Neurosciences Commons^™

Statins Are Rarely Prescribed For Incidentally Discovered Covert Cerebrovascular Disease: A Retrospective Cohort In A Large Electronic Health Record (Ehr) Identified Using Natural Language Processing, Lester Y Leung, Eric Puttock, David F Kallmes, Patrick Luetmer, Sunyang Fu, Chengyi X Zheng, Hongfang Liu, Wansu Chen, David M Kent

Faculty, Staff and Student Publications

Introduction: While incidentally discovered covert cerebrovascular diseases (id-CCD) are associated with future stroke, it is not known if patients with id-CCD are prescribed statins.

Methods: Patients age ≥50 with id-CCD on neuroimaging from 2009 to 2019 with no prior ischaemic stroke, transient ischaemic attack or dementia were identified using natural language processing in a large real-world cohort. Robust Poisson multivariable regression was used to assess statin prescription among patients without prior statins.

Results: Among 2 41 050 patients, 74 975 patients (31.1%; 4.7% with covert brain infarcts (CBI); 29.0% with white matter disease (WMD)) had id-CCD. 53.5% (95% CI 53.2 …

Vagus Nerve Stimulation For The Therapy Of Dravet Syndrome: A Systematic Review And Meta-Analysis, Shuang Chen, Man Li, Ming Huang

Faculty, Staff and Student Publications

OBJECTIVE: Dravet syndrome (DS) is a refractory developmental and epileptic encephalopathy characterized by seizures, developmental delay and cognitive impairment with a variety of comorbidities, including autism-like behavior, speech dysfunction, and ataxia. Vagus nerve stimulation (VNS) is one of the common therapies for DS. Here, we aim to perform a meta-analysis and systematic review of the efficacy of VNS in DS patients.

METHODS: We systematically searched four databases (PubMed, Embase, Cochrane and CNKI) to identify potentially eligible studies from their inception to January 2024. These studies provided the effective rate of VNS in treating patients with DS. The proportions of DS …

A Transcriptomic Taxonomy Of Mouse Brain-Wide Spinal Projecting Neurons, Carla C Winter, Anne Jacobi, Junfeng Su, Leeyup Chung, Cindy T J Van Velthoven, Zizhen Yao, Changkyu Lee, Zicong Zhang, Shuguang Yu, Kun Gao, Geraldine Duque Salazar, Evgenii Kegeles, Yu Zhang, Makenzie C Tomihiro, Yiming Zhang, Zhiyun Yang, Junjie Zhu, Jing Tang, Xuan Song, Ryan J Donahue, Qing Wang, Delissa Mcmillen, Michael Kunst, Ning Wang, Kimberly A Smith, Gabriel E Romero, Michelle M Frank, Alexandra Krol, Riki Kawaguchi, Daniel H Geschwind, Guoping Feng, Lisa V Goodrich, Yuanyuan Liu, Bosiljka Tasic, Hongkui Zeng, Zhigang He

Faculty, Staff and Student Publications

The brain controls nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from the brain to the spinal cord. However, a comprehensive molecular characterization of brain-wide SPNs is still lacking. Here we transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain1. This taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) heterogeneous populations in the reticular formation with broad …

Single-Cell Analysis Of Chromatin Accessibility In The Adult Mouse Brain, Songpeng Zu, Yang Eric Li, Kangli Wang, Ethan J Armand, Sainath Mamde, Maria Luisa Amaral, Yuelai Wang, Andre Chu, Yang Xie, Michael Miller, Jie Xu, Zhaoning Wang, Kai Zhang, Bojing Jia, Xiaomeng Hou, Lin Lin, Qian Yang, Seoyeon Lee, Bin Li, Samantha Kuan, Hanqing Liu, Jingtian Zhou, Antonio Pinto-Duarte, Jacinta Lucero, Julia Osteen, Michael Nunn, Kimberly A Smith, Bosiljka Tasic, Zizhen Yao, Hongkui Zeng, Zihan Wang, Jingbo Shang, M Margarita Behrens, Joseph R Ecker, Allen Wang, Sebastian Preissl, Bing Ren

Faculty, Staff and Student Publications

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are …

Molecularly Defined And Spatially Resolved Cell Atlas Of The Whole Mouse Brain, Meng Zhang, Xingjie Pan, Won Jung, Aaron R Halpern, Stephen W Eichhorn, Zhiyun Lei, Limor Cohen, Kimberly A Smith, Bosiljka Tasic, Zizhen Yao, Hongkui Zeng, Xiaowei Zhuang

Faculty, Staff and Student Publications

In mammalian brains, millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells have impeded our understanding of the molecular and cellular basis of brain function. Recent advances in spatially resolved single-cell transcriptomics have enabled systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3, including several brain regions (for example, refs. 1-11). However, a comprehensive cell atlas of the whole brain is still missing. Here we imaged a panel of more than 1,100 genes in approximately 10 million cells across the …

Epileptic Seizure Classification Using Image-Based Data Representation, Amber Surles

Graduate Theses and Dissertations (2019 - present)

Epilepsy is a recurrence of seizures caused by a disorder of the brain in over 3.4 million people nationwide. Some people are able to predict their seizures based off prodrome, which is an early sign or symptom that usually resembles mood changes or a euphoric feeling even days to an hour before occurrence. Consequently, the natural instincts of the body to react to an upcoming attack lends credence to the existence of a pre-ictal state that precedes seizure episodes. Physicians and researchers have thus sought for an automated approach for predicting or detecting seizures.

In this research, we evaluate the …

Inferring Personalized Treatment Effect Of Antihypertensives On Alzheimer's Disease Using Deep Learning, Pulakesh Upadhyaya, Yaobin Ling, Luyao Chen, Yejin Kim, Xiaoqian Jiang

Faculty, Staff and Student Publications

Alzheimer's disease (AD) is one of the leading causes of death in the United States, especially among the elderly. Recent studies have shown how hypertension is related to cognitive decline in elderly patients, which in turn leads to increased mortality as well as morbidity. There have been various studies that have looked at the effect of antihypertensive drugs in reducing cognitive decline, and their results have proved inconclusive. However, most of these studies assume the treatment effect is similar for all patients, thus considering only the average treatment effects of antihypertensive drugs. In this paper, we assume that the effect …

Predicting The Risk Of Alzheimer's Disease And Related Dementia In Patients With Mild Cognitive Impairment Using A Semi-Competing Risk Approach, Zhaoyi Chen, Yuchen Yang, Dazheng Zhang, Jingchuan Guo, Yi Guo, Xia Hu, Yong Chen, Jiang Bian

Faculty, Staff and Student Publications

Alzheimer's disease (AD) and AD-related dementias (AD/ADRD) are a group of progressive neurodegenerative diseases. The progression of AD can be conceptualized as a continuum in which patients progress from normal cognition to preclinical AD (i.e., no symptoms but biological changes in the brain) to mild cognitive impairment (MCI) due to AD (i.e., mild symptoms but not interfere with daily activities), followed by increasing severity of dementia due to AD. Early detection and prediction models for the transition of MCI to AD/ADRD are needed, and efforts have been made to build predictions of MCI conversion to AD/ADRD. However, most existing studies …

Target Cell-Specific Synaptic Dynamics Of Excitatory To Inhibitory Neuron Connections In Supragranular Layers Of Human Neocortex, Mean-Hwan Kim, Cristina Radaelli, Elliot R Thomsen, Deja Monet, Thomas Chartrand, Nikolas L Jorstad, Joseph T Mahoney, Michael J Taormina, Brian Long, Katherine Baker, Trygve E Bakken, Luke Campagnola, Tamara Casper, Michael Clark, Nick Dee, Florence D'Orazi, Clare Gamlin, Brian E Kalmbach, Sara Kebede, Brian R Lee, Lindsay Ng, Jessica Trinh, Charles Cobbs, Ryder P Gwinn, C Dirk Keene, Andrew L Ko, Jeffrey G Ojemann, Daniel L Silbergeld, Staci A Sorensen, Jim Berg, Kimberly A Smith, Philip R Nicovich, Tim Jarsky, Hongkui Zeng, Jonathan T Ting, Boaz P Levi, Ed Lein

Faculty, Staff and Student Publications

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- …

Genetic Correlations Between Alzheimer’S Disease And Gut Microbiome Genera, Davis Cammann, Yimei Lu, Melika J Cummings, Mark L Zhang, Joan Manuel Cue, Jenifer Do, Jeffrey Ebersole, Xiangning Chen, Edwin C Oh, Jeffrey L Cummings, Jingchun Chen

Faculty, Staff and Student Publications

A growing body of evidence suggests that dysbiosis of the human gut microbiota is associated with neurodegenerative diseases like Alzheimer's disease (AD) via neuroinflammatory processes across the microbiota-gut-brain axis. The gut microbiota affects brain health through the secretion of toxins and short-chain fatty acids, which modulates gut permeability and numerous immune functions. Observational studies indicate that AD patients have reduced microbiome diversity, which could contribute to the pathogenesis of the disease. Uncovering the genetic basis of microbial abundance and its effect on AD could suggest lifestyle changes that may reduce an individual's risk for the disease. Using the largest genome-wide …

Mclena-1: A Phase Ii Clinical Trial For The Assessment Of Safety, Tolerability, And Efficacy Of Lenalidomide In Patients With Mild Cognitive Impairment Due To Alzheimer's Disease; Trial Design And Rationale, Boris Decourt

Annual Research Symposium

No abstract provided.

Synthesize Heterogeneous Biological Knowledge Via Representation Learning For Alzheimer’S Disease Drug Repurposing, Kang-Lin Hsieh, German Plascencia-Villa, Ko-Hong Lin, George Perry, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Developing drugs for treating Alzheimer's disease has been extremely challenging and costly due to limited knowledge of underlying mechanisms and therapeutic targets. To address the challenge in AD drug development, we developed a multi-task deep learning pipeline that learns biological interactions and AD risk genes, then utilizes multi-level evidence on drug efficacy to identify repurposable drug candidates. Using the embedding derived from the model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, efficacy in preclinical models, population-based treatment effects, and clinical trials. We mechanistically validated the top-ranked candidates in neuronal cells, identifying drug combinations with efficacy in …

Integrating Comorbidity Knowledge For Alzheimer's Disease Drug Repurposing Using Multi-Task Graph Neural Network, Ko-Hong Lin, Kang-Lin Hsieh, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Alzheimer's Disease (AD) is a multifactorial disease that shares common etiologies with its multiple comorbidities, especially vascular diseases. To predict repurposable drugs for AD utilizing the relatively well-investigated comorbidities' knowledge, we proposed a multi-task graph neural network (GNN)-based pipeline that incorporates the corresponding biomedical interactome of these diseases with their genetic markers and effective therapeutics. Our pipeline can accurately capture the interactions and disease classification in the network. Next, we predicted drugs that might interact with the AD module by the node embedding similarity. Our candidates are mostly BBB permeable, and literature evidence showed their potential for treating AD pathologies, …

Characterizing Performance Gaps Of A Code-Based Dementia Algorithm In A Population-Based Cohort Of Cognitive Aging, Maria Vassilaki, Sunyang Fu, Luke R Christenson, Muskan Garg, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn

Faculty, Staff and Student Publications

BACKGROUND: Multiple algorithms with variable performance have been developed to identify dementia using combinations of billing codes and medication data that are widely available from electronic health records (EHR). If the characteristics of misclassified patients are clearly identified, modifying existing algorithms to improve performance may be possible.

OBJECTIVE: To examine the performance of a code-based algorithm to identify dementia cases in the population-based Mayo Clinic Study of Aging (MCSA) where dementia diagnosis (i.e., reference standard) is actively assessed through routine follow-up and describe the characteristics of persons incorrectly categorized.

METHODS: There were 5,316 participants (age at baseline (mean (SD)): 73.3 …

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson

Psychology Faculty Articles and Research

Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …

Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, Samiksha Pachade, Ivan Coronado, Rania Abdelkhaleq, Juntao Yan, Sergio Salazar-Marioni, Amanda Jagolino, Charles Green, Mozhdeh Bahrainian, Roomasa Channa, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering …

A Multiple Input Multiple Output Framework For The Automatic Optical Fractionator-Based Cell Counting In Z-Stacks Using Deep Learning, Palak Dave

USF Tampa Graduate Theses and Dissertations

Quantifying cells in a defined region of biological tissue is critical for many clinical and preclinical studies, especially in pathology, toxicology, cancer, and behavior. Unbiased stereology is the state-of-art method for quantification of the total number and other morphometric parameters of stained objects in a defined region of biological tissue. As part of a program to develop accurate, precise, and more efficient automatic approaches for quantifying morphometric changes in biological tissue, our group has shown that both deep learning-based and hand-crafted algorithms can estimate the total number of histologically stained cells at their maximal profile of focus in extended depth …

Secure Human Action Recognition By Encrypted Neural Network Inference, Miran Kim, Xiaoqian Jiang, Kristin Lauter, Elkhan Ismayilzada, Shayan Shams

Faculty, Staff and Student Publications

Advanced computer vision technology can provide near real-time home monitoring to support "aging in place" by detecting falls and symptoms related to seizures and stroke. Affordable webcams, together with cloud computing services (to run machine learning algorithms), can potentially bring significant social benefits. However, it has not been deployed in practice because of privacy concerns. In this paper, we propose a strategy that uses homomorphic encryption to resolve this dilemma, which guarantees information confidentiality while retaining action detection. Our protocol for secure inference can distinguish falls from activities of daily living with 86.21% sensitivity and 99.14% specificity, with an average …

The Effects Of Paclitaxel On Cellular Migration And The Cytoskeleton, Ashley Salguero-Gonzalez

Thinking Matters Symposium

In a clinical setting, some patients are exposed to an anti-cancer chemotherapy agent, paclitaxel. Cancerous cells undergo rapid, continuous cell division without control. Chemotherapy treatments try to slow and stop the uncontrollable cell division cycles and eliminate cancerous cells in the process. Paclitaxel serves as a treatment for some types of cancers, including lung, melanoma, bladder, and esophageal. Because it targets the cytoskeleton, paclitaxel can also influence cell migration. This project utilizes a cellular migration assay and an immunohistochemistry assay to analyze the effects of paclitaxel on the movement of cells and on the cytoskeleton of neuroglia rat cells with …

Counterfactual Analysis Of Differential Comorbidity Risk Factors In Alzheimer’S Disease And Related Dementias, Yejin Kim, Kai Zhang, Sean I Savitz, Luyao Chen, Paul E Schulz, Xiaoqian Jiang

Faculty, Staff and Student Publications

Alzheimer’s disease and related dementias (ADRD) is a multifactorial disease that involves several different etiologic mechanisms with various comorbidities. There is also significant heterogeneity in the prevalence of ADRD across diverse demographics groups. Association studies on such heterogeneous comorbidity risk factors are limited in their ability to determine causation. We aim to compare counterfactual treatment effects of various comorbidity in ADRD in different racial groups (African Americans and Caucasians). We used 138,026 ADRD and 1:1 matched older adults without ADRD from nationwide electronic health records, which extensively cover a large population’s long medical history in breadth. We matched African Americans …

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …

Identifying Key Elements To Assess Patient’S Acceptability Of Neurorehabilitation In Stroke Survivors–A Delphi Method, Manonita Ghosh, Kaoru Nosaka, Lisa Whitehead, Kazunori Nosaka

Research outputs 2014 to 2021

Purpose: Assessing patient acceptability of treatment is a clinical concern. No guidance exists to determine the best way to measure acceptability in stroke neurorehabilitation. This study identifies key elements to measure patient’s acceptance of stroke neurorehabilitation by establishing expert consensus.

>Materials and methods: A four-phase Delphi method with a three-round electronic-based survey was conducted. Experts were considered as stroke survivors or their caregivers and professionals in stroke neurorehabilitation. A twenty-five-item list was sourced from a literature review and discussion with a consumer panel (n = 22). In Round-1 (n = 118) and Round-2 (n = 80), experts …

3-Dimensional Agent-Based Model Of Neural Activity In The Central Nucleus Of The Amygdala During Pain, Carley Reith, Rachael Neilan, Benedict Kolber

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Medical Schools Ignore The Nature Of Consciousness At Great Cost, Anoop Kumar

Journal of Wellness

The essential question of the relationship between consciousness and matter is ignored in medical school curricula, leading to a machine-like view of the human being that contributes to physician burnout and intellectual dissatisfaction. The evidence suggesting that the brain may not be the seat of consciousness is generally ignored to preserve the worldview of the primacy of matter. By investigating new frameworks detailing the nature of consciousness at different levels of hierarchy, we can bring intellectual rigor to a once opaque subject that supports a fundamental reality about our experience: We are human beings, not only human bodies.

A Highly Predictive Microrna Panel For Determining Delayed Cerebral Vasospasm Risk Following Aneurysmal Subarachnoid Hemorrhage, Wang-Xia Wang, Joe E. Springer, Kevin Xie, David W. Fardo, Kevin W. Hatton

Sanders-Brown Center on Aging Faculty Publications

Approximately one-third of aneurysmal subarachnoid hemorrhage (aSAH) patients develop delayed cerebral vasospasm (DCV) 3–10 days after aneurysm rupture resulting in additional, permanent neurologic disability. Currently, no validated biomarker is available to determine the risk of DCV in aSAH patients. MicroRNAs (miRNAs) have been implicated in virtually all human diseases, including aSAH, and are found in extracellular biofluids including plasma and cerebrospinal fluid (CSF). We used a custom designed TaqMan Low Density Array miRNA panel to examine the levels of 47 selected brain and vasculature injury related miRNAs in CSF and plasma specimens collected from 31 patients with or without DCV …

Neural Oscillatory Activity Serving Sensorimotor Control Is Regulated By The Mitochondrial Redox Environment In Health And Disease, Rachel Spooner

Theses & Dissertations

Despite effective regimens of combination antiretroviral therapy, individuals with HIV are still at higher risk for developing forms of cognitive impairment, with one of the most common behavioral abnormalities to manifest being motor dysfunction. This is an important consideration, as deficits in motor control likely contribute to higher-order cognitive impairments, which together, lead to functional dependencies in the ever-growing aging population of HIV-infected adults. While the neuroanatomical bases of motor dysfunction have recently been illuminated in people living with HIV (PLWH), there remains an open question regarding the molecular processes supporting the circuit-level neuronal dynamics that potentially serve these behavioral …

The Mechanism Of Β-N-Methylamino-L-Alanine Inhibition Of Trna Aminoacylation And Its Impact On Misincorporation, Nien-Ching Han, Tammy J. Bullwinkle, Kaeli F. Loeb, Kym F. Faull, Kyle Mohler, Jesse Rinehart, Michael Ibba

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

β-N-methylamino-l-alanine (BMAA) is a nonproteinogenic amino acid that has been associated with neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD). BMAA has been found in human protein extracts; however, the mechanism by which it enters the proteome is still unclear. It has been suggested that BMAA is misincorporated at serine codons during protein synthesis, but direct evidence of its cotranslational incorporation is currently lacking. Here, using LC-MS–purified BMAA and several biochemical assays, we sought to determine whether any aminoacyl-tRNA synthetase (aaRS) utilizes BMAA as a substrate for aminoacylation. Despite BMAA's previously predicted misincorporation at serine …

Mitochondria Exert Age-Divergent Effects On Recovery From Spinal Cord Injury, Andrew N. Stewart, Katelyn E. Mcfarlane, Hemendra J. Vekaria, William M. Bailey, Stacey A. Slone, Lauren A. Tranthem, Bei Zhang, Samir P. Patel, Patrick G. Sullivan, John C. Gensel

Physiology Faculty Publications

The extent that age-dependent mitochondrial dysfunction drives neurodegeneration is not well understood. This study tested the hypothesis that mitochondria contribute to spinal cord injury (SCI)-induced neurodegeneration in an age-dependent manner by using 2,4-dinitrophenol (DNP) to uncouple electron transport, thereby increasing cellular respiration and reducing reactive oxygen species (ROS) production. We directly compared the effects of graded DNP doses in 4- and 14-month-old (MO) SCI-mice and found DNP to have increased efficacy in mitochondria isolated from 14-MO animals. In vivo, all DNP doses significantly exacerbated 4-MO SCI neurodegeneration coincident with worsened recovery. In contrast, low DNP doses (1.0-mg/kg/day) improved tissue …

Therapeutic Potential Of Mitophagy-Inducing Microflora Metabolite, Urolithin A For Alzheimer’S Disease, Dona Pamoda W. Jayatunga, Eugene Hone, Harjot Khaira, Taciana Lunelli, Harjinder Singh, Gilles J. Guillemin, Binosha Fernando, Manohar L. Garg, Giuseppe Verdile, Ralph N. Martins

Research outputs 2014 to 2021

Mitochondrial dysfunction including deficits of mitophagy is seen in aging and neuro-degenerative disorders including Alzheimer’s disease (AD). Apart from traditionally targeting amyloid beta (Aβ), the main culprit in AD brains, other approaches include investigating impaired mitochondrial pathways for potential therapeutic benefits against AD. Thus, a future therapy for AD may focus on novel candidates that enhance optimal mitochondrial integrity and turnover. Bi-oactive food components, known as nutraceuticals, may serve as such agents to combat AD. Uro-lithin A is an intestinal microbe-derived metabolite of a class of polyphenols, ellagitannins (ETs). Urolithin A is known to exert many health benefits. Its antioxidant, …

Bypassing The Blood-Brain Barrier: A Physical And Pharmacological Approach For The Treatment Of Metastatic Brain Tumors, Samuel A. Sprowls

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation (a) provided an in depth literature review of methods to disrupt the BBB/BTB and improve therapeutic distribution to brain tumors, (b) evaluated the use of azacitidine as a single agent therapy for the treatment of brain metastasis of breast cancer and a potential molecular mechanism by which brain tropic cells are sensitized to hypomethylating agents, (c) determined the impact cannabidiol has on P-glycoprotein mediated efflux at the blood-brain barrier and its potential for use as a single agent treatment for metastatic brain tumors, (d) developed a preclinical radiation therapy protocol for use in small animals and in vitro …