// +author:j adelstein +author:adelstein 
var _ajax_res = {
  hits: 3,

  first: 0,

  results: [

{userid:"aungkowin", "articletype":"article","pages":"6-13","author":"Joanne P Young, Aung Ko Win, Christophe Rosty, Ingrid Flight, David Roder, Graeme P Young, Oliver Frank, Graeme K Suthers, Peter J Hewett, Andrew Ruszkiewicz, Ehud Hauben, Barbara-Ann Adelstein, Susan Parry, Amanda Townsend, Jennifer E Hardingham, Timothy J Price","year":"2015","title":"Rising incidence of early-onset colorectal cancer in Australia over two decades: report and review.","month":"Jan","journal":"Journal of gastroenterology and hepatology","publisher":"","volume":"30","number":"1","note":"","tags":"Adult,Age Factors,Age of Onset,Aged,Aged, 80 and over,Australia,Colonic Polyps,Colonoscopy,Colorectal Neoplasms,Early Diagnosis,Female,Genetic Predisposition to Disease,Humans,Incidence,Life Style,Male,Mass Screening,Middle Aged,Risk Factors,Time Factors,Young Adult","booktitle":"","editor":"","abstract":"The average age at diagnosis for colorectal cancer (CRC) in Australia is 69, and the age-specific incidence rises rapidly after age 50 years. The incidence has stabilized or is declining in older age groups in Australia during recent decades, possibly related to the increased uptake of screening and high-risk surveillance. In the same time frame, a rising incidence of CRC in younger adults has been well-documented in the United States. This rise in incidence in the young has not been reported from other countries that share long-term exposure to westernised urban lifestyles. Using data from the Australian Institute of Health and Welfare, we examined trends in national incidence rates for CRC under age 50 years and observed that rates in people under age 40 years have been rising for the last two decades. We further performed a review of the literature regarding CRC in young adults to outline the extent of current understanding, explore potential risk factors such as obesity, alcohol, and sedentary lifestyles, and to identify the questions remaining to be addressed. Although absolute numbers might not justify a population screening approach, the dispersal of young adults with CRC across the primary health-care system decreases probability of their recognition. Patient and physician awareness, aided by stool and emerging blood-screening tests and risk profiling tools, have the potential to aid in identification of those young adults who would most benefit from a colonoscopy through early detection of CRCs or by removal of advanced polyps.","address":"","school":"","issn":"1440-1746","doi":"10.1111\/jgh.12792","isi":"","pubmed":"25251195","key":"Young2015","howpublished":"","urllink":"","refid":48,"weight":48}
,

{userid:"xinian.zuo", "articletype":"article","pages":"4734-4739","author":"Bharat B Biswal, Maarten Mennes, Xi-Nian Zuo, Suril Gohel, Clare Kelly, Steve M Smith, Christian F Beckmann, Jonathan S Adelstein, Randy L Buckner, Stan Colcombe, Anne-Marie Dogonowski, Monique Ernst, Damien Fair, Michelle Hampson, Matthew J Hoptman, James S Hyde, Vesa J Kiviniemi, Rolf K\u00f6tter, Shi-Jiang Li, Ching-Po Lin, Mark J Lowe, Clare Mackay, David J Madden, Kristoffer H Madsen, Daniel S Margulies, Helen S Mayberg, Katie McMahon, Christopher S Monk, Stewart H Mostofsky, Bonnie J Nagel, James J Pekar, Scott J Peltier, Steven E Petersen, Valentin Riedl, Serge A R B Rombouts, Bart Rypma, Bradley L Schlaggar, Sein Schmidt, Rachael D Seidler, Greg J Siegle, Christian Sorg, Gao-Jun Teng, Juha Veijola, Arno Villringer, Martin Walter, Lihong Wang, Xu-Chu Weng, Susan Whitfield-Gabrieli, Peter Williamson, Christian Windischberger, Yu-Feng Zang, Hong-Ying Zhang, F Xavier Castellanos, Michael P Milham","year":"2010","title":"Toward discovery science of human brain function.","month":"Mar","journal":"Proc Natl Acad Sci U S A","publisher":"","volume":"107","number":"10","note":"","tags":"Adolescent,Adult,Age Factors,Aged,Algorithms,Analysis of Variance,Brain,Brain Mapping,Female,Humans,Magnetic Resonance Imaging,Male,Middle Aged,Neural Pathways,Sex Factors,Young Adult","booktitle":"","editor":"","abstract":"Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's \"functional connectome.\" Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org\/projects\/fcon_1000\/.","address":"","school":"","issn":"1091-6490","doi":"10.1073\/pnas.0911855107","isi":"","pubmed":"20176931","key":"Biswal2010","howpublished":"","urllink":"http:\/\/www.pnas.org\/content\/107\/10\/4734.full","refid":17,"pdflink":"http:\/\/www.pnas.org\/content\/107\/10\/4734.full.pdf+html"}
,

{userid:"d.s.margulies", "articletype":"article","pages":"4734-9","author":"Bharat B Biswal, Maarten Mennes, Xi-Nian Zuo, Suril Gohel, Clare Kelly, Steve M Smith, Christian F Beckmann, Jonathan S Adelstein, Randy L Buckner, Stan Colcombe, Anne-Marie Dogonowski, Monique Ernst, Damien Fair, Michelle Hampson, Matthew J Hoptman, James S Hyde, Vesa J Kiviniemi, Rolf K\u00f6tter, Shi-Jiang Li, Ching-Po Lin, Mark J Lowe, Clare Mackay, David J Madden, Kristoffer H Madsen, Daniel S Margulies, Helen S Mayberg, Katie McMahon, Christopher S Monk, Stewart H Mostofsky, Bonnie J Nagel, James J Pekar, Scott J Peltier, Steven E Petersen, Valentin Riedl, Serge A R B Rombouts, Bart Rypma, Bradley L Schlaggar, Sein Schmidt, Rachael D Seidler, Greg J Siegle, Christian Sorg, Gao-Jun Teng, Juha Veijola, Arno Villringer, Martin Walter, Lihong Wang, Xu-Chu Weng, Susan Whitfield-Gabrieli, Peter Williamson, Christian Windischberger, Yu-Feng Zang, Hong-Ying Zhang, F Xavier Castellanos, Michael P Milham","year":"2010","title":"Toward discovery science of human brain function","month":"Mar","journal":"Proc Natl Acad Sci U S A","publisher":"","volume":"107","number":"10","note":"","tags":"","booktitle":"","editor":"","abstract":"Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual\u2019s \"functional connectome.\" Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual\u2019s functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org\/projects\/fcon_1000\/.","address":"","school":"","issn":"","doi":"10.1073\/pnas.0911855107","isi":"","pubmed":"","key":"biswal2010a","howpublished":"","urllink":"","refid":197,"weight":197}
  ]
}

;
ajaxResultsLoaded(_ajax_res);