A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.

Model and visualise the relationship between energy consumption and temperature distribution in cold rooms

In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

Simplified decoding techniques for linear block codes

Error correcting codes are combinatorial objects, designed to enable reliable transmission of digital data over noisy channels. They are ubiquitously used in communication, data storage etc. Error correction allows reconstruction of the original data from received word. The classical decoding algorithms are constrained to output just one codeword. However, in the late 50’s researchers proposed a relaxed error correction model for potentially large error rates known as list decoding. The research presented in this thesis focuses on reducing the computational effort and enhancing the efficiency of decoding algorithms for several codes from algorithmic as well as architectural standpoint. The codes in consideration are linear block codes closely related to Reed Solomon (RS) codes. A high speed low complexity algorithm and architecture are presented for encoding and decoding RS codes based on evaluation. The implementation results show that the hardware resources and the total execution time are significantly reduced as compared to the classical decoder. The evaluation based encoding and decoding schemes are modified and extended for shortened RS codes and software implementation shows substantial reduction in memory footprint at the expense of latency. Hermitian codes can be seen as concatenated RS codes and are much longer than RS codes over the same aphabet. A fast, novel and efficient VLSI architecture for Hermitian codes is proposed based on interpolation decoding. The proposed architecture is proven to have better than Kötter’s decoder for high rate codes. The thesis work also explores a method of constructing optimal codes by computing the subfield subcodes of Generalized Toric (GT) codes that is a natural extension of RS codes over several dimensions. The polynomial generators or evaluation polynomials for subfield-subcodes of GT codes are identified based on which dimension and bound for the minimum distance are computed. The algebraic structure for the polynomials evaluating to subfield is used to simplify the list decoding algorithm for BCH codes. Finally, an efficient and novel approach is proposed for exploiting powerful codes having complex decoding but simple encoding scheme (comparable to RS codes) for multihop wireless sensor network (WSN) applications.

P-glycoprotein inhibition as a strategy to increase drug delivery across the blood-brain barrier: focus on antidepressants

Depression is among the leading causes of disability worldwide. Currently available antidepressant drugs have unsatisfactory efficacy, with up to 60% of depressed patients failing to respond adequately to treatment. Emerging evidence has highlighted a potential role for the efflux transporter P-glycoprotein (P-gp), expressed at the blood-brain barrier (BBB), in the aetiology of treatment-resistant depression. In this thesis, the potential of P-gp inhibition as a strategy to enhance the brain distribution and pharmacodynamic effects of antidepressant drugs was investigated. Pharmacokinetic studies demonstrated that administration of the P-gp inhibitors verapamil or cyclosporin A (CsA) enhanced the BBB transport of the antidepressants imipramine and escitalopram in vivo. Furthermore, both imipramine and escitalopram were identified as transported substrates of human P-gp in vitro. Contrastingly, human P-gp exerted no effect on the transport of four other antidepressants (amitriptyline, duloxetine, fluoxetine and mirtazapine) in vitro. Pharmacodynamic studies revealed that pre-treatment with verapamil augmented the behavioural effects of escitalopram in the tail suspension test (TST) of antidepressant-like activity in mice. Moreover, pre-treatment with CsA exacerbated the behavioural manifestation of an escitalopram-induced mouse model of serotonin syndrome, a serious adverse reaction associated with serotonergic drugs. This finding highlights the potential for unwanted side-effects which may occur due to increasing brain levels of antidepressants by P-gp inhibition, although further studies are needed to fully elucidate the mechanism(s) at play. Taken together, the research outlined in this thesis indicates that P-gp may restrict brain concentrations of escitalopram and imipramine in patients. Moreover, we show that increasing the brain distribution of an antidepressant by P-gp inhibition can result in an augmentation of antidepressant-like activity in vivo. These findings raise the possibility that P-gp inhibition may represent a potentially beneficial strategy to augment antidepressant treatment in clinical practice. Further studies are now warranted to evaluate the safety and efficacy of this approach.

Akt signal transduction dysfunction in the 3xTg-AD mouse model of Alzheimer's disease

Alzheimer’s disease (AD) is an incurable neurodegenerative disorder, accounting for over 60% of all cases of dementia. The primary risk factor for AD is age, however several genetic and environmental factors are also involved. The pathological characteristics of AD include extracellular deposition of the beta-amyloid peptide (Aβ) and intraneuronal accumulation of neurofibrillary tangles (NFTs) made of aggregated paired helical filaments (PHFs) of the hyperphosphorylated tau protein, along with synaptic loss and neuronal death. There are numerous biochemical mechanisms involved in AD pathogenesis, however the reigning hypothesis points to toxic oligomeric Aβ species as the primary causative factor in a cascade of events leading to neuronal stress and dyshomeostasis that initiate abnormal regulation of tau. The insulin and IGF-1 receptors (IR, IGF-1R) are the primary activators of PI3- K/Akt through which they regulate cell growth, development, glucose metabolism, and learning and memory. Work in our lab and others shows increased Akt activity and phosphorylation of its downstream targets in AD brain, along with insulin and insulin-like growth factor-1 signalling (IIS) dysfunction. This is supported by studies of AD models in vivo and in vitro. Our group and others hypothesise that Aβ activates Akt through IIS to initiate a negative feedback mechanism that desensitises neurons to insulin/IGF-1, and sustains activation of Akt. In this study the functions of endogenous Akt, IR, and the insulin receptor substrate (IRS-1) were examined in relationship to Aβ and tau pathology in the 3xTg-AD mouse model, which contains three mutant human transgenes associated with familial AD or dementia. The 3xTg-AD mouse develops Aβ and tau pathology in a spatiotemporal manner that best recapitulates the progression of AD in human brain. Western blotting and immunofluorescent microscopy techniques were utilised in vivo and in vitro, to examine the relationship between IIS, Akt, and AD pathology. I first characterised in detail AD pathology in 3xTg-AD mice, where an age-related accumulation of intraneuronal Aβ and tau was observed in the hippocampal formation, amygdala, and entorhinal cortex, and at late stages (18 months), extracellular amyloid plaques and NFTs, primarily in the subiculum and the CA1 layer of the hippocampal formation. Increased activity of Akt, detected with antibody to phosphoSer473-Akt, was increased in 3xTg-AD mice compared to age-matched non-transgenic mice (non-Tg), and in direct correlation to the accumulation of Aβ and tau in neuronal somatodendritic compartments. Akt phosphorylates tau at residue Ser214 within a highly specific consensus sequence for Akt phosphorylation, and phosphoSer214-tau strongly decreases microtubule (MT) stabilisation by preventing tau-MT binding. PhosphoSer214-tau increased concomitantly with this in the same age-related and region-specific fashion. Polarisation of tau phosphorylation was observed, where PHF-1 (tauSer396/404) and phosphoSer214-tau both appeared early in 3xTg-AD mice in distinct neuronal compartments: PHF-1 in axons, and phosphoSer214-tau in neuronal soma and dendrites. At 18 months, phosphoSer214-tau strongly colocalised with NFTs positive for the PHF- 1 and AT8 (tauSer202/Thr205) phosphoepitopes. IR was decreased with age in 3xTg-AD brain and in comparison to age-matched non-Tg, and this was specific for brain regions containing Aβ, tau, and hyperactive Akt. IRS-1 was similarly decreased, and both proteins showed altered subcellular distribution. Phosphorylation of IRS-1Ser312 is a strong indicator of IIS dysfunction and insulin resistance, and was increased in 3xTg-AD mice with age and in relation to pathology. Of particular note was our observation that abberant IIS and Akt signalling in 3xTg-AD brain related to Aβ and tau pathology on a gross anatomical level, and specifically localised to the brain regions and circuitry of the perforant path. Finally, I conducted a preliminary study of the effects of synthetic Aβ oligomers on embryonic rat hippocampus neuronal cultures to support these results and those in the literature. Taken together, these novel findings provide evidence for IIS and Akt signal transduction dysfunction as the missing link between Aβ and tau pathogenesis, and contribute to the overall understanding of the biochemical mechanisms of AD.

Molecular analysis of inflammatory mechanisms associated with Escherichia coli and inflammatory bowel diseases

Inflammatory bowel diseases (IBD), encompasses a range of chronic, immune-mediated inflammatory disorders that are usually classified under two major relapsing conditions, Crohn’s Disease (CD) and ulcerative colitis (UC). Extensive studies in the last decades have suggested that the etiology of IBD involves environmental and genetic factors that lead to dysfunction of epithelial barrier with consequent deregulation of the mucosal immune system and inadequate responses to gut microbiota.Over the last decade, the microbial species that has attracted the most attention, with respect to CD etiology, is Eschericia coli. In CD tissue, E. coli antigens have also been identified in macrophages within the lamina propria, granulomas, and in the germinal centres of mesenteric lymph nodes of patients. They have been shown to adhere to and invade intestinal epithelial cells whilst also being able to extensively replicate within macrophages. Through the work of genome-wide association studies (GWAS), there is growing evidence to suggest that the microbial imbalance between commensal and pathogenic bacteria in the gut is aided by a defect in the innate immune system. Autophagy represents a recently investigated pathway that is believed to contribute to the pathogenesis of CD, with studies identified a variant of the autophagy gene, ATG16L1, as a susceptibility gene. The aim of my thesis was to study the cellular and molecular mechanism promoted by E.coli strains in epithelial cells and to assess their contribution to IBD pathology. To achieve this we focused on developing both an in vitro and in vivo model of AIEC infection. This allowed us to further our knowledge on possible mechanisms utilised by AIEC that promoted their survival, as well as developing a better understanding of host reactions. We demonstrate a new survival mechanism promoted by E.coli HM605, whereby it induces the expression of the anti-apoptotic proteins Bcl-XL and BCL2, all of which is exacerbated in an autophagy deficient system. We have also demonstrated the presence of AIEC-induced inflammasome responses in epithelial cells which are exacerbated in an autophagy deficient system and expression of NOD-like receptors (NLRs) which might mediate inflammasome responses in vivo. Finally, we used the Citrobacter rodentium model of infectious colitis to identify Pellino3 as an important mediator in the NOD2 pathway and regulator of intestinal inflammation. In summary, we have developed robust and versatile models of AIEC infection as well as provide new insights into AIEC mediated survival pathways. The collected data provides a new perception into why AIEC bacteria are able to prosper in conditions associated with Crohn’s disease patients with a defect in autophagy.

Gait and behavior in an IL1β-mediated model of rat knee arthritis and effects of an IL1 antagonist.

Interleukin-1 beta (IL1β) is a proinflammatory cytokine that mediates arthritic pathologies. Our objectives were to evaluate pain and limb dysfunction resulting from IL1β over-expression in the rat knee and to investigate the ability of local IL1 receptor antagonist (IL1Ra) delivery to reverse-associated pathology. IL1β over-expression was induced in the right knees of 30 Wistar rats via intra-articular injection of rat fibroblasts retrovirally infected with human IL1β cDNA. A subset of animals received a 30 µl intra-articular injection of saline or human IL1Ra on day 1 after cell delivery (0.65 µg/µl hIL1Ra, n = 7 per group). Joint swelling, gait, and sensitivity were investigated over 1 week. On day 8, animals were sacrificed and joints were collected for histological evaluation. Joint inflammation and elevated levels of endogenous IL1β were observed in knees receiving IL1β-infected fibroblasts. Asymmetric gaits favoring the affected limb and heightened mechanical sensitivity (allodynia) reflected a unilateral pathology. Histopathology revealed cartilage loss on the femoral groove and condyle of affected joints. Intra-articular IL1Ra injection failed to restore gait and sensitivity to preoperative levels and did not reduce cartilage degeneration observed in histopathology. Joint swelling and degeneration subsequent to IL1β over-expression is associated limb hypersensitivity and gait compensation. Intra-articular IL1Ra delivery did not result in marked improvement for this model; this may be driven by rapid clearance of administered IL1Ra from the joint space. These results motivate work to further investigate the behavioral consequences of monoarticular arthritis and sustained release drug delivery strategies for the joint space.

A soft robust model for optimization under ambiguity

In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.

A von Bertalanffy Based Model for the Estimation of Oyster (Crassostrea virginica) Growth on Restored Oyster Reefs in Chesapeake Bay

A model to estimate the mean monthly growth of Crassostrea virginica oysters in Chesapeake Bay was developed. This model is based on the classic von Bertalanffy growth function, however the growth constant is changed every monthly timestep in response to short term changes in temperature and salinity. Using a dynamically varying growth constant allows the model to capture seasonal oscillations in growth, and growth responses to changing environmental conditions that previous applications of the von Bertalanffy model do not capture. This model is further expanded to include an estimation of Perkinsus marinus impacts on growth rates as well as estimations of ecosystem services provided by a restored oyster bar over time. The model was validated by comparing growth estimates from the model to oyster shell height observations from a variety of restoration sites in the upper Chesapeake Bay. Without using the P. marinus impact on growth, the model consistently overestimates mean oyster growth. However, when P. marinus effects are included in the model, the model estimates match the observed mean shell height closely for at least the first 3 years of growth. The estimates of ecosystem services suggested by this model imply that even with high levels of mortality on an oyster reef, the ecosystem services provided by that reef can still be maintained by growth for several years. Because larger oyster filter more water than smaller ones, larger oysters contribute more to the filtration and nutrient removal ecosystem services of the reef. Therefore a reef with an abundance of larger oysters will provide better filtration and nutrient removal. This implies that if an oyster restoration project is trying to improve water quality through oyster filtration, it is important to maintain the larger older oysters on the reef.

Characterization of topographical effects on macrophage behavior in a foreign body response model.

Current strategies to limit macrophage adhesion, fusion and fibrous capsule formation in the foreign body response have focused on modulating material surface properties. We hypothesize that topography close to biological scale, in the micron and nanometric range, provides a passive approach without bioactive agents to modulate macrophage behavior. In our study, topography-induced changes in macrophage behavior was examined using parallel gratings (250 nm-2 mum line width) imprinted on poly(epsilon-caprolactone) (PCL), poly(lactic acid) (PLA) and poly(dimethyl siloxane) (PDMS). RAW 264.7 cell adhesion and elongation occurred maximally on 500 nm gratings compared to planar controls over 48 h. TNF-alpha and VEGF secretion levels by RAW 264.7 cells showed greatest sensitivity to topographical effects, with reduced levels observed on larger grating sizes at 48 h. In vivo studies at 21 days showed reduced macrophage adhesion density and degree of high cell fusion on 2 mum gratings compared to planar controls. It was concluded that topography affects macrophage behavior in the foreign body response on all polymer surfaces examined. Topography-induced changes, independent of surface chemistry, did not reveal distinctive patterns but do affect cell morphology and cytokine secretion in vitro, and cell adhesion in vivo particularly on larger size topography compared to planar controls.

Changes in midbrain pain receptor expression, gait and behavioral sensitivity in a rat model of radiculopathy.

Intervertebral disc herniation may contribute to inflammatory processes that associate with radicular pain and motor deficits. Molecular changes at the affected dorsal root ganglion (DRG), spinal cord, and even midbrain, have been documented in rat models of radiculopathy or nerve injury. The objective of this study was to evaluate gait and the expression of key pain receptors in the midbrain in a rodent model of radiculopathy. Radiculopathy was induced by harvesting tail nucleus pulposus (NP) and placing upon the right L5 DRG in rats (NP-treated, n=12). Tail NP was discarded in sham-operated animals (n=12). Mechanical allodynia, weight-bearing, and gait were evaluated in all animals over time. At 1 and 4 weeks after surgery, astrocyte and microglial activation was tested in DRG sections. Midbrain sections were similarly evaluated for immunoreactivity to serotonin (5HT(2B)), mu-opioid (µ-OR), and metabotropic glutamate (mGluR4 and 5) receptor antibodies. NP-treated animals placed less weight on the affected limb 1 week after surgery and experienced mechanical hypersensitivity over the duration of the study. Astroctye activation was observed at DRGs only at 4 weeks after surgery. Findings for pain receptors in the midbrain of NP-treated rats included an increased expression of 5HT(2B) at 1, but not 4 weeks; increased expression of µ-OR and mGluR5 at 1 and 4 weeks (periaqueductal gray region only); and no changes in expression of mGluR4 at any point in this study. These observations provide support for the hypothesis that the midbrain responds to DRG injury with a transient change in receptors regulating pain responses.

Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.

Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA) historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal) hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1) this mechanism can produce spontaneous divergence of local elevation; 2) divergent and homogenous states can exhibit global bi-stability; and 3) feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Incorporating grape seed antioxidants into a functional food model

Gemstone Team IMMUNE (Innovative Medicines for Maladies Utilizing Nutraceutical Enhancements)

CMIP5 climate model analyses: Climate extremes in the United States

Given the increases in spatial resolution and other improvements in climate modeling capabilities over the last decade since the CMIP3 simulations were completed, CMIP5 provides a unique opportunity to assess scientific understanding of climate variability and change over a range of historical and future conditions. With participation from over 20 modeling groups and more than 40 global models, CMIP5 represents the latest and most ambitious coordinated international climate model intercomparison exercise to date. Observations dating back to 1900 show that the temperatures in the twenty-first century have the largest spatial extent of record breaking and much above normal mean monthly maximum and minimum temperatures. The 20-yr return value of the annual maximum or minimum daily temperature is one measure of changes in rare temperature extremes.