Targeting mutant fibroblast growth factor receptors in cancer

Fibroblast growth factor receptors (FGFRs) play diverse roles in the control of cell proliferation, cell differentiation, angiogenesis and development. Activating the mutations of FGFRs in the germline has long been known to cause a variety of skeletal developmental disorders, but it is only recently that a similar spectrum of somatic FGFR mutations has been associated with human cancers. Many of these somatic mutations are gain-of-function and oncogenic and create dependencies in tumor cell lines harboring such mutations. A combination of knockdown studies and pharmaceutical inhibition in preclinical models has further substantiated genomically altered FGFR as a therapeutic target in cancer, and the oncology community is responding with clinical trials evaluating multikinase inhibitors with anti-FGFR activity and a new generation of specific pan-FGFR inhibitors.

Cross likelihood ratio based speaker clustering using eigenvoice models

This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Hyaluronic acid : evaluation as a potential delivery vehicle for vitronectin:growth factor complexes in wound healing applications

We have previously reported that novel vitronectin:growth factor (VN:GF) complexes significantly increase re-epithelialization in a porcine deep dermal partial-thickness burn model. However, the potential exists to further enhance the healing response through combination with an appropriate delivery vehicle which facilitates sustained local release and reduced doses of VN:GF complexes. Hyaluronic acid (HA), an abundant constituent of the interstitium, is known to function as a reservoir for growth factors and other bioactive species. The physicochemical properties of HA confer it with an ability to sustain elevated pericellular concentrations of these species. This has been proposed to arise via HA prolonging interactions of the bioactive species with cell surface receptors and/or protecting them from degradation. In view of this, the potential of HA to facilitate the topical delivery of VN:GF complexes was evaluated. Two-dimensional (2D) monolayer cell cultures and 3D de-epidermised dermis (DED) human skin equivalent (HSE) models were used to test skin cell responses to HA and VN:GF complexes. Our 2D studies revealed that VN:GF complexes and HA stimulate the proliferation of human fibroblasts but not keratinocytes. Experiments in our 3D DED-HSE models showed that VN:GF complexes, both alone and in conjunction with HA, led to enhanced development of both the proliferative and differentiating layers in the DED-HSE models. However, there was no significant difference between the thicknesses of the epidermis treated with VN:GF complexes alone and VN:GF complexes together with HA. While the addition of HA did not enhance all the cellular responses to VN:GF complexes examined, it was not inhibitory, and may confer other advantages related to enhanced absorption and transport that could be beneficial in delivery of the VN:GF complexes to wounds.

A tan in a test tube -in vitro models for investigating ultraviolet radiation-induced damage in skin

Presently, global rates of skin cancers induced by ultraviolet radiation (UVR) exposure are on the rise. In view of this, current knowledge gaps in the biology of photocarcinogenesis and skin cancer progression urgently need to be addressed. One factor that has limited skin cancer research has been the need for a reproducible and physiologically-relevant model able to represent the complexity of human skin. This review outlines the main currently-used in vitro models of UVR-induced skin damage. This includes the use of conventional two-dimensional cell culture techniques and the major animal models that have been employed in photobiology and photocarcinogenesis research. Additionally, the progression towards the use of cultured skin explants and tissue-engineered skin constructs, and their utility as models of native skin's responses to UVR are described. The inherent advantages and disadvantages of these in vitro systems are also discussed.

Intrinsic kinetics of titania photocatalysis : simplified models for their investigation

Even though titanium dioxide photocatalysis has been promoted as a leading green technology for water purification, many issues have hindered its application on a large commercial scale. For the materials scientist the main issues have centred the synthesis of more efficient materials and the investigation of degradation mechanisms; whereas for the engineers the main issues have been the development of appropriate models and the evaluation of intrinsic kinetics parameters that allow the scale up or re-design of efficient large-scale photocatalytic reactors. In order to obtain intrinsic kinetics parameters the reaction must be analysed and modelled considering the influence of the radiation field, pollutant concentrations and fluid dynamics. In this way, the obtained kinetic parameters are independent of the reactor size and configuration and can be subsequently used for scale-up purposes or for the development of entirely new reactor designs. This work investigates the intrinsic kinetics of phenol degradation over titania film due to the practicality of a fixed film configuration over a slurry. A flat plate reactor was designed in order to be able to control reaction parameters that include the UV irradiance, flow rates, pollutant concentration and temperature. Particular attention was paid to the investigation of the radiation field over the reactive surface and to the issue of mass transfer limited reactions. The ability of different emission models to describe the radiation field was investigated and compared to actinometric measurements. The RAD-LSI model was found to give the best predictions over the conditions tested. Mass transfer issues often limit fixed film reactors. The influence of this phenomenon was investigated with specifically planned sets of benzoic acid experiments and with the adoption of the stagnant film model. The phenol mass transfer coefficient in the system was calculated to be km,phenol=8.5815x10-7Re0.65(ms-1). The data obtained from a wide range of experimental conditions, together with an appropriate model of the system, has enabled determination of intrinsic kinetic parameters. The experiments were performed in four different irradiation levels (70.7, 57.9, 37.1 and 20.4 W m-2) and combined with three different initial phenol concentrations (20, 40 and 80 ppm) to give a wide range of final pollutant conversions (from 22% to 85%). The simple model adopted was able to fit the wide range of conditions with only four kinetic parameters; two reaction rate constants (one for phenol and one for the family of intermediates) and their corresponding adsorption constants. The intrinsic kinetic parameters values were defined as kph = 0.5226 mmol m-1 s-1 W-1, kI = 0.120 mmol m-1 s-1 W-1, Kph = 8.5 x 10-4 m3 mmol-1 and KI = 2.2 x 10-3 m3 mmol-1. The flat plate reactor allowed the investigation of the reaction under two different light configurations; liquid and substrate side illumination. The latter of particular interest for real world applications where light absorption due to turbidity and pollutants contained in the water stream to be treated could represent a significant issue. The two light configurations allowed the investigation of the effects of film thickness and the determination of the catalyst optimal thickness. The experimental investigation confirmed the predictions of a porous medium model developed to investigate the influence of diffusion, advection and photocatalytic phenomena inside the porous titania film, with the optimal thickness value individuated at 5 ìm. The model used the intrinsic kinetic parameters obtained from the flat plate reactor to predict the influence of thickness and transport phenomena on the final observed phenol conversion without using any correction factor; the excellent match between predictions and experimental results provided further proof of the quality of the parameters obtained with the proposed method.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Lifestyle risk factor modification in midlife women with type 2 diabetes : theoretical modelling of perceived barriers

Objective: The aim of this paper is to propose a ‘Perceived barriers and lifestyle risk factor modification model’ that could be incorporated into existing frameworks for diabetes education to enhance lifestyle risk factor education in women. Setting: Diabetes education, community health. Primary argument: ‘Perceived barriers’ is a health promotion concept that has been found to be a significant predictor of health promotion behaviour. There is evidence that women face a range of perceived barriers that prevent them from engaging in healthy lifestyle activities. Despite this, current evidence based models of diabetes education do not explicitly incorporate the concept of perceived barriers. A model of risk factor reduction that incorporates ‘perceived barriers’ is proposed. Conclusion: Although further research is required, current approaches to risk factor reduction in type 2 diabetes could be enhanced by identification and goal setting to reduce an individual’s perceived barriers.

A confirmatory factor analysis of the Observer Alexithymia Scale in treatment seeking alcohol-dependent patients

Confirmatory factor analyses evaluated the factorial validity of the Observer Alexithymia Scale (OAS) in an alcohol-dependent sample. Observation was conducted by clinical psychologists. All models examined were rejected, given their poor fit. Given the psychometric limitations of the OAS shown in this study, the OAS may not be the most appropriate measure to use early in treatment among alcohol-dependent individuals.

Modelling word activation in semantic networks : three scaled entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

Alternative models of cardiac rehabilitation : a systematic review

The traditional hospital-based model of cardiac rehabilitation faces substantial challenges, such as cost and accessibility. These challenges have led to the development of alternative models of cardiac rehabilitation in recent years. The aim of this study was to identify and critique evidence for the effectiveness of these alternative models. A total of 22 databases were searched to identify quantitative studies or systematic reviews of quantitative studies regarding the effectiveness of alternative models of cardiac rehabilitation. Included studies were appraised using a Critical Appraisal Skills Programme tool and the National Health and Medical Research Council's designations for Level of Evidence. The 83 included articles described interventions in the following broad categories of alternative models of care: multifactorial individualized telehealth, internet based, telehealth focused on exercise, telehealth focused on recovery, community- or home-based, and complementary therapies. Multifactorial individualized telehealth and community- or home-based cardiac rehabilitation are effective alternative models of cardiac rehabilitation, as they have produced similar reductions in cardiovascular disease risk factors compared with hospital-based programmes. While further research is required to address the paucity of data available regarding the effectiveness of alternative models of cardiac rehabilitation in rural, remote, and culturally and linguistically diverse populations, our review indicates there is no need to rely on hospital-based strategies alone to deliver effective cardiac rehabilitation. Local healthcare systems should strive to integrate alternative models of cardiac rehabilitation, such as brief telehealth interventions tailored to individual's risk factor profiles as well as community- or home-based programmes, in order to ensure there are choices available for patients that best fit their needs, risk factor profile, and preferences.

Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.

Coexpression of epidermal growth factor receptor with related factors is associated with a poor prognosis in non-small-cell lung cancer

The epidermal growth factor receptor (EGFR) is commonly expressed in non-small-cell lung cancer (NSCLC) and promotes a host of mechanisms involved in tumorigenesis. However, EGFR expression does not reliably predict prognosis or response to EGFR-targeted therapies. The data from two previous studies of a series of 181 consecutive surgically resected stage I-IIIA NSCLC patients who had survived in excess of 60 days were explored. Of these patients, tissue was available for evaluation of EGFR in 179 patients, carbonic anhydrase (CA) IX in 177 patients and matrix metalloproteinase-9 (MMP-9) in 169 patients. We have previously reported an association between EGFR expression and MMP-9 expression. We have also reported that MMP-9 (P=0.001) and perinuclear (p)CA IX (P=0.03) but not EGFR expression were associated with a poor prognosis. Perinuclear CA IX expression was also associated with EGFR expression (P<0.001). Multivariate analysis demonstrated that coexpression of MMP-9 with EGFR conferred a worse prognosis than the expression of MMP-9 alone (P<0.001) and coexpression of EGFR and pCA IX conferred a worse prognosis than pCA IX alone (P=0.05). A model was then developed where the study population was divided into three groups: group 1 had expression of EGFR without coexpression of MMP-9 or pCA IX (number=21); group 2 had no expression of EGFR (number=75); and group 3 had coexpression of EGFR with pCA IX or MMP-9 or both (number=70). Group 3 had a worse prognosis than either groups 1 or 2 (P=0.0003 and 0.027, respectively) and group 1 had a better prognosis than group 2 (P=0.036). These data identify two cohorts of EGFR-positive patients with diametrically opposite prognoses. The group expressing either EGFR and or both MMP-9 and pCA IX may identify a group of patients with activated EGFR, which is of clinical relevance with the advent of EGFR-targeted therapies. © 2004 Cancer Research UK.

An analysis of regression models for predicting the speed of a wave glider autonomous surface vehicle

An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

Targeting nuclear factor-kappa B to overcome resistance to chemotherapy

Intrinsic or acquired resistance to chemotherapeutic agents is a common phenomenon and a major challenge in the treatment of cancer patients. Chemoresistance is defined by a complex network of factors including multi-drug resistance proteins, reduced cellular uptake of the drug, enhanced DNA repair, intracellular drug inactivation, and evasion of apoptosis. Pre-clinical models have demonstrated that many chemotherapy drugs, such as platinum-based agents, antracyclines, and taxanes, promote the activation of the NF-κB pathway. NF-κB is a key transcription factor, playing a role in the development and progression of cancer and chemoresistance through the activation of a multitude of mediators including anti-apoptotic genes. Consequently, NF-κB has emerged as a promising anti-cancer target. Here, we describe the role of NF-κB in cancer and in the development of resistance, particularly cisplatin. Additionally, the potential benefits and disadvantages of targeting NF-κB signaling by pharmacological intervention will be addressed.

Factor Five : Transforming the Global Economy through 80% Improvements in Resource Productivity

The 21st century will see monumental change. Either the human race will use its knowledge and skills and change the way it interacts with the environment, or the environment will change the way it interacts with its inhabitants. In the first case, the focus of this book, we would see our sophisticated understanding in areas such as physics, chemistry, engineering, biology, planning, commerce, business and governance accumulated over the last 1,000 years brought to bear on the challenge of dramatically reducing our pressure on the environment. The second case however is the opposite scenario, involving the decline of the planet’s ecosystems until they reach thresholds where recovery is not possible, and following which we have no idea what happens. For instance, if we fail to respond to Sir Nicolas Stern’s call to meet appropriate stabilisation trajectories for greenhouse gas emissions, and we allow the average temperature of our planets surface to increase by 4-6 degrees Celsius, we will see staggering changes to our environment, including rapidly rising sea level, withering crops, diminishing water reserves, drought, cyclones, floods… allowing this to happen will be the failure of our species, and those that survive will have a deadly legacy. In this update to the 1997 International Best Seller, Factor Four, Ernst von Weizsäcker again leads a team to present a compelling case for sector wide advances that can deliver significant resource productivity improvements over the coming century. The purpose of this book is to inspire hope and to then inform meaningful action in the coming decades to respond to the greatest challenge our species has ever faced – that of living in harmony with our planet and its other inhabitants.