Dartmouth Institute for Health Policy and Clinical Practice
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Emergence of Heterogeneity in Bacteria During Antibiotic Exposures
No full textBacterial populations exposed to antibiotics often exhibit phenotypic heterogeneity, with individual cells displaying distinct responses with fates ranging from survival to arrest or death. The emergence of this heterogeneity is largely driven by feedback mechanisms mediated by the interactions between antibiotic action, gene regulation, and cellular metabolism. These responses unfold in dynamic environments where conditions such as nutrient availability and drug concentration fluctuate over time and space. Yet, these complex interactions and their role in shaping population-level outcomes during drug responses remain poorly understood. Using tetracycline resistance in E. coli as a model system, this thesis focuses on how these interconnected processes integrate with environmental factors to drive bacterial survival in the context of dynamical responses to antibiotic exposure. Using single-cell and biofilm microfluidics, mathematical modeling, and RNA sequencing, we describe the mechanisms by which tetracycline exposure induces the emergence of heterogeneous phenotypes. We also show that in spatially structured populations, nutrient gradients lead to the emergence of a range of metabolic states that mediate a collective mechanism of survival to drug exposures. Finally, we describe how selective pressures relating to the costs and benefits of expressing resistance shape the evolution of the regulation of drug responses. These findings provide a quantitative framework to understand how bacteria survive antibiotic exposure and adapt to changing environments. By quantitatively linking gene regulation, metabolism, and antibiotic response dynamics, this thesis provides insights into bacterial adaptation under antibiotic stress, aiding the design of antibiotic therapies that minimize population-level resistance
The Influence of Oncology Outreach on Cancer Care Delivery in the United States
No full textCancer poses an enormous public health burden in the United States, which is disproportionality reflected among rural populations. Existing rural-urban cancer disparities in mortality are a function of the many social determinants of health but are largely attributable to differential access to oncology providers. One strategy for addressing rural workforce shortages is known as oncology outreach, whereby oncologists commute to satellite clinics to extend specialized care on a set cadence. While the outreach model is linked with increased proximity to cancer care for rural-residing patients, evidence is limited and mostly confined to Iowa-based populations. Questions surrounding the outreach model\u27s generalizability, versatility, and efficacy remain unaddressed.
This dissertation uses nationwide fee-for-service Medicare claims to study the influence of oncology outreach on measures of access, quality, and the cost of care. Aim 1 assesses the association between oncology outreach and patient travel burden. Aim 2 extends this work by evaluating the association between oncology outreach and timely treatment, a measure of quality. Aim 3 leverages network analysis to quantify system-level associations between oncology outreach and measures of care coordination, a hypothesized “cost” of outreach. Aim 4 outlines a simulation framework for evaluating and optimizing potential outreach policies, in addition to testing it on two Dartmouth Health use cases.
I found that oncology outreach was associated with reduced travel burden to cancer treatment and reduced odds of treatment delay for rural-residing patients. However, I found that health systems that employ high levels of oncology outreach were associated with decreased measures of care coordination, representing a trade-off of the outreach model. Lastly, I developed a novel simulation approach for evaluating and optimizing outreach policies and demonstrated its utility within Dartmouth Health’s catchment area.
This work provides evidence supporting oncology outreach as a viable strategy for addressing oncology workforce shortages, while jointly highlighting one trade-off. In addition, it provides methodology to quantify/track such policies using administrative data and establishes an approach for evaluating and optimizing potential outreach policies. I hope this work increases our understanding of oncology outreach, leads to better usage of these arrangements, and ultimately results in more equitable cancer care delivery
Behavioral and Neural Microstructures of Dynamic Cue-Motivated Responses
No full textSign-tracking, a conditioned response in which animals are physically attracted to reward-predictive cues due to motivational value attribution, is known to be persistent but can be flexible under some circumstances. For example, during an omission paradigm, in which vigorous responses must be withheld to avoid reward cancellation, animals can quickly restructure their responses. However, sign-tracking does not cease entirely, and cue attraction persists. This dissertation explores the behavioral and neural mechanisms underlying the simultaneous persistence and flexibility of sign-tracking during omission procedures. First, a novel method for behavioral analysis is introduced to accurately depict sign-tracking animals in dynamic tasks such as omission, as current automated measures were found to be insufficient and sometimes inaccurate. Next, a set of pharmacological experiments were conducted in which acetylcholine receptors in the nucleus accumbens core were found to have opposing roles in sign-tracking flexibility and response restructuring during omission. These results may indicate acetylcholine as a regulator of motivation when circumstances change. Finally, using fiber photometry, dopamine transmission underlying separable motivational and reinforcement mechanisms during omission were uncovered. This revealed a unique framework of the two reward processes in which both motivation and reinforcement can coexist within distinct phasic dopamine signals, and challenges current models of reward processes. Altogether, these results characterize sign-tracking in a new light as a dynamic and rich behavior that can provide a critical and unique window to study reward processing in the brain. These results will be particularly relevant to understanding the neural underpinnings of excessive motivation in disorders such as addiction
Hierarchical lineage tracing to unravel mechanisms of cancer treatment resistance
No full textCancer cells adapt to treatment, leading to the emergence of clones that are more aggressive and resistant to anti-cancer therapies. We have a limited understanding of the development of treatment resistance as we lack technologies to map the evolution of cancer under the selective pressure of treatment. To address this, we developed a hierarchical, dynamic lineage tracing method called FLARE (Following Lineage Adaptation and Resistance Evolution). We use this technique to track the progression of acute myeloid leukemia (AML) cell lines through exposure to Cytarabine (AraC), a front-line treatment in AML, in vitro and in vivo. We map distinct cellular lineages in murine and human AML cell lines predisposed to AraC persistence and/or resistance via the upregulation of cell adhesion and motility pathways. Additionally, we highlight the heritable expression of immunoproteasome 11S regulatory cap subunits as a potential mechanism aiding AML cell survival, proliferation, and immune escape in vivo. Finally, we validate the clinical relevance of these signatures in the TARGET-AML cohort, with a bisected response in blood and bone marrow. Our findings reveal a broad spectrum of resistance signatures attributed to significant cell transcriptional changes. To our knowledge, this is the first application of dynamic lineage tracing to unravel treatment response and resistance in cancer, and we expect FLARE to be a valuable tool in dissecting the evolution of resistance in a wide range of tumor types
Late Holocene to Modern Dust Increases in Antarctic Ice Cores
No full textDust aerosols impact global climate by influencing direct and indirect radiative forcing, serving as cloud condensation nuclei, and supplying trace nutrients to the ocean that affect the marine biological pump. Antarctic ice core dust records show dust deposition changing in step with global climate over the past eight ice-age cycles. However, fewer studies have focused on Antarctic dust deposition during the late Holocene-to-modern period. Notably, 20th-century increases in dust deposition have been observed in ice cores from James Ross Island (JRI) and Dronning Maud Land, with the JRI record hypothesized to reflect desertification and land-use changes in Patagonia. To investigate this dust increase, I test these hypotheses using existing glaciochemical records from a suite of Antarctic ice cores from the South Pole-West Antarctic region over the Common Era. I also investigate this increase by conducting new analyses on archived South Pole Ice Core (SPC-14) samples to better understand the physical and chemical properties of the dust. My combined analysis of existing ice core derived dust records and satellite-based reanalysis data (MERRA-2 Aer-2d) confirm a near tripling of dust deposition within the South Pole-West Antarctic region. I find that the 20th century dust increase is driven primarily by expansion of sheep pastoralism in Patagonia triggering widespread vegetation change and soil erosion. The anthropogenically induced positive shift in the Southern Annular Mode (at ~1955 CE) enhanced the effects of this land use change through amplifying desertification. Novel single-particle and bulk chemical and physical analyses on archived SPC-14 samples were contaminated by small (\u3c 3 µm) aluminum oxide alloy particles. While their origin remains unknown, the absence of these contaminating particles in methodological blanks suggest that they were introduced to the archive samples during storage or transport prior to arriving to the Dartmouth College laboratory facilities. Nevertheless, single particle time-of-flight mass spectrometry (spTOF-ICPMS) shows promise as a useful analytical method in ice core dust studies
Toward General Purpose LLMs: From Domain Alignment to Multimodal and Multi-Agent Systems
Get PDFLarge Language Models have shown remarkable capabilities, but their generalization across domains, modalities, and collaborative settings remains limited. This work explores how LLMs can be adapted along three dimensions: domain specialization, multimodal processing, and multi-agent reasoning. First, we introduce a reward-guided retrieval mechanism that fine-tunes the retrieval component of a language model using preference-based supervision, improving response relevance in specialized domains. Building on this, we design a multi-agent framework for complex information-seeking tasks, where distinct agents handle query clarification, evidence extraction, and answer synthesis, enabling robust reasoning without additional model training. Extending beyond language, we investigate how LLMs can operate in visual domains. We adapt pretrained models for image restoration by tokenizing images and applying fine- tuning techniques. This enables flexible restoration across degradation types and supports multi-agent collaboration through an extension that structures the restoration process into interactive components. Finally, we present an exploratory study of LLMs in cybersecurity. In a simulated enterprise network, an LLM-based agent performs monitoring, analysis, and deception to defend against attacks. While not optimized for state-of-the-art performance, the study reveals practical insights into the potential of LLMs for autonomous decision-making in real world environments. Together, these studies demonstrate how LLMs can be reconfigured to address a broad range of tasks, offering a deeper understanding of their versatility across domain-specific reasoning, multimodal processing, and collaborative agent systems
The New England Trail, End to End in Five Days: A Running Couple Test Their Limits
Get PDFA moment-by-moment narrative of a grueling run from Mount Monadnock in New Hampshire to Guilford, Connecticut from June 17 through June 22, 2020
Alpina
Get PDFReports of mountaineering in the greater ranges in 2024 include President Donald Trump’s ruling that Denali be called Mount McKinley again. A flash ascent of Freerider on Yosemite National Park’s El Capitan. A century after he went missing, Andrew “Sandy” Irvine’s frozen foot encased in a boot was found on Everest. Drones and helicopters expand access to Everest. First ascent of the western ridge of Gasherbrum III. A pair climbs Pholesobi in Eastern Nepal. Climbers scale the east ridge of Lalung I in India. A new route is opened on Greenland’s east coast. In memoriam: Christopher Jones, 1939-2024
FIRST PRINCIPLES MATERIALS DISCOVERY AND DESIGN FOR PHOTOVOLTAIC AND SOLAR THERMAL ALLOYS USING HIGH THROUGHPUT METHODS
Get PDFMaterials selection has been a challenge since the dawn of time. With the advent of computational methods and high throughput databases, materials can be discovered and assessed before they are even synthesized. In this thesis I will discuss my work towards designing new materials for clean energy uses, especially alloys which have been underexplored from computational methods. To begin, I present a case study explaining the synthesis of the Yb14ZnSb11 thermoelectric material. Next, I explore the class of AM2Pn2 Zintl materials. From the previously identified BaCd2P2, it is suspected that other materials of this stoichiometry may also exhibit its same “defect-tolerance.” I find that there is a large number of other AM2Pn2 materials that are stable and isostructural to BaCd2P2, while possessing a large range of bandgaps which could make them useful for a variety of devices, such as infrared detectors, thermoelectrics, single junction photovoltaics, and tandem solar cells. Extending this class of materials, I turn to the idea of creating alloys among the AM2Pn2 to take advantage of their isostructural nature. Focusing on solar absorber materials for tandem top cells, I search among all possible quaternary alloys in this family and screen for the most promising candidates. I identify Mg-alloying as a key strategy to increase the bandgap high enough for a tandem top cell solar absorbers. I show Ca(Cd0.8Mg0.2)2P2, one of the most promising candidates, has the ideal bandgap of 1.8 eV for optimal efficiency and find that its bandgap is direct in nature. Finally, I present a comparison of the cluster expansion and machine learned interatomic potential (MLIP) methods for predictions of Fe-Mn-Ni-Al-Cr high entropy alloys. From a set of about 5,000 DFT calculations for training, I show that each method is able to achieve a similar level of accuracy of about 30 meV/atom, but that the performance of MLIPs from the Multi Atomic Cluster Expansion (MACE) converge faster. This aids in addressing the outstanding challenge of including disordered phases in computationally predicted phase diagrams
Role of Axial Ligation in the Conformational and Redox Properties of Cytochromes
No full textHeme proteins are crucial for many biological processes including respiration, transport, and catalysis. As electron carriers containing redox active metal centers, their electron transfer (ET) properties are tuned by the protein environment, wherein the reduction potential can be influenced by factors such as heme solvent accessibility, charge, the presence of neighboring redox centers, as well as the identity of the axial ligand. The axial ligand in heme proteins is especially crucial for tuning the electronic properties of the metal center, as it affects the driving force of the reaction. However, the redox properties of heme proteins are further modulated by other facets of the protein structure, such as 2° sphere interactions, protein dynamics, and the presence of neighboring heme groups. Herein, the impact of the axial ligation on conformational and redox properties of monoheme and multiheme cytochrome proteins is examined. In the first study, hydrogen bonds formed by a moiety on the heme periphery were discovered to play a role in stabilizing Met80 ligation to the heme iron in yeast iso-1 cytochrome c. This moiety, heme propionate 6 (HP6), makes particularly critical connections to two low stability substructures in the protein through hydrogen bonding interactions with residues Thr49 and Thr78. Perturbations to this network through the creation of Thr-to-Val mutations affect the stabilities of the Met80- ligated form of the ferric and ferrous protein by comparable amounts, but leads to redox-dependent ligation changes. In the second study, the conformational properties of the yeast iso-1 cytochrome c variant with Thr-to-Val mutations are discovered to be distinct, as groups of hydrophobic residues cluster in the absence of peripheral HP6 contacts to create a channel to the heme. This variant shares similarities with a hydrocarbon-bound structure of cytochrome c, and the implications of this structure in the conformational change of cytochrome c from an electron carrier to a peroxidase are discussed. In the third study, Lys as an axial ligand in yeast iso-1 cytochrome c is revealed to introduce protein dynamics that affect the intramolecular electron transfer kinetics of this protein, shedding light on the properties of this residue as an axial ligand in a number of heme proteins and enzymes. In the final study, the axial ligation of a diheme cytochrome c4 protein from the pathogenic bacteria Neisseria gonorrhoeae is altered to isolate the redox properties of individual heme groups, and facets of the protein structure are discovered to affect the redox properties of the heme domains