechanism. That is, if selective attention involves suppression of irrelevant auditory dimensions, then training that improves a listener’s ability to suppress irrelevant auditory information should be associated with concomitant gains in auditory selective attention. Listeners will receive eight days of auditory training that either will require them to perform increasingly fine- grained processing in a target frequency band (promoting enriched representations of target dimensions) or will place increasing demands on the extent to which they must suppress irrelevant auditory dimensions (e.g., a non- target frequency band). Of interest is whether training is associated with improved auditory selective attention, as measured through classic behavioral and electrophysiological indices of attention. The second aim is to determine whether different forms of auditory selective attention (e.g., source-based and dimension-based) are supported by common mechanisms. If they are, then training that leads to improvements in one type of auditory selective attention (e.g., dimension-based) should generalize to another (e.g., source-based). Listeners will complete tests of generalization before, midway through, and after the training regimen. Of interest is whether an improved ability to attend to target auditory dimensions is associated with an improved ability to direct attention toward a specific source. Tests will also assess whether training with non-speech stimuli generalizes to speech. The results will provide insight into the extent to which different forms of auditory selective attention are supported by common mechanisms. Overall, the proposed work will clarify the mechanisms supporting auditory selective attention and provide a vital missing link between the nonhuman animal and human literatures.

NIH Research Projects · FY 2025 · 2022-09

Through innovations in both imaging techniques and the ability to process these images at scale, high- resolution imaging is transforming the eld of molecular biology, yet its power has yet to be fully utilized for asking questions in evolutionary biology. Just as demographic surveys can reveal more or less densely populated areas where, for example, a contagious disease may spread at di erent rates, these imaging datasets can help us quantify cellular and molecular patterns of spatial variation and understand how this variation a ects rates of evolution, by impeding or accelerating the spread of new variants through the population. My research program, at the interface of computer vision and evolutionary biology, is exploring how molecular and cellular communities spatially organize, and how the resulting spatial topologies can be generated, stably maintained and further shape the outcome of the evolutionary process. What are spatial topologies that act to amplify the selective advantage of new mutations in the pop- ulation, versus structures that dampen the force of selection and slow down rates of evolution? We build theoretical evolutionary models that explore how the rate of evolution is shaped by complex spatial struc- ture and nd the relevant spatial features for evolutionary ampli cation or selective suppression. We link these theoretical population genetic models to high-resolution imaging datasets and study the resulting spatial architectures. This allows us to go beyond simply describing patterns of cellular or molecular spatial variation, and enables exploration of the generative processes, as well as of the evolutionary trajectories of the system. Beyond the purely theoretical interest in these questions, understanding the role of spatial structure in shaping the mode and tempo of evolutionary dynamics is particularly timely because, by using modern microfuidics and organoid technologies, we can start building population structures that control the topol- ogy and migration patterns of a molecular or cellular population, amplifying the selective bene t of chosen mutations, boosting the ability to nd optimized protein complexes for medical or industrial applications, or as a screening tool for faster replicating pathogenic variants.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY Janine M. Dutcher, PhD aims to understand the brain mechanisms for behavioral interventions for stress reduction and health. The research and training plan described in this proposal will strengthen her experience in neuroimaging with additional training in structural neuroimaging, and launch her independent career as a multi-modal health neuroscientist. To enable this training, Dr. Dutcher will analyze data from a randomized controlled trial (RCT) of mindfulness training in stressed employees. This study features functional and structural neuroimaging, and stress assessments—and experience with these data will help the PI build a career that explores the brain mechanisms for stress reduction interventions. Candidate: Dr. Dutcher is a Special Faculty Researcher in the Psychology department at Carnegie Mellon University (CMU). She received her doctorate at UCLA in social and health psychology. Her work focused on understanding the neural mechanisms of stress reduction, the neuroscience of inflammation and social experience, and the relationship between reward and stress. She has worked primarily on cross-sectional and experimental studies, using functional neuroimaging methods for testing neural mechanisms. She plans to receive training in structural neuroimaging and RCTs to advance her studies on the longitudinal brain mechanisms for behavioral interventions. Training Goals: Dr. Dutcher aims to learn more about RCT study design, intervention integrity, and mindfulness meditation programs—goals that her mentor Dr. Creswell can aid in. Analytically, Dr. Dutcher will receive training in diffusion spectrum imaging from Dr. Verstynen, learning statistical techniques for linking longitudinal structural and functional brain changes, and assessing those relationships as a mechanism for the benefits that interventions have on stress and health. Finally, Dr. Dutcher will hone the professional skills that will support her pathway to independence, including grant writing, networking, and more mentoring opportunities through managing research teams. Mentors/Environment: Dr. Dutcher has overseen the day-to-day execution of an RCT exploring the effects of a mindfulness training program on stress and burnout in a stressed employee population with Dr. Creswell. She and Dr. Verstynen coordinated to add diffusion spectrum and functional neuroimaging pre- and post-intervention. Thus, she will be leveraging an existing dataset and existing collaborations to achieve her training and research goals. She has the resources and support of CMU, proximity to other collaborators, and the ideal mentoring team for executing this proposal. Research: Although the literature has established mindfulness as an effective stress reduction intervention, the brain mechanisms are as yet unclear. The purpose of this project is to analyze data from a rigorous RCT of a 30-day smartphone mindfulness program compared to an active control program (problem solving) to evaluate how mindfulness changes the brain in a sample of stressed employees (N=100). Analyses will examine changes in white matter integrity over the 30- day intervention, compared to control, and link these changes in white matter to changes in stress. This project has the potential for mapping the brain mechanisms for stress reduction, providing greater understanding of how to effectively intervene and reduce the risk of stress-related health conditions in the population.

NIH Research Projects · FY 2025 · 2022-09

Project Summary The intestine plays essential roles in health and disease based on its two main functions: nutrient absorption and immune defense. These two processes are highly intertwined with each other and are influenced by a variety of genetic and environmental factors. Abnormal absorption causes nutrient deficiency or excess, which leads to various metabolic diseases. Compromised immune defense increases the exposure to pathogens and other noxious agents, and promotes systemic immune activation, infections and metabolic disorders. Therefore, understanding how the two processes are regulated in the intestine is critical for fighting these digestive system diseases. Intriguingly, many of the metabolic and immune functions are integrated in the same group of cells, the intestinal epithelial cells. However, how these cells coordinate the two distinct processes, especially in the face of environmental challenges, remains a puzzle. We recently identified that the gut microbiota, a community of microorganisms in the gut, controls a 24-hour diurnal rhythm in the intestinal epithelium through an epigenetic mechanism. This leads to a hypothesis that the microbiota may temporally orchestrate metabolic and immune functions in the intestine to maintain just-in-time capacities of nutrient uptake and immune defense in response to the diurnal oscillations of nutrient availability and microbial burden. In this proposal, we will examine how metabolic and immune activities are temporally coordinated in the intestine and how these rhythms are affected by environmental interventions. We will scrutinize the components and activities of the microbiota to understand how gut microbes regulate the circadian system to influence host metabolic health and immune integrity. We will identify and characterize other epigenetic programs that integrate microbial and circadian cues to regulate intestinal physiology. From a preliminary screen, we found that the microbiota drives the rhythm of another chromatin modification that is only present in male mice but not females. This finding provides a new avenue for understanding how microbial, circadian and sexual dimorphic signals converge in the intestine to control metabolic and immune functions. We will exploit multidisciplinary techniques including bacteria and mouse genetics, genomics, gnotobiotics, and more importantly we will develop new computational approaches and screening assays to understand the crosstalk between the gut microbiota and host circadian rhythms. These studies will provide novel mechanistic insights into the microbial regulation of host circadian programs and shed light on unexpected roles of the microbiota and epigenetic modification in regulating sexual dimorphisms of mammalian metabolism and immunity. Ultimately, the findings will help develop new strategies to protect against metabolic and immune diseases by targeting the microbiota or epigenetic pathways.

NIH Research Projects · FY 2025 · 2022-09

Abstract Over 190,000 people suffer from acute respiratory distress syndrome in the US each year, with mortality rates from 30-40% with the best treatment. In addition, there are over 12 million patients with chronic lung disease, 6.9 million emergency room visits, and over 180,000 deaths. When mechanical ventilation is insufficient to support these patients, extra-corporeal membrane oxygenation (ECMO) is used as a bridge to recovery or bridge to transplantation. Unfortunately, ECMO is plagued by bleeding and thrombotic complications that reduce patient survival by approximately 40 and 33%, respectively. The cause of coagulation is primarily surface adsorption of plasma proteins, subsequent activation of the intrinsic branch of the coagulation cascade, and platelet binding to adsorbed fibrinogen. This is combated using systemic, intravenous heparin, but this inhibits both biomaterial- induced coagulation in the ECMO circuit and tissue-factor induced coagulation in the patient’s tissues, resulting in bleeding complications. To eliminate both of these problems simultaneously, we propose to combine two means of selectively inhibiting coagulation at the blood-biomaterial interface while leaving tissue-based coagulation intact. The first is biomaterial surface coating with zwitterionic polycarboxybetaine (PCB). Our initial results demonstrate that the PCB coating dramatically decreases protein adsorption and platelet binding in vitro and long-term clot formation during sheep ECMO. The second is FXII900, a potent, highly-selective bicyclic peptide FXIIa inhibitor. FXII900 inhibits surface-induced activation of coagulation at nanomolar concentrations without affecting the tissue-based extrinsic branch or common branch of the coagulation cascade. In our preliminary, short-term rabbit ECMO studies, we demonstrate a 94% reduction in clot formation vs. standard clinical heparin anticoagulation. At the same time, FXII900 plus PCB maintained a normal bleeding time, while the heparin increased the bleeding time to 2.9 times normal. The goals of this proposal are to extend this technology toward clinical applications by i) proving the effectiveness of combined PCB plus FXII900 anticoagulation during 5-day in vivo extracorporeal life support and ii) developing long-acting FXII900 formulations that enable bolus dosing every 8 or 12 hours rather than a continuous intravenous drip. If successful, these studies would lead to a clinical anticoagulation strategy that i) reduces bleeding and thrombotic complications during ECMO, ii) reduces ECMO mortality, and iii) simplifies clinical application of ECMO. These benefits, when combined, might also allow safe long-term ECMO outside the intensive care unit.

NIH Research Projects · FY 2025 · 2022-09

DESIGNING A HIGH-THROUGHPUT PLATFORM TO BIOPROSPECT THE HUMAN MICROBIOME AND MANIPULATE ITS INTERPLAY WITH HOST ENVIRONMENTS Project Summary The human microbiome, comprising hundreds of microbial species living in and on the body, is now recognized to play critical roles in human health and performance as well as disease prevention and management. A healthy microbiome (which has not yet been fully characterized because some key species cannot be cultured) keeps in check harmful microbes that are normally present. However, when this balance is perturbed, pathogenic microbes may overgrow, a condition called dysbiosis, and compromise both gut and immune functions. Development of technologies for the growth and manipulation of microbial consortia are urgently needed to assess the beneficial effects attributed to probiotics and synthetic communities. Developing such ability would enable clinicians to reverse microbial imbalance by providing a personalized set of microorganisms capable of restoring gut functions associated with infectious, inflammatory, metabolic, cardiovascular, and cognitive diseases in patients. To this end, my group aims to advance a bold and unique microfluidic-based technology to isolate, culture, reconstruct, and, in the long-term, manipulate the human gastrointestinal (GI, gut) microbiome to treat diseases. This application specifically aims to develop a nanoculture system to grow microbial isolates from the gut, including those as yet unculturable, and identify beneficial interactions or bioactive metabolites essential to design synthetic communities capable of eradicating or inhibiting the growth of pathogens such as Clostridium difficile. The preliminary effectiveness of the ‘designed’ communities will be determined by treating Clostridium difficile Infection (CDI) in an established mouse model. Our long-term goal is to develop a microbial bank of live biotherapeutics of human origin comprising defined microbial communities applicable for personalized and precision medicine. We envision this technology to be a safe, easy-to-deliver, and efficient alternative to fecal microbiota transplant (FMT) to treat diverse dysbiotic conditions, and thus help restore a healthy gut microbiome.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY/ABSTRACT It is widely accepted that failure to restore pre-injury biomechanics after anterior cruciate ligament reconstruction (ACL-R) surgery is one of the key contributing factors to the high prevalence of post-traumatic osteoarthritis (PTOA). Precision rehabilitation, which refers to the delivery of the right feedback to the right patient at the right time, is now a feasible approach for PTOA prevention given recent advances in wearable sensing and computer vision technologies. Flexible and unobtrusive skin patches can objectively quantify movement out of the clinic and deliver real-time haptic feedback, while simple videos from smartphones can assess physical therapy quality and deliver corrective visual or auditory feedback. To effectively apply emerging smart-health technologies toward PTOA prevention, the multi-modal and multivariate data produced by these sensors must be distilled to identify digital biomarkers of PTOA that can be targeted with biofeedback therapy in the future. Accordingly, the central objective of this proposed work is to determine if characteristics of gait extracted from video and wearable sensors (digital biomarkers) can predict longitudinal changes in cartilage microstructure (early PTOA) extracted from quantitative Magnetic Resonance Imaging (qMRI). Our central hypothesis is that future risk of PTOA can be predicted in the first few months after surgery using passively collected data from wearable sensors and video. This hypothesis is supported by our previous work on pre-arthritic subjects, where we demonstrated that wearable sensing data could predict detrimental changes in cartilage microstructure that are indicative of OA risk. To accomplish the overall objective of this work, physical therapy, natural environment ambulation, and cartilage health will be monitored longitudinally. Exercise correctness during pre- and post-operative physical therapy will be quantified using computer vision and machine learning algorithms. Out-of-lab movement will be monitored at baseline (3 weeks), 3, and 9 months after surgery with epidermal sensors placed on the thighs and shanks. Quantitative MRI data will be collected at baseline (3 weeks), 3 and 18 months after the surgery. Specifically, we will determine (1) if gait symmetry restoration measured by wearable sensors can predict qMRI changes up to 18 months post-surgery and (2) if physical therapy quality, to the extent that is quantifiable with passive computer vision algorithms, can predict gait symmetry restoration up to 9 months post-surgery. This work is innovative because it breaks with the current norms of studying the role of biomechanics in PTOA in the laboratory. Instead, we will use wearable sensing, computer vision, and machine learning to generate previously unavailable knowledge on the role of natural environment biomechanics. If successful, this work could enable personalized, technology- assisted rehabilitation—a paradigm shift in clinical care. Additionally, the discovery of new PTOA biomarkers could improve the efficiency of clinical trials for new surgical techniques, while the proposed framework is also extensible to the study and prevention of primary OA, and possibly other orthopaedic conditions.

NIH Research Projects · FY 2025 · 2022-09

Our research program identifies the systems that support mathematics learning during early childhood – a foundational issue in the fields of cognitive development and cognitive neuroscience. By using functional magnetic imaging (fMRI) in longitudinal studies of 4- to 8-year-old children, we will assess, for the first time, how children’s early neural representations of spatial-numerical concepts relate to their subsequent mathematical competence in school. We predict that children’s early neural activations predict their growth in calculation abilities. Our proposal examines whether patterns of neural development generalize across children. Some behavioral evidence suggests that mathematics development in boys and girls is largely similar whereas other evidence suggests asymmetries. The current proposal will evaluate similarities and differences in the mathematics development of boys and girls. The reason this is important is because prior research in this area is extremely limited, prior methods and statistical techniques were flawed, and the prior evidence is mixed. We will address prior flaws in this research area by using rigorous new statistical methods, and we will investigate these questions at the neural level which provides new data on patterns of similarity and difference. We then examine the connection between children’s neural development and behavior, socialization, and learning activities. Based on previous research and our preliminary data, we hypothesize that boys and girls are largely similar in the cognitive and neural mechanisms, and that differences only emerge at later ages in narrow tasks, depending on children’s experiences. Our research brings new theoretical distinctions, innovative methods, and new neural data to a long-standing behavioral research tradition on the development of mathematics. The hypotheses, experiments, and analyses that we propose are all well-founded in prior research but also offer novel insights with broad significance for psychology, neuroscience, and education.

NIH Research Projects · FY 2025 · 2022-09

The link between neural circuits and behavioral performance has been an enduring mystery in neuroscience. A fundamental observation of both neurons and behavior has been that they both exhibit variability. This variability can manifest on a variety of time scales, from minutes to hours to days, and across many spatial scales, from local populations of neurons to the whole brain. One important missing feature in our understanding of cognition and behavior, that may explain some of the apparent variability, is a lack of insight into the brain’s internal cognitive state while performing any task. The coordination among neurons across the brain is critical to achieving any internal cognitive state, such as attention or arousal. This coordination has been extensively studied at the level of field potentials, but relatively rarely in populations of single neurons. Furthermore, because the coordination among neurons in a pair of brain areas may relate to the action of distant brain circuits, teasing apart the fundamental neural circuits that give rise to coordinated neural activity, and the link in turn to behavior, has been challenging. At the same time, pharmacological approaches targeted at neuromodulatory systems have proved a powerful, if coarse, means to influence behavior and treat disease. We will study neural coordination across scales, from field potentials and neurovascular signals measured at the scalp, to populations of spiking neurons in cortex, to individual neurons in a deep brain structure that modulates cortical activity. Simultaneously, we will measure behavior on cognitive and perceptual tasks as well as the pupil, which we have shown in previous work exhibit slow fluctuations on the time scale of minutes to hours. Our strategy is to identify how neuronal coordination of cortical neurons is indicative of internal cognitive state and neuromodulatory input, and can be modified to alter cognition and behavior. We will do this in a computational framework that links the variability among neurons in a population to internal states of the brain and in turn to behavior. In our first specific aim, we will test the hypothesis that field potentials and neurovascular signals at the scalp are directly linked to neuronal coordination in prefrontal cortex and behavior. In the second aim, we will test the hypothesis that neuronal coordination in prefrontal cortex as well as systemic indicators of arousal are influenced by norepinephrine efflux from the locus coeruleus. Finally, in the third aim, we will test the hypothesis that direct intervention in this circuit by microstimulating the locus coeruleus can alter neuronal coordination in cortex and in turn influence behavior. The overall result of this study will be to establish a direct link between coordinated activity in the cortex, neuromodulatory drive, and cognition and behavior. This will aid in developing treatments for myriad neurological disorders that involve altered states of arousal or changes in norepinephrine drive, and establish a framework for understanding the link between large-scale measures of neuronal coordination (like oscillations in field potentials at the scalp) and neuronal circuit mechanisms.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY Parkinson’s disease (PD) is a debilitating neurological disorder affecting up to 10 million people worldwide with symptoms of tremor, bradykinesia, and rigidity that severely limit the quality of life of patients. Deep brain stimulation (DBS) is an effective treatment used in patients who demonstrate symptoms that are inadequately controlled by medications. This treatment involves the delivery of continuous high frequency stimulation to either the subthalamic nucleus (STN) or the globus pallidus interna (GPi), two modulatory nuclei in the basal ganglia (BG). DBS improves motor symptoms acutely but does not differentiate between neuronal circuits, and its effects decay rapidly when stimulation is turned off. The need for constant stimulation increases the risk of side effects and the frequency of battery replacement. Hence the investigation of alternative patterns of stimulation that produce long-lasting recovery is critical. Such stimulation paradigms could minimize adverse outcomes caused by constant current delivery while also inducing therapeutic plasticity in the form of reversal of the aberrant synchronous activity of the BG seen in PD patients. Since the cellular mechanism of action of DBS is unknown, the clinical advances in identifying these patterns have been limited. Recent findings in the Gittis lab suggest that optogenetically manipulating distinct neuronal subpopulations (specifically, activating PV neurons and inhibiting Lhx6 neurons) in the external globus pallidus (GPe), a central nucleus of the BG, provides long-lasting reduction in immobility in dopamine-depleted mice that show bradykinesia or akinesia at baseline. In an effort to make this finding translatable, using insights from the synaptic features of these cell-types, we identified that electrical stimulation delivered in the entopeduncular nucleus (EPN, rodent homolog of the GPi) as bursts can produce the same cell-type modulation described above. Such a DBS protocol when tested in vivo produced motor recovery that lasted for hours after stimulation was stopped. These findings could hugely impact the standard of care for Parkinson’s disease patients that show a narrow therapeutic window, by maximizing their therapeutic duration, minimizing side effects, and potentially altering their pathological circuitry. The goal of this proposal is to demonstrate a clinically translatable optimized burst DBS protocol which can produce long-lasting motor recovery by reversing the underlying pathological activity in the BG. In an effort to optimize burst DBS from a translational standpoint, Aim 1 will establish the combination of stimulation frequency and duration required to see prolonged therapeutic benefits. To potentially accelerate the translation to PD patients with DBS implants in the STN, the effect of burst DBS in the STN will be compared to burst DBS in the EPN. Since patients show motor vs. non-motor symptoms at varying stages of the disease, Aim 2 will characterize the behavioral effects of burst DBS on symptoms at varying levels of dopamine depletion. Finally, in an effort to understand the underlying mechanism of the long-lasting motor rescue, Aim 3 will evaluate whether burst DBS induces therapeutic plasticity by attenuating the pathological firing of Substantia nigra pars reticulata (SNr) neurons.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY / ABSTRACT There are approximately 25 million Americans that suffer from Type 2 diabetes. Furthermore, about 35 million Americans >20 years old are diagnosed with prediabetes. More than one-third of Americans are also obese, an incidence that has nearly tripled from 1960 to 2010. Recent studies have shown that the gut-brain axis places a critical role in digestive and metabolic diseases. Further, direct communication between the sensory neurons in the gut and neural reward circuits in the brain plays a crucial role in detecting chemical cues such as hormones, satiety signals, or small molecule metabolites produced by bacteria in the gut. Chemicals in the small intestine are detected by specialized epithelial cells that transduce chemical signals into neuronal activity that can be interpreted by the central nervous system. An ingestible device that supersedes chemical cues and stimulates sensory neurons directly using electronic pulses could mimic the chemical milieu in the gut that is associated with healthy metabolic and digestive states. Spatiotemporal control of intraluminal sensory nerve stimulation in the gut could with help us understand the link between chemical signaling in the digestive system and neural circuits in the brain that are modulated by the gut-brain axis. Here we propose an ingestible electronic device with flexible electrodes that can pace sensory nerve activity in the gut of a pig model. Physiological responses will be measured, and brain activity will be monitored using fMRI. Initially, this project will validate this proof-of-concept using tethered electrodes in porcine subjects. Specifically, sensory neurons in the gut will be paced using biomimetic waveforms that will simulate fed or fasted states in porcine subjects while brain activity will be measured simultaneously using fMRI. These results will help us understand the connection between gustatory signaling, sensory nerve activity, and neural reward circuits in the brain such as satiety. In the future, we will design a fully autonomous smart pill with an on-board power supply and circuitry that selectively and non-invasively stimulate or block the activity of sensory neurons in the gut of human subjects. If successfully, this smart pill could serve as a low-risk device-based approach to help understand and potentially treat digestive and metabolic disorders of the gut-brain axis such as obesity and diabetes.

NIH Research Projects · FY 2025 · 2022-08

The Human BioMolecular Atlas Program (HuBMAP) is redefining our understanding of the human body by recovering multi-scale tissue organization -- anatomical, histological, and molecular -- at unprecedented resolution, through computational integration of diverse experimental measurements. The HuBMAP Integration, Visualization & Engagement (HIVE) Collaboratory is an effort among interdisciplinary components developing pipelines for data ingestion and processing, enabling visualization of datasets spanning dozens of biomolecular assays on the HuBMAP portal, leading the development of a human common coordinate framework (CCF), constructing molecularly and spatially resolved reference maps of human tissues, developing mapping frameworks for the interpretation of new datasets, and coordinating extensive collaborative activities both within HuBMAP and with the broader community. In the production phase of HuBMAP, the HIVE will construct a Human Reference Atlas (HRA), establishing the HuBMAP Portal as the “go-to” resource for human tissue reference maps and multimodal singlecell data. The next iteration of the HIVE will coalesce the HuBMAP Consortium around a joint vision, develop cutting-edge and scalable tools to achieve it, and ensure its open dissemination to partners and users across the wider international community. As the HIVE Infrastructure Component (IC), the Pittsburgh Supercomputing Center (PSC), the University of Pittsburgh (Pitt), and Stanford University will provide infrastructure, based on our flexible hybrid cloud microservices architecture, along with community engagement, that will support delivery of this vision in the production phase. To accomplish this, we will focus our efforts in the following key areas: 1) Curation and Ingestion: Increased automation of data ingestion from HuBMAP data providers, community partners, and the general research community to maximize efficiency and usefulness for building the HRA; 2) Integration: Automated integration and mapping of ingested data to the HRA based on data standards; 3) Findability and Accessibility: Manifestation of backend resources in the modular architecture of APIs and containers, services, and documentation that minimize user friction in integrated searching, querying, analyzing/aligning and viewing of tissue maps at multiple spatial scales and among multiple layers of information; 4) Interoperability: Extension of the HuBMAP Knowledge Graph to translate HuBMAP data, HRA assets, and community data among one another via ontologies; 5) Analysis: Infrastructure support to maximally enable users with scalable analyses and workflows among both HuBMAP and user-contributed data and tools, including integration and mapping against the HRA; and 6) Sustainability: Sustainment of open tools, data, and infrastructure for reuse beyond the production phase. We will grow and harden our model for collaboration, coordination, and engagement led by the IC, with substantial leadership from all HIVE members and participation from all HuBMAP Members.

NIH Research Projects · FY 2025 · 2022-08

Summary/Abstract Immune cell therapies are a powerful new class of “living medicines” for treating cancer and other diseases, but producing them remains laborious, inefficient, and slow. The chief bottleneck is the challenge of making accurate changes to the DNA of extremely large numbers—often billions—of human cells ex vivo. Gene editing with CRISPR-Cas9 is much more precise than lentiviral or retroviral vectors, but it remains difficult to deliver controlled amounts of the Cas9 endonuclease into human cells, particularly immune cells. A promising approach is to momentarily disrupt the plasma membrane, allowing direct transport of DNA-editing proteins into the cytosol. However, current & emerging nonviral delivery methods are nonuniform, damaging to cells, and too slow for clinical applications that require billions of cells. Therefore, the research objective of this proposal is to develop a very fast microfluidic method of permeabilizing the plasma membrane to facilitate efficient delivery of DNA- editing proteins. The central innovation is to use viscoelastic fluid forces to stretch the plasma membrane without cells touching any surfaces. As a result, this “contactless” approach is efficient, gentle, robust, and extraordinarily fast—exceeding 100 million cells per minute in a single microchannel. The K99 phase of the project will focus on developing this technology for efficient gene editing of T cells with CRISPR, to address the main bottleneck in T cell engineering. In Aim 1, we will develop viscoelastic stretching for ribonucleoprotein delivery and allogenic T cell engineering at one billion cells per minute, and we will characterize the biological effects of cell stretching on T cells. In Aim 2, we will use this method to generate allogenic chimeric antigen receptor (CAR) T cells from primary T cells, and assay their anti-tumor potency in vitro. In the R00 phase, viscoelastic cell stretching will be developed into a high throughput “cell surgery” platform for directly transplanting exogenous proteins and other nanoscale cargoes into the cytosol, towards the long-term goal of increasing the safety, accuracy, and efficiency of gene editing in human cells. Building upon the knowledge, skills, and technologies gained during the K99 phase, Aim 3 will focus on delivering DNA repair factors such as Rad52 in protein form for the first time, to temporarily increase the frequency of homology-directed repair and thereby safely increase the efficiency of precision gene editing with CRISPR. The training objective of this project is to provide Dr. Sevenler—who has a background in biomedical engineering—with additional scientific training from leading experts in microfluidics (Dr. Toner, lead mentor, MGH/HMS), immunology (Dr. Yarmush, co-mentor, MGH/HMS), gene & drug delivery (Dr. Bhatia, MIT), and T cell engineering (Dr. Maus, MGH/HMS, Dr. Choi, MGH/HMS and Dr. Ritz, DFCI/HMS). This additional training will prepare Dr. Sevenler to lead an independent research program in biomedical engineering focused on improved methods of reading and writing the molecular information of life.

NIH Research Projects · FY 2025 · 2022-08

The HuBMAP Computational Tools Component is responsible for development of standardized processing pipeline for all HuBMAP data, which is the foundation that enables joint storage, indexing, display, querying and mapping of HuBMAP datasets. A key innovative aspect that we have championed and, which as far as we know is unique for large consortia with several groups, platforms and data modalities is the fact that all HuBMAP pipelines we implemented provide uniform processing of all data from the same modality. Specifically, for each of these modalities we use the same computational algorithm for initial and downstream processing. For example, all scRNA-Seq datasets, regardless of which of the 7 platforms they were generated by, are processed by our Salmon quantification pipeline. This makes integration and comparison much easier across all HuBMAP data. In addition, all downstream analysis including dimensionality reduction, clustering, differential expression etc. are also performed using the same methods for all platforms making it easy to organize the display of the data on the portal and to index the data for quantitative queries. Similar pipelines have been developed for other modalities. In the production phase of the HuBMAP Consortium, we will extend these computational pipelines to support additional data types from new tissue mapping centers and other data providers. We will additionally extend our focus beyond single-cell image segmentation to support the mapping efforts of the Human Reference Atlas (HRA) collaboration, producing hierarchical links from cells to functional tissue units to higher-level anatomical structures.