"Cancer 2015": a prospective, population-based cancer cohort-phase 1: feasibility of genomics-guided precision medicine in the clinic

"Cancer 2015" is a longitudinal and prospective cohort. It is a phased study whose aim was to pilot recruiting 1000 patients during phase 1 to establish the feasibility of providing a population-based genomics cohort. Newly diagnosed adult patients with solid cancers, with residual tumour material for molecular genomics testing, were recruited into the cohort for the collection of a dataset containing clinical, molecular pathology, health resource use and outcomes data. 1685 patients have been recruited over almost 3 years from five hospitals. Thirty-two percent are aged between 61-70 years old, with a median age of 63 years. Diagnostic tumour samples were obtained for 90% of these patients for multiple parallel sequencing. Patients identified with somatic mutations of potentially "actionable" variants represented almost 10% of those tumours sequenced, while 42% of the cohort had no mutations identified. These genomic data were annotated with information such as cancer site, stage, morphology, treatment and patient outcomes and health resource use and cost. This cohort has delivered its main objective of establishing an upscalable genomics cohort within a clinical setting and in phase 2 aims to develop a protocol for how genomics testing can be used in real-time clinical decision-making, providing evidence on the value of precision medicine to clinical practice.

Cancer 2015: a longitudinal whole-of-system study of genomic cancer medicine

Genomic cancer medicine promises revolutionary change in oncology. The impacts of 'personalized medicine', based upon a molecular classification of cancer and linked to targeted therapies, will extend from individual patient outcomes to the health economy at large. To address the 'whole-of-system' impact of genomic cancer medicine, we have established a prospective cohort of patients with newly diagnosed cancer in the state of Victoria, Australia, about whom we have collected a broad range of clinical, demographic, molecular, and patient-reported data, as well as data on health resource utilization. Our goal is to create a model for investigating public investment in genomic medicine that maximizes the cost:benefit ratio for the Australian community at large.

Complementary medicine use among people living with HIV/AIDS in Victoria, Australia: practices, attitudes and perceptions

There is limited evidence suggesting the underlying reasons for the use of complementary and alternative medicines (CAMs) by people with HIV/AIDS, or individual attitudes and beliefs about the use of CAMs. Using focus groups and a survey with 151 individuals attending the HIV Clinics at The Alfred Hospital, Melbourne, we aimed to provide insights into factors that influence the use of CAMs among people living with HIV/AIDS. Roughly half (49%) of the participants had used CAMs to manage their HIV/AIDs. Users of CAMs utilized a wide range of treatments in managing their condition, but costs of the CAMs meant that users were not necessarily able to use them as much as they might have liked. Use of CAMs was based on a desire to find something beneficial rather than on being dissatisfied with conventional medicine. Further research is needed into (a) the effects of CAMs and (b) the enhancement of communication and collaboration between patients, doctors and complementary medicine practitioners.

Response to Islamophobia in the Arabic Islamic discourse: a critical discourse analysis

In the aftermath of September 11, Muslim scholars made numerous attempts to explain Islamophobia from the Islamic perspective; they presented arguments that are not addressed in the Western narrative. Two texts in Arabic by the prominent Muslim preacher, Mohammad Hassan and by the Muslim orator Fadhel Sliman are analysed from a Critical Discourse Analysis (CDA) viewpoint. This analysis aims to demonstrate how language is inextricably linked with ideology. This paper demonstrates that textual strategies in the Arabic Islamic discourse and their ideological implications show distinct characteristics some of which add to the present literature on discourse. The aim of the chosen texts is to educate and create solidarity between the speakers and the audience in fighting Islamophobia. The reliance of the speakers on tactics such as quoting from the Holy Qur’ān and ḥadīth to defend Islam, and choice of words and sentence structures may instigate discussions about the persuasive power of the Arabic Islamic narrative.

Barriers and enablers to healthcare access and use among Arabic-speaking and Caucasian English-speaking patients with type 2 diabetes mellitus: a qualitative comparative study

OBJECTIVE: The objective of this study was to explore the decision-making processes and associated barriers and enablers that determine access and use of healthcare services in Arabic-speaking and English-speaking Caucasian patients with diabetes in Australia. STUDY SETTING AND DESIGN: Face-to-face semistructured individual interviews and group interviews were conducted at various healthcare settings-diabetes outpatient clinics in 2 tertiary referral hospitals, 6 primary care practices and 10 community centres in Melbourne, Australia. PARTICIPANTS: A total of 100 participants with type 2 diabetes mellitus were recruited into 2 groups: 60 Arabic-speaking and 40 English-speaking Caucasian. DATA COLLECTION: Interviews were audio-taped, translated into English when necessary, transcribed and coded thematically. Sociodemographic and clinical information was gathered using a self-completed questionnaire and medical records. PRINCIPAL FINDINGS: Only Arabic-speaking migrants intentionally delayed access to healthcare services when obvious signs of diabetes were experienced, missing opportunities to detect diabetes at an early stage. Four major barriers and enablers to healthcare access and use were identified: influence of significant other(s), unique sociocultural and religious beliefs, experiences with healthcare providers and lack of knowledge about healthcare services. Compared with Arabic-speaking migrants, English-speaking participants had no reluctance to access and use medical services when signs of ill-health appeared; their treatment-seeking behaviours were straightforward. CONCLUSIONS: Arabic-speaking migrants appear to intentionally delay access to medical services even when symptomatic. Four barriers to health services access have been identified. Tailored interventions must be developed for Arabic-speaking migrants to improve access to available health services, facilitate timely diagnosis of diabetes and ultimately to improve glycaemic control.

Co-encapsulation and characterisation of omega-3 fatty acids and probiotic bacteria in whey protein isolate-gum Arabic complex coacervates

Omega-3 fatty acids and probiotic bacteria were co-encapsulated in a single whey protein isolate (WPI)-gum Arabic (GA) complex coacervate microcapsule. Tuna oil (O) and Lactobacillus casei 431 (P) were used as models of omega-3 and probiotic bacteria, respectively. The co-microcapsules (WPI-P-O-GA) and L.casei containing microcapsules (WPI-P-GA) were converted into powder by using spray and freeze drying. The viability of L.casei was significantly higher in WPI-P-O-GA co-microcapsules than in WPI-P-GA. The oxidative stability of tuna oil was significantly higher in spray dried co-capsules than in freeze dried ones.

The construction of power in family medicine bedside teaching: a video observation study

INTRODUCTION: Bedside teaching is essential for helping students develop skills, reasoning and professionalism, and involves the learning triad of student, patient and clinical teacher. Although current rhetoric espouses the sharing of power, the medical workplace is imbued with power asymmetries. Power is context-specific and although previous research has explored some elements of the enactment and resistance of power within bedside teaching, this exploration has been conducted within hospital rather than general practice settings. Furthermore, previous research has employed audio-recorded rather than video-recorded observation and has therefore focused on language and para-language at the expense of non-verbal communication and human-material interaction. METHODS: A qualitative design was adopted employing video- and audio-recorded observations of seven bedside teaching encounters (BTEs), followed by short individual interviews with students, patients and clinical teachers. Thematic and discourse analyses of BTEs were conducted. RESULTS: Power is constructed by students, patients and clinical teachers throughout different BTE activities through the use of linguistic, para-linguistic and non-verbal communication. In terms of language, participants construct power through the use of questions, orders, advice, pronouns and medical/health belief talk. With reference to para-language, participants construct power through the use of interruption and laughter. In terms of non-verbal communication, participants construct power through physical positioning and the possession or control of medical materials such as the stethoscope. CONCLUSIONS: Using this paper as a trigger for discussion, we encourage students and clinical teachers to reflect critically on how their verbal and non-verbal communication constructs power in bedside teaching. Students and clinical teachers need to develop their awareness of what power is, how it can be constructed and shared, and what it means for the student-patient-doctor relationship within bedside teaching.

DeepCare: a deep dynamic memory model for predictive medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.