Grants

Benton County

Benton County SBE

Benjamin Evett (The Poets' Theatre)

Beowulf

Bergen Place Activation Committee

The Bergen Place Activation Committee will produce a free, summer, lunchtime concert series in Bergen Place Park, in the heart of Ballard's business district. By providing a weekly program of music and cultural performances, this event series will bring together the local community.

Waterbury Town Treasurer

Non-Priority

SP APPROP Municipal Restructuring

Bergmann Associates DRI

Upstate Revitalization Initiat Round 1

Bergmann Associates URI Greater Binghamton Fund

Martin Luther King Junior School

Berklee Performance Center

DECD

Berlin Peck Library Reroofing and Mechanical Replacement Project

DOT

Berlin Sidewalks 2020

DECD

Berlin Steel Boulevard Park Project

State of Connecticut

Berlin Worthington FD

State of Connecticut

Berlin Worthington FD

State of Connecticut

Berlin Worthington FD

Yamhill County

Bernau Estate Biodynamic Wine & Ag Experience

NIAID - National Institute of Allergy and Infectious Diseases

ABSTRACT Digital base editors hold tremendous promise for precision gene therapies for monogenic diseases, such as severe combined immunodeficiency A (SCID-A), a primary immunodeficiency (PID). PIDs can be treated with allogeneic hematopoietic stem cell transplant (HSCT), however, >70% of patients lack suitable matched donors and of those transplanted, many encounter severe complications, such as graft-versus-host-disease and even death. An alternative and ideal approach would be genetic correction of hematopoietic stem/progenitor cells (HSPCs) in vivo, yet base editing therapies require tandem delivery of two component payloads (mRNA encoding base editor protein along with gRNA). Major clinical challenges include safe and effective development of delivery systems for two-component digital base editors, which involves packaging uniformity/stability, formulation optimization, safe/effective editing performance in vivo, and collective elucidation/prediction of structure-activity relationships. The objective of this application is to develop a build-test-learn-predict-refine closed loop machine learning (ML)-driven workflow of synthesis, formulation generation, and screening that will optimize micellar nanoparticles (MNPs) for binary base editor (gRNA and mRNA expressing adenine base editor, ABE) delivery in vitro with a novel engineered cell model and in vivo to HSPCs using a novel genetically humanized SCID-A mouse model (all developed by our team). To accomplish this, we will synthesize a novel uniform library of amphiphilic polymers for blended assembly into MNP vehicles. The proposed work is innovative and unique as a high throughput workflow will be combined with a novel multi-fidelity ML model to drive our synthesis/formulation strategy that will uniquely correlate chemistry/composition to size/stability (Aim 1), in vitro (Aim 2), and in vivo (Aim 3) performance relationships. The Specific Aims of this proposal are: Aim 1. Driven by ML, a novel library of precise amphiphilic block polymers will be synthesized, assembled into a library of compositions, formulated into MNPs with gRNA and mRNA expressing ABE, quantitatively characterized, and optimized for physicochemical properties. Aim 2. A novel engineered SCID-A cell model will enable quantitation and correlation of MNP cellular internalization, ABE editing, and toxicity to physicochemical properties via ML to identify and predict structural drivers of performance and safety in vitro. Aim 3. A novel genetically humanized SCID-A mouse model will enable quantitation and ML prediction of MNP physicochemical properties to functional in vivo ABE editing, immune system recovery, toxicity, and in vitro-in vivo performance trends. Our world-leading team is particularly well suited to undertake the proposed studies providing expertise in polymer synthesis and physicochemical characterization (Reineke), ML and computation (Sarupria), along with in vitro and in vivo model development, ABE therapies, and translational research (Moriarty and McIvor). Our pioneering and versatile MNP platform, ML, and biological discovery tools enable our long-term goals of achieving well-defined, safe, stable, and effective in vivo base editing therapy for PIDs currently treated by HSCT.

NIA - National Institute on Aging

Alzheimer's disease and related dementias (AD/ADRD) present significant global public health challenges, with a projected majority of future cases occurring in low- and middle-income countries. Cross-national research is essential to understand the diverse factors influencing cognitive aging and to develop effective interventions. The International Health and Retirement Study (HRS) Family and its Harmonized Cognitive Assessment Protocol (HCAP) offer unique datasets across diverse populations providing unparalleled opportunities for such research. However, the complexity of these datasets and the advanced methodological skills required for their analysis are barriers to widespread utilization. We propose a research education program titled Best Practices for the Measurement and Analysis of Cognitive Data in the International Health and Retirement Study (HRS) Family and its Harmonized Cognitive Assessment Protocol (HCAP). The program consists of two complementary short courses: Course One: Designing and Leading Cross-National Studies with HRS and HCAP Cognitive Data introduces participants to the cognitive data available in the International HRS and HCAP studies, the concept of harmonization, and best practices for designing substantive research questions and analyses involving cross-national comparisons. It is tailored for principal investigators, lab leaders, and researchers planning studies utilizing international HRS or HCAP cognitive data. Course Two: Applied Measurement Modeling in Cross-National Cognitive Aging Research provides advanced instruction in statistical methods, including item response theory and structural equation modeling, with hands-on computing practice using the international HRS and HCAP data. It is intended for researchers who wish to develop practical data analysis skills necessary for conducting advanced psychometric analyses required for statistical harmonization. Our specific aims are to develop and deliver the two-part summer short course to equip researchers with the necessary skills to conduct rigorous cross-national AD/ADRD research using the International HRS and HCAP data (Aim 1); expand the reach and impact of the training program through online resources and outreach activities. Course materials and lectures publicly will be available on-demand, offering condensed versions as pre-conference workshops, and providing "flipped" classroom options for remote participants (Aim 2); and, develop a community of practice among researchers by facilitating communication and collaboration through online forums, networking opportunities, and continuous engagement (Aim 3). By providing targeted training and resources, our program will empower researchers to utilize the International HRS and HCAP data effectively to enhance the quality and impact of cross-national cognitive aging research. This initiative will contribute to significant scientific advancements in understanding the cognitive health of older adults worldwide and support efforts to mitigate the global impact of AD/ADRD.

NSF

Empirical analysts now routinely generate new data by deploying artificial intelligence (AI) or machine learning (ML) algorithms on large, unstructured data sets. Examples include quantifying sentiment or uncertainty in news text using large language models or natural language processing methods; measuring product characteristics from review text and product images on online platforms; or imputing missing variables from demographic information. In standard practice, AI- or ML-generated data are treated as if they were regular numerical data for the purposes of data analysis. However, this standard approach can introduce bias in parameter estimates and lead to invalid conclusions. This project develops new econometric methods and statistical theory to inform best practice for empirical researchers using these data. This research project improves the quality of data analysis performed by businesses, non-profits, and government organizations. The interdisciplinary nature of the research helps to forge connections between academia, policy makers, and industry. The research improves the validity of empirical research using AI- and ML-generated data. The projects contribute novel econometric methods for working with data generated by AI and ML algorithms that correct the bias and inference problems present in current empirical practice. The methods are rigorously justified with new statistical theory for AI- and ML generated data. A key contribution is the development of novel asymptotic frameworks that are appropriate for modern use cases where AI and ML algorithms are deployed on massive data sets. Additionally, the projects develop an effciency theory for working with AI- and ML-generated data. General methods and frameworks are developed, along with specialized approaches for important business and economic contexts. These include demand estimation using text and image data (relevant for pricing decisions on online platforms) and vector autoregressions with AI- and ML-generated components (relevant for fiscal and monetary policy analysis). 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.

NHLBI - National Heart Lung and Blood Institute

PROJECT SUMMARY Sixty percent of people worldwide die due to inflammatory diseases like cardiovascular disease, chronic obstructive pulmonary disease (COPD), and stroke. This highlights the need for an improved mechanistic understanding of the initiation and progression of inflammation. Macrophages are ubiquitous in all major tissues and play an essential role in inflammation, driving the development and progression of inflammatory disorders by secreting cytokines and other inflammatory mediators. Proinflammatory macrophage activation is initiated via NF-κB signaling, a master transcriptional regulator of inflammation. However, broad inhibition of the NF-κB pathway results in many unacceptable patient toxicities, including impaired tissue repair. Recent studies have shown that the bromodomain and extraterminal domain (BET) family of epigenetic reader proteins promote transcription of a subset of NF-κB-regulated inflammatory target genes in a cell- and context-specific manner. Small molecule inhibitors of the BET family (BETi) provide broad anti-inflammatory effects, significantly decrease macrophage-mediated inflammation, and exhibit beneficial anti-inflammatory effects in several inflammatory disease models by attenuating a subset of NF-κB target genes. However, the transcriptional mechanisms by which BETi modulate inflammatory gene transcription remain largely unknown. The BET family consists of four members (BRD2/3/4/T), each with two independent acetyl-lysine binding bromodomains (BD1 and BD2). Most studies of BET transcriptional regulation use non-selective BETi that block both BD1 and BD2 across the entire protein family (pan-BETi). In clinical trials, pan-BETi are associated with significant adverse effects and dose-limiting toxicities. Thus, BETi with improved selectivity for a subset of BET bromodomains are urgently required to improve inflammatory disease treatment options. We are determining the specific role of BET proteins and their individual bromodomains in macrophage activation and contrasting that activity to BET protein functions in non-immune cells. While our prior work has suggested that BRD4-BD1 is required for non-immune cell inflammatory transcription, our preliminary studies in macrophages suggest that both bromodomains of BRD2 promote inflammatory transcription. Here, we will elucidate the precise biochemical mechanisms and individual BET bromodomains regulating macrophage inflammatory activation and identify the exact protein interactions underlying that regulation. Aim 1 will identify the precise transcriptional role of each BET bromodomain in macrophage inflammatory activation with a focus on BRD2. Aim 2 will examine the BET bromodomain-based protein interactions that drive BET protein nuclear localization and activity. This fellowship addresses knowledge gaps in the biochemical mechanisms underlying BET bromodomain control of macrophage inflammation. Completing this fellowship will further develop precision medicine approaches for inflammatory disorders by identifying which BET bromodomains are the most attractive therapeutic targets to modulate inflammation with fewer off-target toxicities.

NIDA - National Institute on Drug Abuse

ABSTRACT Hyper-palatable foods (HPF) are highly rewarding and often consumed in excess. HPF contains combinations of palatability-inducing macronutrients (e.g., fat and sodium) at thresholds that do not occur in nature. The macronutrient combinations produce an artificially rewarding eating experience (beyond what a single macronutrient produces alone), leading to excess intake. Similar to the effects of substances such as alcohol and nicotine, HPF can induce neuroadaptive changes in the brain, yielding hyper-sensitivity to HPF cues in the environment (sensitization), compulsive HPF use, and use despite physical and psychological consequences. Thus, HPF may be best conceptualized as an addictive substance. Understanding the abuse liability of a substance, or the degree to which a substance may be used in excess and lead to negative consequences, is a critical component of regulatory science. However, despite the proliferation of HPF in the US food supply and their substantial public health harms, a major scientific gap is that the abuse liability of HPF is not well understood. The purpose of the study is to conduct a comprehensive abuse liability assessment of HPF using procedures required by the US Food and Drug Administration (FDA) for the testing of potentially addictive products. We will also test whether macronutrients (e.g., fat, sodium) may be modifiable contributors to HPF abuse potential, with the goal of establishing a systematic method to test the addictive potential of HPF using abuse liability framework. A within subjects, double-blind, randomized crossover trial will test the abuse liability of a commonly consumed HPF (potato chips), which contain a trifecta of elevated fat, sodium, and starchy carbohydrates. Full dose HPF (potato chips) will be compared with a negative control low in fat, sodium, and carbohydrates (Jicama root vegetable chip, baked). In addition, modified ‘dose’ chips with one macronutrient removed (fat or sodium) will be tested to examine readily modifiable macronutrients that may reduce HPF reinforcer potency. Consistent with FDA requirements, an acute dose effects comparison will be used to examine the acute subjective effects of HPF, and the reinforcer potency of full dose HPF and modified doses will be tested using behavioral self-administration and food purchase tasks. Currently, HPF are considered foods, alongside whole foods found in nature (e.g., apple). However, HPF effects on neurobiology and behavior may more strongly resemble those of addictive substances than whole foods. Evidence regarding the abuse potential of HPF should inform our conceptualization of HPF, and the potential need for FDA regulatory action. The findings of the proposed study may indicate whether HPF should be conceptualized as a food or addictive substance, and regulated accordingly.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. More than 8 million people worldwide are afflicted with type 1 diabetes (T1D), a disease that despite improved insulin treatment still results in a reduction of life expectancy by 12 years. The current model for T1D progression posits that in a subset of individuals with genetic susceptibility, the disease is precipitated by an as yet ill-defined triggering event. The nature of this triggering event remains a crucial open question in T1D. Viral infections have been extensively studied as precipitating events, but no causative viruses have been proven to date. Importantly, an anti-viral interferon response in recent onset T1D patients is well documented. However, this response can be activated not only by viral infection, but also by insufficient adenine to inosine editing of endogenous double stranded RNAs. Recent work from our team has shown that loss of adenine to inosine editing in mouse beta cells or in human islets causes sterile activation of a massive interferon response, and, in mice, beta cell destruction, while ablation of the critical editing enzyme from pancreatic alpha cells has no effect, supporting a unique susceptibility of beta cells to unedited double stranded RNAs. In addition, we demonstrated that genetic variants that reduce adenine to inosine editing in the human pancreas, so called editing quantitative trait loci or edQTLs, are associated with an increased interferon response and elevated risk of T1D. In this project, we are testing the hypothesis that the interferon response that characterizes early-stage T1D does not result from viral infection, but rather from insufficient editing of endogenous double stranded RNAs. We will evaluate three non-exclusive paths to a sterile IFN response in human islets. Firstly, we will test the impact of germline genetic variation on editing of cis transcripts. Secondly, we will build a dsRNA burden model to quantitively predict the amount of insufficiently edited dsRNAs as a trigger of the IFN response. Thirdly, we will determine if disruption of mRNA homeostasis via metabolic stress, ER stress, or abnormal splicing causes accumulation of double stranded RNAs that exceed the beta cell’s capacity for editing, thus resulting in activation of the interferon response. In sum, the proposed studies have the potential to lead to a paradigm shift in our understanding of the earliest events in the pathogenesis of T1D.

City of Gainesville

Beta Pi

City Of Hartford

Priority

City of Hartford

Priority

NYC Department of Cultural Affairs

Beth Morrison Projects