Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Study of remote sensing based parameter uncertainty in Production Efficiency Models

The remote sensing based Production Efficiency Models (PEMs), springs from the concept of "Light Use Efficiency" and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Evaluation of nonlinear chromatographic performance by frontal analysis using a simple multi-plate mathematical model

A multi-plate (NIP) mathematical model was proposed by frontal analysis to evaluate nonlinear chromatographic performance. One of its advantages is that the parameters may be easily calculated from experimental data. Moreover, there is a good correlation between it and the equilibrium-dispersive (E-D) or Thomas models. This shows that it can well accommodate both types of band broadening that is comprised of either diffusion-dominated processes or kinetic sorption processes. The MP model can well describe experimental breakthrough curves that were obtained from membrane affinity chromatography and column reversed-phase liquid chromatography. Furthermore, the coefficients of mass transfer may be calculated according to the relationship between the MP model and the E-D or Thomas models. (C) 2004 Elsevier B.V. All rights reserved.

Neuroprotective and immunomodulatory properties of the new PPARγ agonist MDG548: an in vitro and in vivo study in PD models

Neuroinflammation is a key component of Parkinson’s disease (PD) neuropathology. Skewed microglia activation with pro-inflammatory prevailing over anti-inflammatory phenotypes may contribute to neurotoxicity via the production of cytokines and neurotoxic species. Therefore, microglia polarization has been proposed as a target for neuroprotection. The peroxisome proliferator-activated receptor gamma (PPARγ) is expressed in microglia and peripheral immune cells, where it is involved in macrophages polarization and in the control of inflammatory responses, by modulating gene transcription. Several studies have shown that PPARγ agonists are neuroprotective in experimental PD models in rodents and primates. however safety concerns have been raised about PPARγ agonists thiazolidinediones (TZD) currently available, prompting for the development of non-TZD compounds. Aim of this study was to characterize a novel PPARγ agonist non TZD, MDG548, for its potential neuroprotective effect in PD models and its immunomodulatory activity as the underlying mechanism of neuroprotection. The neuroprotective activity of MDG548 was assessed in vivo in the subacute MPTP model and in the chronic MPTP/probenecid (MPTPp) model of PD. MDG548 activity on microglia activation and phenotype was investigated in the substantia nigra pars compacta (SNc) via the evaluation of pro- (TNF-α and iNOS) and anti-inflammatory (CD206) molecules, with fluorescent immunohistochemistry. Moreover, cultured murine microglia MMGT12 were treated with MDG548 in association with the inflammagen LPS, pro- and anti-inflammatory molecules were measured in the medium by ELISA assay and phagocytosis was evaluated by fluorescent immunohistochemistry for CD68. MDG548 arrested dopaminergic cells degeneration in the SNc in both the subacute MPTP and the chronic MPTPp models of PD, and reverted MPTPp-induced motor impairment. Moreover, MDG548 reduced microglia activation, iNOS and TNF-α production, while induced CD206 in microglia. In cultured unstimulated microglia, LPS increased TNF-α production and CD68 expression, while decreased CD206 expression. MDG548 reverted LPS effect on TNF-α and CD206 restoring physiological levels, while strongly increased CD68 expression. Results suggest that the PPARγ agonist MDG548 is neuroprotective in experimental models of PD. MDG548 targets microglia polarization by correcting the imbalance between pro- over antiinflammatory molecules, offering a novel immunomodulatory approach to neuroprotection.

Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001

Toivonen, H., Srinivasan, A., King, R. D., Kramer, S. and Helma, C. (2003) Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001. Bioinformatics 19: 1183-1193

The evaluation of evidence for exponentially distributed data

C.G.G. Aitken, Q. Shen, R. Jensen and B. Hayes. The evaluation of evidence for exponentially distributed data. Computational Statistics & Data Analysis, vol. 51, no. 12, pp. 5682-5693, 2007.

Subsethood-based Fuzzy Rule Models and their Application to Student Performance

K. Rasmani and Q. Shen. Subsethood-based Fuzzy Rule Models and their Application to Student Performance Classification. Proceedings of the 14th International Conference on Fuzzy Systems, pages 755-760, 2005.

Simultaneous Learning of Nonlinear Manifold and Dynamical Models for High-dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

A Quantitative Evaluation of the AVITEWRITE Model of Handwriting Learning

Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose activities overlap in time to generate continuous, curved movements that obey an intense relation between curvature and speed. The Adaptive Vector Integration to Endpoint (AVITEWRITE) model of Grossberg and Paine (2000) proposed how such complex movements may be learned through attentive imitation. The model suggest how frontal, parietal, and motor cortical mechanisms, such as difference vector encoding, under volitional control from the basal ganglia, interact with adaptively-timed, predictive cerebellar learning during movement imitation and predictive performance. Key psycophysical and neural data about learning to make curved movements were simulated, including a decrease in writing time as learning progresses; generation of unimodal, bell-shaped velocity profiles for each movement synergy; size scaling with isochrony, and speed scaling with preservation of the letter shape and the shapes of the velocity profiles; an inverse relation between curvature and tangential velocity; and a Two-Thirds Power Law relation between angular velocity and curvature. However, the model learned from letter trajectories of only one subject, and only qualitative kinematic comparisons were made with previously published human data. The present work describes a quantitative test of AVITEWRITE through direct comparison of a corpus of human handwriting data with the model's performance when it learns by tracing human trajectories. The results show that model performance was variable across subjects, with an average correlation between the model and human data of 89+/-10%. The present data from simulations using the AVITEWRITE model highlight some of its strengths while focusing attention on areas, such as novel shape learning in children, where all models of handwriting and learning of other complex sensory-motor skills would benefit from further research.

An evaluation of reovirus as an effective therapeutic for cancer

Cancer is a global problem. Despite the significant advances made in recent years, a definitively effective therapeutic has yet to be developed. Oncolytic virology has fallen back into favour for the treatment of cancer with several viruses and viral vectors currently under investigation including vesicular stomatitis virus (VSV), adenovirus vectors and herpes simplex virus (HSV) vectors. Reovirus has an advantage over many viral vectors in that its wild-type form is non-pathogenic and will selectively infect transformed cells, particularly those mutated in the Ras pathway. These advantages make Reovirus an ideal candidate as a safe and non-toxic therapeutic. The aim of the first part of this study was to determine the effect, if any, of Reovirus on cell lines derived from cancers of the gastrointestinal tract. These cancers, particularly those of the oesophagus and stomach, have extremely poor prognoses and little improvement has been seen in survival of these patients in recent years. Reovirus as a single therapy showed promising results in cell lines of oesophageal, gastric and colorectal origin. Further study of partially resistant cell lines using a combination of Reovirus and conventional therapies, either chemotherapy or radiation, showed that a multi-modal approach to therapy is possible with Reovirus and no antagonism between Reovirus and other treatments was observed. The second part of this study focused on investigating a novel use of Reovirus in an in vivo setting. Cancer vaccination or the use of vaccines in cancer therapy is gaining momentum and success has been seen both in a prophylactic approach and a therapeutic approach. A cell-based Reovirus vaccine was used in both these approaches with encouraging success. When used as a prophylactic vaccine tumour development was subsequently inhibited even upon exposure to a tumorigenic dose of cells. The use of the cell-based Reovirus vaccine as a therapeutic for established tumours showed significant delay in tumour growth and a prolongation of survival in all models. This study has proven that Reovirus is an effective therapeutic in a range of cancers and the successful use of a cell-based Reovirus vaccine leads the way for new advancements in cancer immunotherapy.

An evaluation of orogenic kinematic evolution utilizing crystalline and magnetic anisotropy in granitoids

The Silurian-Devonian Galway Granite Complex (GGC ~425-380Ma) is defined here as a suite of granitoid plutons that comprise the Main Galway Granite Batholith and the Earlier Plutons. The Main Batholith is a composite of the Carna Pluton in the west and the Kilkieran Pluton in the east and extends from Galway City ~130km to the west. The Earlier Plutons are spatially, temporally and structurally distinct, situated northwest of the Main Batholith and include the Roundstone, Omey, Inis and Letterfrack Plutons. The majority of isotopic and structural data currently available pertain to the Kilkieran Pluton, several tectonic models have already been devised for this part of the complex. These relate emplacement of the Kilkieran Pluton to extension across a large east-west Caledonian lineament, i.e. the Skird Rocks Fault, during late Caledonian transtension. No chronological data have been published that directly and accurately date the emplacement of the Carna Pluton or any of the Earlier Plutons. There is also a lack of data pertaining to the internal structure of these intrusions. Accordingly, no previous study has established the mechanisms of emplacement for the Earlier Plutons and only limited work is available for the Carna Pluton. As a consequense of this, constituents of the GGC have not previously been placed in a context relative to each other or to regional scale Silurio-Devonian kinematics. The current work focuses on the Omey, Roundstone and Carna Plutons. Here, results of detailed field and Anisotropy of Magnetic Susceptibiliy (AMS) fabric studies are presented. This work is complemented by geological mapping that focuses on fault dynamics and contact relationships. Interpretation of AMS data is aided by rock magnetic experiment data and petrographic microstructural evaluations of representative samples. A new geological map of the the Omey Pluton demonstrates that this intrusion has a defined roof and base which are gently inclined parallel to the fold hinge of the Connemara Antiform. AMS and petrographic data show the intrusion is cross cut by NNW-SSE shear zones that extend into the country rock. These pre-date and were active during magma emplacement. It is proposed that the Omey pluton was emplaced as a discordant phacolith. Pre-existing subvertical D5 faults in the host rock were reactived during emplacement, due to regional sinistral transpression, and served as centralised ascent conduits. A central portion of the Roundstone Pluton was mapped in detail for the first time. Two facies are identified, G1 forms the majority of the pluton and coeval G2 sheets cross cut G1 at the core of the pluton. NNW-SSE D5 faults mapped in the country rock extend across the pluton. These share a geometrical relationship with the distribution of submagmatic strain in the pluton and parallel the majoity of mapped subvertical G2 dykes. These data indicate that magma ascent was controlled by NNW-SSE conduits that are inherently related to those identifed in the Omey Pluton. It is proposed that the Roundstone Pluton is a punched laccolith, the symmetry and structure of which was controlled by pre-exising host rock structures and regional sinistral transpressive stress which presided during emplacement. Field relationships show the long axis of the Carna Pluton lies parallel to mulitple NNW-SSE shear zones. These are represented on a regional scale by the Clifden-Mace Fault which cross cuts the core of this intrusion. AMS and petrographic data show concentric emplacement fabrics were tectonically overprinted as magma cooled from the magmatic state due to this faulting. It is proposed that the Clifden-Mace Fault system was active during ascent and emplacement of the magma and that pluton inflation only terminated as this controlling structure went into compression due to the onset of regional transtension. U-Pb zircon laser ablation inductively coupled mass spectrometry (LA-ICP-MS) data has been compiled from four sample sites. New geochronological data from the Roundstone Pluton (RD1 = ± 3.2Ma) represent the oldest age determination obtained from any member of the GGC and demonstrates that this pluton predates the Carna Pluton by ~10Ma and probably intruded synchronously with the Omey Pluton (~422.5 ± 1.7Ma). Chronological data from the Carna Pluton (CN2 = 412.9 ± 2.5Ma; CN3 = 409.8 ± 7.2Ma; CN4 = 409.6 ± 3.6Ma) represent the first precise magma crystallisation age for this intrusion. This work shows this pluton is 10Ma older than the Kilkieran Pluton and that the supply of magma into the Carna Pluton had terminated by ~409Ma. Chronological, magnetic and field data have been utilised to evaluate the kinematic evolution of the Caledonides of western Ireland throughout the construction of the GGC. It is proposed that the GGC was constructed during four distinct episodes. The style of emplacement and the conduits used for magma transport to the site of emplacement was dependent on the orientation of local structures relative to the regional ambiant stress field. This philosophy is used to critically evaluate and progress existing hypotheses on the transition from regional transpression to regional transtension at the end of the Caledonian Orogeny.

Evaluation of tumor response, disease control, progression-free survival, and time to progression as potential surrogate end points in metastatic breast cancer.

PURPOSE: Overall survival (OS) can be observed only after prolonged follow-up, and any potential effect of first-line therapies on OS may be confounded by the effects of subsequent therapy. We investigated whether tumor response, disease control, progression-free survival (PFS), or time to progression (TTP) could be considered a valid surrogate for OS to assess the benefits of first-line therapies for patients with metastatic breast cancer. PATIENTS AND METHODS: Individual patient data were collected on 3,953 patients in 11 randomized trials that compared an anthracycline (alone or in combination) with a taxane (alone or in combination with an anthracycline). Surrogacy was assessed through the correlation between the end points as well as through the correlation between the treatment effects on the end points. RESULTS: Tumor response (survival odds ratio [OR], 6.2; 95% CI, 5.3 to 7.0) and disease control (survival OR, 5.5; 95% CI, 4.8 to 6.3) were strongly associated with OS. PFS (rank correlation coefficient, 0.688; 95% CI, 0.686 to 0.690) and TTP (rank correlation coefficient, 0.682; 95% CI, 0.680 to 0.684) were moderately associated with OS. Response log ORs were strongly correlated with PFS log hazard ratios (linear coefficient [rho], 0.96; 95% CI, 0.73 to 1.19). Response and disease control log ORs and PFS and TTP log hazard ratios were poorly correlated with log hazard ratios for OS, but the confidence limits of rho were too wide to be informative. CONCLUSION: No end point could be demonstrated as a good surrogate for OS in these trials. Tumor response may be an acceptable surrogate for PFS.