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Open Access Publications from the University of California

Scholarly Works (7 results)

  • Article
The 150 Women Project - Holding Series (2024)
    Cover page: College ofEngineering: 150 Years of Women in Engineering
    • Article
    • Peer Reviewed
    LBL Publications (2021)
    Dopamine neuromodulation of neural synapses is a process implicated in a number of critical brain functions and diseases. Development of protocols to visualize this dynamic neurochemical process is essential to understanding how dopamine modulates brain function. We have developed a non-genetically encoded, near-IR (nIR) catecholamine nanosensor (nIRCat) capable of identifying ~2-µm dopamine release hotspots in dorsal striatal brain slices. nIRCat is readily synthesized through sonication of single walled carbon nanotubes with DNA oligos, can be readily introduced into both genetically tractable and intractable organisms and is compatible with a number of dopamine receptor agonists and antagonists. Here we describe the synthesis, characterization and implementation of nIRCat in acute mouse brain slices. We demonstrate how nIRCat can be used to image electrically or optogenetically stimulated dopamine release, and how these procedures can be leveraged to study the effects of dopamine receptor pharmacology. In addition, we provide suggestions for building or adapting wide-field microscopy to be compatible with nIRCat nIR fluorescence imaging. We discuss strategies for analyzing nIR video data to identify dopamine release hotspots and quantify their kinetics. This protocol can be adapted and implemented for imaging other neuromodulators by using probes of this class and can be used in a broad range of species without genetic manipulation. The synthesis and characterization protocols for nIRCat take ~5 h, and the preparation and fluorescence imaging of live brain slices by using nIRCats require ~6 h.
      Cover page: Near-infrared catecholamine nanosensors for high spatiotemporal dopamine imaging.
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2023)

      Background

      The Floating Sign is a histopathologic clue to the diagnosis of autoimmune sclerosing skin disorders such as morphea and interstitial granulomatous dermatitis (IGD). On the other hand, the "free-floating" sign has been associated with neoplasms, for example, dermatofibroma and interstitial mycosis fungoides. Herein, we report the Free Sign in sclerosing skin disorders.

      Methods

      In a case-control study, we applied detailed histopathologic definitions of Floating Sign and Free Sign to assess their presence in morphea, IGD, and other sclerosing disorders.

      Results

      Free Sign was present in most cases of morphea (46/55, 84%) and IGD (7/13, 54%) but not necrobiosis lipoidica (NL) (6/14, 42.8%) or sclerodermoid graft versus host disease (SGVHD) (2/7, 28.5%). The sensitivity and specificity of Free Sign for morphea versus other disorders was 84% and 56%, respectively. Floating Sign was not identified in most cases: NL (3/14, 21.4%), SGVHD (1/7, 14.2%), morphea (5/55, 9%), IGD (1/13, 7.7%). The diagnostic sensitivity of Floating Sign in morphea was 9%.

      Conclusions

      The Free Sign was present in most cases of morphea in our series and may represent a clue to the presence of evolving sclerosis. Free Sign may be seen in other sclerosing disorders. Technical artifact is a potential cause of a false-positive Free Sign.
        Creative Commons 'BY' version 4.0 license
        • Thesis
        • Peer Reviewed
        UC Berkeley Electronic Theses and Dissertations (2022)

        Dopamine neuromodulation is a critical process that facilitates learning, motivation, and movement. Disruption of these processes has been implicated in several neurological and psychiatric disorders including Huntington’s Disease (HD). While many treatments for physical and psychiatric HD symptoms target dopaminergic neuromodulation, the mechanism by which dopaminergic dysfunction occurs during HD is unknown. This is partly due to limited capability to visualize dopamine release at the spatiotemporal resolution of both neuromodulator release (ms) and dopaminergic boutons (µm). We have designed a synthetic, optical probe for catecholamines that utilizes near-infrared (nIR) fluorescent, polymer-functionalized single wall carbon nanotubes to report dopamine dynamics within striatal brain tissue. These nIR catecholamine sensors (nIRCats) show a strong response to dopamine within the near-infrared wavelengths ideal for imaging in optically scattering brain tissue. Furthermore, the chemically synthetic molecular recognition elements of nIRCats allow for expression-free imaging of dopamine in the presence of dopamine receptor pharmacology. These characteristics of nIRCat imaging make it a powerful tool uniquely suited for the study of dopamine release in diseased tissues.

        In this dissertation I develop methods to utilize nIRCat imaging for the study of dopamine release within R6/2 Huntington’s Disease Model mice (R6/2). Using nIRCat’s high spatial resolution, I show that dopamine release in R6/2 HD mice decreases with progressive motor degeneration and that these decreases are primarily driven by a decrease in the number of dopamine hotspots combined with decreased release intensity. I adapt this analytical framework towards elucidating how dopamine release sensitivity to extracellular calcium concentration and D2-autoreceptor modulation is affected over the course of HD. In contrast to findings from spatially diffuse dopamine recordings, nIRCat imaging in ex vivo R6/2 HD slices indicates that calcium signaling within dopamine hotspots is altered late in disease and D2-autoreceptor signaling is altered early in disease. Lastly, I utilize nIRCat's ability to track individual dopamine hotspots over repeated stimulations and pharmacological washes to measure the release fidelity of dopamine hotspots in late disease. Compellingly, I demonstrate that antagonism of D2-autoreceptors using Sulpiride and direct blocking of Kv1.2 channels using 4-Aminopyradine (4-AP) increases the fidelity of dopamine hotspot activity in the striatum of WT slices, but not in the striatum of late HD slices. Altogether, these findings --- enabled by nIRCats --- provide a deeper look into how dopamine release is disrupted and dysregulated during Huntington’s Disease to alter the coverage of dopamine modulation across the dorsal striatum.

          Cover page: Imaging Synaptic Scale Dopamine Disruption in Huntington’s Disease Model Mice With Near Infrared Catecholamine Nanosensors
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2023)
          The emergence of new tools to image neurotransmitters, neuromodulators, and neuropeptides has transformed our understanding of the role of neurochemistry in brain development and cognition, yet analysis of this new dimension of neurobiological information remains challenging. Here, we image dopamine modulation in striatal brain tissue slices with near-infrared catecholamine nanosensors (nIRCat) and implement machine learning to determine which features of dopamine modulation are unique to changes in stimulation strength, and to different neuroanatomical regions. We trained a support vector machine and a random forest classifier to decide whether the recordings were made from the dorsolateral striatum (DLS) versus the dorsomedial striatum (DMS) and find that machine learning is able to accurately distinguish dopamine release that occurs in DLS from that occurring in DMS in a manner unachievable with canonical statistical analysis. Furthermore, our analysis determines that dopamine modulatory signals including the number of unique dopamine release sites and peak dopamine released per stimulation event are most predictive of neuroanatomy. This is in light of integrated neuromodulator amount being the conventional metric used to monitor neuromodulation in animal studies. Lastly, our study finds that machine learning discrimination of different stimulation strengths or neuroanatomical regions is only possible in adult animals, suggesting a high degree of variability in dopamine modulatory kinetics during animal development. Our study highlights that machine learning could become a broadly utilized tool to differentiate between neuroanatomical regions or between neurotypical and disease states, with features not detectable by conventional statistical analysis.
            Cover page: Identifying Neural Signatures of Dopamine Signaling with Machine Learning.
            • Article
            • Peer Reviewed
            UC Berkeley Previously Published Works (2019)
            Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000-1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution.
              Cover page: Imaging striatal dopamine release using a nongenetically encoded near infrared fluorescent catecholamine nanosensor.
              • Article
              • Peer Reviewed
              UC Berkeley Previously Published Works (2019)
              Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000-1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution.
                Cover page: Imaging striatal dopamine release using a nongenetically encoded near infrared fluorescent catecholamine nanosensor
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