University Of California, San Diego

NIH Research Projects · FY 2025 · 2024-08

Abstract Dr. Janna Raphelson is a Pulmonary Critical Care fellow at UCSD and she is applying for this F32 grant to further her development as an academic physician scientist. Throughout the time period of this award she hopes to develop an expertise in heart/lung/sleep physiology that will be the foundation of her path to independence as a clinician researcher. She will also pursue proficiency in biostatistical methods and trial design through formal coursework and direct mentoring, and gain exposure to the field of control of breathing. Her specific project for this period will focus on cardiovascular outcomes in patients with comorbid obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD), referred to as overlap syndrome (OVS). To our knowledge, no randomized trials have been performed in OVS leaving a major void regarding how best to treat >1% of the adult US population. The proposed work is a mechanistic study to evaluate the underlying mechanisms behind increased cardiovascular risk in patients with OVS compared to patients with COPD or OSA alone. The central hypothesis is that poor outcomes in OVS vs. COPD or OSA alone are driven by right and left heart remodeling which is more pronounced when exposed to both sustained and intermittent hypoxia in OVS as determined by cardiac MRI imaging metrics. Aim 1 will test the hypothesis that RV remodeling (as measured by RV mass index, primary outcome) will be more elevated in patients with OVS compared to patients with COPD or OSA alone. Given the high vascular risk among afflicted patients, the very high population prevalence of disease, and the lack of current data, further mechanistic research is imperative. Aim 2 will assess the ability of the BODE index, a commonly used clinical tool to predict mortality in COPD, to predict cardiac changes as seen on cardiac MRI. Exercise capacity limitations (an important component of the BODE index) have been linked to myocardial fibrosis and LV remodeling, thus in Aim 2 we hypothesize that high BODE index scores will predict a greater degree of myocardial fibrosis (primary outcome) and increased LV remodeling index (secondary outcome) by cardiac MRI in patients with COPD. This grant period will help launch Janna’s academic career as she is highly focused and deeply committed to making a scientific impact on patients afflicted with pulmonary and sleep related disease. She is working in a highly supportive environment with a mentoring team with a proven track record, and she is passionate about her vision of becoming a leading physician scientist running an NIH funded laboratory in the coming years.

NSF Awards · FY 2024 · 2024-08

Humans can perceive the three-dimensional world from a single two-dimensional image, even though such images do not contain explicit three-dimensional information. This capability in humans stems from two main factors: 1) the image of the three-dimensional world that matches the two-dimensional image content and 2) prior knowledge about the three-dimensional world. In statistics, this visual understanding process has traditionally been modeled using Bayesian inference, which combines the likelihood of something happening with a prior likelihood. However, this once prevailing theory has been challenged in the era of big data and deep learning, where three-dimensional understanding or inference is achieved by directly learning a mapping from two-dimensional images to the three-dimensional world. This award makes a timely effort by developing a new statistical inference technique, Bayesian Diffusion Models, which updates traditional Bayesian theory with a novel methodology to build advanced visual perception and cognition systems. As a general framework, the Bayesian Diffusion Model method is expected to have a profound impact on a wide range of tasks beyond visual perception. The ever-increasing power of generative models presents an unprecedented opportunity to revisit the analysis-by-synthesis methodology by carefully integrating the generative prior into the learning and inference of the posterior. The data under study is becoming increasingly rich, encompassing images, language, and three-dimensional data. In such contexts, data-driven techniques alone are insufficient to fully capture the posterior. Furthermore, despite significant advances in generative modeling, the synthetic content produced by state-of-the-art generative models has not yet demonstrated its potential in broadly enhancing analysis and recognition tasks. Intuitively, rich augmentation from synthetic data should play an important role in improving these data-intensive analysis tasks. This project aims to bring scientific and engineering guidance in utilizing the synthetic data for the improvements to various computer vision applications, including both closed-world and open-world 3D reconstruction, policy learning, image classification, and scene understanding. The novel Bayesian Diffusion Model (BDM) framework, grounded in Bayesian theory, promises to serve as a new statistical tool for a wide array of tasks in computer vision, autonomous driving, robotics, human-computer interaction, and computational biology. 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 MSM remain disparately impacted by HIV, with only 35% of US MSM with indications for PrEP having ever used PrEP. Meth use is an established and persistent driver of HIV incidence for MSM, with up to 33% of incident HIV infections in MSM attributable to stimulant use. There is increasing interest in delivering HIV prevention interventions via a mobile health (mHealth) platform, while implementing PrEP, to replicate the successes of mHealth delivery among meth-using MSM living with HIV. We seek to address this gap by evaluating the combination of state-of-the-art, multi-modal pharmaco-behavioral interventions for the greatest improvement in PrEP adherence (i.e., the “CHAMPION”). CHAMPION will combine two mobile health technologies: (PREPAPP with virtual cognitive behavioral therapy [CBT4CBT]). We aim to (1) Evaluate the feasibility and acceptability of CHAMPION, compared to a waitlist control, and (2) Evaluate the preliminary efficacy of CHAMPION on increasing PrEP adherence, compared to a waitlist control. To advance these aims, we will enroll 100 HIV-negative MSM who use meth in a 6-month randomized-controlled trial of PrEPAPP and CBT4CBT with a 3-month waitlist control. Eligible participants include those with meth use disorder (MUD). Enrolled participants will be randomized to either receive the CHAMPION intervention package, or have a 3- month usual care waitlist control. Behavioral assessments will be administered monthly and objective measures of PrEP adherence will be examined using dried blood spot (DBS) samples collected every 3 months. Feasibility will be assessed through treatment retention and engagement rates at month 3 and 6 follow-up. Preliminary efficacy will be assessed using DBS endpoints. In exploratory aims, we will examine preliminary efficacy on meth use and sexual risk behavior. This study will focus on MSM because meth is highly prevalent in this population and meth has been linked to HIV transmission and acquisition among MSM. If CHAMPION is efficacious, it may ultimately expand available strategies for MSM to reduce meth use, increase PrEP adherence, and reduce meth-associated sexual risk behaviors.

NSF Awards · FY 2024 · 2024-08

When two states face off in an international crisis, why does one state believe that its rival will capitulate, rather than escalate to war? Recent research suggests specific past actions – such as fighting in past crises or honoring alliance commitments – influence a state’s reputation as resolved to fight. Yet past studies have explored just one determinant of reputation in isolation from the others. This project will develop a comprehensive theoretical framework to explain which actions, or combinations of actions, matter most for building a reputation. It will also collect new data on cross-national historical events and cross-national survey data to establish which past foreign and domestic policy choices by states influence their likelihood of facing military challenges and the outcomes of international crises. This project advances U.S. national security in two ways. First, it will help to identify periods of heighted risk to U.S. interests by showing which specific domestic and foreign policy choices can create the impression of weak U.S. resolve. Second, it will explain how reputational damage from avoiding international conflict in one instance can be offset by other choices, such as alliance commitments or even domestic political actions. This means that the U.S. does not need to engage in every possible conflict in order to sustain a reputation as resolved to fight in future disputes. This project is the first to investigate how international reputations accumulate through many different past actions. Instead of simply studying whether past actions matter, it will provide a framework for assessing how much different actions matter relative to each other, and how they work in combination. The framework will bridge the gap between rationalist and psychological studies of reputation by using formal theory to predict how much actions that reveal certain psychological attributes will contribute to perceptions of resolve. The investigators will test expectations in a rigorous, multi-method manner. They will use U.S. and international survey experiments to provide causal estimates of the relative reputational impact of various actions. They will use quantitative coding of declassified intelligence documents, qualitative case studies, and interviews with U.S. officials to illuminate how elites utilize their rival’s diverse actions to estimate their rival’s resolve. Finally, they will collect novel cross-national data to understand which past actions influence reputations across history. 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

Overall - Abstract High- and low-level computations for coordination of orofacial motor actions Neuronal circuits in the brainstem integrate control of life-sustaining motor actions, such as breathing and feeding, with exploratory motor actions, such as sniffing, licking, nose and head turning, and, for rodents, whisking. All of these contain a rhythmic component that is entrained by the breathing cycle. What are the underlying circuits that produce these motor actions and how are they coordinated into flexible behaviors? Our hypothesis is that high-level rhythmic signals use feedback to modulate the phase of low-level oscillator activity on a cycle-wise basis. High-level broadband signals also regulate set-point and posture of effectors. Together, low- and high-level signals lead to coordinated and precise rhythmic behaviors to achieve sensory goals. We address our hypothesis using two theoretical concepts and a plethora of experimental procedures. One theoretical concept is control theory. This concept emphasizes internal models, that is, computations that yield signals to drive a physical plant, such as the vibrissae or the tongue, that respect the innervation of the musculature. Control theory also emphasizes the role of feedback signals to correct the timing of rhythmic actions. The second theoretical concept is coupled oscillators circuits, one for each rhythmic action with an overall "coordinator". These guide schemes for the continual adjustment rhythmic action phases to form a precise behavior. Theoretical guidance was pivotal toward the discovery of the oscillator for whisking, identify a mechanism brain used to create a hierarchy of oscillators, and identifying modularity in the control of movement. We seek to discover a second fundamental oscillator in the brainstem, one that controls chewing and licking. In parallel, we will complete a biomechanical model of the tongue that includes changes in shape and turgidity based on motor innervation of the muscles and the control of blood flow by local parasympathetic neurons. Together with whisking and joint vibrissa and head movement, these are a trifecta of targets for high-level control. A novel concept in our proposal is the fine control of rhythmic motion by high-level feedback to refine the relative timing of different rhythm motor actions. Thus head position, tongue position, possibly whisker position are optimized in the context of a behavior. We address this possibility through three interdependent approaches: anatomical tracing of molecularly identified high-level cell types to molecularly identified low-level targets in the medulla; recording and perturbing signals in superior colliculus that influence head orientation and whisking; and recording and perturbing cortical signals that influence licking. The collective expertise of our Team bridges state-of-the-art anatomical, behavioral, computational, molecular, and physiological technologies. We have historically adhered to the highest standards in experimentation, analysis, and theory. Critically, we are joined by top trainees in a diverse workforce committed to progress on motor control, and we are dedicated to educating our trainees in a culture of curiosity and scholastic excellence.

NSF Awards · FY 2024 · 2024-08

This project seeks to advance wireless communication by incorporating a cutting-edge type of reconfigurable antenna, known as a dynamic metasurface antenna (DMA), into multiple-input multiple-output (MIMO) wireless communication systems. DMAs consist of tightly packed reconfigurable elements that can provide high beamforming gains at very low power. Unlike conventional antennas, DMAs are passive devices that use tunable components to reconfigure each element and achieve a desired response. This project develops methods to integrate DMAs into MIMO communication to form what is called the tri-hybrid MIMO architecture. The main novelty in the tri-hybrid architecture is the integration of digital beamforming, analog beamforming and antenna reconfiguration all together. If successful, this project will facilitate the development of MIMO wireless communication systems with ten times larger apertures than previously deployed in commercial wireless systems like cellular systems. As a result, such systems will be able to serve more users simultaneously with better spectral efficiency and higher data rates than achieved by state-of-the-art commercial systems today. By developing technologies that consume less power and enable the formation of large, dense arrays, this project will contribute to the progress of science and technological innovation in wireless communications and array processing. From a scientific perspective, this project will result in the development to new approaches for dealing with tri-hybrid MIMO architectures that combine elements of signal processing, circuits and electromagnetics. It will also facilitate the development of new approaches for configuring tri-hybrid MIMO links, some that are data-driven and based on machine learning. The outcomes of this project will improve wireless cellular connectivity including data rates and reliability. This research project aims to develop new models, analyses, algorithms, and design insights through the advancement of the tri-hybrid MIMO architecture. The key component of this new MIMO configuration is the use of reconfigurable antennas in the form of DMAs, in conjunction with analog and digital beamforming. The proposed research will develop key aspects of the tri-hybrid MIMO architecture by leveraging tools from communication theory, electromagnetics, and circuit theory. Utilizing existing circuit and antenna models, the project will create MIMO input-output models that accurately capture waveguide attenuation, mutual coupling between elements, and the impact of reconfiguration on the channel. These models will be used to investigate how DMA reconfiguration constraints affect communication performance and to determine necessary adjustments for other signal processing components in MIMO systems. Specialized algorithms will be developed to address key challenges when incorporating DMAs into a MIMO communication architecture, including over-the-air beam calibration and multi-user beam training, utilizing tools such as machine learning. Insights from the analysis and modeling will guide the design of DMA-based transceivers to maximize spectral efficiency and minimize power consumption. Comprehensive evaluations will demonstrate the effectiveness of the developed designs, algorithms, and analyses by leveraging a combination of electromagnetic, circuit, and communication system-level simulations. The outcomes of this research will provide a comprehensive solution for integrating reconfigurable antennas into large-scale MIMO systems, significantly enhancing future wireless communication technologies. 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

The chemical and physical properties of molecules are determined by their electronic structure. Computing the latter starts with finding the molecular ground state because this knowledge helps compute many properties, such as their dipole moment and charge density. Since classical algorithms are computationally expensive, a tremendous academic and commercial effort has made advances in using quantum computers as an efficient future alternative. These efforts are based on the quantum version of classical bits known as qubits. However, electrons in a molecule are not qubits but rather fermions, and translating fermions into qubits is resource-intensive in computation and storage. This project aims to complete the construction of a proof-of-principle quantum computer based on fermions to determine the ground state of molecular systems. The goal is to set the groundwork for a fermionic computer that is better than classical supercomputers at finding the electronic structure of molecules, hopefully setting the stage for quantum chemistry computations that will impact industry and medicine. Along with these efforts, this project will have an educational impact by training graduate and undergraduate students in quantum science and technology. The project impacts will broaden by creating a Young Quantum Physicist Program to bring middle and high-school students, with an effort to achieve a diverse group representing society, to our labs and introduce them to the rapidly developing quantum technology. This proposal aims to leverage the latest advances in building qubit-based quantum computers using neutral atoms in optical tweezers to assemble and benchmark a new one based on fermions. This quantum computer will implement a hybrid classical-quantum algorithm called Variational Quantum Eigensolver using fermions. This implementation will find the ground state of small molecules and develop new tools and approaches to apply the algorithm to larger molecules. Obtaining this molecular ground state is the first step in calculating many properties that determine the molecules’ physics and chemistry. Starting from a degenerate fermi gas of strontium atoms, we will load a register array of 20 by 20 optical tweezers with atoms in their electronic and motional ground states. Using a second tweezer that traps particles in the excited clock state, but not those in their ground state, and another tweezer tuned on the clock transition, we will implement an effective tunneling gate through shuttling and optical pulses on this transition. A fourth tweezer will drive a Rydberg blockade on pairs of tweezers interacting in the VQE circuit. Our goal is to achieve state-of-the-art performance in all of these operations. With this toolbox, we will find the ground state of small molecules. Finally, we will apply the intuition gained in optimizing the classical-quantum algorithm for small molecules, as well as in circuit depth and measurement, to engineer an integrated algorithm for larger molecules —a simultaneously hardware-efficient and chemically-inspired VQE— possibly resorting to quantum machine learning. Most importantly, the goal at the end of the project is to establish a roadmap for scalability and achieving optimizations of fermionic quantum computers based on neutral atoms beyond the capacity of classical computers. 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

This proposal concerns research in combinatorics, focusing on a new approach involving pseudorandomness. The general philosophy is that rich structures hide inside pseudorandom combinatorial structures, such as graphs and hypergraphs, and can be found using a combination of spectral, geometric and probabilistic methods. Motivation for their study comes from striking connections and applications to algorithms, coding theory, finite geometry, information theory and cryptography. Their study has led to major breakthroughs on decades-old problems, and in particular in Ramsey Theory, which is underpinned by the qualitative statement that in any sufficiently large combinatorial structure, a relatively large uniform substructure must exist. The new approach marks a shift in focus and direction, away from purely random objects to pseudorandom objects, and leads to exciting questions relative to explicit constructions of codes and algorithms for finding the sought-after structures. This project will provide research training opportunities for students. Pseudorandom graphs and hypergraphs are central to an area known broadly as extremal combinatorics, and have a richly developed theory over the last few decades. The main idea is to define deterministic properties of a combinatorial structure which force it to behave in many ways similarly to a purely random object. The author and co-researchers discovered in recent work that interesting extremal and Ramsey graphs appear inside pseudorandom graphs, in the sense that a simple random sample tends to produce such graphs. This leads to the solution to classical mathematical problems, some of which have been studied for almost a century, such as the growth of Ramsey numbers. An interesting line of questioning is whether such objects can be constructed without randomness, for instance the promising approach that an exponential construction for diagonal Ramsey numbers could be found by sampling from suitable pseudorandom graphs. This project will develop a deeper analysis of these questions using a broad variety of mathematical tools, including probabilistic and polynomial methods and finite geometric and spectral methods, in order to tackle the most central and important problems in the area. 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

Over the past decade, Research Software Engineers (RSEs) have been increasingly recognized by academia and national labs for their crucial role enabling and accelerating scientific and engineering discovery. The acknowledgement is evident in many projects and initiatives such as the founding of eight Research Software Engineer Associations worldwide, the NSF Cybertraining INTERSECT for RSEs, and the initiative Better Scientific Software driven mostly by national labs. Since 2021 NSF has explicitly included the term "RSE" as a Cyberinfrastructure professional in solicitations such as the NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) that has been open for submissions annually since 2018. The US-RSE Association is the leading professional community of research software engineering practitioners in the United States. The organization and its ~2500 members are dedicated to creating research software that is fit for purpose, sustainable over the long-term and reliably developed and supported. The members come from diverse backgrounds but share a common goal: to support and promote the role of research software and research software engineers in driving innovation and solving complex problems. The US-RSE Association has members from all over the country, representing a diverse range of research institutions, including academic institutions, national labs, and industry. The members work in various scientific fields, including but not limited to physics, life science, chemistry, geosciences, engineering, and social sciences. The first-ever US-RSE conference in 2023 hosted 250 attendees and over a hundred virtual attendees for online tutorials. Attendees included students, researchers, software developers, IT staff, data professionals, and educators. This travel grant allows more students and early-career researchers to be involved in US-RSE 2024. US-RSE 2024 is the major event for the RSE community in the US to build the community, to discuss challenges and solutions in research software engineering. Topics of interest for the 2024 conference include past or present research software engineering research and practice, research software engineering techniques, frameworks, libraries, research data management, reproducibility, and software sustainability. The meeting also explores diversity, equity, and inclusion issues in research software engineering, workforce development, and building a robust and sustainable RSE profession. The knowledge transfer can be transformative between different research domains and technical content. The US-RSE conference sets the stage for learning, engaging and empowering the different stakeholders in the community and to foster innovation and collaboration. Research software is crucial for many research areas that need computational tools, addressing large challenges such as genomics, pandemics, climate change, global sustainability on food, water and land use driven by growing population and rising per capita incomes. By attending the US-RSE Conference, students and early-career researchers will gain exposure to the latest advancements in research software engineering. This experience will provide critical skills and knowledge that are essential for growth and success in the field. The opportunity to engage with cutting-edge discussions will enhance technical competencies and inspire innovative approaches in research endeavors. Providing travel grants for students and early-career researchers will include a diverse audience and support underrepresented minorities. 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

This project is composed of two parts. The main objective is the study of mathematical models of fluid motions, and more specifically creation of small-scale structures and singularities in fluids. This is a question of great importance in mathematics as well as in physics and engineering, as it is related to fluid turbulence and also explores how well the theoretical models describe real world phenomena in extreme situations. The project will focus on singularity creation for motions of fluids in porous media (e.g. underground aquifers), in atmospheric science models, as well as for dynamics of fluids near walls and other boundaries. The second objective of the project is the study of propagation of reactive processes (e.g. forest fires) through combustive media. While the dynamics of such a process may intricately depend on small scale variations in the environment, the goal of this part of the project is to demonstrate that in many situations averaging of these variations over large regions results in a more regular and predictable large scale and long-term behavior of the process. This part will also involve the study of propagation of bacterial colonies through nutrient-rich environments, and the enhancement of its speed due to the phenomenon of bacterial chemotaxis. The proposal will provide opportunities for the involvement of students and junior researchers in the research projects. The primary focus of this project is the study of singularities and singular solutions for several nonlinear partial differential equations (PDEs) that serve as models of incompressible fluid dynamics. This includes motion of fluids in porous media on domains with boundaries, such as aquifers sitting on top of impermeable rocky layers; atmospheric science models such as generalized surface quasi-geostrophic (gSQG) equations; as well as Euler equations, modeling motions of ideal fluids, on planar domains with irregular boundaries. In some of these models the relevant local well-posedness theories have not been found yet, so their development will also be an integral part of the project. A secondary focus of the project is a better understanding of large-scale behavior of reactive processes spreading through heterogeneous media, specifically development of a homogenization theory for the nonlinear reaction-diffusion PDE that models such processes occurring in multi-dimensional random media. The goal is to show that under fairly general hypotheses, large scale behavior of solutions to this model is governed by much simpler homogenized PDE that capture the effects of the random variations in the medium averaging out in the long term. In addition, effects of chemotaxis on the speed of propagation of bacterial colonies through nutrient-rich environments will also be studied. 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

SUMMARY Alzheimer's disease (AD) affects over 50 million people worldwide. In the vast majority of patients, AD develops sporadically in the absence of any known etiology other than advanced age and is further influenced by a plethora of etiological mechanisms. Old age stands out as the most important risk factor for the development of AD in most cases. The first pathological events leading to mild cognitive impairment (MCI) start many years before the onset of symptoms. Identification of the mechanisms that cause MCI, and those that trigger the conversion of MCI to AD, are of major interest, as they promise strong therapeutic benefit via halting or slowing disease progression. However, a much better understanding of how the multiple heterogenous risk factors for MCI/AD, which include polygenic risk variants and biological aging, converge on key molecular pathways that initiate and drive MCI are needed. The teams around Dr. Mertens have established that direct conversion of human patient fibroblasts into induced neurons (iNs) preserves signatures of cell aging and sporadic AD, and allows for the detection of cellular pathologies and disease drivers. Patient-derived iNs reflect an adult-like neuronal identity, and they stand out as a unique and complementary model system to animal and iPSC-based models to study the age- dependent pathogenesis of MCI/AD. Importantly, patient-specific iNs capture the strongest risk factors, the genetic makeup and the biological age, of a patient at a given stage, and we here harness MCI patient iNs as a disease stage-specific model system to investigate the early trajectory of MCI/AD in human neurons. Preliminary evidence indicates marked MCI-related signatures in iNs that intersect with the transcriptomic, epigenetic, and metabolic signatures of accelerated aging, and partially overlap with signatures of AD iNs. This project will integrate polygenetic risk scores for AD with deep and unbiased multi-omic phenotyping, and will assess effects of impaired MCI neurons on human astrocytes and microglia in 3D microcarrier-based co-cultures. The teams will further assess how the underlying epigenetic landscapes and DNA binding patterns of disease factors associate with age acceleration and MCI neuronal phenotypes, and will provide a deep functional characterization of the cells. The goal is to better understand early MCI/AD disease ethology, and to exploit the comprehensive multi-layered information emerging from this project for new treatment strategies.

NIH Research Projects · FY 2026 · 2024-08

PROJECT SUMMARY There are few effective treatment options for smoking cessation. The identification and validation of reliable biomarkers for tobacco use disorder has the potential to greatly facilitate treatment development and improve clinical outcomes. Attentional bias, a behavioral correlate and potential biomarker of addiction, is consistently observed in nicotine users and is related to the risk of subsequent relapse following smoking cessation. Our group has developed and tested a novel virtual reality (VR) nicotine cue exposure paradigm with promising preliminary results, including obtaining large nicotine-related attentional bias effect sizes. Thus, the goal of the proposed project is to validate the attentional bias neurophysiological marker derived from the VR Nicotine Cue Exposure paradigm (VR-AB) as a biomarker of tobacco use disorder and investigate its potential as a predictive marker and candidate surrogate endpoint for use in the development of novel pharmacologic interventions for smoking cessation. To achieve the goals of this project, 200 daily tobacco cigarette users will be assessed on the VR Nicotine Cue Exposure paradigm then pseudo-randomized (matched on age and sex) to receive varenicline or placebo (n per group=100). Following eight days of titration, participants will be assessed again on the VR Nicotine Cue Exposure paradigm at target dose of varenicline (1 mg twice daily). They will then be followed via mobile assessments for eight days on the target dose to assess short-term nicotine use behaviors. Varenicline will be used as a pharmacological challenge to validate the VR-AB marker given this medication’s proven ability to attenuate nicotine craving/cue salience and reinforcement. In accordance with NIDA’s Notice of Special Interest on Biomarker and Biotypes of Drug Addiction (NOT-DA- 20-012) and the FDA’s Biomarkers, EndpointS, and other Tools (BEST) resources, the broad aims of the proposed project are to: (1) validate the reliability of the VR attentional bias (VR-AB) marker and estimate the VR-AB effect size as moderated by varenicline, (2) evaluate VR-AB as a predictive biomarker for response to varenicline, and (3) evaluate VR-AB as a candidate surrogate endpoint by assessing the predictive validity of the VR-AB biomarker on short-term nicotine use behaviors as moderated by varenicline.

NIH Research Projects · FY 2025 · 2024-08

Project Summary The proposed Conference on ADRD Research among Diverse Latinos (CARDL) is based on the cells-to-society framework, and uses the SOL-INCA conceptual model for addressing Latino cognitive aging and ADRD. The HCHS/SOL and SOL-INCA studies have large samples of diverse and representative Latinos, including those of Mexican, Puerto Rican, Central American, Cuban and Dominican origin. Over 14-years of longitudinal cognitive and functional assessments, plasma Amyloid Tau Neurodegeneration (ATN) biomarkers, neuroimaging, deep behavioral and cardiometabolic phenotyping, and multi-layered `omics, these study data provide fertile resources for new scientists of diverse cultural and disciplinary backgrounds to stimulate and produce new brain aging science on diverse Latino groups facing excess ADRD disease burden. This conference series will create a unique space for bringing leading and aspiring scientists together to work on high-priority scientific areas, including methodological, behavioral, social and neuroscientific ADRD-related topics. Conference participants will learn about the “state of the science” of Latino cognitive aging, and the “state of the data” by hearing about existing studies in the topic areas. They will also learn the “state of the methods” necessary to address complex study designs, meet with leaders in these respective fields, and have the opportunity to apply their understanding by developing new research questions for manuscripts and novel specific aims for grant proposals. The conference series will result in a measurable increase in the scientific output of early-stage (or new to the field) scientists, and will promote the development of biomedical research led by diverse investigators focused on between and within Latino population differences in cognitive aging outcomes.

NIH Research Projects · FY 2024 · 2024-08

Alzheimer disease (AD) exacts enormous personal and financial burdens in the aging. People with Down syndrome (DS) (i.e., trisomy 21, HSA21) are at markedly increased risk of AD, a disorder called DS-AD. The clinical and pathological hallmarks of AD are replicated in AD-DS. More than 80% of those living beyond age 65 are diagnosed with DS-AD. The emergence of DS-AD is thus essentially inevitable in the DS elderly and serves as the leading cause of death. DS-AD thus constitutes the largest population in which a genetic lesion causes AD. An important insight into DS-AD is that increased dose of the gene for APP, present on HSA21, is necessary. Findings in mouse models of DS-AD concur, demonstrating a necessary role for increased APP dose and expression for DS-AD neurodegenerative phenotypes. Studies of DS-AD mouse models have provided important insights, but no current model captures all the pathological features of DS-AD. Three important missing features are: amyloid plaques, congophilic angiopathy, and neurofibrillary tangles (NFTs). We propose to develop and validate a DS-AD model to capture these phenotypes. We will genetically modify the TcMAC21 mouse. This mouse carries an essentially full copy of HSA21 in addition to two copies of homologous mouse chromosomes. To replicate DS-AD amyloid pathology we will humanize the Aβ sequence in mouse APP by crossing with mice in which the Aβ peptide sequence in mouse APP has been humanized, thus conferring a human pattern for processing with increases in APP-C99 and its Aβ products. To introduce human-like tau pathology, including NFTs, the resulting mouse (TcMAC21:APP/hu/hu/hu) will be crossed with mice deleted for mouse tau that express a transgene encoding wild type human Tau. In addition to amyloid and tau pathology we predict the genetically modified TcMAC21 mice will replicate key DS-AD phenotypes. Our hypothesis is that the TcMAC21 mouse will model key pathological features and age-related changes in molecular, cellular and circuit function characteristic of DS-AD. In the R61 Phase: Specific Aim 1 (Project Years 1-3), we will demonstrate feasibility and scale of use, and internally validate it by documenting measures of molecular, cellular, and synaptic age-related phenotypes characteristic of DS-AD with rigor, precision, reliability, and sensitivity, and dependence on APP gene dose. Go/NoGo criteria must be satisfied for moving to the R33 Phase: Specific Aim 2 (Project Years 4,5) in which we will externally validate, through demonstrations of : face validity: 1) measures of cognition; 2) clinical biomarkers, including Aβ42, Aβ40, p-tau species and NFL; construct validity: 1) presence and structure of amyloid plaques and congophilic angiopathy; 2) aggregates of phosphorylated tau; 3) neuroinflammation, including changes in microglia and astrocytes; 4) deficits in synapse number and function; 5) neuron loss; and 6) transcriptomic/genomic signatures; and predictive validity: 1) demonstrate that reducing APP gene copy number prevents/reverses DS-AD linked signatures; and 2) show that clinically feasible interventions prevent and/or reverse DS-AD phenotypes. A valid model will accelerate the ability to understand and treat DS-AD.

NIH Research Projects · FY 2025 · 2024-08

SUMMARY Dilated cardiomyopathy (DCM) associated heart failure is a leading cause of death and new therapeutic strategies are needed. Pathogenic variants in over 50 genes contribute to DCM, but the molecular mechanisms of disease are poorly understood. Much remains to be done to understand disease mechanisms and translate the basic science into therapeutic strategies. The goal of this project is to identify targeted therapeutic strategies for DCM. This goal aligns with my long-term career goal to become an independent researcher leading an academic lab that focuses on better understanding human tissue-specific post-transcriptional regulation of gene expression and developing mechanism-based therapeutics. My primary hypothesis, supported by my preliminary results, is that some of the microRNA (miRNA) upregulated in end stage heart failure (HF) exert a compensatory effect on the disease phenotype and that some of these miRNAs have mutation-specific beneficial effects while others have effects independent of etiology. I propose to study the mechanisms of both kinds of miRNA to identify new therapeutic targets. In my earlier work, I developed an experimental platform to quantify several of the physiological phenotypes of DCM in induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs). I used this system to identify a potential therapeutic strategy (published and patented) for a specific variant of DCM. I used this system in my preliminary work for this project to identify several miRNAs that ameliorate contractile phenotypes in iPSC-CMs carrying DCM causal variants selected for their diverse molecular etiologies (PLN, RBM20, and TNNT2). As hypothesized, some miRNAs had etiology-specific beneficial effects while others demonstrated improvement across all etiologies. My first aim is to test candidate miRNA targets to identify the mechanisms through which they exert the beneficial effect in iPSC-CMs. My second aim is to identify the target genes of candidate miRNAs that regulate sarcomeric and contractile functions and to test their effect in an alternative in vitro model (Engineered Heart Tissues) and in a mouse model of DCM. My third aim is to test the hypothesis that the target space differs for the miRNAs that have a mutation-specific effect and those that have a therapeutic effect on all DCM lines by comparing the targets of mutation-specific and non-specific therapeutic miRNAs. This project will expand our understanding of heart failure mechanisms and identify new points of intervention for drug development. This project will also identify the etiology-specific and etiology-independent disease mechanisms leading to DCM and test whether these differences can be exploited therapeutically. The knowledge and tools generated will be of value to the DCM community and serve as a foundation for my subsequent, independent work in developing personalized, mechanism-based therapeutic strategies.

NIH Research Projects · FY 2025 · 2024-08

The distinctive features of humanity—our intelligence, creativity, language, as well as our ecological and demographic success—are thought to be the result of evolutionary changes elicited by several non-mutually exclusive genetic mechanisms. One means by which this may be achieved is through the action of ancient DNA sequence that have undergone rapid evolution specifically in the human lineage. These sequences—called human accelerated regions (HARs)—have since been shown to be almost exclusively non-coding sequences. Of HARs that have been evaluated functionally, 30 to 50% are transcriptional enhancers. It has been hypothesized that rapid evolution of these HAR enhancers in the human lineage has driven changes in gene expression that ultimately yielded useful human-specific traits. In support, a handful of HAR enhancers have been shown to regulate neighboring genes in a temporal and/or spatial-specific manner. However, to date, none of the identified >3000 HARs have been definitively shown to confer human-specific traits. This application is focused on one particular HAR—called “HAR123”—that has characteristics that we believe make it a strong candidate to confer human-specific traits. HAR123 is a neural enhancer highly conserved in mammals and marsupials, but has undergone rapid evolution specifically in the human lineage. HAR123 strongly promotes the generation of human neural progenitor cells (NPCs). In support of human HAR123 having human-specific functions, we found—through single-cell RNA-sequencing (scRNAseq) analysis—that human HAR123 drives cellular and molecular events that differ from those elicited by chimpanzee HAR123. To examine its function in vivo, we deleted HAR123 in mice and found that this causes a specific defect in cognitive flexibility, as determined by two independent behavioral tests. Together, these data lead to our central hypothesis that HAR123 is an ancient neural enhancer that has acquired new properties in the human lineage, leading to changes in gene expression that impact NPC generation and, ultimately, cognitive flexibility. In this application, we propose to address this central hypothesis. Towards this goal, we will elucidate the cellular and molecular functions of mouse, chimpanzee, and human HAR123. Aim 1: to decipher the roles of HAR123 in human neural cells, including NPCs, with a focus on how HAR123 acts as an enhancer. We will investigate how human HAR123 differs—at both the cellular and molecular level—from chimpanzee HAR123 in its impact on NPC genesis and neural development. Our planned studies are designed to elucidate the selective forces that have acted on HAR123 during primate evolution. Aim 2: to elucidate the neural roles of HAR123 in vivo. In this Aim, we will investigate the cellular and molecular mechanisms underlying the intriguing cognitive flexibility defect we have defined in HAR123-KO mice. Through behavioral, cellular, and molecular analyses of human and chimp HAR123 knock-in mice, we will elucidate the evolving functions of HAR123 in an in vivo context. The proposed research addresses a fundamental question that is currently a black box in the field.

NIH Research Projects · FY 2024 · 2024-08

ABSTRACT A formidable barrier to a cure for HIV-1 infection is the existence of latently infected cells that sporadically activate HIV transcription during antiretroviral therapy (ART) and reignite widespread virus replication upon cessation of ART. Viral RNA expressing (vRNA+) cells are detected at low frequencies in secondary lymphoid tissues (SLT) of people with HIV (PWH) on ART, constitute the major HIV RNA reservoir in the human body, and are likely the principal source of rebound viremia when ART is stopped. Little is known about the microenvironment of vRNA+ cells in SLT of PWH during ART. In lymph nodes and spleen from PWH on prolonged ART the majority of vRNA+ cells reside outside of B cell follicles and only a minority are TFH. We observed that vRNA+ cells are preferentially located adjacent to B cells not only in follicular, but also in extrafollicular regions (EF) of SLT in PWH and SIV-infected rhesus macaques on ART; frequencies of B cells in EF of SLT correlate with frequencies of vRNA+ cells. In an ex vivo tonsil model of HIV infection, germinal center B cells (GCB) upregulate HIV expression in TFH. Gene expression analysis revealed GCB induce expression of multiple cytokines including IL-10, pro-survival molecules, and markers of immune activation. Further studies revealed that upregulation of HIV expression is not confined to GCB, but that multiple subsets of tonsil B cells upregulate HIV replication in both TFH and non-TFH CD4+ T cells. IL-10 was shown to augment survival of HIV-expressing cells in the tonsil model, and we observed that the majority of vRNA+ cells in spleen from two PWH expressed IL-10. We hypothesize that B cells are major drivers of vRNA expression in CD4+ T cells in secondary lymphoid tissues of PWH on ART through induction of pro- survival factors, including IL-10, as well as immune activation. In Aim 1, we will determine the location, phenotype, and microenvironment of vRNA+ cells in spleen, lymph nodes, and ileum of PWH on prolonged ART using state-of-the-art immunostaining techniques to assess the hypothesis that vRNA+ cells preferentially exist adjacent to B cells and express pro-survival and activation markers. In Aim 2, we will evaluate the impact of SLT B cells on HIV expression in non-TFH CD4+ T cells, and evaluate the role of IL-10 and immune activation using HIV GFP reporter viruses in SLT from people without HIV infection, as well as spleen and lymph node tissues from people with HIV infection on prolonged ART. In Aim 3 we will determine whether depletion of B cells leads to reductions in numbers of vRNA+ cells in SLT during ART using SIV-infected rhesus macaques. Collectively, these studies will provide a wealth of new information on the cells that express HIV in SLT and factors within their microenvironment that promote or impair HIV expression during ART. This knowledge could be used to develop strategies to reverse or alternatively enhance viral latency in vivo to achieve a functional remission of HIV.

NIH Research Projects · FY 2025 · 2024-08

immunomodulatory therapies. Although these breakthroughs unleash the immune system and can be deadly to tumors, there are a high percentage of cancers that fail to respond. One complicating aspect is tumor heterogeneity, both within the same cancer type and within a single patient. This aspect is especially prominent in pancreatic adenocarcinoma (PDA), which is notoriously resistant to many frontline immunotherapies and has a low 5-year survival rate. Although mouse models have made research into PDA more accessible, these models frequently fail to capture the spectrum of tumor heterogeneity in human PDA. Innovation. To address this limitation, I will use a unique collection of mouse pancreatic tumor clones with distinct and reproducible responses to treatment, mimicking the tumor heterogeneity seen in the clinic. This will provide me with unparalleled comparative and combinatorial power to interrogate the tumor microenvironment. Additionally, my proposed experimental approach will leverage emerging high-content imaging methods that are able to reveal the phenotype, activity, and spatial organization of the tumor microenvironment in situ.

NSF Awards · FY 2024 · 2024-08

Modern artificial intelligence (AI) and machine learning (ML) systems are trained using massive datasets and complex models combined with optimization algorithms. Traditional "greedy" methods, which make incremental improvements at each step, often fall short in both efficiency and adaptability when faced with problems at this scale. This project proposes a novel framework for algorithm design based on the Hamiltonian dynamics, a fundamental concept in physics and mathematics that uses the conservation principles to describe the interaction of multiple objects. Such dynamics appear naturally in many branches of computational sciences but are rarely used as a fundamental principle in algorithm design. Motivated by emerging challenges in ML, this project aims to develop a systematic methodology that leverages Hamiltonian conservation to solve problems in optimization, random sampling, and game theory. This project has the potential to revolutionize our understanding of computational and statistical problems by introducing a new class of algorithmic principles for training modern ML systems. This project will also advance the curricula for algorithms in computer science and electrical engineering, with unique training opportunities for undergraduates and graduate students, the development of open-source software, and a dissemination of ideas via joint workshops. This project will explore a framework called “the LCP scheme”, which stands for Lift, Conserve, and Project. This proceeds by taking a parameterized decision space, appropriately lifting the problem to incorporate additional variables, applying the conservation property of the Hamiltonian dynamics to update the problem state in the augmented parameter space, and finally projecting the state back into the original space. This scheme provides a fresh perspective for analyzing several known algorithms, and developing new ones, in the domains of optimization and random sampling, as well as to understand the behavior of players in multi-agent systems. This project will develop a robust algorithmic complexity theory for implementing the continuous-time Hamiltonian dynamics as discrete-time sequential procedures with an emphasis on the large-scale modern applications. By introducing concepts such as invariance, conservation, and the principle of least action, this project will provide a more nuanced view of the state evolution of computational objects that can help overcome many limitations of the standard algorithm design paradigm. 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 Day/night cycles profoundly impact animals’ physiology and behavior to allow adaptation to rhythmic environmental cues. Daily rhythmic behaviors are believed to be patterned by central clock neurons. However, the physiology of primary sensory neurons, such as olfactory receptor neurons (ORNs), can also exhibit oscillatory changes, but whether such changes can guide rhythmic behaviors remains undetermined. Progress is further hindered by the lack of information on whether or which odor-guided behaviors are regulated by day/night cycles. This proposal leverages the powerful genetic toolkit and tractable olfactory system of D. melanogaster to address these fundamental yet outstanding questions. Preliminary studies showed that pheromone-sensing ORNs exhibit higher responses in flies at subjective night (henceforth referred to as night flies) than in flies at subjective day (henceforth referred to as day flies). Importantly, this heightened pheromone sensitivity in night flies in turn elevates odor-guided social behavior. Mechanistically, the day or night modulation is respectively signaled via two neuromodulators. Preliminary experiments further showed that in theses ORNs, the day/night modulation of olfactory acuity requires a cation channel subunit whose expression likely reduces neuronal input resistance or causes accommodation, thus lowering spike response frequency. These findings led to the hypothesis that day/night cycles, through the antagonistic actions of two neuromodulators, up- or down-regulate the cation channel in ORNs to dynamically modulate olfactory acuity and odor-guided behavior. To test this central hypothesis, this research will determine how the two neuromodulators antagonistically regulate ORN responses (Aim 1), characterize the effector(s) capable of altering olfactory responses in the target ORNs (Aim 2), and investigate the generality of the neuromodulatory mechanism across ORN types (Aim 3). The mechanistic insights expected from this research will advance our understanding of how day/night cycles influence olfactory physiology and behavior. Of further significance, this research demonstrates that neuromodulatory impairment at the ORN level precludes the potential influence of central circadian mechanisms on odor-guided behavior. The idea that peripheral sensory neuromodulation plays a critical role in gating day/night-regulated behaviors is conceptually innovative. Furthermore, in rodents, the neuronal responses to ethologically relevant odors are also heightened at subjective nighttime. Therefore, success of this research will likely carry broad implications across animal species.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY: Individual humans and animals can lie anywhere along a continuum of high to low risk- taking propensity. Several neuropsychiatric conditions are characterized by extremes of risk-taking propensity. For example, patients with pathological anxiety or anorexia nervosa show high risk aversion, while patients with gambling disorder, or substance use disorder exhibit low risk aversion. Both high and low risk-taking propensity are thought to drive and maintain maladaptive behavior in these disorders. Therefore, novel pharmacological agents that shift risk-taking propensity closer to population mean values could provide novel treatments for these disorders. Although risky decision-making paradigms exist for humans and animals, behavioral assays that also elicit robust and translationally relevant neurophysiological markers are lacking. Here, we propose to optimize, pharmacologically test, and mechanistically probe a novel in vivo behavioral and neurophysiological assay to be used for translational studies and for screening for novel drugs to treat psychiatric conditions associated with high or low aversion to risk. Recent work in wild-type rats suggests that the activity of dopamine receptor 2 expressing medium spiny neurons (D2-MSNs) in the nucleus accumbens core (NAcC) encodes prior outcomes and predicts future choices during a risky decision-making operant task. First, we will manipulate operant task parameters to establish that the task fully captures both extremes of risk- taking propensity, and also measures constructs underlying risky decision-making, including reward and loss sensitivity, motivation, and goal-directed versus habitual responding. We will also identify neurophysiological markers of risky versus safe choices during the task using fiber photometry and whole brain local field potentials (LFP). We predict that during the decision period immediately preceding safe or risky lever selection, increases in both NAcC D2-MSN activity and theta oscillations within a corticostriatal circuit including the NAcC/ventral striatum (VS), medial prefrontal cortex (mPFC), and orbitofrontal cortex (OFC), will precede safe choices. In contrast, we predict that decreases in NAcC D2-MSN activity and theta activity within this corticostriatal circuit will precede risky choices. Theta activity within corticostriatal brain regions will provide a non-invasive and translationally relevant neurophysiological marker of risk-propensity, while NAcC D2-MSN activity will provide a marker of risk-propensity for drug screening using animals. Second, we will test whether drugs with known effects on risky decision-making in humans produce the same effects on the behavior of rats in the optimized paradigm. We will assess the effects of the dopamine D2/D3 agonist pramipexole, which increases problem gambling in Parkinson’s Disease, and the D2/D3 antagonist sulpiride, which increases risk aversion in humans. We will also determine drug effects on NAcC D2-MSN activity and corticostriatal theta. Third, we will use intra-NAcC drug infusions and optogenetics to test whether changes in NAcC D2-MSN activity during the decision period of the operant task plays a causal role in safe versus risky decision-making.

NSF Awards · FY 2024 · 2024-08

This award supports studies of mathematical and computational analysis methods to advance our scientific understanding of gravitational interaction. This study will focus on a series of problems where strong gravitational fields play an interesting role in a variety of astrophysical situations. These include studies of the properties of neutron stars, black holes, gravitational waves, and the large-scale structure of the universe itself. The new insights discovered by this project could have impacts in a wide range of scientific areas that extend well beyond gravitational astrophysics. This research on neutron-star physics should lead to more accurate methods of measuring the detailed properties of the extremely high-density material inside neutron stars. These results could have an impact on earth-based laboratory nuclear physics, in addition to its contribution to astrophysics. This project will also develop new computational methods for performing simulations of gravitational effects on the large-scale structure and evolution of the entire universe. These methods will provide advances in the field of computational mathematics. Some of these research projects are likely to involve undergraduate and graduate students, and will therefore contribute to the development of the next generation of scientists. New research will be conducted that will allow observations of neutron stars and our understanding of strong gravitational fields to be used to determine the neutron-star equation of state in a way that is free from any assumptions about the microphysics of neutron star matter. The projects include work in numerical relativity that involves developing techniques for solving Einstein's equations on manifolds with arbitrary spatial topologies. These methods will be used to study a variety of problems, including an effort to explore the gravitational analog of the turbulent cascade seen in fluid systems, and exploring cosmological models numerically to determine whether and how non-trivial topology could be recognized through observations. 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

In much of physical science, two competing factors determine the behavior of systems: deterministic laws of nature, and random "noise". Physical laws are usually described mathematically by differential equations. Over the last half century, a comprehensive theory of differential equations with random noise, called stochastic differential equations, has been developed and is very well-understood in many regimes. One area where foundational work is still needed is understanding how the behavior of systems described by stochastic differential equations scales as the dimension, i.e. the number of features in the system, grows. This project aims to provide a broad theoretical framework and a general scaling limit theory for high-dimensional stochastic differential equations. This theory will have significant applications to research fields as diverse as deep learning and neural networks, neurobiology (understanding learning structures in the brains of insects and other animals), the design of broadband wireless networks, and theoretical physics (quantum field theory). The award will also support the training of graduate student researchers the dissemination of the research at conferences and workshops around the US and the world. The principal research goals of this award are to study noncommutative stochastic calculus, developing a broad analytic foundation for the subject, and to prove general scaling limit theorems about the solutions of matrix stochastic differential equations (SDEs) as the matrix size grows. Noncommutative stochastic calculus has been developed in several quarters since the 1980s, but key analytic features of the classical theory have been missed owing to the noncommutativity - often, the methods are combinatorial, and function classes are restricted to polynomials or analytic functions. Current work has developed a new approach to noncommutative stochastic calculus, using noncommutative function theory which mirrors the classical martingale theoretic approach. This yields a general theory of noncommutative quadratic variation and an Ito formula which extends all previously known Ito formulations in free probability. This project will use these tools to study the large-N limits of NxN matrix SDEs, proving a general scaling limit for their solutions as described by noncommutative SDEs in free probability. The outline of this approach for self-adjoint processes is now clear, and the technical difficulties should be approachable with methods described above. A further goal is to extend such scaling limits to the non-self-adjoint setting using Brown measure. 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

Plant leaves have a very large number of tiny pores, named stomata, that regulate water loss while providing the pathway for carbon dioxide (CO2) to enter leaves. CO2 is a vital plant nutrient, and is required for plant growth and crop production. However, a typical plant loses between 150 and 500 water molecules through these stomatal pores for every carbon atom that is absorbed from CO2 for nutrition and growth. The opening and closing of these stomatal “breathing” pores in leaves is regulated by the concentration of CO2 inside leaves. Since the concentration of CO2 in the air is now 50% higher than it was 150 years ago, plants could more easily take up CO2 from the air while losing less water. Yet important mechanisms and genes that enable this agriculturally important CO2 response of stomatal pore regulation are unknown. This research will identify proteins and genes of a recently discovered CO2 sensor in order to determine cellular signaling mechanisms through which carbon dioxide controls plant water loss and CO2 intake. The ability to improve the response of stomatal pores to carbon dioxide is important for unfavorable weather conditions, agricultural ground water availability, and droughts that are becoming more frequent in several of the major agricultural regions in the US. Project personnel will prepare graduate students for professional careers and further conduct an outreach program with scientific training internships and professional preparation of students and mentoring with the public Preuss School for disadvantaged high school students in San Diego County, as well as training and professional preparation of visiting underrepresented summer research interns with UC San Diego’s STARS and ENLACE program. The researchers will be active with community outreach work that brings science and innovation close to the public. The PI will also conduct outreach through presentations and discussions with students and K-12 teachers in San Diego. Atmospheric CO2 is predicted to double during this century and the ensuing concentration rise in CO2 rise will reduce stomatal conductance of plants globally, which will have severe effects on gas exchange, leaf heat stress, plant water use efficiency, and plant robustness, but can also benefit plant growth. A network of signal transduction mechanisms senses and transduces CO2 changes to regulate stomatal movements for optimization of CO2 influx, water loss and plant growth under diverse conditions. In recent research these researchers have identified a major CO2/bicarbonate sensor consisting of a complex of a Raf-like kinase (HT1) and a MAP kinase (MPK12 & MPK4). Major questions and new hypotheses have arisen from this advance as to the unknown cellular locations and protein properties of the recently discovered reversible MPK12/4 – HT1 CO2/bicarbonate sensor, the molecular nature of unknown protein phosphatases that are predicted to be required to “shut off” this CO2 sensing core, and a gap in molecular and cellular mechanisms linking this proposed CO2 sensing core to downstream guard cell signaling mechanisms. Moreover, no forward genetics stomatal CO¬2-specific response screen in grasses has been reported, despite the agronomic important of grasses. New hypotheses will be directly investigated based on the team’s recent discoveries. This project will leverage interdisciplinary cell biological, molecular genetic, biophysical, biochemical and genomic approaches to identify new critical molecular components of the CO2 signaling network and characterize how this network operates to regulate stomatal pore apertures, plant transpiration and CO2 influx. This award is funded by the Cellular Dynamics and Function Cluster of the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences. 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

Gateways 2024 is the major event for the science gateway community in the US to discuss challenges and solutions in the area, to identify new issues, to shape future directions for research, foster the exchange of ideas, standards and common requirements and push towards the wider adoption of science gateways. The topics covered by the Gateways conference series range from technical topics to use cases to related content such as usability or sustainability of science gateways. The knowledge transfer can be transformative between different research domains and technical content. The building blocks of science gateway frameworks are re-usable in diverse research areas evident in widely used frameworks such as Hubzero and Tapis. The Gateways conference series sets the stage for learning, engaging and empowering the different stakeholders in the community who are science gateway users, developers and providers as well as funders and decision makers. Providing travel grants for students and early-career researchers allows to include a diverse audience and support underrepresented minorities. Science gateways are a key part of NSF funded Cyberinfrastructure, and they are used by hundreds of thousands of researchers and students, supporting both publication-quality science and at-scale education. Science gateways involve a comprehensive set of research domains that has a broad impact on society, addressing considerable challenges such as pandemics, climate change, global sustainability of food, water, and land use driven by growing populations and rising per capita incomes. In recognition of their importance, NSF has funded the Science Gateways Community Institute (SGCI) and more recently the SGX3 Science Gateways Center of Excellence to provide leadership for the science gateways community. The Gateways conference series is one of the of flagships of SGCI and SGX3 and the major event in the US to bring the science gateways community together. The conference series has existed since 2016 and has attracted each year between 100-170 participants. In 2023 it has moved from an SGX3-organized conference to a community-driven conference with the first time the general chair being selected by a newly established advisory board for the conference and who is not part of the SGCI/SGX3 team. The goal is to attract additional research domains and tap into the chair's networks that are not already in contact with SGCI/SGX3. SGX3 continues to guide the conference while inviting each year since 2023 a different general chair. Gateways 2024 features various program formats such as keynotes, presentations, tutorials, demos, panels, posters and Bring Your Own Portal. Accepted submissions are published in open-access proceedings and accepted papers are invited to a special issue in a journal. SGCI/SGX3 has an impressive record of underrepresented minority involvement within the science gateway community. The travel grant allows to involve more students and early-career researchers at Gateways 2024 and they are selected under consideration of diversity, equity and inclusion. 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.