Bystander-induced differentiation: a major response to targeted irradiation of a urothelial explant model.

A ureter primary explant technique, using porcine tissue sections was developed to study bystander effects under in vivo like conditions where dividing and differentiated cells are present. Targeted irradiations of ureter tissue fragments were performed with the Gray Cancer Institute charged particle microbeam at a single location (2 microm precision) with 10 3He2+ particles (5 MeV; LET 70 keV/microm). After irradiation the ureter tissue section was incubated for 7 days allowing explant outgrowth to be formed. Differentiation was estimated using antibodies to Uroplakin III, a specific marker of terminal urothelial differentiation. Even although only a single region of the tissue section was targeted, thousands of additional cells were found to undergo bystander-induced differentiation in the explant outgrowth. This resulted in an overall increase in the fraction of differentiated cells from 63.5+/-5.4% to 76.6+/-5.6%. These changes are much greater than that observed for the induction of damage in this model. One interpretation of these results is that in the tissue environment, differentiation is a much more significant response to targeted irradiation and potentially a protective mechanism.

The effects of the specific adsorption of anion on the reactivity of the Ru(0001) surface towards CO adsorption and oxidation: in situ FTIRS studies

The dynamics of adsorption and oxidation of CO on Ru(0001) electrode in sulfuric acid solution have been studied using in situ FTIR spectroscopy under potential control and at open circuit, the latter at 20 and 55 degrees C. The in situ IR data show clearly that the bisulfate anion adsorbs on the Ru(0001) surface over the potential range from -200 mV to 350 mV (vs. Ag/AgCl) at 20 degrees C in the absence and presence of adsorbed CO; however, increasing the temperature to 55 degrees C and/ or increasing the concentration of dissolved O-2 reduces the bisulfate adsorption. The formation of surface (hydro-) oxide at higher potentials replaces the bisulfate adsorbates. Both linear (COL) and three-fold hollow bonded CO (COH) adsorbates were produced following CO adsorption at Ru(0001) in H2SO4, as was observed in our previous studies in HClO4. However, the amount of adsorbed CO observed in H2SO4 was ca. 10% less than that in HClO4; in addition, the COL and COH frequencies were higher in H2SO4, and the onset potential for COads oxidation 25 mV lower. These new results are interpreted in terms of a model in which the adsorbed bisulfate weakens the CO adlayer, allowing the active Ru oxide layer to form at lower potentials. Significantly different results were observed at open circuit in H2SO4 compared both to the data under potential control and to our earlier data in HClO4, and these observations were rationalized in terms of the adsorbed HSO4- anions (pre-adsorbed at -200 mV) inhibiting the oxidation of the surface at open circuit (after stepping from the initial potential of -200 mV), as the latter was no longer driven by the imposed electrochemical potential but via chemical oxidation by trace dissolved O-2. Results from experiments at open circuit at 55 degrees C and using oxygen-saturated H2SO4 supported this model. The difference in Ru surface chemistry between imposed electrochemical control and chemical control has potential implications with respect to fuel cell electrocatalysis.

Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Is shyness context specific? Relation between shyness and online self-disclosure with and without a live webcam in young adults

The Internet provides a new tool to investigate old questions in experimental social psychology regarding Person x Context interaction. We examined the interaction of self-reported shyness and context on computer-mediated communication measures. Sixty female undergraduates unfamiliar were paired in dyads and engaged in a 10 min free chat conversation on the Internet with and without a live webcam. Free chat conversations were archived, transcripts were objectively coded for communication variables, and a linear mixed model used for data analysis of dyadic interaction was performed on each communication measure. As predicted, increases in self-reported shyness were significantly related to decreases in the number of prompted self-disclosures (after controlling for the number of opportunities to self-disclose) only in the webcam condition. Self-reported shyness was not related to the number of prompted self-disclosures in the no webcam condition, suggesting that shyness was context dependent. The present study appears to be the first to objectively code measures of Internet behaviour in relation to the study of personality in general and shyness in particular. Theoretical and clinical implications for understanding the contextual nature of shyness are discussed. (C) 2006 Elsevier Inc. All rights reserved.

Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals

A fundamental aspect of health care management is the effective allocation of resources. This is of particular importance in geriatric hospitals where elderly patients tend to have more complex needs. Hospital managers would benefit immensely if they had advance knowledge of patient duration of stay in hospital. Managers could assess the costs of patient care and make allowances for these in their budget. In this paper, we tackle this important problem via a model which predicts the duration of stay distribution of patients in hospital. The approach uses phase-type distributions conditioned on a Bayesian belief network.

Using Coxian Phase-Type Distributions to Identify Patient Characteristics for Duration of Stay in Hospital

Coxian phase-type distributions are a special type of Markov model that describes duration until an event occurs in terms of a process consisting of a sequence of latent phases. This paper considers the use of Coxian phase-type distributions for modelling patient duration of stay for the elderly in hospital and investigates the potential for using the resulting distribution as a classifying variable to identify common characteristics between different groups of patients according to their (anticipated) length of stay in hospital. The identification of common characteristics for patient length of stay groups would offer hospital managers and clinicians possible insights into the overall management and bed allocation of the hospital wards.

Simulating Coxian Phase-type Distributions for Patient Survival

Coxian phase-type distributions are a special type of Markov model that can be used to represent survival times in terms of phases through which an individual may progress until they eventually leave the system completely. Previous research has considered the Coxian phase-type distribution to be ideal in representing patient survival in hospital. However, problems exist in fitting the distributions. This paper investigates the problems that arise with the fitting process by simulating various Coxian phase-type models for the representation of patient survival and examining the estimated parameter values and eigenvalues obtained. The results indicate that numerical methods previously used for fitting the model parameters do not always converge. An alternative technique is therefore considered. All methods are influenced by the choice of initial parameter values. The investigation uses a data set of 1439 elderly patients and models their survival time, the length of time they spend in a UK hospital.

The 67-kd laminin receptor is preferentially expressed by proliferating retinal vessels in a murine model of ischemic retinopathy.

Endothelial cell association with vascular basement membranes is complex and plays a critical role in regulation of cell adhesion and proliferation. The interaction between the membrane-associated 67-kd receptor (67LR) and the basement membrane protein laminin has been studied in several cell systems where it was shown to be crucial for adhesion and attachment during angiogenesis. As angiogenesis in the pathological setting of proliferative retinopathy is a major cause of blindness in the Western world we examined the expression of 67LR in a murine model of hyperoxia-induced retinopathy that exhibits retinal neovascularization. Mice exposed to hyperoxia for 5 days starting at postnatal day 7 (P7) and returned to room air (at P12) showed closure of the central retinal vasculature. In response to the ensuing retinal ischemia, there was consistent preretinal neovascularization starting around P17, which persisted until P21, after which the new vessels regressed. Immunohistochemistry was performed on these retinas using an antibody specific for 67LR. At P12, immunoreactivity for 67LR was absent in the retina, but by P17 it was observed in preretinal proliferating vessels and also within the adjacent intraretinal vasculature. Intraretinal 67LR immunoreactivity diminished beyond P17 until by P21 immunoreactivity was almost completely absent, although it persisted in the preretinal vasculature. Control P17 mice (not exposed to hyperoxia) failed to demonstrate any 67LR immunoreactivity in their retinas. Parallel in situ hybridization studies demonstrated 67LR gene expression in the retinal ganglion cells of control and hyperoxia-exposed mice. In addition, the neovascular intra- and preretinal vessels of hyperoxia-treated P17 and P21 mice labeled strongly for 67LR mRNA. This study has characterized 67LR immunolocalization and gene expression in a murine model of ischemic retinopathy. Results suggest that, although the 67LR gene is expressed at high levels in the retinal ganglion cells, the mature receptor protein is preferentially localized to the proliferating retinal vasculature and is almost completely absent from quiescent vessels. The differential expression of 67LR between proliferating and quiescent retinal vessels suggests that this laminin receptor is an important and novel target for future chemotherapeutic intervention during proliferative vasculopathies.

ZapA, a virulence factor in a rat model of Proteus mirabilis-induced acute and chronic prostatitis.

Our knowledge of pathogenesis has benefited from a better understanding of the roles of specific virulence factors in disease. To determine the role of the virulence factor ZapA, a 54-kDa metalloproteinase of Proteus mirabilis, in prostatitis, rats were infected with either wild-type (WT) P. mirabilis or its isogenic ZapA- mutant KW360. The WT produced both acute and chronic prostatitis showing the typical histological progressions that are the hallmarks of these diseases. Infection with the ZapA- mutant, however, resulted in reduced levels of acute prostatitis, as determined from lower levels of tissue damage, bacterial colonization, and inflammation. Further, the ZapA- mutant failed to establish a chronic infection, in that bacteria were cleared from the prostate, inflammation was resolved, and tissue was seen to be healing. Clearance from the prostate was not the result of a reduced capacity of the ZapA- mutant to form biofilms in vitro. These finding clearly define ZapA as an important virulence factor in both acute and chronic bacterial prostatitis.

A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times

The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

Rethinking prenatal care within a social model of health: an exploratory study in Northern Ireland

Implementation of maternity reform agendas remains limited by the dominance of a medical rather than social model of health. This article considers group prenatal care as a complex health intervention and explores its potential in the socially divided, postconflict communities of Northern Ireland. Using qualitative inquiry strategies, we sought key informants’ views on existing prenatal care provision and on an innovative group care model (CenteringPregnancy®) as a social health initiative. We argue that taking account of the locally specific context is critical to introducing maternity care interventions to improve the health of women and their families and to contribute to community development.

Recurrent lower gastrointestinal bleeding secondary to cytomegalovirus-associated colonic ulcer in a non human immunodeficiency virus infected patient:Timely diagnosis and treatment averted surgery

Mr C, a 68-year-old Chinese male with diabetes mellitus, previous stroke and ischaemic cardiomyopathy on clopidogrel, presented with haematochezia. Colonoscopy showed a sigmoid ulcer, which was treated endoscopically. Histology of the biopsy from the ulcer revealed non-specific changes. However, he presented with recurrent bleeding from this non-healing sigmoid ulcer. A review of the histologic specimen revealed CMV intranuclear inclusion bodies. He was treated with intravenous ganciclovir, with no further hematochezia.

Keywords Hematochezia, cytomegalovirus, ulcer

The Colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information

BACKGROUND: To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome.

METHODS: DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information.

RESULTS: The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance.

CONCLUSIONS: Analysis from our in vitro and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including IGF2BP2, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear; however, the numbers that have been detected by the disease-specific microarray would suggest that they may be important regulatory transcripts. This study has demonstrated the power of a disease-specific transcriptome-based approach and highlighted the potential novel biologically and clinically relevant information that is gained when using such a methodology.