Bortezomib modulates TRAIL sensitivity in human bladder and prostate cancer

Tumor necrosis factor-related apoptosis-inducing ligand (Apo2L/TRAIL) is a member of the TNF superfamily of cytokines that can induce cell death through engagement of cognate death receptors. Unlike other death receptor ligands, it selectively kills tumor cells while sparing normal cells. Preclinical studies in non-human primates have generated much enthusiasm regarding its therapeutic potential. However, many human cancer cell lines exhibit significant resistance to TRAIL-induced apoptosis, and the molecular mechanisms underling this are controversial. Possible explanations are typically cell-type dependent, but include alterations of receptor expression, enhancement of pro-apoptotic intracellular signaling molecules, and reductions in anti-apoptotic proteins. We show here that the proteasome inhibitor bortezomib (Velcade, PS-341) produces synergistic apoptosis in both bladder and prostate cancer cell lines within 4-6 hours when co-treated with recombinant human TRAIL which is associated with accumulation of p21 and cdk1/2 inhibition. Our data suggest that bortezomib's mechanism of action involves a p21-dependent enhancement of caspase maturation. Furthermore, we found enhanced tumor cell death in in vivo models using athymic nude mice. This is associated with increases in caspase-8 and caspase-3 cleavage as well as significant reductions in microvessel density (MVD) and proliferation. Although TRAIL alone had less of an effect, its biological significance as a single agent requires further investigations. Toxicity studies reveal that the combination of bortezomib and rhTRAIL has fatal consequences that can be circumvented by altering treatment schedules. Based on our findings, we conclude that this strategy has significant therapeutic potential as an anti-cancer agent. ^

Humanos y máquinas : Aspectos epistemológicos de su relación en el debate humanismo-poshumanismo

En la tesis se consideran los procesos de cambio conceptual, teórico y metodológico que modelaron el desarrollo de los estudios sociales de la ciencia desde su emergencia hasta la actualidad, con el objeto de analizar los alcances y límites de las perspectivas humanistas y poshumanistas en la comprensión del vínculo "humano-no humano". Los estudios sociales de la ciencia conforman un campo marginal tanto dentro de los estudios metacientíficos como de la disciplina que les dio origen: la sociología. Si bien en las últimas décadas éstos han dado lugar a un significativo progreso en la comprensión cualitativa y cuantitativa de la ciencia y la tecnología, al responder primordialmente a la inquietud empírico-comparativa de programas de investigación de corte institucionalista han tendido a relegar de sus agendas de investigación el análisis epistemológico de los modelos explicativos considerados. En este sentido, en su afán de dar cuenta del carácter social de la ciencia apenas si han reparado en los nexos que pueden establecerse entre la explicación social de la ciencia y la explicación científica de "lo social". Con el objeto de atender a ello la tesis analiza las implicancias epistemológicas, metodológicas y ontológicas del estudio social de la ciencia considerando a la relación "humano-máquina" o "humano-no humano" como un hilo de Ariadna en la identificación de rupturas y continuidades en la consideración del vínculo "ciencia-sociedad". Desde esta perspectiva se estudia la dinámica de cambio conceptual, teórico y/o metodológico que dio lugar a la emergencia y desarrollo del estudio social de la ciencia en relación con aquella que modeló al estudio científico de "lo social", se identifican los cambios epistemológicos, ontológicos y metodológicos que configuraron a la dimensión no humana como un tópico relevante, cuando no ineludible, en la explicación social de la ciencia, se examinan las implicancias de la incorporación de los objetos naturales y/o tecnológicos a los modelos explicativos del estudio social de la ciencia en el contexto de la crítica poshumanista a las teorías de la acción que han asumido al sujeto como epicentro del análisis, y se analiza el impacto de la mencionada crítica en términos de un reordenamiento de los vínculos entre el estudio social de la ciencia y el estudio científico de "lo social". De este modo se ofrece una faceta de los estudios sociales de la ciencia inadvertida por buena parte de la literatura especializada, más atenta a la confrontación de imágenes sociológicas y filosóficas de la ciencia en el contexto de la denominada "guerra de las ciencias" que a sus implicancias epistemológicas para el estudio científico de "lo social". Enfatizando así el anclaje disciplinar del estudio social de la ciencia no se suscribe una visión "internalista" del progreso epistémico, sino que, por el contrario, se sugiere que la simultánea consideración de factores disciplinares y extra disciplinares resulta una estrategia tan fructífera como innovadora para analizar un campo que, al extender el dominio de la explicación social al ámbito de los fenómenos físico-naturales, ha dado lugar a uno de los más complejos casos de interacción disciplinar.

Humanos y máquinas : Aspectos epistemológicos de su relación en el debate humanismo-poshumanismo

En la tesis se consideran los procesos de cambio conceptual, teórico y metodológico que modelaron el desarrollo de los estudios sociales de la ciencia desde su emergencia hasta la actualidad, con el objeto de analizar los alcances y límites de las perspectivas humanistas y poshumanistas en la comprensión del vínculo "humano-no humano". Los estudios sociales de la ciencia conforman un campo marginal tanto dentro de los estudios metacientíficos como de la disciplina que les dio origen: la sociología. Si bien en las últimas décadas éstos han dado lugar a un significativo progreso en la comprensión cualitativa y cuantitativa de la ciencia y la tecnología, al responder primordialmente a la inquietud empírico-comparativa de programas de investigación de corte institucionalista han tendido a relegar de sus agendas de investigación el análisis epistemológico de los modelos explicativos considerados. En este sentido, en su afán de dar cuenta del carácter social de la ciencia apenas si han reparado en los nexos que pueden establecerse entre la explicación social de la ciencia y la explicación científica de "lo social". Con el objeto de atender a ello la tesis analiza las implicancias epistemológicas, metodológicas y ontológicas del estudio social de la ciencia considerando a la relación "humano-máquina" o "humano-no humano" como un hilo de Ariadna en la identificación de rupturas y continuidades en la consideración del vínculo "ciencia-sociedad". Desde esta perspectiva se estudia la dinámica de cambio conceptual, teórico y/o metodológico que dio lugar a la emergencia y desarrollo del estudio social de la ciencia en relación con aquella que modeló al estudio científico de "lo social", se identifican los cambios epistemológicos, ontológicos y metodológicos que configuraron a la dimensión no humana como un tópico relevante, cuando no ineludible, en la explicación social de la ciencia, se examinan las implicancias de la incorporación de los objetos naturales y/o tecnológicos a los modelos explicativos del estudio social de la ciencia en el contexto de la crítica poshumanista a las teorías de la acción que han asumido al sujeto como epicentro del análisis, y se analiza el impacto de la mencionada crítica en términos de un reordenamiento de los vínculos entre el estudio social de la ciencia y el estudio científico de "lo social". De este modo se ofrece una faceta de los estudios sociales de la ciencia inadvertida por buena parte de la literatura especializada, más atenta a la confrontación de imágenes sociológicas y filosóficas de la ciencia en el contexto de la denominada "guerra de las ciencias" que a sus implicancias epistemológicas para el estudio científico de "lo social". Enfatizando así el anclaje disciplinar del estudio social de la ciencia no se suscribe una visión "internalista" del progreso epistémico, sino que, por el contrario, se sugiere que la simultánea consideración de factores disciplinares y extra disciplinares resulta una estrategia tan fructífera como innovadora para analizar un campo que, al extender el dominio de la explicación social al ámbito de los fenómenos físico-naturales, ha dado lugar a uno de los más complejos casos de interacción disciplinar.

Humanos y máquinas : Aspectos epistemológicos de su relación en el debate humanismo-poshumanismo

En la tesis se consideran los procesos de cambio conceptual, teórico y metodológico que modelaron el desarrollo de los estudios sociales de la ciencia desde su emergencia hasta la actualidad, con el objeto de analizar los alcances y límites de las perspectivas humanistas y poshumanistas en la comprensión del vínculo "humano-no humano". Los estudios sociales de la ciencia conforman un campo marginal tanto dentro de los estudios metacientíficos como de la disciplina que les dio origen: la sociología. Si bien en las últimas décadas éstos han dado lugar a un significativo progreso en la comprensión cualitativa y cuantitativa de la ciencia y la tecnología, al responder primordialmente a la inquietud empírico-comparativa de programas de investigación de corte institucionalista han tendido a relegar de sus agendas de investigación el análisis epistemológico de los modelos explicativos considerados. En este sentido, en su afán de dar cuenta del carácter social de la ciencia apenas si han reparado en los nexos que pueden establecerse entre la explicación social de la ciencia y la explicación científica de "lo social". Con el objeto de atender a ello la tesis analiza las implicancias epistemológicas, metodológicas y ontológicas del estudio social de la ciencia considerando a la relación "humano-máquina" o "humano-no humano" como un hilo de Ariadna en la identificación de rupturas y continuidades en la consideración del vínculo "ciencia-sociedad". Desde esta perspectiva se estudia la dinámica de cambio conceptual, teórico y/o metodológico que dio lugar a la emergencia y desarrollo del estudio social de la ciencia en relación con aquella que modeló al estudio científico de "lo social", se identifican los cambios epistemológicos, ontológicos y metodológicos que configuraron a la dimensión no humana como un tópico relevante, cuando no ineludible, en la explicación social de la ciencia, se examinan las implicancias de la incorporación de los objetos naturales y/o tecnológicos a los modelos explicativos del estudio social de la ciencia en el contexto de la crítica poshumanista a las teorías de la acción que han asumido al sujeto como epicentro del análisis, y se analiza el impacto de la mencionada crítica en términos de un reordenamiento de los vínculos entre el estudio social de la ciencia y el estudio científico de "lo social". De este modo se ofrece una faceta de los estudios sociales de la ciencia inadvertida por buena parte de la literatura especializada, más atenta a la confrontación de imágenes sociológicas y filosóficas de la ciencia en el contexto de la denominada "guerra de las ciencias" que a sus implicancias epistemológicas para el estudio científico de "lo social". Enfatizando así el anclaje disciplinar del estudio social de la ciencia no se suscribe una visión "internalista" del progreso epistémico, sino que, por el contrario, se sugiere que la simultánea consideración de factores disciplinares y extra disciplinares resulta una estrategia tan fructífera como innovadora para analizar un campo que, al extender el dominio de la explicación social al ámbito de los fenómenos físico-naturales, ha dado lugar a uno de los más complejos casos de interacción disciplinar.

Multiple genotypes of Chlamydia pneumoniae identified in human carotid plaque

Chlamydia pneumoniae is an obligate intracellular respiratory pathogen that causes 10% of community-acquired pneumonia and has been associated with cardiovascular disease. Both whole-genome sequencing and specific gene typing suggest that there is relatively little genetic variation in human isolates of C. pneumoniae. To date, there has been little genomic analysis of strains from human cardiovascular sites. The genotypes of C. pneumoniae present in human atherosclerotic carotid plaque were analysed and several polymorphisms in the variable domain 4 (VD4) region of the outer-membrane protein-A (ompA) gene and the intergenic region between the ygeD and uridine kinase (ygeD-urk) genes were found. While one genotype was identified that was the same as one reported previously in humans (respiratory and cardiovascular), another genotype was found that was identical to a genotype from non-human sources (frog/koala).

Emerging of human factor in risk analysis of home care service

Risk management in healthcare represents a group of various complex actions, implemented to improve the quality of healthcare services and guarantee the patients safety. Risks cannot be eliminated, but it can be controlled with different risk assessment methods derived from industrial applications and among these the Failure Mode Effect and Criticality Analysis (FMECA) is a largely used methodology. The main purpose of this work is the analysis of failure modes of the Home Care (HC) service provided by local healthcare unit of Naples (ASL NA1) to focus attention on human and non human factors according to the organization framework selected by WHO. © Springer International Publishing Switzerland 2014.

The development of an optimized system of narcotic and explosive contraband mimics for calibration and training of biological detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

The Development of an Optimized System of Narcotic and Explosive Contraband Mimics for Calibration and Training of Biological Detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

RE-MEANING THE SACRED: COLONIAL DAMAGE AND INDIGENOUS COSMOLOGIES

Indigenous ways of knowing are dependent on an inheriting process both amongst humans and between human and non-human being. These multi-relationships cross material and immaterial borders as sites of knowledge production. This manuscript will interrogate how three particular Indigenous cosmological relationships have been purposefully re-meaninged by colonial institutions: 1) How Anishinaabe and Haudenosaunee origin stories have been abstracted into a distinctive epistemological versus ontological site; 2) How Anishnaabe spirit worlds are impacted by colonial relations, and how state institutions benefit from the re-meaning of these worlds; and 3) How Indigenous sovereignty in Canada is imagined from a statist perspective, and how these polices have re-meaninged the sacred relationships within a cosmological understanding of Haudenosaunee governance. The re-meaning of sacredly-held Indigenous relationships is both accelerated by, and contributes to, a practice of reducing upon Indigenous and non-human societies. Throughout expressions of colonialism on Indigenous territories (the academy, the state, Indian policy), Indigenous knowledge is consistently either dismissed or appropriated. This reduction of Indigenous knowledge continues to bolster functions of the state as related to the elimination of the “Indian Problem” via reducing the “Indian” to an adaptive subject.

Humankindness: Illness, Animality, and the Limits of the Human in the Victorian Novel

This project posits a link between representations of animals or animality and representations of illness in the Victorian novel, and examines the narrative uses and ideological consequences of such representations. Figurations of animality and illness in Victorian fiction have been examined extensively as distinct phenomena, but examining their connection allows for a more complex view of the role of sympathy in the Victorian novel. The commonplace in novel criticism is that Victorian authors, whether effectively or not, constructed their novels with a view to the expansion of sympathy. This dissertation intervenes in the discussion of the Victorian novel as a vehicle for sympathy by positing that texts and scenes in which representations of illness and animality are conjoined reveal where the novel draws the boundaries of the human, and the often surprising limits it sets on sympathetic feeling. In such moments, textual cues train or direct readerly sympathies in ways that suggest a particular definition of the human, but that direction of sympathy is not always towards an enlarged sympathy, or an enlarged definition of the human. There is an equally (and increasingly) powerful antipathetic impulse in many of these texts, which estranges readerly sympathy from putatively deviant, degenerate, or dangerous groups. These two opposing impulses—the sympathetic and the antipathetic—often coexist in the same novel or even the same scene, creating an ideological and affective friction, and both draw on the same tropes of illness and animality. Examining the intersection of these different discourses—sympathy, illness, and animality-- in these novels reveals the way that major Victorian debates about human nature, evolution and degeneration, and moral responsibility shaped the novels of the era as vehicles for both antipathy and sympathy. Focusing on the novels of the Brontës and Thomas Hardy, this dissertation examines in depth the interconnected ways that representations of animals and animality and representations of illness function in the Victorian novel, as they allow authors to explore or redefine the boundary between the human and the non-human, the boundary between sympathy and antipathy, and the limits of sympathy itself.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

MRI indices of functional recovery following intracerebral implantation of a human neural stem cell line in a pre-clinical model of ischaemic stroke

Stem cell therapy for ischaemic stroke is an emerging field in light of an increasing number of patients surviving with permanent disability. Several allogenic and autologous cells types are now in clinical trials with preliminary evidence of safety. Some clinical studies have reported functional improvements in some patients. After initial safety evaluation in a Phase 1 study, the conditionally immortalised human neural stem cell line CTX0E03 is currently in a Phase 2 clinical trial (PISCES-II). Previous pre-clinical studies conducted by ReNeuron Ltd, showed evidence of functional recovery in the Bilateral Asymmetry test up to 6 weeks following transplantation into rodent brain, 4 weeks after middle cerebral artery occlusion. Resting-state fMRI is increasingly used to investigate brain function in health and disease, and may also act as a predictor of recovery due to known network changes in the post-stroke recovery period. Resting-state methods have also been applied to non-human primates and rodents which have been found to have analogous resting-state networks to humans. The sensorimotor resting-state network of rodents is impaired following experimental focal ischaemia of the middle cerebral artery territory. However, the effects of stem cell implantation on brain functional networks has not previously been investigated. Prior studies assessed sensorimotor function following sub-cortical implantation of CTX0E03 cells in the rodent post-stroke brain but with no MRI assessments of functional improvements. This thesis presents research on the effect of sub-cortical implantation of CTX0E03 cells on the resting- state sensorimotor network and sensorimotor deficits in the rat following experimental stroke, using protocols based on previous work with this cell line. The work in this thesis identified functional tests of appropriate sensitivity for long-term dysfunction suitable for this laboratory, and investigated non-invasive monitoring of physiological variables required to optimize BOLD signal stability within a high-field MRI scanner. Following experimental stroke, rats demonstrated expected sensorimotor dysfunction and changes in the resting-state sensorimotor network. CTX0E03 cells did not improve post-stroke functional outcome (compared to previous studies) and with no changes in resting-state sensorimotor network activity. However, in control animals, we observed changes in functional networks due to the stereotaxic procedure. This illustrates the sensitivity of resting-state fMRI to stereotaxic procedures. We hypothesise that the damage caused by cell or vehicle implantation may have prevented functional and network recovery which has not been previously identified due to the application of different functional tests. The findings in this thesis represent one of few pre-clinical studies in resting-state fMRI network changes post-stroke and the only to date applying this technique to evaluate functional outcomes following a clinically applicable human neural stem cell treatment for ischaemic stroke. It was found that injury caused by stereotaxic injection should be taken into account when assessing the effectiveness of treatment.

Cosmoscapes and the promotion of uncosmopolitan values

Globality generates increasingly diffuse networks of human and non-human innovators, carriers and icons of exotic, polyethnic cosmopolitan difference; and this diffusion is increasingly hard to ignore or police (Latour 1993). In fact, such global networks of material-symbolic exchange can frequently have the unintended consequence of promoting status systems and cultural relationships founded on uncosmopolitan values such as cultural appropriation and status-based social exclusion. Moreover, this materialsymbolic engagement with cosmopolitan difference could also be rather mundane, engaged in routinely without any great reflexive consciousness or capacity to destabilise current relations of cultural power, or interpreted unproblematically as just one component of a person’s social environment. Indeed, Beck’s (2006) argument is that cosmopolitanism, in an age of global risk, is being forced upon us unwillingly, so there should be no surprise if it is a bitter pill for some to swallow. Within these emergent cosmopolitan networks, which we call ‘cosmoscapes’, there is no certainty about the development of ethical or behavioural stances consistent with claims foundational to the current literature on cosmopolitanism. Reviewing historical and contemporary studies of globality and its dynamic generative capacity, this paper considers such literatures in the context of studies of cultural consumption and social status. When one positions these diverse bodies of literature against one another, it becomes clear that the possibility of widespread cosmopolitan cultural formations is largely unpromising.

An old language for a new landscape

Because aesthetics can have a profound effect upon the human relationship to the non-human environment the importance of aesthetics to ecologically sustainable designed landscapes has been acknowledged. However, in recognition that the physical forms of designed landscapes are an expression of the social values of the time, some design professionals have called for a new aesthetic ― one that reflects these current ecological concerns. To address this, some authors have suggested various theoretical design frameworks upon which such an aesthetic could be based. Within these frameworks there is an underlying theme that the patterns and processes of natural systems have the potential to form a new aesthetic for landscape design —an aesthetic based on fractal rather than Euclidean geometry. Perry, Reeves and Sim (2008) have shown that it is possible to differentiate between different landscape forms by fractal analysis. However, this research also shows that individual scenes from within very different landscape forms can possess the same fractal properties. Early data, revealed by transforming landscape images from the spatial to the frequency domain, using the fast Fourier transform, suggest that fractal patterning can have a significant effect within the landscape. In fact, it may be argued that any landscape design that includes living processes will include some design element whose ultimate form can only be expressed through the mathematics of fractal geometry. This paper will present ongoing research into the potential role of fractal geometry as a basis for a new form language – a language that may articulate an aesthetic for landscape design that echoes our ecological awakening.