Following a cortical injury, neurons in areas near and connected to the site of injury begin to degenerate. The observed neuronal death may contribute to the severity of the observed behavioral impairments. The purpose of the present study was to examine if progesterone, a hormone known for its effectiveness at reducing cerebral edema, could protect against secondary neuronal death and facilitate the acquisition of an avoidance learning task in an ablation model of cortical injury. Rats served as sham controls or received bilateral ablation of the medial prefrontal cortex followed by a 10-day regimen of progesterone (4 mg/kg) or oil vehicle (1 ml/kg) beginning 1 h after cortical lesions. Progesterone-treated lesion rats showed a significant facilitation of avoidance learning compared to oil- treated lesion controls. In addition, progesterone-treated lesion animals did not differ from either progesterone- or oil-treated sham controls in avoidance learning. Anatomical analysis revealed that progesterone treatment decreased the amount of neuronal death seen in the striatum and the mediodorsal nucleus of the thalamus. The findings are consistent with the notion that progesterone is an effective neuroprotective agent and suggest that the hormone can reduce the behavioral impairments associated with frontal cortical ablation injury.

Spatial learning in rodents requires normal functioning of hippocampal and cortical structures. Recent data suggest that the cerebellum may also be esential. Neurological mutant mice with dysgenesis of the cerebellum provide useful models to examine the effects of abnormal cerebellar function. Mice with one such mutation, Purkinje cell degeneration (pcd), in which Purkinje cells degenerate between the third and fourth postnatal weeks, were evaluated for performance of spatial navigation learning and visual guidance learning in the Morris maze swim-escape task. Unaffected littermates and C57BL/6J mice served as controls. Separate groups of pcd and control mice were tested at 30, 50 and 110 days of age. At all ages, pcd mice had severe deficits in distal-cue (spatial) navigation, failing to decrease path lengths over training and failing to express appropriate spatial biases on probe trials. On the proximal-cue (visual guidance) task, whenever performance differences between groups did occur, they were limited to the initial trials. The ability of the pcd mice to perform the proximal-cue but not the distal-cue task indicates that the massive spatial navigation deficit was not due simply to motor dysfunction. Histological evaluations confirmed that the pcd mutation resulted in Purkinje cell loss without significant depletion of cells in the hippocampal formation. Teese data provide further evidence that the cerebellum is vital for the expression of behavior directed by spatial cognitive processes.

Degeneration of the noradrenergic neurons has been reported in the brain of patients suffering from neurodegenerative diseases. However, their pathological characteristics during the neurodegenerative course and underlying mechanisms remain to be elucidated. In the present study, we used the neurotoxin camptothecin (CPT) to induce the DNA damage response in neuroblastoma SH-SY5Y cells, normal fibroblast cells, and primarily cultured locus coeruleus (LC) and raphe neurons to examine cellular responses and repair capabilities after neurotoxin exposure. To our knowledge, the present study is the first to show that noradrenergic SH-SY5Y cells are more sensitive to CPT-induced DNA damage and deficient in DNA repair, as compared to fibroblast cells. Furthermore, similar to SH-SY5Y cells, primarily cultured LC neurons are more sensitive to CPT-induced DNA damage and show a deficiency in repairing this damage. Moreover, while N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP4) exposure also results in DNA damage in cultured LC neurons, neither CPT nor DSP4 induce DNA damage in neuronal cultures from the raphe nuclei. Taken together, noradrenergic SH-SY5Y cells and LC neurons are sensitive to CPT-induced DNA damage and exhibit a repair deficiency, providing a mechanistic explanation for the pathological characteristics of LC degeneration when facing endogenous and environmental DNA-damaging insults in vivo.

Dopamine β-hydroxylase (DBH) and norepinephrine (NE) transporter (NET) are the noradrenergic phenotypes for their functional importance to noradrenergic neurons. It is known that in vivo N-(2-chloroethyl)-N-ethyl-2- bromobenzylamine (DSP4) treatment induces degeneration of noradrenergic terminals by interacting with NET and depleting intracellular NE. However, DSP4's precise mechanism of action remains unclear. In this study various biochemical approaches were employed to test the hypothesis that DSP4 down-regulates the expression of DBH and NET, and to determine molecular mechanisms that may be involved. The results showed that treatment of SH-SY5Y neuroblastoma cells with DSP4 significantly decreased mRNA and protein levels of DBH and NET. DSP4-induced reduction of DBH mRNA and proteins, as well as NET proteins showed a time- and concentration-dependent manner. Flow cytometric analysis demonstrated that DSP4-treated cells were arrested predominantly in the S-phase, which was reversible. The arrest was confirmed by several DNA damage response markers (phosphorylation of H2AX and p53), suggesting that DSP4 causes replication stress which triggers cell cycle arrest via the S-phase checkpoints. Moreover, the comet assay verified that DSP4 induced single-strand DNA breaks. In summary, the present study demonstrated that DSP4 down-regulates the noradrenergic phenotypes, which may be mediated by its actions on DNA replication, leading to replication stress and cell cycle arrest. These action mechanisms of DSP4 may account for its degenerative consequence after systematic administration for animal models.

The World Health Organization estimates that there are 285 million people suffering from visual impairment worldwide. The top two causes of uncorrectable vision loss are glaucoma and age-related macular degeneration (AMD), with 112 million people anticipated to be impacted by glaucoma by 2040 and nearly 15% of U.S. adults aged 43-86 predicted to be diagnosed with AMD over the next 15 years. To slow the progression of these ophthalmic diseases, the most valuable preventive action is timely detection and treatment by an ophthalmologist. However, over 50% of glaucoma cases go undetected due to lack of timely assessment by a medical expert. This thesis seeks to transform artificial intelligence (AI) into a trustworthy partner to clinicians, aiding in expediting diagnostic screening for obvious cases and serving as corroboration/a ‘second opinion’ in ambiguous cases. In order to develop AI algorithms that can be trusted as team-mates in the clinic, the AI must be robust to data collected at various sites/from various patient populations, its decision-making mechanisms must be explainable, and to benefit the broadest population (for whom expensive imaging equipment and/or specialist time may not be available), it must be portable. This thesis addresses these three challenges (1) by developing and evaluating robust deep learning (DL) algorithms for detection of glaucoma and AMD from data collected at multiple sites or using multiple imaging modalities, (2) by making AI interpretable, through: (a) comparison of image concepts used by DL systems for decision-making with image regions fixated upon by human experts during glaucoma diagnosis, and (b) through odds ratio ranking of clinical biomarkers most indicative of AMD risk used by both experts and AI, and (3) by enhancing theimage quality of data collected via a portable OCT device using deep-learning based super-resolution generative adversarial network (GAN) approaches. The resulting robust deep learning algorithms achieve accuracy as high as 95% at detection of glaucoma and AMD from optical coherence tomography (OCT) and OCT angiography images/volumes. The interpretable AI-concept/expert-eye-movement comparison showed the importance of three OCT-report sub-regions used by both AI and human experts for glaucoma detection. The pipeline described here for evaluating AI robustness and validating interpretable image concepts used by deep learning systems in conjunction with expert eye movements has the potential to help standardize the acceptance of new AI tools for use in the clinic. Furthermore, the eye movement collection protocols introduced in this thesis may also help to train current medical residents and fellows regarding key features employed by expert specialists for accurate and efficient eye disease diagnosis. The odds ratio ranking of AMD biomarkers distinguished the top two clinical features (choroidal neovascularization and geographic atrophy) most indicative of AMD risk that are agreed upon by both AI and experts. Lastly, GAN-based super-resolution of portable OCT images boosted performance of downstream deep learning systems for AMD detection, facilitating future work toward embedding AI algorithms within portable OCT systems, in order for a larger population to gain access to potentially sight-saving technology. By enhancing AI robustness, interpretability, and portability, this work paves the way for ophthalmologist-AI teams to achieve augmented performance compared to human experts or AI alone, leading to expedited eye disease detection, treatment, and thus better patient outcomes.

No description available.

Age-related macular degeneration (AMD) is a major cause of blindness in adults. Abnormal growth of blood vessels in the eye during the course of AMD causes damage to the retina, resulting in irreversible blindness. The goal of this research was to determine whether physical pressure on retinal cells can contribute to the increased blood vessel formation. To replicate the tears in the cell layers, a micropatterning method was used as a means of detaching cells from each other. Two new devices were also developed to mimic slow and fast increases in mechanical pressure on cell layers of the eye. After detaching cells from each other and adding mechanical stress to cells, the levels of angiogenic proteins secreted by retinal cells were measured. The results showed that both cell-cell detachment and mechanical stress can increase the secretion of angiogenic proteins. After adding mechanical stress, we also added the secreted proteins to blood vessel cells and observed an increase in blood vessel formation, indicating that mechanical stress can independently induce angiogenesis. These results suggest that physical stimuli in the eye can contribute to the aberrant blood vessel formation in AMD.

Indiana University-Purdue University Indianapolis (IUPUI) / The thesis includes two application studies of computational fluid dynamics. The first is new and efficient drug delivery to the posterior part of the eye, a growing health necessity worldwide. Current treatment of eye diseases, such as age-related macular degeneration (AMD), relies on repeated intravitreal injections of drug-containing solutions. Such a drug delivery has significant cant drawbacks, including short drug life, vital medical service, and high medical costs. In this study, we explore a new approach of controlled drug delivery by introducing unique porous implants. Computational modeling contains physiological and anatomical traits. We simulate the IgG1 Fab drug delivery to the posterior eye to evaluate the effectiveness of the porous implants to control the drug delivery. The computational model was validated by established computation results from independent studies and experimental data. Overall, the results indicate that therapeutic drug levels in the posterior eye are sustained for eight weeks, similar to those performed with intravitreal injection of the same drug. We evaluate the effects of the porous implant on the time evaluation of the drug concentrations in the sclera, choroid, and retina layers of the eye. Subsequent simulations were carried out with varying porosity values of a porous episcleral implant. Our computational results reveal that the time evolution of drug concentration is distinctively correlated to drug source location and pore size. The response of this porous implant for controlled drug delivery applications was examined. A correlation between porosity and fluid properties for the porous implants was revealed in this study. The second application lays in the computational modeling of the oscillating

The accumulation of misfolded proteins within intracellular aggregates is a distinctive feature observed within multiple neurodegenerative diseases (NDDs). However, the genes and pathways that regulate protein misfolding, aggregation, and subsequent cellular toxicity remain poorly understood. Here I describe a high-throughput discovery platform that enables the simultaneous screening of dozens of neurodegenerative disease models to rapidly uncover genetic modifiers that alter the solubility and toxicity of a wide variety of aggregation-prone proteins. From these studies, I identify the human HSP40 chaperone, DNAJB6 as a potent rescuer of the misfolding and proteotoxicity of multiple RNA-binding proteins implicated in Frontotemporal dementia (FTD) and Amyotrophic Lateral Sclerosis (ALS) including FUS, TDP-43, and hnRNPA1. I, with collaborator help, further demonstrate that DNAJB6 has an intrinsic ability to phase separate under physiologic conditions and can alter the properties of FUS containing condensates by maintaining them in a gel-like state over long periods, preventing FUS aggregation. By conducting domain mapping studies and a deep mutational scan on DNAJB6, I am able to gain detailed insight into its mechanism of action while also uncovering a series of novel variants with enhanced activity. During the development of this multiplexed screening approach for neurodegenerative disease models, research was interrupted by a global pandemic caused by SARS-CoV-2. I realized that the themes of studying proteotoxicity of multiple related, yet distinct models could be applied towards drug development to identify inhibitors of the essential 3CL proteases encoded by multiple coronaviruses, which cause proteotoxicity when expressed in cells. As such, I develop and describe a mammalian cell-based assay to identify coronavirus 3CL protease (3CLpro) inhibitors. This essay is based on rescuing protease-mediated cytotoxicity and does not require live virus. By enabling the facile testing of compounds across a range of 15 distantly related coronavirus 3CLpro enzymes, I identify compounds with broad 3CLpro inhibitory activity. I also adapt the assay for use in compound screening and in doing so uncover additional SARS-CoV-2 3CLpro inhibitors. I observe strong concordance between data emerging from this assay and those obtained from live virus testing. The reported approach democratizes the testing of 3CLpro inhibitors by developing a simplified method for identifying coronavirus 3CLpro inhibitors that can be used by the majority of laboratories, rather than the few with extensive biosafety infrastructure. I identify two lead compounds, GC376 and compound 4, with broad activity against all 3CL proteases tested including 3CLpro enzymes from understudied zoonotic coronaviruses.

京都大学 / 0048 / 新制・課程博士 / 博士(医科学) / 甲第18904号 / 医科博第60号 / 新制||医科||4(附属図書館) / 31855 / 京都大学大学院医学研究科医科学専攻 / (主査)教授 小柳 義夫, 教授 吉村 長久, 教授 髙橋 淳 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM