Biomimetic engineered muscle with capacity for vascular integration and functional maturation in vivo.

Tissue-engineered skeletal muscle can serve as a physiological model of natural muscle and a potential therapeutic vehicle for rapid repair of severe muscle loss and injury. Here, we describe a platform for engineering and testing highly functional biomimetic muscle tissues with a resident satellite cell niche and capacity for robust myogenesis and self-regeneration in vitro. Using a mouse dorsal window implantation model and transduction with fluorescent intracellular calcium indicator, GCaMP3, we nondestructively monitored, in real time, vascular integration and the functional state of engineered muscle in vivo. During a 2-wk period, implanted engineered muscle exhibited a steady ingrowth of blood-perfused microvasculature along with an increase in amplitude of calcium transients and force of contraction. We also demonstrated superior structural organization, vascularization, and contractile function of fully differentiated vs. undifferentiated engineered muscle implants. The described in vitro and in vivo models of biomimetic engineered muscle represent enabling technology for novel studies of skeletal muscle function and regeneration.

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Changes in Brain Resting-state Functional Connectivity Associated with Peripheral Nerve Block: A Pilot Study.

BACKGROUND: Limited information exists on the effects of temporary functional deafferentation (TFD) on brain activity after peripheral nerve block (PNB) in healthy humans. Increasingly, resting-state functional connectivity (RSFC) is being used to study brain activity and organization. The purpose of this study was to test the hypothesis that TFD through PNB will influence changes in RSFC plasticity in central sensorimotor functional brain networks in healthy human participants. METHODS: The authors achieved TFD using a supraclavicular PNB model with 10 healthy human participants undergoing functional connectivity magnetic resonance imaging before PNB, during active PNB, and during PNB recovery. RSFC differences among study conditions were determined by multiple-comparison-corrected (false discovery rate-corrected P value less than 0.05) random-effects, between-condition, and seed-to-voxel analyses using the left and right manual motor regions. RESULTS: The results of this pilot study demonstrated disruption of interhemispheric left-to-right manual motor region RSFC (e.g., mean Fisher-transformed z [effect size] at pre-PNB 1.05 vs. 0.55 during PNB) but preservation of intrahemispheric RSFC of these regions during PNB. Additionally, there was increased RSFC between the left motor region of interest (PNB-affected area) and bilateral higher order visual cortex regions after clinical PNB resolution (e.g., Fisher z between left motor region of interest and right and left lingual gyrus regions during PNB, -0.1 and -0.6 vs. 0.22 and 0.18 after PNB resolution, respectively). CONCLUSIONS: This pilot study provides evidence that PNB has features consistent with other models of deafferentation, making it a potentially useful approach to investigate brain plasticity. The findings provide insight into RSFC of sensorimotor functional brain networks during PNB and PNB recovery and support modulation of the sensory-motor integration feedback loop as a mechanism for explaining the behavioral correlates of peripherally induced TFD through PNB.

Spin-state splittings, highest-occupied-molecular-orbital and lowest-unoccupied-molecular-orbital energies, and chemical hardness.

It is known that the exact density functional must give ground-state energies that are piecewise linear as a function of electron number. In this work we prove that this is also true for the lowest-energy excited states of different spin or spatial symmetry. This has three important consequences for chemical applications: the ground state of a molecule must correspond to the state with the maximum highest-occupied-molecular-orbital energy, minimum lowest-unoccupied-molecular-orbital energy, and maximum chemical hardness. The beryllium, carbon, and vanadium atoms, as well as the CH(2) and C(3)H(3) molecules are considered as illustrative examples. Our result also directly and rigorously connects the ionization potential and electron affinity to the stability of spin states.

Structural manifestation of the delocalization error of density functional approximations: C(4N+2) rings and C(20) bowl, cage, and ring isomers.

The ground state structure of C(4N+2) rings is believed to exhibit a geometric transition from angle alternation (N < or = 2) to bond alternation (N > 2). All previous density functional theory (DFT) studies on these molecules have failed to reproduce this behavior by predicting either that the transition occurs at too large a ring size, or that the transition leads to a higher symmetry cumulene. Employing the recently proposed perspective of delocalization error within DFT we rationalize this failure of common density functional approximations (DFAs) and present calculations with the rCAM-B3LYP exchange-correlation functional that show an angle-to-bond-alternation transition between C(10) and C(14). The behavior exemplified here manifests itself more generally as the well known tendency of DFAs to bias toward delocalized electron distributions as favored by Huckel aromaticity, of which the C(4N+2) rings provide a quintessential example. Additional examples are the relative energies of the C(20) bowl, cage, and ring isomers; we show that the results from functionals with minimal delocalization error are in good agreement with CCSD(T) results, in contrast to other commonly used DFAs. An unbiased DFT treatment of electron delocalization is a key for reliable prediction of relative stability and hence the structures of complex molecules where many structure stabilization mechanisms exist.

Reformulating time-dependent density functional theory with non-orthogonal localized molecular orbitals.

Time-dependent density functional theory (TDDFT) has broad application in the study of electronic response, excitation and transport. To extend such application to large and complex systems, we develop a reformulation of TDDFT equations in terms of non-orthogonal localized molecular orbitals (NOLMOs). NOLMO is the most localized representation of electronic degrees of freedom and has been used in ground state calculations. In atomic orbital (AO) representation, the sparsity of NOLMO is transferred to the coefficient matrix of molecular orbitals (MOs). Its novel use in TDDFT here leads to a very simple form of time propagation equations which can be solved with linear-scaling effort. We have tested the method for several long-chain saturated and conjugated molecular systems within the self-consistent charge density-functional tight-binding method (SCC-DFTB) and demonstrated its accuracy. This opens up pathways for TDDFT applications to large bio- and nano-systems.

Phosphorylation/dephosphorylation of the beta-adrenergic receptor regulates its functional coupling to adenylate cyclase and subcellular distribution.

Prolonged exposure of cells or tissues to drugs or hormones such as catecholamines leads to a state of refractoriness to further stimulation by that agent, known as homologous desensitization. In the case of the beta-adrenergic receptor coupled to adenylate cyclase, this process has been shown to be intimately associated with the sequestration of the receptors from the cell surface through a cAMP-independent process. Recently, we have shown that homologous desensitization in the frog erythrocyte model system is also associated with increased phosphorylation of the beta-adrenergic receptor. We now provide evidence that the phosphorylation state of the beta-adrenergic receptor regulates its functional coupling to adenylate cyclase, subcellular translocation, and recycling to the cell surface during the process of agonist-induced homologous desensitization. Moreover, we show that the receptor phosphorylation is reversed by a phosphatase specifically associated with the sequestered subcellular compartment. At 23 degrees C, the time courses of beta-adrenergic receptor phosphorylation, sequestration, and adenylate cyclase desensitization are identical, occurring without a lag, exhibiting a t1/2 of 30 min, and reaching a maximum at approximately 3 hr. Upon cell lysis, the sequestered beta-adrenergic receptors can be partially recovered in a light membrane vesicle fraction that is separable from the plasma membranes by differential centrifugation. The increased beta-adrenergic receptor phosphorylation is apparently reversed in the sequestered vesicle fraction as the sequestered receptors exhibit a phosphate/receptor stoichiometry that is similar to that observed under basal conditions. High levels of a beta-adrenergic receptor phosphatase activity appear to be associated with the sequestered vesicle membranes. The functional activity of the phosphorylated beta-adrenergic receptor was examined by reconstituting purified receptor with its biochemical effector the guanine nucleotide regulatory protein (Ns) in phospholipid vesicles and assessing the receptor-stimulated GTPase activity of Ns. Compared to controls, phosphorylated beta-adrenergic receptors, purified from desensitized cells, were less efficacious in activating the Ns GTPase activity. These results suggest that phosphorylation of the beta-adrenergic receptor leads to its functional uncoupling and physical translocation away from the cell surface into a sequestered membrane domain. In the sequestered compartment, the phosphorylation is reversed thus enabling the receptor to recycle back to the cell surface and recouple with adenylate cyclase.

A Dynamic Directional Model for Effective Brain Connectivity using Electrocorticographic (ECoG) Time Series.

We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated sub-networks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

Engineering Highly-functional, Self-regenerative Skeletal Muscle Tissues with Enhanced Vascularization and Survival in Vivo

Tissue engineering of biomimetic skeletal muscle may lead to development of new therapies for myogenic repair and generation of improved in vitro models for studies of muscle function, regeneration, and disease. For the optimal therapeutic and in vitro results, engineered muscle should recreate the force-generating and regenerative capacities of native muscle, enabled respectively by its two main cellular constituents, the mature myofibers and satellite cells (SCs). Still, after 20 years of research, engineered muscle tissues fall short of mimicking contractile function and self-repair capacity of native skeletal muscle. To overcome this limitation, we set the thesis goals to: 1) generate a highly functional, self-regenerative engineered skeletal muscle and 2) explore mechanisms governing its formation and regeneration in vitro and survival and vascularization in vivo.

By studying myogenic progenitors isolated from neonatal rats, we first discovered advantages of using an adherent cell fraction for engineering of skeletal muscles with robust structure and function and the formation of a SC pool. Specifically, when synergized with dynamic culture conditions, the use of adherent cells yielded muscle constructs capable of replicating the contractile output of native neonatal muscle, generating >40 mN/mm2 of specific force. Moreover, tissue structure and cellular heterogeneity of engineered muscle constructs closely resembled those of native muscle, consisting of aligned, striated myofibers embedded in a matrix of basal lamina proteins and SCs that resided in native-like niches. Importantly, we identified rapid formation of myofibers early during engineered muscle culture as a critical condition leading to SC homing and conversion to a quiescent, non-proliferative state. The SCs retained natural regenerative capacity and activated, proliferated, and differentiated to rebuild damaged myofibers and recover contractile function within 10 days after the muscle was injured by cardiotoxin (CTX). The resulting regenerative response was directly dependent on the abundance of SCs in the engineered muscle that we varied by expanding starting cell population under different levels of basic fibroblast growth factor (bFGF), an inhibitor of myogenic differentiation. Using a dorsal skinfold window chamber model in nude mice, we further demonstrated that within 2 weeks after implantation, initially avascular engineered muscle underwent robust vascularization and perfusion and exhibited improved structure and contractile function beyond what was achievable in vitro.

To enhance translational value of our approach, we transitioned to use of adult rat myogenic cells, but found that despite similar function to that of neonatal constructs, adult-derived muscle lacked regenerative capacity. Using a novel platform for live monitoring of calcium transients during construct culture, we rapidly screened for potential enhancers of regeneration to establish that many known pro-regenerative soluble factors were ineffective in stimulating in vitro engineered muscle recovery from CTX injury. This led us to introduce bone marrow-derived macrophages (BMDMs), an established non-myogenic contributor to muscle repair, to the adult-derived constructs and to demonstrate remarkable recovery of force generation (>80%) and muscle mass (>70%) following CTX injury. Mechanistically, while similar patterns of early SC activation and proliferation upon injury were observed in engineered muscles with and without BMDMs, a significant decrease in injury-induced apoptosis occurred only in the presence of BMDMs. The importance of preventing apoptosis was further demonstrated by showing that application of caspase inhibitor (Q-VD-OPh) yielded myofiber regrowth and functional recovery post-injury. Gene expression analysis suggested muscle-secreted tumor necrosis factor-α (TNFα) as a potential inducer of apoptosis as common for muscle degeneration in diseases and aging in vivo. Finally, we showed that BMDM incorporation in engineered muscle enhanced its growth, angiogenesis, and function following implantation in the dorsal window chambers in nude mice.

In summary, this thesis describes novel strategies to engineer highly contractile and regenerative skeletal muscle tissues starting from neonatal or adult rat myogenic cells. We find that age-dependent differences of myogenic cells distinctly affect the self-repair capacity but not contractile function of engineered muscle. Adult, but not neonatal, myogenic progenitors appear to require co-culture with other cells, such as bone marrow-derived macrophages, to allow robust muscle regeneration in vitro and rapid vascularization in vivo. Regarding the established roles of immune system cells in the repair of various muscle and non-muscle tissues, we expect that our work will stimulate the future applications of immune cells as pro-regenerative or anti-inflammatory constituents of engineered tissue grafts. Furthermore, we expect that rodent studies in this thesis will inspire successful engineering of biomimetic human muscle tissues for use in regenerative therapy and drug discovery applications.