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ACCELERATING THE EXPLORATION OF CARBOXYLIC ACID-ZEOLITE INTERACTIONS: USING CLASSICAL AND MACHINE LEARNING INTERATOMIC POTENTIALS
Full text linkThe upgrading of carboxylic acids over zeolitic catalysts is a promising path to a sustainable future. In this study, we systematically investigated the interactions between various carboxylic acids and Brønsted acid sites within zeolite frameworks. A combination of classical interatomic potentials simulations, machine learning interatomic potentials (MLIPs), and density functional theory (DFT) calculations was employed to predict adsorption configurations and energies. MLIPs trained using NequIP improved accuracy, although challenges remained in transferability. This work highlights both the potential and current limitations of computational modeling in catalyst design, suggesting future improvements through more transferable ML models
FUNCTIONAL REGROWTH OF NOREPINEPHRINE AXONS IN THE ADULT MOUSE BRAIN FOLLOWING INJURY
Full text linkIt is widely believed that axons in the central nervous system of adult mammals do not regrow following injury. This failure contributes to the limited recovery of function following injury to the brain or spinal cord. Some studies of fixed tissue have suggested that, counter to dogma, neurons that express monoamine neurotransmitters regrow following injury. While suggestive, these studies were limited in their scope and unable to determine if the reappearance of axon density was indeed due to regrowth of damaged axons, as opposed to sprouted collaterals from the shafts of surviving axons, or if these newly grown axon are competent to release neurotransmitter in physiologically relevant contexts. Previous work in the Linden Lab demonstrated that serotonin neurons are capable of regrowth following injury but was unable to establish whether these regrown axons were competent to release neurotransmitter in a physiologically relevant context.
In this thesis, I tested the hypothesis that norepinephrine (NE) neurons have the ability to regrow axons functional to release neurotransmitter in response to external stimuli following injury. I used in vivo two-photon microscopy in layer 1 of the primary somatosensory cortex in transgenic mice harboring a fluorophore selectively expressed in NE neurons. This protocol allowed me to explore the dynamic nature of NE axons following injury with the selective NE axon toxin N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP4). Following DSP4 treatment, NE axons were massively depleted and then slowly and partially recovered their density over a period of weeks. This regrowth was dominated by new axons entering the imaged volume. There was almost no contribution from local sprouting from spared NE axons. Regrown axons did not appear to use either the paths of previously lesioned NE axons nor NE axons that were spared and survived DSP4 treatment as a guide. To measure NE release, GCaMP8s was selectively expressed in neocortical astrocytes and startle-evoked, NE receptor-mediated Ca2+ transients were measured. These Ca2+ transients were abolished soon after DSP4 lesion but returned to pre-lesion values after 3-5 weeks, roughly coincident with NE axon regrowth, suggesting that the regrown NE axons are competent to release NE in response to a physiological stimulus in the awake mouse.
Both NE and serotonin axons have very similar dynamic properties. Both are thin, unmyelinated, and predominantly signal through volume transmission rather than synaptic transmission. These shared dynamic properties indicate that the molecular machinery enabling this unusual capacity for regrowth may also be shared. Here, we provide initial evidence supporting the hypothesis of an existing mechanistic pathway to enable axon regeneration in the adult mammalian brain, the elucidation of which could provide the foundation for novel therapies to promote axon regeneration and functional recovery within the CNS
EXAMINING THE EFFECTS OF VIOLENCE EXPOSURE ON NEUROBEHAVIORAL DEVELOPMENT DURING EARLY ADOLESCENCE
Full text linkChildhood exposure to violence is a global epidemic, affecting over one billion children annually. Early adolescence, a critical developmental stage, is marked by rapid changes. While the impact of violence on developmental outcomes has been extensively studied, understanding the precise pathways linking exposure to violence and neurobehavioral development remains limited.
This study aimed to examine the effects of violence exposure on neurobehavioral development and the role of environmental factors in youth ages 9-10, using data from the Adolescent Brain and Cognitive Development (ABCD) Study. Participants (n=2420) with baseline violence exposure were followed for three years. Linear regression, mixed effects modeling, and multiple linear regression were used to assess the cumulative impact of violence on neurobehavioral development, the mediating role of brain connectivity, and the moderating effect of caregiver support.
Results showed that internet victimization had persistent effects on brain communication. Cumulative violence exposure was linked to increased progression of brain communication between the Default Mode Network (DMN) and Salience Network (SN), as well as between the SN and Hippocampus. Additionally, several cortical network and subcortical region pairs were found to partially mediate the relationship between violence exposure and psychopathological outcomes. Notably, increased communication between the SN and Hippocampus partially mediated the link between violence exposure and both internalizing and externalizing symptoms. Lifetime exposure to witnessing violence influenced connectivity between the Frontoparietal Network and SN, with stronger effects in youth reporting low caregiver support and weaker effects in those with high caregiver support.
Findings highlight how violence exposure alters brain communication across networks involved in emotional regulation, cognitive control, and threat detection, suggesting targeting these neural pathways could mitigate the mental health impact of violence. Violence exposure disrupts neural development, increasing the risk for psychopathology. Addressing violence exposure early is crucial to mitigating its long-term mental health impact.
Pediatric primary care providers play a critical role in screening, evaluating, and addressing violence exposure in children and adolescents to promote healthy transitions into adulthood. Findings from this study support expansion of nursing practice to include comprehensive screening tools inclusive of various forms of violence encompassing both virtual and in person exposure. An interdisciplinary approach to understanding violence exposure’s impact on neurodevelopment and mental health, including collaborations across healthcare providers, will enhance the ability to develop targeted, effective treatments. Integration of these findings into nursing practice offers a holistic, translatable approach to care, positioning nurse clinician scientists to bridge the gap between research and practice, ultimately improving long-term outcomes for violence exposed youth
INVESTIGATION OF BLADDER CANCER PLASTICITY WITH REPRODUCIBLE COMPUTATIONAL TOOLING
No full textMuscle invasion is a critical point in the progression of bladder cancer, but it is difficult to determine if or when it will occur in a given patient. While Src — one of the first discovered proto–oncogenes — has been implicated in tumor progression for a variety of cancers, previous work has determined that Src acts as a tumor suppressor in bladder cancer. The second chapter of this thesis investigates how molecular subtypes of bladder cancer may be important for resolving this apparent paradox.
Upon muscle wall invasion, metastasis becomes a primary threat to the patient. While immune checkpoint blockade (ICB) can provide complete, durable response, it is only in a subset of patients. It has been suggested that combination therapy of erdafitinib and ICB can allow would–be non–responders to respond, but this is surrounded by conflicting evidence and little mechanistic work. In the third chapter of this thesis, we note a consistent increase in interferon signatures upon FGFR3 inhibition, but that in vivo this inhibition may not be sufficient to stimulate immune infiltration.
The behavior of cells is sensitive to their environment, complicating in vitro studies. Previous work has shown that cells take on basal characteristics when in culture, a phenotype that can be reverted to luminal when placed in vivo. During the development of the models in the previous chapter, we discovered that cells placed in vivo became more aggressive and lost markers of differentiation. We note our observations as well as preliminary mechanistic
findings.
Orchestrating the acquisition and analysis of datasets large and small from disparate sources has become the standard for modern science. Unfortunately, this often results in publications that are difficult to reproduce due to lack of sufficient (immense) detail. Reproducible science takes time, but the ‘activation energy’ can be reduced with the help of tailor–made software. In the final chapter of this thesis, I describe case studies of software I have created to aide reproducible science, and the importance of creating software for the particular as well as the general
Enhancing Power System and Market Operations through Stochastic Modeling, Inverse Optimization, and Machine Learning
Full text linkModern power system and market operations are characterized by both challenges and opportunities, often in paradoxical ways. First, the increasing integration of renewable energy sources (RES) and distributed energy resources (DERs) introduces stochasticity, which can reduce system efficiency but also provide additional flexibility to support operations. Second, while information asymmetry among power market participants continues to hinder operational efficiency, advancements in data availability and data mining create opportunities for information recovery. Third, while machine learning offers promising solutions to manage the complexity of operational models, it may also compromise their explainability. This dissertation explores these paradoxes, aiming to leverage emerging opportunities while addressing critical challenges in power system and market operations.
The research begins by tackling challenges in power transmission systems and wholesale markets. First, to efficiently use flexible resources like energy storage, a chance-constrained stochastic market framework is proposed, enabling the co-optimization and pricing of energy, reserves, and a new service called virtual inertia provision. This framework mitigates high uncertainty and inertia shortages in RES-dominated systems. Second, to address information asymmetry among power producers and improve market participant strategy design, a data-driven inverse optimization model is developed to recover private offer prices from public market-clearing results. This method is computationally efficient, robust, and offers strong performance guarantees for information recovery. Additionally, an operational-adversarial conditional generative adversarial network is introduced to enhance grid-awareness in scenario generation for extreme operational conditions. By integrating feedback from downstream operational models through modified gradient descent, this model identifies critical scenarios for system operations, enabling effective scenario-based reserve scheduling.
The focus then shifts to power distribution systems, examining incentive-based voltage regulation using grid-edge DERs in environments with uncertainty and partial information. A distributionally robust incentive design model with online learning is introduced, enabling the distribution system operator (DSO) to effectively incentivize DER aggregators to participate in voltage regulation. Aggregators respond to these incentives by adjusting their DER settings, while the DSO dynamically adjusts its conservativeness level based on aggregator responses. This work highlights the potential of combining stochastic modeling, inverse optimization, and machine learning to tackle diverse challenges in power system and market operations
ASSESSING RELIABILITY OF CAUSAL MODELS OF TRANSCRIPTION
No full textTo begin building computational simulations of human cells, we will need a list of genes, a gene regulatory network (GRN) showing how the genes control one another, and a set of dynamic models that recapitulates activity over time. Our list of parts is making steady progress owing to new technologies that sequence DNA and reveal which regions are unpacked for use. However, the GRN and the dynamic models remain a challenge even a quarter century after the completion of the Human Genome Project. Using publicly available data, this work empirically evaluates a broad array of modern GRN inference approaches on two of their main functions: inferring direct regulators of transcription and predicting outcomes of genetic perturbations. Direct regulators are inferred using statistical independence tests on transcriptome data and are checked by combining genetic perturbations with assays of protein-to-DNA binding. Perturbation predictions are generated from diverse machine learning methods, and their adequacy for causal inference is tested using genetic perturbations that are not present in any algorithm’s training data. None of the algorithms tested on either task yield reliable results, with false discovery proportions far exceeding expected rates and with trivial baselines typically achieving lower prediction error than bespoke models. A key takeaway is that transcriptome data lack an essential statistical property, causal sufficiency, without which reliable causal networks cannot be inferred
MULTIPHYSICS MODELING FOR LONG-TERM NEURAL ORGANOID VIABILITY
No full textNeural organoids (NOs), derived from human-induced pluripotent stem cells, are microphysiological systems that recapitulate key aspects of neurodevelopment. They offer powerful in vitro models for studying brain development and disease mechanisms underlying disorders such as Alzheimer’s disease, microcephaly, and autism spectrum disorders. However, a major limitation of current NO models is the development of core necrosis, primarily due to oxygen and nutrient diffusion constraints. This necrosis restricts regional organization and functional complexity, limiting the fidelity of NOs. Although strategies such as orbital shaking and microfluidic culture have been explored to alleviate diffusion limitations, they have achieved only partial success, particularly for organoids exceeding ~800 μm in diameter.
In this thesis, I will present a 3D finite element model to simulate O₂ transport and consumption within NOs, incorporating Michaelis-Menten kinetics and the Damköhler number (Da) to capture oxygen-limited necrosis. Experimental measurements of necrotic regions using fluorescent viability staining were used to calibrate the computational model, allowing for accurate prediction of oxygen starvation under various culture conditions. Using this calibrated framework, we systematically compared static, orbital shaking, and flow-based microfluidic culture strategies, quantifying their relative impacts on necrotic progression.
Building on these insights, I propose a 3D spatial perfusion strategy using embedded microchannels to actively deliver oxygen throughout the NO. Parametric studies varying channel spacing, density, and insertion geometry revealed critical design parameters for achieving near-uniform oxygenation and minimizing necrosis. Additionally, we evaluated how variations in Da influence perfusion efficiency, offering a predictive guide for tuning culture conditions based on organoid-specific metabolic demands. Complementary simulations demonstrated oxygen diffusion dynamics in perfusion systems prior to consumption onset and explored the effects of increasing perfusion density by replicating arrays of fluidic channels within the organoid. Our findings not only advance the understanding of oxygen transport limitations in NOs but also provide a foundation for engineering next-generation microfabricated bioreactors and organoid culture platforms applicable to a broad range of 3D tissue models
Skin reinnervation by regeneration and collateral sprouting after peripheral nerve injury in mice
No full textPeripheral nerve injury (PNI) often leads to both sensory and motor impairments.
Following injury, nerve regeneration, in which injured neurons regrow under the guidance of Schwann cells, facilitates nerve reconnection with their original target. Apart from regeneration, collateral sprouting—a distinct mechanism involving the sprouting of adjacent intact nerve branches into the denervated territory—also contributes to the skin
reinnervation process. However, the relative contribution and temporal progression of these two processes remain poorly defined, particular in models involving complete nerve transection. To address this gap in knowledge, we utilized the sciatic nerve transection (SNT) model to investigate the temporal reinnervation pattern in denervated
skin regions. Animal behavioral assays were conducted to assess the pain phenotypes and functional recovery throughout the reinnervation process. Immunohistochemical staining and subtype-specific neuronal labeling were used to identify neuroanatomical changes in the mouse hind paw and dorsal ganglions (DRG). Our findings revealed partial axonal recovery in denervated skin territories in the mouse hind paw after SNT injury. CGRP immunoreactive peptidergic fibers and NF-H immunoreactive myelinated fibers exhibited continuous reinnervation in the denervated skin areas. Functional and anatomical assays performed after second surgeries indicated that both regenerating and collateral sprouting nerves contribute to reinnervation and modulate functional
outcomes. In parallel, increased expression of immune cell in denervated skin suggests potential roles for the cutaneous immune response in mediating skin reinnervation following SNT.
Altogether, our findings indicate that regeneration and collateral sprouting both contribute to skin reinnervation. These two processes may differ in timing, spatial reach, and fiber subtype involvement, but together they shape the functional outcome of
reinnervation. To specifically evaluate the component of reinnervation driven by collateral sprouting, future studies will need to be refined, for example by adopting alternative surgical approach, focusing on blocking regenerating injured axons at earlier time points, to minimize potential confounding effects from axonal regeneration
THE PROTON-ACTIVATED CHLORIDE CHANNEL: A REVIEW OF FORM AND FUNCTION AND SPECIFIC ROLES IN THE CENTRAL NERVOUS SYSTEM
Full text linkThe transport of ions through cellular membranes is essential for life and is achieved by ion transporters that are usually specific for one type of ion. Of known ion channels, cation-specific channels are disproportionally better characterized than anion channels. Due to this, the understanding of anion homeostasis, particularly of chloride, has lagged despite their important roles in the cell. Chloride is involved in maintaining electrostatic balance, cell excitability, acid/base homeostasis, cell volume regulation, and many other functions. Thus, discovering and understanding the roles of novel chloride channels is physiologically important.
We provide a comprehensive review of what is known about the proton-activated chloride (PAC) channel (encoded by PACC1 or TMEM206) from multiple studies that have been published since the cloning of the channel in 2019. Insights into its trimeric structure, proton-sensing, inactivation mechanism, and lipid regulation are discussed. PAC also has a newly discovered function as an endosomal chloride channel that maintains pH balance. This has functional significance in various cellular contexts, such as receptor trafficking and phagosome/macropinosome maturation.
PAC is highly enriched in the brain. The role of PAC in neurons is explored in-depth, with the finding that PAC is involved in neurotransmitter receptor trafficking during synaptic plasticity. Synaptic plasticity entails long-term potentiation (LTP) and long-term depression (LTD), or the activity-dependent strengthening and weaking of synapses, respectively. This has been proposed to be the mechanistic basis of cognitive processes such as learning and memory and is shown to depend on endosomal PAC channel. Mice with neuron-specific PAC deletion had impaired hippocampal LTD and performed poorly in the Morris water maze reversal test, which assesses behavioral adaptation. PAC is also highly expressed in microglia, the resident immune cells of the brain. PAC notably participates in phagosome acidification and cellular uptake of amyloid β, which forms pathogenic protein aggregates in Alzheimer’s disease.
PAC has important roles in broad cellular contexts. Specifically in the central nervous system, regulation of vesicular chloride and pH homeostasis have emerged as important players in endocytic processes that support neuronal and microglial function
The impact of tobacco product use and dual/poly-tobacco use on depressive symptoms among cancer survivors: Evidence from the National Health and Nutrition Examination and Survey (NHANES) 2005-2018
Full text linkBackground: Depression is a more common experience among cancer survivors compared to the general population. Tobacco use is linked to depression in the general population, but its impact among cancer survivors remains underexplored, especially those using multiple tobacco products. This study investigates the association between tobacco use and depressive symptoms among U.S. cancer survivors.
Methods: We studied 3,366 adult cancer survivors who participated in the 2005 – 2018 National Health and Nutrition Examination Survey (NHANES) . Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), with scores ≥ 10 indicating clinically relevant depressive symptoms. Information on smoking status and use of specific combustible and smokeless tobacco products during the past five days was assessed using a self-reported questionnaire. Cancer survivors were categorized based on their tobacco use pattern as: non-user, mono-tobacco user (use of only one type of tobacco product), and dual/poly-tobacco user (use of ≥2 types of tobacco products). We evaluated odds ratios (OR, 95% confidence interval [CI]) for the presence of depressive symptoms comparing tobacco use patterns using logistic regression models, adjusted for sociodemographic characteristics and lifestyle factors. Sensitivity analyses were conducted using a broader depressive symptom threshold (PHQ-9 ≥ 5).
Results: Among participants, 81.5% were non-users, 17.3% were mono-users, and 1.1% were dual/poly-users. Depressive symptoms were present in 17.3% of cancer survivors. Compared to non-users, mono-users (OR = 2.04, 95% CI: 1.36 - 3.05), and dual/poly-users (OR = 3.00, 95% CI: 1.02 - 8.85) had significantly increased odds of depressive symptoms. Furthermore, sensitivity analyses using a lower PHQ-9 threshold (≥ 5) showed similar but attenuated associations. Conclusions: Tobacco use, particularly involving multiple products, was strongly associated with elevated depressive symptoms among cancer survivors in the U.S. This highlights the need for integrated approaches in survivorship care addressing both tobacco cessation and mental health interventions