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The role of STING agonist-induced interferon stimulated genes in the anti-melanoma immune response
No full textSuccessful infiltration of pro-inflammatory immune cells into the tumor can promote an anti-tumor microenvironment that leads to tumor growth control and regression. However, the tumor has many mechanisms, both intrinsic and extrinsic, to inhibit the anti-tumor immune response and promote a pro-tumor microenvironment. Recently, treatment of solid tumors with STING agonists has been investigated pre-clinically and clinically as a strategy to promote immune cell entry into the tumor and exert their anti-tumor effector function in the tumor, which can be exploited for cancer immunotherapies. STING is a cytosolic dsDNA sensor that induces the expression of type I interferons and other interferon stimulated genes upon its activation, leading to immune cell entry into the tumor and a delay in tumor growth. Although many STING agonists have shown promise in pre-clinical and early phase clinical testing, they have been unable to induce complete tumor regressions. One reason for this result is the upregulation of inhibitory molecules in the tumor following treatment with STING agonists. In this thesis, I show that treatment of murine melanoma with antagonists of these inhibitory molecules (ARG2, COX2, NOS2, ISG15, PD-L1) in combination with STING agonist, ADU-S100, leads to an improvement in tumor growth control compared to STING agonist monotherapy. In the B16 melanoma model, the combination of anti-PD-L1 + ADU-S100 or anti-ISG15 + ADU-S100 leads to a delay in tumor growth compared to ADU-S100 alone. This therapeutic response is driven by changes in the myeloid and lymphoid compartments that promote an inflammatory, anti-tumor
microenvironment. Meanwhile, in the BPR20 melanoma model, treatment with ARG2i/COX2i/NOS2i + ADU-S100 promotes improved tumor growth control compared to ADU- S100 alone. These changes in tumor growth are associated with the increased expression of genes associated with inflammation and an anti-tumor immune response and the decreased expression of genes associated with tumor growth and survival. Overall, these data demonstrate that tumor- mediated mechanisms of resistance to therapy can be overcome and provide guidance for future combination therapies
Evaluating the Palisades of Vogt in Optical Coherence Tomography Volumes; Enface Segmentation, Scoring and Reporting for Clinical Assessment
No full textEvaluating the Palisades of Vogt in Optical Coherence Tomography Volumes; Enface Segmentation, Scoring and Reporting for Clinical Assessment
Kira Lynn Lathrop, PhD
University of Pittsburgh, 2024
Normal vision depends on the constant replenishment of the cells that protect the clear surface of the eye. Every time you blink your eyes, you clear away some corneal epithelial cells, which are then replaced by new cells originating from the Palisades of Vogt (POV). Within the fibrovascular ridges of the POV, this lifelong regeneration relies on proper functioning of limbal epithelial stem cells. The goal of this dissertation is to improve our ability to research corneal surface related visual loss by developing a way to visualize, document and report the status of the POV.
First, we developed and validated an open-source approach to enface evaluation of the status of the POV from optical coherence tomography (OCT) volumes. The POV are located primarily in the superior and inferior limbus and are defined by fibrovascular ridges in the basement membrane of the epithelium. Providing a consistent method to produce enface images from OCT requires extracting images ranging around the basement membrane of the epithelium rather than using the corneal surface as a reference because different ocular pathologies can change the depth of the epithelium.
Second, we developed a rating system referencing OCT volumes acquired from both normal and pathological eyes to describe the configuration of the POV. Changes in the status of the POV in different pathological conditions have been reported, but there is no current scale that characterizes the configuration of the palisades at the level of the basement membrane. Five corneal experts were recruited to validate the rating instrument.
Finally, we developed reporting guidelines for documenting the acquisition method of POV volumes for enface imaging. There is no current documentation recommendation, and ambiguous reporting can confound the ability to synthesize results of future clinical trials. Standardizing reporting will facilitate comparability and consistency between research groups
Teleophthalmology to Prevent Diabetic Retinopathy: Implementation, Outcomes, and Associated Factors with Lack of Follow-Up in Western Pennsylvania
No full textThis dissertation explores the implementation and outcomes of a teleophthalmology program designed to prevent diabetic retinopathy in Western Pennsylvania, focusing on why some patients do not follow up after screening. By examining asynchronous telemedicine implementations at the University of Pittsburgh and UPMC, the work highlights the significant barriers to routine diabetic retinopathy screenings and subsequent follow-up care. The findings underscore the impact of socioeconomic, clinical, and systemic factors on patient engagement and adherence to follow-up recommendations. Through a detailed analysis of program data and patient characteristics, the research identifies key factors that contribute to patients being lost to follow-up, offering insights into improving patient outcomes in teleophthalmology and diabetic care
Creation of a single-cell atlas of the injured zebrafish heart uncovers the importance of cited4a in cardiomyocyte maturation during regeneration
No full textMyocardial infarction leaves the heart permanently damaged and more susceptible to future cardiac failure. This is because almost all mammalian adult cardiomyocytes are in a post mitotic, non-proliferative state and therefore fail to replace the damaged tissue. In contrast, zebrafish can fully regenerate their hearts following injury through the proliferation of existing cardiomyocytes and have become an important tool for identifying molecular mechanisms driving heart regeneration. Using snRNA sequencing and multiplexed RNAscope in situ hybridization, we have shown that zebrafish CMs are heterogeneous and there are subpopulations of cardiomyocytes with distinct transcriptional responses to injury. We also show similarities to cardiomyocyte populations identified in regenerating neonatal mouse hearts. cited4a, a transcriptional co-activator classified by its interaction with the CBP/p300 complex, is increased at the onset of cardiomyocyte proliferation and expressed highest in mature, non-proliferating cardiomyocytes following injury. We created two cited4a mutant zebrafish lines using CRISPR/Cas9. Both mutant alleles contain deletions that cause a frameshift and early stop codon. We show that cited4a is involved in maintaining cardiomyocyte maturation and loss of cited4a allows for more cardiomyocytes to dedifferentiate and proliferate following injury, leading to an acceleration of regeneration. This response to injury and the role of cited4a could be important for maintaining heart function during regeneration and limiting excessive cardiac growth. Transcriptional analysis of cited4a mutants suggests deficiencies in sarcomere and mitochondrial structure and function. Furthermore, many of the decreased transcripts are targets of Estrogen-Related Receptor (ERR)-mediated cardiomyocyte maturation programs. Like ERR⍺
Saudi Arabia as an Emerging Donor: Understanding Its Foreign Aid
No full textThis dissertation presents an analysis of Saudi development assistance and humanitarian aid since 2015, with a particular focus on exploring the religious underpinnings driving such aid endeavors and determining if there is a potential presence of Da’wah activities. The study also delves into the alignment of Saudi foreign aid with the Sustainable Development Goals (SDGs). In addition, it examines the crises in neighboring countries to determine whether the escalation in aid and assistance provision to these countries is a result of their crises affecting the Kingdom of Saudi Arabia, particularly in the context of aid allocation to specific nations such as Yemen. The research methodology includes conducting interviews with officials and aid beneficiaries, as well as visiting multiple projects supported by two key Saudi entities, the King Salman Humanitarian Aid and Relief Centre (KSRelief) and the Saudi Fund for Development (SFD). These serve as the primary conduits for official Saudi humanitarian aid and development assistance outside the Kingdom. Furthermore, regression analysis is conducted using recently acquired data from KSRelief and SFD to delve deeper into the motivations shaping Saudi Arabia’s foreign aid policies. The study’s main finding is that both KSRelief and SFD utilize aid and assistance not as instruments for propagating Salafism or Da’wah activities, but rather to combat the spillover effects of external events that disproportionately impact the Kingdom. In addition, the SFD strives to create new market opportunities for Saudi companies to participate in construction projects within recipient nations. Moreover, the dissertation highlights the alignment of Saudi foreign aid with the SDGs, indicating a commitment to global development objectives. This dissertation examines the motivations behind Saudi Arabia’s foreign aid policy and the Kingdom’s role as an emerging donor since 2015, shedding light on a new era of Saudi foreign aid
Molecular Modeling with Atomistic Machine Learning Methods
No full textQuantum mechanics (QM) provides a method for computing energies and forces on atoms and ions within condensed phase and molecular systems to arbitrary accuracy. This allows us, in principle, to compute a vast array of properties, including reaction pathways, equilibrium properties, and transport properties. However, application of QM is severely limited by the adverse scaling of QM methods. In practice, QM-based simulations are limited to a few hundred atoms with dynamic time scales of 10s to 100s of ps. Machine learning (ML) potentials can be used to effectively extend the range of QM methods by allowing us to compute energies and forces of condensed phase and molecular systems with near-QM accuracy for tens of thousands of atoms with dynamic time scales to tens of ns.
We focus on developing ML potentials for various applications. Firstly, we trained highly-accurate deep learning potentials (DPs) for graphanol (hydroxy functionalized graphane). Our simulations demonstrated that graphanol conducts protons efficiently without hydration. Our investigations into proton diffusion and barriers, along with temperature fluctuations, revealed insights for designing improved proton exchange membranes. Additionally, we employed accurate DPs for modeling diffusion in metal-organic frameworks (MOFs) like UiO-66, and interface diffusion in chalcogenide alloys and electrodes for non-volatile memory cells, using the moment tensor approach (MTP) for construction.
Training these potentials typically relies on molecular dynamics (MD)-based active learning, which is inefficient for accurately predicting chemical reactions. To overcome this, we developed a reactive active learning approach that automates reaction generation and employs transition-state finding techniques. This active learning scheme resulted in accurate prediction of reaction barriers with fewer configurations compared to traditional MD-based active learning.
ML potentials do not contain information about charge densities. Therefore, we developed a method called DeepCDP (deep learning for charge density prediction) to predict electron densities solely from atomic coordinates. We achieved linear scaling in density prediction with near-DFT accuracy. Our predicted densities were utilized to track protons in graphanol and compute dipole moments for several molecules
Mesothelial Barrier Dysfunction in Ovarian Cancer Metastasis
No full textOvarian cancer is the leading cause of death among all gynecological cancers, with most patients being diagnosed with metastatic disease. For metastatic implants to form, mesothelial interactions are critical in many steps of the metastatic cascade. However, the mechanisms by which mesothelial barrier integrity is impaired, as well as how mesothelial cells respond to environmental and treatment-induced stress, are not well understood. We utilized multiple models both in vitro and ex vivo to study ovarian cancer cell adhesion and transmigration. We first employed pharmacological approaches to strengthen the mesothelial barrier using the cAMP agonist forskolin, which has been previously utilized in endothelial and epithelial monolayers. Our findings reveal that forskolin treatment reduced ovarian cancer spheroid transmigration by decreasing mesothelial contractility and enhancing cell-cell junction organization. Conversely, upregulation of mesothelial cell contractility using calyculin A led to increased spheroid transmigration and weakening of mesothelial cell-cell junctions. Next, we utilized platinum-based chemotherapy to induce clinically-relevant therapeutic stress in mesothelial cells. We found that treating the mesothelial monolayers with cisplatin resulted in increased ovarian spheroid transmigration. Inhibition of STAT3 protected mesothelial cells from chemotherapy without compromising the cytotoxic efficacy of cisplatin on ovarian cancer spheroids. Finally, we investigated how a major environmental stress stimulus, hypoxia in the tumor microenvironment, perturbs mesothelial barrier integrity. Utilizing a microfluidic model with a mesothelial monolayer formed in one channel and ovarian cancer cells seeded in the other, we found that hypoxic conditions drove mesothelial cell invasion into the collagen gel toward the cancer cells. Inhibition of SRC signaling using the FDA-approved agent saracatinib under hypoxia reduced mesothelial cell invasion into the collagen gel. Overall, our findings demonstrate that strengthening the mesothelial barrier and targeting mesothelial cell responses to environmental or chemotherapy-induced stress signaling block ovarian cancer spheroid metastatic potential. Our work has important implications for discovering new therapeutic targets in the peritoneal microenvironment and developing mesothelial-targeted combination therapies to reduce ovarian cancer metastatic progression
Electron transfer rate of Cytochrome c immobilized on chiral self-assembled monolayers
No full textProtein film voltammetry (PFV) techniques are used to study and characterize electrochemical and physicochemical properties of redox biomolecules. One technique, consists in employing self-assembled monolayers (SAMs) with a head group that allows a redox enzyme to immobilize over the surface of an electrode, leading to non-destructive studies and a design that imitates the biological one. Cytochrome c (Cyt c) is a small protein that has been widely studied due to its importance in metabolic and respiratory cycles, and the ease in which it forms a reversible electron-transfer complex on SAMs. This work covers two sections, (1) the importance of chirality on electron transfer in biomimetic systems (2) and the effect of the electrolyte’s pH on electron transfer. A tripeptide SAM consisting of Cysteine, Alanine, and Glutamic acid, respectively, was employed for the chirality based experiments, focused on LLL, LDL, and DDD enantiomeric forms. The LLL-tripeptide demonstrated to have a higher electron transfer rate (k0) in comparison to the other enantiomers, showing that electron transfer is favored by homochirality; moreover, by breaking the homochirality, the k0 drops significantly. The spin polarization displayed by the LLL and DDD-tripeptide also cause the magnetization of ferromagnetic electrode (Ni/Au) to affect the electron transfer rate. This effect on electron transfer and the effect of homochirality correlate with the chiral induced spin selectivity (CISS) effect. In addition, pH dependence experiments were carried out by using pure 8-mercaptooctanoic acid SAM and mixed with 6-mercapto-1-hexanol. The results demonstrated that a more basic pH gives a slower k0, in relation to a more acidic one
TEA of the CO2 Capture in Post-combustion Applications Using Chemical Solvents and the Blue H2 Production in the SMR-CCS Process Using Physical Solvents
No full textAs a greenhouse gas (GHG), CO2 has become one of the chief drivers of climate change primarily due to combustion of fossil fuels. Increasing CO2 emissions into the atmosphere is raising global temperature, leading to detrimental impacts on humans and the environment. These include, increasing frequency and intensity of extreme heatwaves, hurricanes and floods, rising sea levels, increasing conflicts among nations due to migration arising from resources scarcity, and deteriorating human physical and mental health. Therefore, reducing CO2 emissions is the most crucial step in mitigating the catastrophic impacts of climate change. Existing technologies for CO2 capture from energy systems and industrial sectors include post-combustion, pre-combustion and oxy-combustion.
The objectives of this study were to develop models in Aspen Plus V.12.1 and perform techno-economic analysis (TEA) for the CO2 capture process in two post-combustion industrial power plants (Longview, WV and Wolverine, MI) using five chemical solvents; and for a novel steam methane reforming-carbon capture and storage (SMR-CCS) process to produce blue hydrogen using thirty-six physical solvents. To achieve these objectives, the overall process block flow diagrams and constraints were created and the solvents’ physico-chemical properties, reaction kinetics and rates, and water retention were determined. The process hydraulics and mass transfer characteristics were also calculated. For the post-combustion processes, the capital expenditure (CAPEX), operating expenditure (OPEX) and the levelized cost of carbon capture (LCOC) were calculated for five chemical solvents. For the novel SMR-CCS process, the CAPEX, OPEX and LCOC of the CO2 capture unit and the levelized cost of blue hydrogen production (LCOH) were calculated for thirty-six physical solvents.
The Aspen Plus V.12.1 simulation results indicated the following:
(1) Potassium glycinate was the most economically feasible chemical solvent for the post-combustion CO2 capture at LCOC of 0.93/kg H2 produced, due mainly to its high CO2 solubility at low partial pressures (< 5 bar)
Dissecting the molecular mechanism of nitroalkene-mediated PARPi sensitization.
No full textPARP inhibitors (PARPi) represent a prime example of the fulfillment of the promise of targeted therapy in cancer. However, complex and heterogeneous resistance mechanisms limit their effectiveness. Multi-target agents present an opportunity to address PARPi resistance while avoiding many of the challenges posed by combination therapy with multiple agents. Electrophilic nitroalkenes represent one such option for multi-target agent therapy in cancer. Electrophilic nitroalkenes are endogenous products of the nitrite and nitric oxide-dependent metabolism of unsaturated fatty acids and post-translationally modify multiple protein thiols to mediate diverse anti-inflammatory signaling activities. In contrast to their canonical anti-inflammatory roles in benign cells, nitroalkenes exert anti-cancer effects in triple-negative breast cancer (TNBC) in vitro and in vivo, and sensitize TNBC cells to multiple antineoplastic DNA damaging agents including PARPi. Therefore, we sought to better characterize the molecular mechanisms driving nitroalkene-mediated PARPi sensitization in cancer.
Global proteomic analyses of the effects of nitro-alkylation on cancer cell signaling in U2OS osteosarcoma cells revealed that nitro-alkylation elicited adaptive changes in fatty acid metabolism, was distinct from global thiol alkylation, and was dynamically regulated by the cellular redox environment. A survey of novel nitroalkene targets observed in this proteomics study revealed that the emerging cancer therapeutic target RECQL4 was alkylated by the nitroalkene OA-NO2 at Cys1052. Nitro-alkylation of RECQL4 was further confirmed by click chemistry-based chemoproteomics, and nitro-alkylation of both RECQL4 Cys1052 and the previously validated nitroalkene target, RAD51 recombinase, were determined to be DNA damage-dependent using this approach.
Next, nitro-alkylation of RECQL4 was shown to inhibit RECQL4 helicase activity and prevent RECQL4 recruitment to DNA double-strand breaks. Consequently, nitro-alkylation of RECQL4 suppressed DSB end resection in a manner dependent on Cys1052 and selectively inhibited downstream homology-dependent DSB repair. Finally, nitroalkenes were observed to sensitize multiple high-grade serous ovarian cancer (HGSOC) cell lines to multiple PARPi and were revealed to be far less potent in a HGSOC cell line harboring a deep deletion in the gene encoding RECQL4. Taken together, the studies described here (1) identify OA-NO2 as a first in-class RECQL4 inhibitor, (2) supports reveal a previously unknown functional role for Cys1052 in regulating RECQL4 helicase activity, and (3) motivate further evaluation of small molecule nitroalkenes as PARPi-sensitizing agents in cancer