Using lithium as a neuroprotective agent in patients with cancer

Neurocognitive impairment is being increasingly recognized as an important issue in patients with cancer who develop cognitive difficulties either as part of direct or indirect involvement of the nervous system or as a consequence of either chemotherapy-related or radiotherapy-related complications. Brain radiotherapy in particular can lead to significant cognitive defects. Neurocognitive decline adversely affects quality of life, meaningful employment, and even simple daily activities. Neuroprotection may be a viable and realistic goal in preventing neurocognitive sequelae in these patients, especially in the setting of cranial irradiation. Lithium is an agent that has been in use for psychiatric disorders for decades, but recently there has been emerging evidence that it can have a neuroprotective effect.

This review discusses neurocognitive impairment in patients with cancer and the potential for investigating the use of lithium as a neuroprotectant in such patients.

A novel trust measurement method based on certified belief in strength for a multi-agent classifier system

A novel trust measurement method, namely, certified belief in strength (CBS), for a multi-agent classifier system (MACS) is proposed in this paper. The CBS method aims to improve the performance of the constituent agents of the MACS, viz., the fuzzy min-max (FMM) neural network classifier. Trust measurement is accomplished using reputation and strength of the constituent agents. Trust is built from strong elements that are associated with the FMM agents, allowing the CBS method to improve the performance of the MACS. An auction procedure based on the sealed bid, namely, the first price method, is adopted for the MACS in determining the winning agent. The effectiveness of the CBS method and the bond (based on trust) is verified by using a number of benchmark data sets. The results demonstrate that the proposed MACS-CBS model is able to produce better accuracy and stability as compared with those from other existing methods. © 2012 Springer-Verlag London.

An impaired mitochondrial electron transport chain increases retention of the hypoxia imaging agent diacetylbis(4-methylthiosemicarbazonato)copper II

Radiolabeled diacetylbis(4-methylthiosemicarbazonato)copper^II [Cu^II(atsm)] is an effective positron-emission tomography imaging agent for myocardial ischemia, hypoxic tumors, and brain disorders with regionalized oxidative stress, such as mitochondrial myopathy, encephalopathy, and lactic acidosis with stroke-like episodes (MELAS) and Parkinson’s disease. An excessively elevated reductive state is common to these conditions and has been proposed as an important mechanism affecting cellular retention of Cu from Cu^II(atsm). However, data from whole-cell models to demonstrate this mechanism have not yet been provided. The present study used a unique cell culture model, mitochondrial xenocybrids, to provide whole-cell mechanistic data on cellular retention of Cu from Cu^II(atsm). Genetic incompatibility between nuclear and mitochondrial encoded subunits of the mitochondrial electron transport chain (ETC) in xenocybrid cells compromises normal function of the ETC. As a consequence of this impairment to the ETC we show xenocybrid cells upregulate glycolytic ATP production and accumulate NADH. Compared to control cells the xenocybrid cells retained more Cu after being treated with Cu^II(atsm). By transfecting the cells with a metal-responsive element reporter construct the increase in Cu retention was shown to involve a Cu^II(atsm)-induced increase in intracellular bioavailable Cu specifically within the xenocybrid cells. Parallel experiments using cells grown under hypoxic conditions confirmed that a compromised ETC and elevated NADH levels contribute to increased cellular retention of Cu from CuII(atsm). Using these cell culture models our data demonstrate that compromised ETC function, due to the absence of O2 as the terminal electron acceptor or dysfunction of individual components of the ETC, is an important determinant in driving the intracellular dissociation of Cu^II(atsm) that increases cellular retention of the Cu.

Mitomycin C: a promising agent for the treatment of canine corneal scarring

Objective  To evaluate the safety and efficacy of mitomycin C (MMC) in prevention of canine corneal scarring.

Methods  With an in vitro approach using healthy canine corneas, cultures of primary canine corneal fibroblasts or myofibroblasts were generated. Primary canine corneal fibroblasts were obtained by growing corneal buttons in minimal essential medium supplemented with 10% fetal bovine serum. Canine corneal myofibroblasts were produced by growing cultures in serum-free medium containing transforming growth factor β1 (1 ng/mL). Trypan blue assay and phase-contrast microscopy were used to evaluate the toxicity of three doses of MMC (0.002%, 0.02% and 0.04%). Real-time PCR, immunoblot, and immunocytochemistry techniques were used to determine MMC efficacy to inhibit markers of canine corneal scarring.

Results  A single 2-min treatment of 0.02% or less MMC did not alter canine corneal fibroblast or keratocyte phenotype, viability, or growth. The 0.02% dose substantially reduced myofibroblast formation (up to 67%; P < 0.001), as measured by the change in RNA and protein expression of fibrosis biomarkers (α-smooth muscle actin and F-actin).

Conclusion  This in vitro study suggests that a single 2-min 0.02% MMC treatment to the canine corneal keratocytes is safe and may be useful in decreasing canine corneal fibrous metaplasia. In vivo studies are warranted.

Mobile-agent based multi-constraint one-to-many bilateral e-Negotiation framework

The thesis proposes a multi-constraint one-to-many bilateral e-Trade negotiation framework. It deploys mobile agents in negotiation, considers trading competition between vendors and search space, efficiently manages the risk of losing top utility offers that expire before the negotiation deadline, accurately evaluates offers, and truly maintains the security of negotiation data.

"Recognition" : Interactive motion tracking installation with neural network agent performer

Public installation running throughout the night at Cube 37 gallery. Morphing forms are projected onto the glass front of the gallery, facing the street. Human perticipants interact with the forms whose morphology changes with the movements of the participants. When no human participants are present, a neural network based agent that has learnt how to dance from a trained dancer, takes over and the forms follow the agent's movement.

Emergent effects in massive agent swarms in real-time game environments

 Computational efficiency and hence the scale of agent-based swarm simulations is bound by the nearest neighbour computation for each agent. This article proposes the use of GPU texture memory to implement lookup tables for a spatial partitioning based k-Nearest Neighbours algorithm. These improvements allow simulation of swarms of 220 agents at higher rates than the current best alternative algorithms. This approach is incorporated into an existing framework for simulating steering behaviours allowing for a complete implementation of massive agent swarm simulations, with per agent behaviour preferences, on a Graphics Processing Unit. These simulations have enabled an investigation of the emergent dynamics that occur when massive swarms interact with a choke point in their environment. Various modes of sustained dynamics with temporal and spatial coherence are identified when a critical mass of agents is simulated and some elementary properties are presented. The algorithms presented in this article enable researchers and content designers in games and movies to implement truly massive agent swarms in real time and thus provide a basis for further identification and analysis of the emergent dynamics in these swarms. This will improve not only the scale of swarms used in commercial games and movies but will also improve the reliability of swarm behaviour with respect to content design goals.

Ethical trust and social moral norms simulation : a bio-inspired agent-based modelling approach

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.

Interplay of ethical trust and social moral norms : environment modelling and computational mechanisms in agent-based social simulation

In many agent-based models theoretical and computational mechanisms are needed for model abstraction and design. However, it can be challenging to arrive at the appropriate mechanisms and models. This research on the interplay of ethical trust and social moral norms addresses that challenge via an analytical framework on the spread of moral norms, the modelling of social environment and the selection of spread mechanisms as applied to agent-based social simulation. We describe the mechanism alignment mapping, two forms of interaction modelling between the social environment and agents, and the results obtained from the simulation of our computational model. These results provide an insight into how the agent-based paradigm can be applied as a technique of investigation for normative moral processes in computational social sciences.