Treatment of neurological disease has made little progress due to the inability of many therapeutics to access the brain environment. However, delivery vehicles like nanoparticles can allow therapeutics to overcome brain-specific biological barriers including the blood-brain barrier (BBB), the dense extracellular space (ECS), and cellular targeting. The ability of nanoparticles to overcome these barriers is influenced by surface properties which can be modified through the formulation process. One understudied parameter is the choice of surfactant, molecules which stabilize nanoparticle formation and likely form an interface between the nanoparticle and brain environment. First, we investigated the potential toxicity of several commonly used surfactants on brain cells and slices. We added surfactant solutions to mouse microglial cells (BV2) or cultured brain slices and assessed cell viability two days later with colorimetric assays. Our results showed that while surfactants cholic acid (CHA) and polysorbate 80 (P80) caused toxicity at high doses, they were nontoxic at the low doses involved with nanoparticle formulation. Other surfactants, including Pluronic® F127 (F127) and poly(vinyl alcohol) (PVA), were nontoxic throughout the tested dose range. Interestingly, although the F127 compound is nontoxic on its own, nanoparticles formulated with F127 reduced cell viability. This result was not observed with any other nanoparticle-surfactant combination. Confocal microscopy indicated higher intracellular accumulation of the nanoparticles formulated with F127 compared to all other formulations, suggesting that toxicity is mediated by nanoparticle internalization and surfactant choice. Finally, we used a live cell imaging technique to capture videos of the nanoparticle internalization process. Building off these results, ongoing experiments will evaluate several nanoparticle-surfactant formulations on their ability to accumulate within brain tissue after in vivo administration. Findings from this work will guide nanoparticle design for future clinical translation.

Brain extracellular matrix (ECM) structure mediates many aspects of neuronal function. When ECM structure becomes dysregulated in neurological disease, one resulting impact is impaired neuronal function. Therefore, probing changes in ECM structure could provide insights into disease mechanisms and expose potential therapeutic pathways. Previous work in our group determined that degrading neural ECM structures, including perineuronal nets (PNNs), leads to a significant increase in the diffusive ability of nanoparticles navigating the brain extracellular space. However, this diffusion-based analysis provides little insight into changes in PNN-specific morphology or structure; it only predicts whether or not they are present and the degree to which they may be altered from normal. With this project, we aim to quantify changes in PNN structure with high spatial resolution. PNNs are stained using a fluorescently labeled lectin (Wisteria floribunda agglutinin) and images are acquired via confocal microscopy. Using Python, a coding language, we developed an automated image processing workflow to characterize morphological and structural features associated with PNNs, including total number of branches, average branch length, average mesh size of the net, and the areal density of fluorescence. This approach was applied to brains that span a range of chronological ages, from 14 days old to adult. PNNs are known to increase in counts early on in life, so this age-based study served as a proof of concept for our methodology. This same approach can be applied to study the effect of various neurological diseases on PNN structure. Collectively, this work aims to enhance our understanding of neurological disease mechanisms and open new avenues of therapeutic intervention.

Extracellular Vesicles (EVs) are group of cell-derived structures including exosomes, microvesicles, and apoptotic bodies, which have been found to play a key role in intercellular communication, through the biological cargo that these EVs can carry. Their ability to deliver proteins and nucleic acids from donor cells to their target cells has led to growing interest in the potential of EVs being used as biomarkers for disease. But, a comprehensive understanding of EVs behavior is lacking, especially in neuroscience, which may hinder the development for further application of the EVs. Thus, we are interested in investigating the effect of brain-derived EVs (bEVs) on brain cells, especially microglia, the brain’s primary resident immune cells. To do this, we first extracted the bEVs from the rat brain through ultracentrifugation and purified them through size exclusion chromatography (SEC). We then applied the bEVs to cultured mouse BV-2 microglial cells and incubated for 24 hours before performing quantitative reverse transcription PCR (RT-qPCR) on the treated BV-2 cells to explore any bEV induced inflammation response. Preliminary results have shown that bEVs play a role in inducing both pro and anti-inflammatory responses in microglial cells, both to varying degrees in the cytokine markers expressed after incubation for 24 hrs. Furthermore, to better understand the interaction between bEVs and microglial cells, we labeled bEVs with fluorescent nano-sized semiconductor quantum dots (QDs). Through fluorescent confocal microscopy and time-lapse imaging, we were able to explore the time-dependent interaction of bEVs and BV-2 cells at high resolution. Our study can provide insights into bEV behavior, which can be used to better understand their potential use as biomarkers for specific brain disease models. 

Sarcopenia, the age-related of loss of muscle mass and function, is associated with a decline in quality of life in the elderly and has few effective treatment options. Sarcopenia is linked to mitochondrial dysfunction and elevated mitochondrial oxidant production. We are investigating the role of elevated mitochondrial oxidative stress in sarcopenia using a mitochondrial targeted therapeutic and a mouse model of accelerated sarcopenia. SS-31 is a mitochondrial targeted peptide that associates with cardiolipin, decreases oxidant production, and increases ATP production in vivo. Superoxide dismutase 1 knockout (Sod1KO) mice lack superoxide dismutase 1 (an enzyme that converts the oxidant superoxide into hydrogen peroxide and molecular oxygen) resulting in an accelerated sarcopenia phenotype. We hypothesize that improving mitochondrial function with SS-31 treatment will delay the decline in muscle function in the Sod1KO mice. To test this, we administered SS-31 to SOD1KO mice through surgically-inserted osmotic pumps for 8 weeks between 3 and 4 months of age, the published timeframe for the onset of skeletal muscle decline in SOD1KO mice. Muscle force generation and fatigue resistance was tested in vivo in the gastrocnemius before pump insertion and monthly after pump insertion for 4 months. At the end of the treatment we used histological and biochemical analyses of mouse tissue samples to determine skeletal muscle fiber type, metabolite and protein concentrations, and muscle fiber respiration and oxidant production. We expected SOD1KO mice with SS-31 to have a lower rate of decline in muscle force production and increased fatigue resistance over time, higher max ATP production, and decreased oxidative stress. The effect of SS-31 on muscle function, mitochondrial quality, and redox homeostasis has exciting potential as a translational therapeutic treatment for human sarcopenia.

Abnormal activity in the extended face processing system has been implicated in face processing challenges in autism spectrum disorder (ASD). However, the impact of comorbid attention deficit hyperactivity disorder in individuals with ASD (ASD-ADHD) on social impairment and the neural substrates underlying face processing has not been investigated. To address this, we conducted an fMRI study of emotional face processing in participants with ASD-ADHD, ADHD and significant sensory processing challenges (ADHD), ASD, and typically developing children (TD). After excluding for motion, 16 children with ASD (Age M (SD) = 9.57 (0.06)), 16 children with ASD-ADHD (Age M (SD) = 10.08 (0.07)), 20 ADHD (Age M (SD) = 9.46 (0.06) and 40 TD controls (M (SD) = 10.04 (0.06)) were included. Social functioning between autism groups were compared using the Autism Diagnostic Interview-Revised (ADI-R). MR data were collected on a 3T Philips Achieva system. For the fMRI task, 54 volumes of high resolution data (2.3mm3) were collected. Participants were shown blocks of rapidly-presented (150 ms) fearful faces, houses and scrambled images. fMRI data were processed in FSL using standard processing methods. We tested group differences in the contrasts faces > houses and faces > scramble. The ASD participants were rated significantly higher than the ASD-ADHD group on the ADI-R social domain (ASD M=17.88, SD=6.18, ASD-ADHD M=12.33, SD=6.29, p<0.05). Children with ASD-ADHD exhibited reduced left amygdala (p = .025) and left fusiform (p = .03) activity compared to children with ADHD for faces > scramble contrast. However, activation in these areas did not significantly differ between the ADHD and ASD groups. These preliminary results indicate significantly altered brain activation during face processing in children with comorbid ASD and ADHD when compared to children with ASD alone, suggesting a possible additive effect of comorbidity on social difficulties.