Current trends in the etiology and diagnosis of HPV-related head and neck cancers

Human papilloma virus (HPV) infection is a major risk factor for a distinct subset of head and neck squamous cell carcinoma (HNSCC). The current review summarizes the epidemiology of HNSCC and the disease burden, the infectious cycle of HPV, the roles of viral oncoproteins, E6 and E7, and the downstream cellular events that lead to malignant transformation. Current techniques for the clinical diagnosis of HPV-associated HNSCC will also be discussed, that is, the detection of HPV DNA, RNA, and the HPV surrogate marker, p16 in tumor tissues, as well as HPV-specific antibodies in serum. Such methods do not allow for the early detection of HPV-associated HNSCC and most cases are at an advanced stage upon diagnosis. Novel noninvasive approaches using oral fluid, a clinically relevant biological fluid, allow for the detection of HPV and cellular alterations in infected cells, which may aid in the early detection and HPV-typing of HNSCC tumors. Noninvasive diagnostic methods will enable early detection and intervention, leading to a significant reduction in mortality and morbidity associated with HNSCC.

What triggers problem recognition? An exploration on young Australian male problematic online gamers

Help-seeking is a complex decision-making process that first begins with problem recognition. However, little is understood about the conceptualisation of the helpseeking process and the triggers of problem recognition. This research proposes the use of the Critical Incident Technique (CIT) to examine and classify incidents that serve as key triggers of problem recognition among young Australian male problematic online gamers. The research provides a classification of five different types of triggers that will aid social marketers into developing effective early detection, prevention and treatment focused social marketing interventions.

Incidence and mortality of female breast cancer in the Asia-Pacific region

Objective: To provide an overview of the incidence and mortality of female breast cancer for countries in the Asia-Pacific region. Methods: Statistical information about breast cancer was obtained from publicly available cancer registry and mortality databases (such as GLOBOCAN), and supplemented with data requested from individual cancer registries. Rates were directly age-standardised to the Segi World Standard population and trends were analysed using joinpoint models. Results: Breast cancer was the most common type of cancer among females in the region, accounting for 18% of all cases in 2012, and was the fourth most common cause of cancer-related deaths (9%). Although incidence rates remain much higher in New Zealand and Australia, rapid rises in recent years were observed in several Asian countries. Large increases in breast cancer mortality rates also occurred in many areas, particularly Malaysia and Thailand, in contrast to stabilising trends in Hong Kong and Singapore, while decreases have been recorded in Australia and New Zealand. Mortality trends tended to be more favourable for women aged under 50 compared to those who were 50 years or older. Conclusion: It is anticipated that incidence rates of breast cancer in developing countries throughout the Asia-Pacific region will continue to increase. Early detection and access to optimal treatment are the keys to reducing breast cancer-related mortality, but cultural and economic obstacles persist. Consequently, the challenge is to customise breast cancer control initiatives to the particular needs of each country to ensure the best possible outcomes.

Current research: Neurocognitive risk assessment

The current research began from the starting point that what we are grappling with when we are dealing with violent extremists by and large is essentially ‘normal people’. What follows in this third major section of this research paper is the theoretical and conceptual search for making researchable the following question: ‘How do you assess someone who is normal?’

Evaluation of a skin self examination attitude scale using an item response theory model approach

Introduction The Skin Self-Examination Attitude Scale (SSEAS) is a brief measure that allows for the assessment of attitudes in relation to skin self-examination. This study evaluated the psychometric properties of the SSEAS using Item Response Theory (IRT) methods in a large sample of men ≥ 50 years in Queensland, Australia. Methods A sample of 831 men (420 intervention and 411 control) completed a telephone assessment at the 13-month follow-up of a randomized-controlled trial of a video-based intervention to improve skin self-examination (SSE) behaviour. Descriptive statistics (mean, standard deviation, item–total correlations, and Cronbach’s alpha) were compiled and difficulty parameters were computed with Winsteps using the polytomous Rasch Rating Scale Model (RRSM). An item person (Wright) map of the SSEAS was examined for content coverage and item targeting. Results The SSEAS have good psychometric properties including good internal consistency (Cronbach’s alpha = 0.80), fit with the model and no evidence for differential item functioning (DIF) due to experimental trial grouping was detected. Conclusions The present study confirms the SSEA scale as a brief, useful and reliable tool for assessing attitudes towards skin self-examination in a population of men 50 years or older in Queensland, Australia. The 8-item scale shows unidimensionality, allowing levels of SSE attitude, and the item difficulties, to be ranked on a single continuous scale. In terms of clinical practice, it is very important to assess skin cancer self-examination attitude to identify people who may need a more extensive intervention to allow early detection of skin cancer.

Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications PREFACE

Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

In vivo mri-based estimation of time-dependent elastic modulus in healthy arteries

The elastic properties of the arterial wall have been the subject of physiological, clinical and biomedical research for many years. There is convincing evidence that the elastic properties of the large arteries are seriously impaired in the presence of cardiovascular disease (CVD), due to alterations in the intrinsic structural and functional characteristics of vessels [1]. Early detection of changes in the elastic modulus of arteries would provide a powerful tool for both monitoring patients at high cardiovascular risk and testing the effects of pharmaceuticals aimed at stabilizing existing plaques by stiffening them or lowering the lipids.

In vivo non-invasive high resolution MR-based method for the determination of the elastic modulus of arterial vessels

The mechanical properties of arterial walls have long been recognized to play an essential role in the development and progression of cardiovascular disease (CVD). Early detection of variations in the elastic modulus of arteries would help in monitoring patients at high cardiovascular risk stratifying them according to risk. An in vivo, non-invasive, high resolution MR-phase-contrast based method for the estimation of the time-dependent elastic modulus of healthy arteries was developed, validated in vitro by means of a thin walled silicon rubber tube integrated into an existing MR-compatible flow simulator and used on healthy volunteers. A comparison of the elastic modulus of the silicon tube measured from the MRI-based technique with direct measurements confirmed the method's capability. The repeatability of the method was assessed. Viscoelastic and inertial effects characterizing the dynamic response of arteries in vivo emerged from the comparison of the pressure waveform and the area variation curve over a period. For all the volunteers who took part in the study the elastic modulus was found to be in the range 50-250 kPa, to increase during the rising part of the cycle, and to decrease with decreasing pressure during the downstroke of systole and subsequent diastole.

An effective, economic way of monitoring menstrual cycle hormones in at risk female athletes

PURPOSE: Female athletes, in response to intensive training, competition stress and a lean, athletic physique, are at increased risk of altered hypothalamic-pituitary ovarian (HPO) axis function associated with menstrual cycle disturbance and reduced secretion of the ovarian hormones estrogen and progesterone. Because there is evidence suggesting possible detrimental effects on skeletal health associated with deficiencies in these hormones, a suitable means to asses ovarian hormone concentrations in at risk athletes is needed. The aim of this study was to evaluate a simple, economical means to monitor the ovarian hormone production in athletes, in the setting of intensive training. METHODS: Subjects comprised 14 adolescent rowers, 12 lightweight rowers, and two groups of 10 matched control subjects. Ovarian function was monitored during the competition season by estimation of urinary excretion of estrone glucuronide (E1G) and pregnanediol glucuronide (PdG), enabling the menstrual cycles to be classified as ovulatory or anovulatory. RESULTS: Results indicated 35% and 75% of schoolgirl and lightweight rowers had anovulatory menstrual cycles, respectively. These findings were highlighted by significantly lower excretion of E1G and PdG during phases of intensive training in both the lightweight and schoolgirl rowers, compared with the control subjects. CONCLUSION: It was concluded that the urinary E1G and PdG assays were an effective means to assess the influence of intense training on ovarian hormone concentrations in at risk athletes. It is recommended that this technique be applied more widely as a means of early detection of athletes with low estrogen and progesterone levels, in an attempt to avoid detrimental influences on skeletal health.

The current status of heart failure diagnostic biomarkers

Heart failure (HF) affects approximately 23 million individuals worldwide and this number is increasing, due to an aging and growing population. Early detection of HF is crucial in the management of this debilitating disease. Current diagnostic methods for HF rely heavily on clinical imaging techniques and blood analysis, which makes them less than ideal for population-based screening purposes. Studies focusing on developing novel biomarkers for HF have utilized various techniques and biological fluids, including urine and saliva. Promising results from these studies imply that these body fluids can be used in evaluating the clinical manifestation of HF and will one day be integrated into a clinical workflow and facilitate HF management.

Mediation of improvements in sun protective and skin self-examination behaviours: Results from the healthy text study

Objective Melanoma is on the rise, especially in Caucasian populations exposed to high ultraviolet radiation such as in Australia. This paper examined the psychological components facilitating change in skin cancer prevention or early detection behaviours following a text message intervention. Methods The Queensland-based participants were 18 to 42 years old, from the Healthy Text study (N = 546). Overall, 512 (94%) participants completed the 12-month follow-up questionnaires. Following the social cognitive model, potential mediators of skin self-examination (SSE) and sun protection behaviour change were examined using stepwise logistic regression models. Results At 12-month follow-up, odds of performing an SSE in the past 12 months were mediated by baseline confidence in finding time to check skin (an outcome expectation), with a change in odds ratio of 11.9% in the SSE group versus the control group when including the mediator. Odds of greater than average sun protective habits index at 12-month follow-up were mediated by (a) an attempt to get a suntan at baseline (an outcome expectation) and (b) baseline sun protective habits index, with a change in odds ratio of 10.0% and 11.8%, respectively in the SSE group versus the control group. Conclusions Few of the suspected mediation pathways were confirmed with the exception of outcome expectations and past behaviours. Future intervention programmes could use alternative theoretical models to elucidate how improvements in health behaviours can optimally be facilitated.

Diagnostic values for skin temperature assessment to detect diabetes-related foot complications

Background Skin temperature assessment is a promising modality for early detection of diabetic foot problems, but its diagnostic value has not been studied. Our aims were to investigate the diagnostic value of different cutoff skin temperature values for detecting diabetes-related foot complications such as ulceration, infection, and Charcot foot and to determine urgency of treatment in case of diagnosed infection or a red-hot swollen foot. Materials and Methods The plantar foot surfaces of 54 patients with diabetes visiting the outpatient foot clinic were imaged with an infrared camera. Nine patients had complications requiring immediate treatment, 25 patients had complications requiring non-immediate treatment, and 20 patients had no complications requiring treatment. Average pixel temperature was calculated for six predefined spots and for the whole foot. We calculated the area under the receiver operating characteristic curve for different cutoff skin temperature values using clinical assessment as reference and defined the sensitivity and specificity for the most optimal cutoff temperature value. Mean temperature difference between feet was analyzed using the Kruskal–Wallis tests. Results The most optimal cutoff skin temperature value for detection of diabetes-related foot complications was a 2.2°C difference between contralateral spots (sensitivity, 76%; specificity, 40%). The most optimal cutoff skin temperature value for determining urgency of treatment was a 1.35°C difference between the mean temperature of the left and right foot (sensitivity, 89%; specificity, 78%). Conclusions Detection of diabetes-related foot complications based on local skin temperature assessment is hindered by low diagnostic values. Mean temperature difference between two feet may be an adequate marker for determining urgency of treatment.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Examination of EXOSC4 as a new prognostic marker and a novel therapeutic avenue in lung adenocarcinoma

Although prevention and early detection of the disease greatly improved over the past few years, lung cancer remains the leading cause of cancer deaths. In order to be able to treat a larger population, we are in urgent need for novel treatments. While it is known that DNA repair genes play a major role in the oncogenic transformation, they also represent a weakness of cancers that constitute a therapeutic opportunity. To identify novel DNA repair genes implicated in Lung cancers, we conducted an in silico investigation to identify genes co-regulated with two DNA repair factors, BRCA2 and hSSB1. This approach allowed for the identification of EXOSC4, a component of the RNA Exosome machinery, as a potential factor involved in the maintenance of genome stability and that is deregulated in lung cancer.