Training program impact on thermoplastic immobilization for head and neck radiation therapy

Purpose: To determine whether uniform guidelines and training in the stabilization and formation of thermoplastic shells can improve the reproducibility of set-up for Head and Neck cancer patients. Methods and materials: Image based measurements of the planning and treatment positions for 35 head and neck cancer patients undergoing radical radiotherapy were analysed to provide a baseline of the reproducibility of thermoplastic immobilization. Radiation therapists (RT) were surveyed to establish a perception of their confidence in thermoplastic procedures. An evidence based staff training program was created and implemented. Set-up reproduction and staff perception were reviewed to measure the impact of the training program. Results: The mean (SD) 3D vectors of anatomical displacement, measured on the patient images, improved from 4.64 (2.03) for the baseline group compared to 3.02 (1.65) following training (p < 0.01). The proportion of 3D displacements of patient data exceeding 5 mm 3D vector was decreased from 37.1% to 5.7% (p < 0.001) and the 3 mm vector from 85.7% to 42.9% (p < 0.001). The post-training survey scores demonstrated improved confidence in reproducibility of set-up for head and neck patients. Conclusion: The Thermoplastic Shells Training Program has been found to improve the treatment reproducibility for head and neck radiation therapy patients. Uniform guidelines have increased RT confidence in thermoplastic procedures.

Pore formation during dehydration of polycrystalline gypsum observed and quantified in a time-series synchrotron radiation based X-ray micro-tomography experiment

We conducted an in-situ X-ray micro-computed tomography heating experiment at the Advanced Photon Source (USA) to dehydrate an unconfined 2.3 mm diameter cylinder of Volterra Gypsum. We used a purpose-built X-ray transparent furnace to heat the sample to 388 K for a total of 310 min to acquire a three-dimensional time-series tomography dataset comprising nine time steps. The voxel size of 2.2 μm3 proved sufficient to pinpoint reaction initiation and the organization of drainage architecture in space and time. We observed that dehydration commences across a narrow front, which propagates from the margins to the centre of the sample in more than four hours. The advance of this front can be fitted with a square-root function, implying that the initiation of the reaction in the sample can be described as a diffusion process. Novel parallelized computer codes allow quantifying the geometry of the porosity and the drainage architecture from the very large tomographic datasets (20483 voxels) in unprecedented detail. We determined position, volume, shape and orientation of each resolvable pore and tracked these properties over the duration of the experiment. We found that the pore-size distribution follows a power law. Pores tend to be anisotropic but rarely crack-shaped and have a preferred orientation, likely controlled by a pre-existing fabric in the sample. With on-going dehydration, pores coalesce into a single interconnected pore cluster that is connected to the surface of the sample cylinder and provides an effective drainage pathway. Our observations can be summarized in a model in which gypsum is stabilized by thermal expansion stresses and locally increased pore fluid pressures until the dehydration front approaches to within about 100 μm. Then, the internal stresses are released and dehydration happens efficiently, resulting in new pore space. Pressure release, the production of pores and the advance of the front are coupled in a feedback loop.

Serine protease inhibition and mitochondrial dysfunction associated with cisplatin resistance in human tumor cell lines : targets for therapy

Indicators of mitochondrial function were studied in two different cell culture models of cis-diamminedichloroplatinum-II (CDDP) resistance: the intrinsically resistant human ovarian cancer cell line CI-80-13S, and resistant clones (HeLa-S1a and HeLa-S1b) generated by stable expression of the serine protease inhibitor—plasminogen activator inhibitor type-2 (PAI-2), in the human cervical cancer cell line HeLa. In both models, CDDP resistance was associated with sensitivity to killing by adriamycin, etoposide, auranofin, bis[1,2-bis(diphenylphosphino)ethane]gold(I) chloride {[Au(DPPE)2]Cl}, CdCl2 and the mitochondrial inhibitors rhodamine-123 (Rhl23), dequalinium chloride (DeCH), tetraphenylphosphonium (TPP), and ethidium bromide (EtBr) and with lower constitutive levels of ATP. Unlike the HeLa clones, CI-80-13S cells were additionally sensitive to chloramphenicol, 1-methyl-4-phenylpyridinium ion (MPP+), rotenone, thenoyltrifluoroacetone (TTFA), and antimycin A, and showed poor reduction of 1-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT), suggesting a deficiency in NADH dehydrogenase and/or succinate dehydrogenase activities. Total platinum uptake and DNA-bound platinum were slightly lower in CI-80-13S than in sensitive cells. The HeLa-S1a and HeLa-S1b clones, on the other hand, showed poor reduction of triphenyltetrazolium chloride (TTC), indicative of low cytochrome c oxidase activity. Total platinum uptake by HeLa-S1a was similar to HeLa, but DNA-bound platinum was much lower than for the parent cell line. The mitochondria of CI-80-13S and HeLa-S1a showed altered morphology and were fewer in number than those of JAM and HeLa. In both models, CDDP resistance was associated with less platinum accumulation and with mitochondrial and membrane defects, brought about one case with expression of a protease inhibitor which is implicated in tumor progression. Such markers may identify tumors suitable for treatment with gold phosphine complexes or other mitochondrial inhibitors.

In vitro primary cell culture as a physiologically relevant method for preclinical testing of human oncolytic adenovirus

Ad[I/PPT-E1A] is an oncolytic adenovirus that specifically kills prostate cells via restricted replication by a prostate-specific regulatory element. Off-target replication of oncolytic adenoviruses would have serious clinical consequences. As a proposed ex vivo test, we describe the assessment of the specificity of Ad[I/PPT-E1A] viral cytotoxicity and replication in human nonprostate primary cells. Four primary nonprostate cell types were selected to mimic the effects of potential in vivo exposure to Ad[I/PPT-E1A] virus: bronchial epithelial cells, urothelial cells, vascular endothelial cells, and hepatocytes. Primary cells were analyzed for Ad[I/PPT-E1A] viral cytotoxicity in MTS assays, and viral replication was determined by hexon titer immunostaining assays to quantify viral hexon protein. The results revealed that at an extreme multiplicity of infection of 500, unlikely to be achieved in vivo, Ad[I/PPT-E1A] virus showed no significant cytotoxic effects in the nonprostate primary cell types apart from the hepatocytes. Transmission electron microscopy studies revealed high levels of Ad[I/PPT-E1A] sequestered in the cytoplasm of these cells. Adenoviral green fluorescent protein reporter studies showed no evidence for nuclear localization, suggesting that the cytotoxic effects of Ad[I/PPT-E1A] in human primary hepatocytes are related to viral sequestration. Also, hepatocytes had increased amounts of coxsackie adenovirus receptor surface protein. Active viral replication was only observed in the permissive primary prostate cells and LNCaP prostate cell line, and was not evident in any of the other nonprostate cells types tested, confirming the specificity of Ad[I/PPT-E1A]. Thus, using a relevant panel of primary human cells provides a convenient and alternative preclinical assay for examining the specificity of conditionally replicating oncolytic adenoviruses in vivo.

The cancer stem-cell hypothesis : its emerging role in lung cancer biology and its relevance for future therapy

The cancer stem-cell (CSC) hypothesis suggests that there is a small subset of cancer cells that are responsible for tumor initiation and growth, possessing properties such as indefinite self-renewal, slow replication, intrinsic resistance to chemotherapy and radiotherapy, and an ability to give rise to differentiated progeny. Through the use of xenotransplantation assays, putative CSCs have been identified in many cancers, often identified by markers usually expressed in normal stem cells. This is also the case in lung cancer, and the accumulated data on side population cells, CD133, CD166, CD44 and ALDH1 are beginning to clarify the true phenotype of the lung cancer stem cell. Furthermore, it is now clear that many of the pathways of normal stem cells, which guide cellular proliferation, differentiation, and apoptosis are also prominent in CSCs; the Hedgehog (Hh), Notch, and Wnt signaling pathways being notable examples. The CSC hypothesis suggests that there is a small reservoir of cells within the tumor, which are resistant to many standard therapies, and can give rise to new tumors in the form of metastases or relapses after apparent tumor regression. Therapeutic interventions that target CSC pathways are still in their infancy and clinical data of their efficacy remain limited. However Smoothened inhibitors, gamma-secretase inhibitors, anti-DLL4 antagonists, Wnt antagonists, and CBP/β-catenin inhibitors have all shown promising anticancer effects in early studies. The evidence to support the emerging picture of a lung cancer CSC phenotype and the development of novel therapeutic strategies to target CSCs are described in this review.

Does the addition of integrated cognitive behaviour therapy and motivational interviewing improve the outcomes of standard care for young people with comorbid depression and substance misuse?

Background: The high rates of comorbid depression and substance use in young people have been associated with a range of adverse outcomes. Yet, few treatment studies have been conducted with this population. Objective: To determine if the addition of Motivational Interviewing and Cognitive Behaviour Therapy (MI/CBT) to standard alcohol and other drug (AOD) care improves the outcomes of young people with comorbid depression and substance use. Participants and Setting: Participants comprised 88 young people with comorbid depression (Kessler 10 score of > 17) and substance use (mainly alcohol/cannabis) seeking treatment at two youth AOD services in Melbourne, Australia. Sixty young people received MI/CBT in addition to standard care (SC) and 28 received SC alone. Outcomes Measures: Primary outcome measures were depressive symptoms and drug and alcohol use in the past month. Assessments were conducted at baseline, 3 and 6 months follow up. Results and Conclusions: The addition of MI/CBT to SC was associated with a significantly greater rate of change in depression, cannabis use, motivation to change substance use and social contact in the first 3 months. However, those who received SC had achieved similar improvements on these variables by 6 months follow up. All young people achieved significant improvements in functioning and quality of life variables over time, regardless of the treatment group. No changes in alcohol or other drug use were found in either group. The delivery of MI/CBT in addition to standard AOD care may offer accelerated treatment gains in the short-term.

IGF2 increases de novo steroidogenesis in prostate cancer cells

Androgen-dependent pathways regulate maintenance and growth of normal and malignant prostate tissues. Androgen deprivation therapy (ADT) exploits this dependence and is used to treat metastatic prostate cancer; however, regression initially seen with ADT gives way to development of incurable castration-resistant prostate cancer (CRPC). Although ADT generates a therapeutic response, it is also associated with a pattern of metabolic alterations consistent with metabolic syndrome including elevated circulating insulin. Because CRPC cells are capable of synthesizing androgens de novo, we hypothesized that insulin may also influence steroidogenesis in CRPC. In this study, we examined this hypothesis by evaluating the effect of insulin on steroid synthesis in prostate cancer cell lines. Treatment with 10 nmol/L insulin increased mRNA and protein expression of steroidogenesis enzymes and upregulated the insulin receptor substrate insulin receptor substrate 2 (IRS-2). Similarly, insulin treatment upregulated intracellular testosterone levels and secreted androgens, with the concentrations of steroids observed similar to the levels reported in prostate cancer patients. With similar potency to dihydrotestosterone, insulin treatment resulted in increased mRNA expression of prostate-specific antigen. CRPC progression also correlated with increased expression of IRS-2 and insulin receptor in vivo. Taken together, our findings support the hypothesis that the elevated insulin levels associated with therapeutic castration may exacerbate progression of prostate cancer to incurable CRPC in part by enhancing steroidogenesis.

Metacognitive therapy for alcohol abuse and dependence

While the consumption of alcohol has been part of the collective psyche of Australians since colonisation, the overconsumption of alcohol has been and continues to be a significant problem for the Australian community. Currently motivational interviewing and cognitive behaviour therapy are seen as the two standard psychological interventions for alcohol abuse and dependence. While these two approaches have shown significant impact on reducing alcohol abuse and dependence, they are not without their limitations. As such there is a need to continue to explore the application of newer developments in psychotherapy to the treatment problematic drinking behaviours. In this chapter we propose that Metacognitive Therapy is one such psychotherapy that is likely to provide a promising new approach to the treatment of alcohol abuse and dependence. In this chapter we will first briefly outline the history and significance of problematic drinking behaviours in Australia. Following this, we will quickly summarise the literature regarding motivational interviewing and cognitive behaviour therapy. Next we will provide an outline of the theoretical framework of Metacognitive Therapy and then describe two brief case studies illustrating the application of Metacognitive Therapy to the treatment of alcohol abuse and dependence. From this discussion we propose that the combination of Motivational Interviewing and Metacognitive Therapy is a promising new approach that can provide great assistance for the treatment of alcohol abuse or dependence.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Response to “Topical agent therapy for prevention and treatment of radiodermatitis : a meta-analysis”

To the Editor; It was with interest that I read the recent article by Zhang et al. published in Supportive Care in Cancer [1]. This paper highlighted the importance of radiodermatitis (RD) being an unresolved and distressing clinical issue in patients with cancer undergoing radiation therapy. However, I am concerned with a number of clinical and methodological issues within this paper: (i) the clinical and operational definition of prophylaxis and treatment of RD; (ii) the accuracy of the identification of trials; and (iii) the appropriateness of the conduct of the meta-analyses...

Compression therapy : getting it right

Teaching basic principles of colonisation, contamination and infection has revolutionised approaches to wound care. Wound colonisation is classified as the existence of bacteria with no obvious host reaction (Carville 2005). The act of wound contamination is recognised as introducing micro-organisms into the wound (Ellis 2004). Wound infection is an invasion and multiplication of micro-organisms causing localised and systemic effects (Baranoski and Ayello 2004). Through clinical practice, nurses inadvertently engage in wound contamination thus setting the environment for wound infection.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.