The Structural and Functional Connectome and Prediction of Risk for Cognitive Impairment in Older Adults

The human connectome refers to a comprehensive description of the brain's structural and functional connections in terms of brain networks. As the field of brain connectomics has developed, data acquisition, subsequent processing and modeling, and ultimately the representation of the connectome have become better defined and integrated with network science approaches. In this way, the human connectome has provided a way to elucidate key features of not only the healthy brain but also diseased brains. The field has quickly evolved, offering insights into network disruptions that are characteristic for specific neurodegenerative disorders. In this paper, we provide a brief review of the field of brain connectomics, as well as a more in-depth survey of recent studies that have provided new insights into brain network pathologies, including those found in Alzheimer's disease (AD), patients with mild cognitive impairment (MCI), and finally in people classified as being "at risk". Until the emergence of brain connectomics, most previous studies had assessed neurodegenerative diseases mainly by focusing on specific and dispersed locales in the brain. Connectomics-based approaches allow us to model the brain as a network, which allows for inferences about how dynamic changes in brain function would be affected in relation to structural changes. In fact, looking at diseases using network theory gives rise to new hypotheses on mechanisms of pathophysiology and clinical symptoms. Finally, we discuss the future of this field and how understanding both the functional and structural connectome can aid in gaining sharper insight into changes in biological brain networks associated with cognitive impairment and dementia

Brain explorer for connectomic analysis

Visualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional, and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomical structure. In this paper, new surface texture techniques are developed to map non-spatial attributes onto both 3D brain surfaces and a planar volume map which is generated by the proposed volume rendering technique, spherical volume rendering. Two types of non-spatial information are represented: (1) time series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image-based phenotypic biomarkers for brain diseases

Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting-state networks

INTRODUCTION: Pathophysiological changes that accompany early clinical symptoms in prodromal Alzheimer's disease (AD) may have a disruptive influence on brain networks. We investigated resting-state functional magnetic resonance imaging (rsfMRI), combined with brain connectomics, to assess changes in whole-brain functional connectivity (FC) in relation to neurocognitive variables. METHODS: Participants included 58 older adults who underwent rsfMRI. Individual FC matrices were computed based on a 278-region parcellation. FastICA decomposition was performed on a matrix combining all subjects' FC. Each FC pattern was then used as a response in a multilinear regression model including neurocognitive variables associated with AD (cognitive complaint index [CCI] scores from self and informant, an episodic memory score, and an executive function score). RESULTS: Three connectivity independent component analysis (connICA) components (RSN, VIS, and FP-DMN FC patterns) associated with neurocognitive variables were identified based on prespecified criteria. RSN-pattern, characterized by increased FC within all resting-state networks, was negatively associated with self CCI. VIS-pattern, characterized by an increase in visual resting-state network, was negatively associated with CCI self or informant scores. FP-DMN-pattern, characterized by an increased interaction of frontoparietal and default mode networks (DMN), was positively associated with verbal episodic memory. DISCUSSION: Specific patterns of FC were differently associated with neurocognitive variables thought to change early in the course of AD. An integrative connectomics approach relating cognition to changes in FC may help identify preclinical and early prodromal stages of AD and help elucidate the complex relationship between subjective and objective indices of cognitive decline and differences in brain functional organization

CRP 463: University Area Multi-Modal Access Plan June 2016

This study outlines work completed as a part of the CRP 463 senior capstone class outlining a new, comprehensive approach to active transportation on the Cal Poly campus. Led by Dr. William Riggs the project assessed the current conditions, identified opportunities and constraints and then developed conceptual options for a campus active transportation plan. In addition to this process the plan involved completion of a draft Bicycle Friendly University application for the Cal Poly campus (included as a supplemental file) and envisioned conceptual design options for various locations on the campus. Key locations evaluated included the Perimeter Road / University Drive corridor running through campus and the Bella Montana residential campus. The ultimate goal for the plan and these concepts was to expand on proposals from the Cal Poly Masterplan, and provide development templates for future planning and growth that supports multi-modal travel

Resting state network profiles of Alzheimer disease and frontotemporal dementia: A preliminary examination

OBJECTIVES/SPECIFIC AIMS: Recent evidence from resting-state fMRI studies have shown that brain network connectivity is altered in patients with neurodegenerative disorders. However, few studies have examined the complete connectivity patterns of these well-reported RSNs using a whole brain approach and how they compare between dementias. Here, we used advanced connectomic approaches to examine the connectivity of RSNs in Alzheimer disease (AD), Frontotemporal dementia (FTD), and age-matched control participants. METHODS/STUDY POPULATION: In total, 44 participants [27 controls (66.4±7.6 years), 13 AD (68.5.63±13.9 years), 4 FTD (59.575±12.2 years)] from an ongoing study at Indiana University School of Medicine were used. Resting-state fMRI data was processed using an in-house pipeline modeled after Power et al. (2014). Images were parcellated into 278 regions of interest (ROI) based on Shen et al. (2013). Connectivity between each ROI pair was described by Pearson correlation coefficient. Brain regions were grouped into 7 canonical RSNs as described by Yeo et al. (2015). Pearson correlation values were then averaged across pairs of ROIs in each network and averaged across individuals in each group. These values were used to determine relative expression of FC in each RSN (intranetwork) and create RSN profiles for each group. RESULTS/ANTICIPATED RESULTS: Our findings support previous literature which shows that limbic networks are disrupted in FTLD participants compared with AD and age-matched controls. In addition, interactions between different RSNs was also examined and a significant difference between controls and AD subjects was found between FP and DMN RSNs. Similarly, previous literature has reported a disruption between executive (frontoparietal) network and default mode network in AD compared with controls. DISCUSSION/SIGNIFICANCE OF IMPACT: Our approach allows us to create profiles that could help compare intranetwork FC in different neurodegenerative diseases. Future work with expanded samples will help us to draw more substantial conclusions regarding differences, if any, in the connectivity patterns between RSNs in various neurodegenerative diseases

Changes in salivary analytes in canine parvovirus : A high-resolution quantitative proteomic study

The present study evaluated the changes in salivary proteome in parvoviral enteritis (PVE) in dogs through a high-throughput quantitative proteomic analysis. Saliva samples from healthy dogs and dogs with severe parvovirosis that survived or perished due to the disease were analysed and compared by Tandem Mass Tags (TMT) analysis. Proteomic analysis quantified 1516 peptides, and 287 (corresponding to 190 proteins) showed significantly different abundances between studied groups. Ten proteins were observed to change significantly between dogs that survived or perished due to PVE. Bioinformatics' analysis revealed that saliva reflects the involvement of different pathways in PVE such as catalytic activity and binding, and indicates antimicrobial humoral response as a pathway with a major role in the development of the disease. These results indicate that saliva proteins reflect physiopathological changes that occur in PVE and could be a potential source of biomarkers for this disease

Science Gateways and AI/ML: How Can Gateway Concepts and Solutions Meet the Needs in Data Science?

Science gateways are a crucial component of critical infrastructure as they provide the means for users to focus on their topics and methods instead of the technical details of the infrastructure. They are defined as end-to-end solutions for accessing data, software, computing services, sensors, and equipment specific to the needs of a science or engineering discipline and their goal is to hide the complexity of the underlying infrastructure. Science gateways are often called Virtual Research Environments in Europe and Virtual Labs in Australasia; we consider these two terms to be synonymous with science gateways. Over the past decade, artificial intelligence (AI) and machine learning (ML) have found applications in many different fields in private industry, and private industry has reaped the benefits. Likewise, in the academic realm, large-scale data science applications have also learned to apply public high-performance computing resources to make use of this technology. However, academic and research science gateways have yet to fully adopt the tools of AI. There is an opportunity in the gateways space, both to increase the visibility and accessibility to AI/ML applications and to enable researchers and developers to advance the field of science gateway cyberinfrastructure itself. Harnessing AI/ML is recognized as a high priority by the science gateway community. It is, therefore, critical for the next generation of science gateways to adapt to support the AI/ML that is already transforming many scientific fields. The goal is to increase collaborations between the two fields and to ensure that gateway services are used and are valuable to the AI/ML community. This chapter presents state-of-the-art examples and areas of opportunity for the science gateways community to pursue in relation to AI/ML and some vision of where these new capabilities might impact science gateways and support scientific research

Abcg2 labels multiple cell types in skeletal muscle and participates in muscle regeneration

Abcg2-expressing cells proliferate after muscle injury and are required for effective regeneration of multiple muscle cell lineages

Modulation of Macrophage Activation State Protects Tissue from Necrosis during Critical Limb Ischemia in Thrombospondin-1-Deficient Mice

International audienceBACKGROUND: Macrophages, key regulators of healing/regeneration processes, strongly infiltrate ischemic tissues from patients suffering from critical limb ischemia (CLI). However pro-inflammatory markers correlate with disease progression and risk of amputation, suggesting that modulating macrophage activation state might be beneficial. We previously reported that thrombospondin-1 (TSP-1) is highly expressed in ischemic tissues during CLI in humans. TSP-1 is a matricellular protein that displays well-known angiostatic properties in cancer, and regulates inflammation in vivo and macrophages properties in vitro. We therefore sought to investigate its function in a mouse model of CLI. METHODS AND FINDINGS: Using a genetic model of tsp-1(-/-) mice subjected to femoral artery excision, we report that tsp-1(-/-) mice were clinically and histologically protected from necrosis compared to controls. Tissue protection was associated with increased postischemic angiogenesis and muscle regeneration. We next showed that macrophages present in ischemic tissues exhibited distinct phenotypes in tsp-1(-/-) and wt mice. A strong reduction of necrotic myofibers phagocytosis was observed in tsp-1(-/-) mice. We next demonstrated that phagocytosis of muscle cell debris is a potent pro-inflammatory signal for macrophages in vitro. Consistently with these findings, macrophages that infiltrated ischemic tissues exhibited a reduced postischemic pro-inflammatory activation state in tsp-1(-/-) mice, characterized by a reduced Ly-6C expression and a less pro-inflammatory cytokine expression profile. Finally, we showed that monocyte depletion reversed clinical and histological protection from necrosis observed in tsp-1(-/-) mice, thereby demonstrating that macrophages mediated tissue protection in these mice. CONCLUSION: This study defines targeting postischemic macrophage activation state as a new potential therapeutic approach to protect tissues from necrosis and promote tissue repair during CLI. Furthermore, our data suggest that phagocytosis plays a crucial role in promoting a deleterious intra-tissular pro-inflammatory macrophage activation state during critical injuries. Finally, our results describe TSP-1 as a new relevant physiological target during critical leg ischemia

Acute periodontal lesions

This is a review and update on acute conditions affecting the gingival tissues, including abscesses in the periodontium, necrotizing periodontal diseases, and other acute conditions that cause gingival lesions with acute presentation, such as infectious process not associated with oral bacterial biofilms, muco-cutanenous disorders, and traumatic and allergic lesions. A periodontal abscess is clinically important since it is a relatively frequent dental emergency, it can compromise the periodontal prognosis of the affected tooth, and because bacteria within the abscess have been identified, mainly by the type of etiology, and there are clear diffrences between those affecting a previously existing periodontal pocket ahd those affecting healthy sites. Therapy for this acute condition consists of drainage and tissue debridement, with individual evaluation of the need for systemic antimicrobial therapy. the definitive treatment of the pre-existing condition should be accomplished after the acute phase is controlled. Necrotizing periodontal disease (NPD) present three typical clinical features : papilla necrosis, gingival bleeding, and pain. Although the prevalence of these diseases is not high, their importance is clear, since they represent the most severe conditions associated with dental biofilm, with very rapid tissue destruction. In adittion to bacteria, the etiology of NPD includes numerous factors that alter the host response and predispose to these diseases, including HIV infection, malnutrition, stress, and tobacco smoking. The treatment consists of superficial debridement, careful mechanical oral hygiene, rinsing with chlorhexidine, and daily re-evaluation. Systemic antimicrobials may be used adjunctively in severe cases or in non-responding conditions and the best option is metronidazole.Once the acute disease is under control, definitive treatment should be provided, including the adequate therapy for the pre-existing gingivitis or periodontitis. Among other acute conditions affecting the periodontal tissues, but not caused by the microorganisms present in oral biofilms , are infectious diseases, muco-cutaneous diseases and traumatic or allergic lesions. In most cases, the gingival envolvement is not severe, though they are common and may prompt a dental emergency visit. These conditions may the direct result of a trauma or the consequence of the breaking of vesicles and bullae. A proper differential diagnosis is important for an adequate management of the case