The Ghrelin axis : does it have an appetite for cancer progression?

Ghrelin, the endogenous ligand for the GH secretagogue receptor (GHSR), is a peptide hormone with diverse physiological roles. Ghrelin regulates GH release, appetite and feeding, gut motility, and energy balance and also has roles in the cardiovascular, immune, and reproductive systems. Ghrelin and the GHSR are expressed in a wide range of normal and tumor tissues, and a fluorescein-labeled, truncated form of ghrelin is showing promise as a biomarker for prostate cancer. Plasma ghrelin levels are generally inversely related to body mass index and are unlikely to be useful as a biomarker for cancer, but may be useful as a marker for cancer cachexia. Some single nucleotide polymorphisms in the ghrelin and GHSR genes have shown associations with cancer risk; however, larger studies are required. Ghrelin regulates processes associated with cancer, including cell proliferation, apoptosis, cell migration, cell invasion, inflammation, and angiogenesis; however, the role of ghrelin in cancer is currently unclear. Ghrelin has predominantly antiinflammatory effects and may play a role in protecting against cancer-related inflammation. Ghrelin and its analogs show promise as treatments for cancer-related cachexia. Further studies using in vivo models are required to determine whether ghrelin has a role in cancer progression.

Predicting the effects of bagasse depithing operations on boiler combustion performance

The sugar industry is pursuing diversification options using bagasse as a feedstock. Depithing, the removal of the smaller bagasse particles, is an integral part of the manufacturing processes for bagasse by-products such as pulp and paper. There are possible environmental and economic benefits associated with incorporating depithing operations into a sugar factory. However there have only been limited investigations into the effects of depithing operations on a sugar factory boiler station. This paper describes a modelling investigation, using the lumped parameter boiler design tool BOILER and the CFD code FURNACE, to predict the effects of pith, depithed bagasse and mixed bagasse/pith firing on the efficiency, fuel consumption and combustion performance of a typical sugar factory boiler.

Spatial modelling of population health screening : the role of accessibility in predicting expected patient flows

This paper describes a generalised linear mixed model (GLMM) approach for understanding spatial patterns of participation in population health screening, in the presence of multiple screening facilities. The models presented have dual focus, namely the prediction of expected patient flows from regions to services and relative rates of participation by region- service combination, with both outputs having meaningful implications for the monitoring of current service uptake and provision. The novelty of this paper lies with the former focus, and an approach for distributing expected participation by region based on proximity to services is proposed. The modelling of relative rates of participation is achieved through the combination of different random effects, as a means of assigning excess participation to different sources. The methodology is applied to participation data collected from a government-funded mammography program in Brisbane, Australia.

Adaptive radiotherapy for virally mediated head and neck cancer : predicting which patients may benefit most

Background: Recent clinical studies have demonstrated an emerging subgroup of head and neck cancers that are virally mediated. This disease appears to be a distinct clinical entity with patients presenting younger and with more advanced nodal disease, having lower tobacco and alcohol exposure and highly radiosensitive tumours. This means they are living longer, often with the debilitating functional side effects of treatment. The primary objective of this study was to determine how virally mediated nasopharyngeal and oropharyngeal cancers respond to radiation therapy treatment. The aim was to determine risk categories and corresponding adaptive treatment management strategies to proactively manage these patients. Method/Results: 121 patients with virally mediated, node positive nasopharyngeal or oropharyngeal cancer who received radiotherapy treatment with curative intent between 2005 and 2010 were studied. Relevant patient demographics including age, gender, diagnosis, TNM stage, pre-treatment nodal size and dose delivered was recorded. Each patient’s treatment plan was reviewed to determine if another computed tomography (re-CT) scan was performed and at what time point (dose/fraction) this occurred. The justification for this re-CT was determined using four categories: tumour and/or nodal regression, weight loss, both or other. Patients who underwent a re-CT were further investigated to determine whether a new plan was calculated. If a re-plan was performed, the dosimetric effect was quantified by comparing dose volume histograms of planning target volumes and critical structures from the actual treatment delivered and the original treatment plan. Preliminary results demonstrated that 25/121 (20.7%) patients required a re-CT and that these re-CTs were performed between fractions 20 to 25 of treatment. The justification for these re-CTs consisted of a combination of tumour and/or nodal regression and weight loss. 16/25 (13.2%) patients had a replan calculated. 9 (7.4%) of these replans were implemented clinically due to the resultant dosimetric effect calculated. The data collected from this assessment was statistically analysed to identify the major determining factors for patients to undergo a re-CT and/or replan. Specific factors identified included nodal size and timing of the required intervention (i.e. how when a plan is to be adapted). This data was used to generate specific risk profiles that will form the basis of a biologically guided adaptive treatment management strategy for virally mediated head and neck cancer. Conclusion: Preliminary data indicates that virally mediated head and neck cancers respond significantly during radiation treatment (tumour and/or nodal regression and weight loss). Implications of this response are the potential underdosing or overdosing of tumour and/or surrounding critical structures. This could lead to sub-optimal patient outcomes and compromised quality of life. Consequently, the development of adaptive treatment strategies that improve organ sparing for this patient group is important to ensure delivery of the prescribed dose to the tumour volume whilst minimizing the dose received to surrounding critical structures. This could reduce side effects and improve overall patient quality of life. The risk profiles and associated adaptive treatment approaches developed in this study will be tested prospectively in the clinical setting in Phase 2 of this investigation.

Predicting the localized surface plasmon resonances of spherical nanoparticles on substrate : electrostatic eigenmode method

We present experimental results that demonstrate that the wavelength of the fundamental localised surface plasmon resonance for spherical gold nanoparticles on glass can be predicted using a simple, one line analytical formula derived from the electrostatic eigenmode method. This allows the role of the substrate in lifting mode degeneracies to be determined, and the role of local environment refractive indices on the plasmon resonance to be investigated. The effect of adding silica to the casting solution in minimizing nanopaticle agglomeration is also discussed.

Morphology-based model for predicting osteocyte-like cell line (MLO-Y4) growth process

This work has led to the development of empirical mathematical models to quantitatively predicate the changes of morphology in osteocyte-like cell lines (MLO-Y4) in culture. MLO-Y4 cells were cultured at low density and the changes in morphology recorded over 11 hours. Cell area and three dimensional shape features including aspect ratio, circularity and solidity were then determined using widely accepted image analysis software (ImageJTM). Based on the data obtained from the imaging analysis, mathematical models were developed using the non-linear regression method. The developed mathematical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analyzing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary.

Nursing a case of the blues : an examination of the role of depression in predicting job-related affective well-being in nurses

The current study explored the effect of depression, optimism, and anxiety on job-related affective well-being in 70 graduate nurses. It was predicted that depression and anxiety would have a significant negative effect on job-related affective well-being, whereas optimism would have a significant positive effect on job-related affective well-being. Questionnaires were completed online or in hard-copy forms. Results revealed that depression, optimism, and anxiety were all significantly correlated to job-related affective well-being in the expected direction however, depression was found to be the only variable that made a significant unique contribution to the prediction of job-related affective well-being. Possible explanations for these findings are explored.

An ensemble method for predicting subnuclear localizations from primary protein structures

Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpr​ed_page.php.

Comparative study of analytical rental model and statistical models for predicting house rental levels

The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.

Predicting vitamin D deficiency in older Australian adults

OBJECTIVE There has been a dramatic increase in vitamin D testing in Australia in recent years, prompting calls for targeted testing. We sought to develop a model to identify people most at risk of vitamin D deficiency. DESIGN AND PARTICIPANTS This is a cross-sectional study of 644 60- to 84-year-old participants, 95% of whom were Caucasian, who took part in a pilot randomized controlled trial of vitamin D supplementation. MEASUREMENTS Baseline 25(OH)D was measured using the Diasorin Liaison platform. Vitamin D insufficiency and deficiency were defined using 50 and 25 nmol/l as cut-points, respectively. A questionnaire was used to obtain information on demographic characteristics and lifestyle factors. We used multivariate logistic regression to predict low vitamin D and calculated the net benefit of using the model compared with 'test-all' and 'test-none' strategies. RESULTS The mean serum 25(OH)D was 42 (SD 14) nmol/1. Seventy-five per cent of participants were vitamin D insufficient and 10% deficient. Serum 25(OH)D was positively correlated with time outdoors, physical activity, vitamin D intake and ambient UVR, and inversely correlated with age, BMI and poor self-reported health status. These predictors explained approximately 21% of the variance in serum 25(OH)D. The area under the ROC curve predicting vitamin D deficiency was 0·82. Net benefit for the prediction model was higher than that for the 'test-all' strategy at all probability thresholds and higher than the 'test-none' strategy for probabilities up to 60%. CONCLUSION Our model could predict vitamin D deficiency with reasonable accuracy, but it needs to be validated in other populations before being implemented.

Measuring mechanical properties of tendon in vivo

Introduction: Understanding the mechanical properties of tendon is an important step to guiding the process of improving athletic performance, predicting injury and treating tendinopathies. The speed of sound in a medium is governed by the bulk modulus and density for fluids and isotropic materials. However, for tendon,which is a structural composite of fluid and collagen, there is some anisotropy requiring an adjustment for Poisson’s ratio. In this paper, these relationships are explored and modelled using data collected, in vivo, on human Achilles tendon. Estimates for elastic modulus and hysteresis based on speed of sound data are then compared against published values from in vitro mechanical tests. Methods: Measurements using clinical ultrasound imaging, inverse dynamics and acoustic transmission techniques were used to determine dimensions, loading conditions and longitudinal speed of sound for the Achilles tendon during a series of isometric plantar flexion exercises against body weight. Upper and lower bounds for speed of sound versus tensile stress in the tendon were then modelled and estimates derived for elastic modulus and hysteresis. Results: Axial speed of sound varied between 1850 to 2090 m.s−1 with a non-linear, asymptotic dependency on the level of tensile stress in the tendon 5–35 MPa. Estimates derived for the elastic modulus ranged between 1–2 GPa. Hysteresis derived from models of the stress-strain relationship, ranged from 3–11%. These values agree closely with those previously reported from direct measurements obtained via in vitro mechanical tensile tests on major weight bearing tendons. Discussion: There is sufficiently good agreement between these indirect (speed of sound derived) and direct (mechanical tensile test derived) measures of tendon mechanical properties to validate the use of this non-invasive acoustic transmission technique. This non-invasive method is suitable for monitoring changes in tendon properties as predictors of athletic performance, injury or therapeutic progression.

Predicting fitness for chemotherapy in older cancer patients

Background: The Vulnerable Elders Survey-13 (VES-13) is increasingly used to screen for older patients who can proceed to intensive chemotherapy without further comprehensive assessment. This study compared the VES-13 determination of fitness for treatment with the oncologist's assessments of fitness. Method: Sample: Consecutive series of solid tumour patients ≥65 years (n=175; M=72; range=65-86) from an Australian cancer centre. Patients were screened with the VES-13 before proceeding to usual treatment. Blinded to screening, oncologists concurrently predicted patient fitness for chemotherapy. A sample of 175 can detect, with 90% power, kappa coefficients of agreement between VES-13 and oncologists’ assessments >0.90 ("almost perfect agreement"). Separate backward stepwise logistic regression analyses assessed potential predictors of VES-13 and oncologists’ ratings of fitness. Results: Kappa coefficient for agreement between VES-13 and oncologists’ ratings of fitness was 0.41 (p<0.001). VES-13 and oncologists’ assessments agreed in 71% of ratings. VES-13 sensitivity = 83.3%; specificity = 57%; positive predictive value = 69%; negative predictive value = 75%. Logistic regression modelling indicated that the odds of being vulnerable to chemotherapy (VES-13) increased with increasing depression (OR=1.42; 95% CI: 1.18, 1.71) and decreased with increased functional independence assessed on the Bartel Index (OR=0.82; CI: 0.74, 0.92) and Lawton instrumental activities of daily living (OR=0.44; CI: 0.30, 0.65); RSquare=.65. Similarly, the odds of a patient being vulnerable to chemotherapy, when assessed by physicians, increased with increasing age (OR=1.15; CI: 1.07, 1.23) and depression (OR=1.23; CI: 1.06, 1.43), and decreased with increasing functional independence (OR=0.91; CI: 0.85, 0.98); RSquare=.32. Conclusions: Our data indicate moderate agreement between VES-13 and clinician assessments of patients’ fitness for chemotherapy. Current ‘one-step’ screening processes to determine fitness have limits. Nonetheless, screening tools do have the potential for modification and enhanced predictive properties in cancer care by adding relevant items, thus enabling fit patients to be immediately referred for chemotherapy.