System-level analyses to identify macrophage-specific mechanisms controlling skeletal muscle regeneration

Skeletal muscle regeneration is a complex interplay between various cell types including invading macrophages. Their recruitment to damaged tissues upon acute sterile injuries is necessary for necrotic debris clearance and for coordination of tissue regeneration. This highly dynamic process is characterized by an in situ transition of infiltrating monocytes from an inflammatory (Ly6Chigh) to a repair (Ly6Clow) macrophage phenotype. System-level gene expression analysis revealed that the time course of muscle regeneration, much more than Ly6C status, was correlated with the largest differential gene expression. This indicated that the time course of inflammation was the predominant driving force of macrophage gene expression. These findings validate the dynamic nature of the macrophage response and associate a specific gene signature to predictive specialized functions of macrophages at each step of muscle regeneration. However, the gene regulatory events supporting the sensory and effector functions of macrophages involved in tissue repair are not well understood. Here, we show that the lipid activated transcription factor (TF), PPARg is required for proper skeletal muscle regeneration acting in repair MFs. PPARg controls the expression of the TGFβ family member, GDF3, which in turn regulates the restoration of skeletal muscle integrity by stimulating myoblast cell fusion. In addition, to delineate the order of transcriptional events during monocyte infiltration and in situ macrophage differentiation we generated chromatin accessibility maps using ATAC-seq. We found that a large class of genomic regulatory elements is becoming de novo accessible during monocyte infiltration in the muscle, and motif analysis showed that these sites are highly enriched to the MARE motif, compared to other common macrophage specific motifs. We also identified BACH1, a heme-regulated MARE-binding TF, as a novel regulatory molecule. The contribution of this molecule and downstream targets such as Hmox1, have been evaluated using full body and macrophage-specific knock-outs. Surprisingly, the inactivation of either Bach1 or Hmox1 in macrophages impairs muscle regeneration by altering the dynamics of the macrophage phenotypic transition. In addition, Bach1 deletion leads to transcriptional deregulation of critical inflammatory genes in macrophages upon injury. By using bone marrow-derived macrophages, we found BACH1 to bind extensively to enhancers of these genes, suggesting that fine-tuning of transient inflammatory transcriptional programs in macrophages during tissue injury, largely depend on MARE-binding TFs. Overall, this work establishes PPARg and BACH1 as required environment sensors and transcriptional regulators of muscle infiltrating MFs. Moreover, this work also establishes GDF3 as a secreted extrinsic effector protein acting on myoblasts and serving as a regeneration factor in tissue repair. The importance of the macrophage phenotypic shift and the cell cross-talk of the local muscle tissue with the infiltrating macrophages during tissue regeneration upon injury are also not fully understood and their study lacks adequate methodology. Here, by using an acute sterile skeletal muscle injury model combined with irradiation, bone marrow transplantation and in vivo imaging we show that preserved muscle integrity and cell composition prior to the injury is necessary for repair macrophage phenotypic transition and subsequently for proper and complete tissue regeneration. Importantly, by using a model of in vivo ablation of PAX7 positive cells, we show that this radiosensitive skeletal muscle progenitor pool contributes to macrophage phenotypic transition following acute sterile muscle injury. Taken together, our data suggest the existence of a more extensive and reciprocal cross-talk between muscle tissue compartments, including satellite cells, and infiltrating myeloid cells upon tissue damage. These interactions are shaping the macrophages in-situ phenotypic shift, which is indispensable for normal muscle tissue repair dynamics.d

In situ macrophage phenotypic transition is affected by altered cellular composition prior to acute sterile muscle injury

K

Scaffold and Tissue Based Therapies to Improve Skeletal Muscle Regeneration After Volumetric Muscle Loss

Volumetric muscle loss (VML) is an injury to skeletal muscle characterized by a loss of more than 20% of a muscles volume. The combination of the bulk loss of tissue, transection and separation of myofibers proximal and distal to the injury, loss of innervation and blood supply, and the depletion of muscle progenitor cells results in permanent fibrosis and functional deficits due to loss of contractile tissue. Scaffolds, cells, and engineered constructs have been explored as potential therapeutic interventions to induce myogenesis at the site of a VML injury in animal models, in addition to limited clinical trials. This dissertation summarizes the current state of the field and explores possible strategies for repairing VML and understanding the mechanisms underlying the regenerative response of VML-damaged muscle. The challenges currently facing the skeletal muscle tissue engineering are presented along with potential approaches to further the field and deliver effective treatment options for patients and their physicians

Architecture + Behavior: the built environment, natural landscapes and at-risk youth

There exists an interesting parallel between the power and the limits of architecture and its relationship to the human experience. This thesis proposes the question of how architecture can affect behavior in light of both the poetic and the practical in regards to the built environment. By understanding the user, incorporating the mission and goals of the client, and striving to connect aspects of the built environment to the two, architecture can act as a powerful influencer on behavior. These ideas, along with research (in camp history, play theory, young adolescent development and learning, experiential learning, environment-behavior relationships, the natural environment and place preference) are used for the planning and design of the summer camp for the Boys and Girls Clubs of Greater Memphis. The thesis serves as a guide for future development at the camp on Sardis Lake in Mississippi

Ecological genomics and adaptation of rosewoods Dalbergia cochinchinensis and D. oliveri for conservation and restoration

Global biodiversity, in particular tropical forests, is decreasing under both environmental change and anthropogenic disturbance. Environmental change alters species’ adaptability to their current habitat, leading to loss of fitness and range shift, while anthropogenic disturbance reduces their adaptive capacity. Conserving and restoring threatened species and ecosystems thus become a grand challenge for the 21st century. This thesis studies two threatened rosewood species, Dalbergia cochinchinensis and D. oliveri, which are illegally exploited for their valuable timber in the Greater Mekong Subregion. They became the world’s most trafficked wild product between 2005 and 2014, amounting to ~40% of the total global trade. Conservation efforts grew in the last decade to tackle the range-wide challenge, aiming to improve the species’ survival, amplify the production of genetic materials, and designate more conservation units. However, a sustainable supply of genetic materials can meet several challenges that compromise the effectiveness of a restoration programme, namely the genetic bottlenecks, maladaptation, and climate change. While knowledge of adaptation can predict and mitigate these risks, standard study approaches such as common garden experiments have become impractical due to the acute threats of illegal logging in these two species, which are lacking in a priori knowledge. This thesis aims to increase the knowledge of genetic and physiological underpinning of adaptation in the two Dalbergia species with relevance to application in conservation and restoration strategies. This thesis presents a rich body of genomic resources such as chromosome-scale genomes and reference transcriptomes, which advance the progress in less-represented angiosperm tree genomes and woody legume genomes and enable studies in genetic diversity. Comparative genomic studies revealed insight into the evolution and potential adaptive role of of certain gene families in tropical Dalbergia species. The landscape genomic study provides a comprehensive scan of adaptive signals and reports significant differences of the adaptive variation between the two species, where D. cochinchinensis is driven by temperature variability and D. oliveri by precipitation variability. The controlled stress experiment provides a physiological understanding of how the two species regulate their water relations and photosynthetic apparatus to respond to drought differently, where D. cochinchinensis has a more anisohydric behaviour than D. oliveri. These contrasting patterns of adaptation indicate how the two species may differentiate their niches, while co-occurring in some habitats. The knowledge of adaptive variation identifies hotspots of local adaptation and vulnerability towards climate change, and thus are expected to help conservation practitioners delineate conservation units, compare provenances for assisted germplasm transfer, and prioritise conservation actions. It also opens new avenues for future research, including combining common garden experiments and genomic approaches to more fully unravel genotype-phenotype-environment relationships

Campus Communications Systems: Converging Technologies

This book is a rewrite of Campus Telecommunications Systems: Managing Change, a book that was written by ACUTA in 1995. In the past decade, our industry has experienced a thousand-fold increase in data rates as we migrated from 10 megabit links (10 million bits per second) to 10 gigabit links (10 billion bits per second), we have seen the National Telecommunications Policy completely revamped; we have seen the combination of voice, data, and video onto one network; and we have seen many of our service providers merge into larger corporations able to offer more diverse services. When this book was last written, A CUT A meant telecommunications, convergence was a mathematical term, triple play was a baseball term, and terms such as iPod, DoS, and QoS did not exist. This book is designed to be a communications primer to be used by new entrants into the field of communications in higher education and by veteran communications professionals who want additional information in areas other than their field of expertise. There are reference books and text books available on every topic discussed in this book if a more in-depth explanation is desired. Individual chapters were authored by communications professionals from various member campuses. This allowed the authors to share their years of experience (more years than many of us would care to admit to) with the community at large. Foreword Walt Magnussen, Ph.D. Preface Ron Kovac, Ph.D. 1 The Technology Landscape: Historical Overview . Walt Magnussen, Ph.D. 2 Emerging Trends and Technologies . Joanne Kossuth 3 Network Security . Beth Chancellor 4 Security and Disaster Planning and Management Marjorie Windelberg, Ph.D. 5 Student Services in a University Setting . Walt Magnussen, Ph.D. 6 Administrative Services David E. O\u27Neill 7 The Business Side of Information Technology George Denbow 8 The Role of Consultants . David C. Metz Glossary Michelle Narcavag

Numerical modeling of thermal bar and stratification pattern in Lake Ontario using the EFDC model

Thermal bar is an important phenomenon in large, temperate lakes like Lake Ontario. Spring thermal bar formation reduces horizontal mixing, which in turn, inhibits the exchange of nutrients. Evolution of the spring thermal bar through Lake Ontario is simulated using the 3D hydrodynamic model Environmental Fluid Dynamics Code (EFDC). The model is forced with the hourly meteorological data from weather stations around the lake, flow data for Niagara and St. Lawrence rivers, and lake bathymetry. The simulation is performed from April to July, 2011; on a 2-km grid. The numerical model has been calibrated by specifying: appropriate initial temperature and solar radiation attenuation coefficients. The existing evaporation algorithm in EFDC is updated to modified mass transfer approach to ensure correct simulation of evaporation rate and latent heatflux. Reasonable values for mixing coefficients are specified based on sensitivity analyses. The model simulates overall surface temperature profiles well (RMSEs between 1-2°C). The vertical temperature profiles during the lake mixed phase are captured well (RMSEs < 0.5°C), indicating that the model sufficiently replicates the thermal bar evolution process. An update of vertical mixing coefficients is under investigation to improve the summer thermal stratification pattern. Keywords: Hydrodynamics, Thermal BAR, Lake Ontario, GIS

Towards Scalable, Private and Practical Deep Learning

Deep Learning (DL) models have drastically improved the performance of Artificial Intelligence (AI) tasks such as image recognition, word prediction, translation, among many others, on which traditional Machine Learning (ML) models fall short. However, DL models are costly to design, train, and deploy due to their computing and memory demands. Designing DL models usually requires extensive expertise and significant manual tuning efforts. Even with the latest accelerators such as Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU), training DL models can take prohibitively long time, therefore training large DL models in a distributed manner is a norm. Massive amount of data is made available thanks to the prevalence of mobile and internet-of-things (IoT) devices. However, regulations such as HIPAA and GDPR limit the access and transmission of personal data to protect security and privacy. Therefore, enabling DL model training in a decentralized but private fashion is urgent and critical. Deploying trained DL models in a real world environment usually requires meeting Quality of Service (QoS) standards, which makes adaptability of DL models an important yet challenging matter.  In this dissertation, we aim to address the above challenges to make a step towards scalable, private, and practical deep learning. To simplify DL model design, we propose Efficient Progressive Neural-Architecture Search (EPNAS) and FedCust to automatically design model architectures and tune hyperparameters, respectively. To provide efficient and robust distributed training while preserving privacy, we design LEASGD, TiFL, and HDFL. We further conduct a study on the security aspect of distributed learning by focusing on how data heterogeneity affects backdoor attacks and how to mitigate such threats. Finally, we use super resolution (SR) as an example application to explore model adaptability for cross platform deployment and dynamic runtime environment. Specifically, we propose DySR and AdaSR frameworks which enable SR models to meet QoS by dynamically adapting to available resources instantly and seamlessly without excessive memory overheads

Science-based restoration monitoring of coastal habitats, Volume Two: Tools for monitoring coastal habitats

Healthy coastal habitats are not only important ecologically; they also support healthy coastal communities and improve the quality of people’s lives. Despite their many benefits and values, coastal habitats have been systematically modified, degraded, and destroyed throughout the United States and its protectorates beginning with European colonization in the 1600’s (Dahl 1990). As a result, many coastal habitats around the United States are in desperate need of restoration. The monitoring of restoration projects, the focus of this document, is necessary to ensure that restoration efforts are successful, to further the science, and to increase the efficiency of future restoration efforts