293 research outputs found
Frequency Shift of Carbon-Nanotube-Based Mass Sensor Using Nonlocal Elasticity Theory
The frequency equation of carbon-nanotube-based cantilever sensor with an attached mass is derived analytically using nonlocal elasticity theory. According to the equation, the relationship between the frequency shift of the sensor and the attached mass can be obtained. When the nonlocal effect is not taken into account, the variation of frequency shift with the attached mass on the sensor is compared with the previous study. According to this study, the result shows that the frequency shift of the sensor increases with increasing the attached mass. When the attached mass is small compared with that of the sensor, the nonlocal effect is obvious and increasing nonlocal parameter decreases the frequency shift of the sensor. In addition, when the location of the attached mass is closer to the free end, the frequency shift is more significant and that makes the sensor reveal more sensitive. When the attached mass is small, a high sensitivity is obtained
Findings in young adults at colonoscopy from a hospital service database audit
Background: Colorectal cancer (CRC) diagnosed at <50 years is predominantly located in the distal colon and rectum. Little is known about which lesion subtypes may serve as CRC precursors in young adults. The aim of this work was to document the prevalence and histological subtype of lesions seen in patients aged <50 years, and any associated clinical features. Methods: An audit of the colonoscopy database at The Queen Elizabeth Hospital in Adelaide, South Australia over a 12-month period was undertaken. Findings were recorded from both colonoscopy reports and corresponding histological examination of excised lesions. Results: Data were extracted from colonoscopies in 2064 patients. Those aged <50 comprised 485 (24%) of the total. CRC precursor lesions (including sessile serrated adenoma/polyps (SSA/P), traditional serrated adenomas, tubular adenomas ≥10 mm or with high-grade dysplasia, and conventional adenomas with villous histology) were seen in 4.3% of patients aged <50 and 12.9% of patients aged ≥50 (P <0.001). Among colonoscopies yielding CRC precursor lesions in patients under 50 years, SSA/P occurred in 52% of procedures (11/21), compared with 27% (55/204) of procedures in patients aged 50 and older (P = 0.02). SSA/P were proximally located in (10/11) 90% of patients aged under 50, and 80% (43/54) of those aged 50 and older (P = 0.46). Conclusions: SSA/P were the most frequently observed CRC precursor lesions in patients aged <50. Most CRCs in this age group are known to arise in the distal colon and rectum suggesting that lesions other than SSA/P may serve as the precursor for the majority of early-onset CRC.Stephanie Wong, Ilmars Lidums, Christophe Rosty, Andrew Ruszkiewicz, Susan Parry, Aung Ko Win, Yoko Tomita, Sina Vatandoust, Amanda Townsend, Dainik Patel, Jennifer E. Hardingham, David Roder, Eric Smith, Paul Drew, Julie Marker, Wendy Uylaki, Peter Hewett, Daniel L. Worthley, Erin Symonds, Graeme P. Young, Timothy J. Price and Joanne P. Youn
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Testing for Gene-Environment Interactions Using a Prospective Family Cohort Design: Body Mass Index in Early and Later Adulthood and Risk of Breast Cancer
The ability to classify people according to their underlying genetic susceptibility to a disease is increasing with new knowledge, better family data, and more sophisticated risk prediction models, allowing for more effective prevention and screening. To do so, however, we need to know whether risk associations are the same for people with different genetic susceptibilities. To illustrate one way to estimate such gene-environment interactions, we used prospective data from 3 Australian family cancer cohort studies, 2 enriched for familial risk of breast cancer. There were 288 incident breast cancers in 9,126 participants from 3,222 families. We used Cox proportional hazards models to investigate whether associations of breast cancer with body mass index (BMI; weight (kg)/height (m) ) at age 18–21 years, BMI at baseline, and change in BMI differed according to genetic risk based on lifetime breast cancer risk from birth, as estimated by BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) software, adjusted for age at baseline data collection. Although no interactions were statistically signifi- cant, we have demonstrated the power with which gene-environment interactions can be investigated using a cohort enriched for persons with increased genetic risk and a continuous measure of genetic risk based on family history.The Australian Breast Cancer Family Registry (ABCFR) was supported in Australia by the National Health and Medical Research Council, the New South Wales Cancer Council, the Victorian Health Promotion Foundation, the Victorian Breast Cancer Research Consortium, Cancer Australia, and the National Breast Cancer Foundation. The ABCFR was also supported by the National Cancer Institute, US National Institutes of Health, under Request for Application CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry: the University of Melbourne (Melbourne, Victoria, Australia) (grant U01 CA69638); the Fox Chase Cancer Center (Philadelphia, Pennsylvania) (grant U01 CA69631); the Huntsman Cancer Institute (Salt Lake City, Utah) (grant U01 CA69446); Columbia University (New York, New York) (grant U01 CA69398); the Cancer Prevention Institute of California (Fremont, California) (grant U01 CA69417); and Cancer Care Ontario (Toronto, Ontario, Canada) (grant U01 CA69467). The Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) was supported by a grant from the Australian National Breast Cancer Foundation and previously by the National Health and Medical Research Council, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia. The Australasian Colorectal Cancer Family Registry (ACCFR) was supported by grant UM1 CA167551 from the National Cancer Institute, US National Institutes of Health, and through cooperative agreements with the members and Principal Investigators of the ACCFR (grants U01 CA074778 and U01/U24 CA097735). A.K.W. is a National Health and Medical Research Council Early Career Fellow. M.A.J. is a National Health and Medical Research Council Senior Research Fellow. K.A.P. is an Australian National Breast Cancer Foundation Fellow
Randomised double-blind trial of megestrol acetate vs placebo in treatment-naive advanced hepatocellular carcinoma
10.1038/bjc.2011.333British Journal of Cancer1057945-952BJCA
Risk prediction tools for cancer in primary care.
Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an 'area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.This is the final version of the article. It was first available from NPG via http://dx.doi.org/10.1038/bjc.2015.40
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