A network processor for a learning based routing protocol

Recently, Cognitive Packet Networks (CPN) is proposed as an alternative to the IP based network architectures and shows similarity with the discrete active networks. In CPN, there is no routing table, instead reinforcement learning (Random Neural Networks) is used to route packets. CPN routes packets based on QoS, using measurements that are constantly collected by packets and deposited in mailboxes at routers. The applicability of the CPN concept has been demonstrated through several software implementations. However, higher data traffic and increasing packet processing demands require the implementation of this new network architecture in hardware. In this paper, we present a network processor architecture which supports this learning based protocol. ©2004 IEEE

Design and implementation of a random neural network routing engine

Random neural network (RNN) is an analytically tractable spiked neural network model that has been implemented in software for a wide range of applications for over a decade. This paper presents the hardware implementation of the RNN model. Recently, cognitive packet networks (CPN) is proposed as an alternative packet network architecture where there is no routing table, instead RNN based reinforcement learning is used to route packets. Particularly, we describe implementation details for the RNN based routing engine of a CPN network processor chip: the smart packet processor (SPP). The SPP is a dual port device that stores, modifies, and interprets the defining characteristics of multiple RNN models. In addition to hardware design improvements over the software implementation such as dual access memory, output calculation step, reduced output calculation module, this paper introduces a major modification to the reinforcement learning algorithm used in the original CPN specification such that the number of weight terms are reduced from 2n2 to 2n. This not only yields significant memory savings, but it also simplifies the calculations for the steady state probabilities (neuron outputs in RNN). Simulations have been conducted to confirm the proper functionality for the isolated SPP design as well as for the multiple SPP\u27s in a networked environment

Subspaces of some nuclear sequence spaces

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23700/1/0000671.pd

A new polymorph of N-(2-{N′-[(1E)-2-hy­dr­oxy­benzyl­­idene]hydrazinecarbon­yl}phen­yl)benzamide

The title compound, C 21 H 17 N 3 O 3 , is a new polymorph of an already published structure [Shashidhar et al. (2006). Acta Cryst. E62, o4473-o4475]. The previously reported structure crystallizes in the monoclinic space group C2/c, whereas the structure reported here is in the tetragonal space group I4 1 /a. The bond lengths and angles are similar in both structures. The molecule adopts an extended conformation via intramolecular N-H⋯O and O-H⋯N hydrogen bonds; the terminal phenyl ring and the hydroxylphenyl ring are twisted with respect to the central benzene ring by 44.43 (7) and 21.99 (8)°, respectively. In the crystal, molecules are linked by N-H⋯O hydrogen bonds, weak C-H⋯O hydrogen bonds and weak C-H⋯π interactions into a three-dimensional supramolecular network

Ret is essential to mediate GDNF’s neuroprotective and neuroregenerative effect in a Parkinson disease mouse model

Glial cell line-derived neurotrophic factor (GDNF) is a potent survival and regeneration-promoting factor for dopaminergic neurons in cell and animal models of Parkinson disease (PD). GDNF is currently tested in clinical trials on PD patients with so far inconclusive results. The receptor tyrosine kinase Ret is the canonical GDNF receptor, but several alternative GDNF receptors have been proposed, raising the question of which signaling receptor mediates here the beneficial GDNF effects. To address this question we overexpressed GDNF in the striatum of mice deficient for Ret in dopaminergic neurons and subsequently challenged these mice with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Strikingly, in this established PD mouse model, the absence of Ret completely abolished GDNF’s neuroprotective and regenerative effect on the midbrain dopaminergic system. This establishes Ret signaling as absolutely required for GDNF’s effects to prevent and compensate dopaminergic system degeneration and suggests Ret activation as the primary target of GDNF therapy in PD

NRF2 Activation Restores Disease Related Metabolic Deficiencies in Olfactory Neurosphere-Derived Cells from Patients with Sporadic Parkinson's Disease

Extent: 14p.Background: Without appropriate cellular models the etiology of idiopathic Parkinson’s disease remains unknown. We recently reported a novel patient-derived cellular model generated from biopsies of the olfactory mucosa (termed olfactory neurosphere-derived (hONS) cells) which express functional and genetic differences in a disease-specific manner. Transcriptomic analysis of Patient and Control hONS cells identified the NRF2 transcription factor signalling pathway as the most differentially expressed in Parkinson’s disease. Results: We tested the robustness of our initial findings by including additional cell lines and confirmed that hONS cells from Patients had 20% reductions in reduced glutathione levels and MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)- 2-(4-sulfophenyl)-2H-tetrazolium, inner salt] metabolism compared to cultures from healthy Control donors. We also confirmed that Patient hONS cells are in a state of oxidative stress due to higher production of H2O2 than Control cultures. siRNA-mediated ablation of NRF2 in Control donor cells decreased both total glutathione content and MTS metabolism to levels detected in cells from Parkinson’s Disease patients. Conversely, and more importantly, we showed that activation of the NRF2 pathway in Parkinson’s disease hONS cultures restored glutathione levels and MTS metabolism to Control levels. Paradoxically, transcriptomic analysis after NRF2 pathway activation revealed an increased number of differentially expressed mRNAs within the NRF2 pathway in L-SUL treated Patient-derived hONS cells compared to L-SUL treated Controls, even though their metabolism was restored to normal. We also identified differential expression of the PI3K/AKT signalling pathway, but only post-treatment. Conclusions: Our results confirmed NRF2 as a potential therapeutic target for Parkinson’s disease and provided the first demonstration that NRF2 function was inducible in Patient-derived cells from donors with uniquely varied genetic backgrounds. However, our results also demonstrated that the response of PD patient-derived cells was not co-ordinated in the same way as in Control cells. This may be an important factor when developing new therapeutics.Anthony L. Cook, Alejandra M. Vitale, Sugandha Ravishankar, Nicholas Matigian, Greg T. Sutherland, Jiangou Shan, Ratneswary Sutharsan, Chris Perry, Peter A. Silburn, George D. Mellick, Murray L. Whitelaw, Christine A. Wells, Alan Mackay-Sim and Stephen A. Woo

Mouse models of neurodegenerative disease: preclinical imaging and neurovascular component.

Neurodegenerative diseases represent great challenges for basic science and clinical medicine because of their prevalence, pathologies, lack of mechanism-based treatments, and impacts on individuals. Translational research might contribute to the study of neurodegenerative diseases. The mouse has become a key model for studying disease mechanisms that might recapitulate in part some aspects of the corresponding human diseases. Neurode- generative disorders are very complicated and multifacto- rial. This has to be taken in account when testing drugs. Most of the drugs screening in mice are very di cult to be interpretated and often useless. Mouse models could be condiderated a ‘pathway models’, rather than as models for the whole complicated construct that makes a human disease. Non-invasive in vivo imaging in mice has gained increasing interest in preclinical research in the last years thanks to the availability of high-resolution single-photon emission computed tomography (SPECT), positron emission tomography (PET), high eld Magnetic resonance, Optical Imaging scanners and of highly speci c contrast agents. Behavioral test are useful tool to characterize di erent ani- mal models of neurodegenerative pathology. Furthermore, many authors have observed vascular pathological features associated to the di erent neurodegenerative disorders. Aim of this review is to focus on the di erent existing animal models of neurodegenerative disorders, describe behavioral tests and preclinical imaging techniques used for diagnose and describe the vascular pathological features associated to these diseases