Acceptance Speech, Tikkun Olam Award Ceremony, November 27, 2007

Commissioner Jonathan S. Adelstein has been a member of the United States Federal Communications Commission since 2004. He was honored by the Center for Christian-Jewish Understanding of Sacred Heart University with the Tikkun Olam Award at the Nostra Aetate Awards Ceremony on November 27, 2007, for his humanitarian leadership and advocacy for access to communication services for all Americans

Personality Is Reflected in the Brain's Intrinsic Functional Architecture

Personality describes persistent human behavioral responses to broad classes of environmental stimuli. Investigating how personality traits are reflected in the brain's functional architecture is challenging, in part due to the difficulty of designing appropriate task probes. Resting-state functional connectivity (RSFC) can detect intrinsic activation patterns without relying on any specific task. Here we use RSFC to investigate the neural correlates of the five-factor personality domains. Based on seed regions placed within two cognitive and affective ‘hubs’ in the brain—the anterior cingulate and precuneus—each domain of personality predicted RSFC with a unique pattern of brain regions. These patterns corresponded with functional subdivisions responsible for cognitive and affective processing such as motivation, empathy and future-oriented thinking. Neuroticism and Extraversion, the two most widely studied of the five constructs, predicted connectivity between seed regions and the dorsomedial prefrontal cortex and lateral paralimbic regions, respectively. These areas are associated with emotional regulation, self-evaluation and reward, consistent with the trait qualities. Personality traits were mostly associated with functional connections that were inconsistently present across participants. This suggests that although a fundamental, core functional architecture is preserved across individuals, variable connections outside of that core encompass the inter-individual differences in personality that motivate diverse responses

Transoral resection of pharyngeal cancer: Summary of a National Cancer Institute Head and Neck Cancer Steering Committee Clinical Trials Planning Meeting, November 6–7, 2011, Arlington, Virginia

Recent advances now permit resection of many pharyngeal tumors through the open mouth, an approach that can greatly reduce the morbidity of surgical exposure. These transoral techniques are being rapidly adopted by the surgical community and hold considerable promise. On November 6–7, 2011, the National Cancer Institute sponsored a Clinical Trials Planning Meeting to address how to further investigate the use of transoral surgery, both in the good prognosis human papillomavirus (HPV)–initiated oropharyngeal cancers, and in those with HPV‐unrelated disease. The proceedings of this meeting are summarized. © 2012 Wiley Periodicals, Inc. Head Neck, 2012Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94490/1/23136_ftp.pd

Alterations in anatomic and functional imaging parameters with repeated FDG PET-CT and MRI during radiotherapy for head and neck cancer: a pilot study

Background: The use of imaging to implement on-treatment adaptation of radiotherapy is a promising paradigm but current data on imaging changes during radiotherapy is limited. This is a hypothesis-generating pilot study to examine the changes on multi-modality anatomic and functional imaging during (chemo)radiotherapy treatment for head and neck squamous cell carcinoma (HNSCC). Methods: Eight patients with locally advanced HNSCC underwent imaging including computed tomography (CT), Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)-CT and magnetic resonance imaging (MRI) (including diffusion weighted (DW) and dynamic contrast enhanced (DCE)) at baseline and during (chemo)radiotherapy treatment (after fractions 11 and 21). Regions of interest (ROI) were drawn around the primary tumour at baseline and during treatment. Imaging parameters included gross tumour volume (GTV) assessment, SUVmax, mean ADC value and DCE-MRI parameters including Plasma Flow (PF). On treatment changes and correlations between these parameters were analysed using a Wilcoxon rank sum test and Pearson’s linear correlation coefficient respectively. A p-value <0.05 was considered statistically significant. Results: Statistically significant reductions in GTV-CT, GTV-MRI and GTV-DW were observed between all imaging timepoints during radiotherapy. Changes in GTV-PET during radiotherapy were heterogeneous and non-significant. Significant changes in SUVmax, mean ADC value, Plasma Flow and Plasma Volume were observed between the baseline and the fraction 11 timepoint, whilst only changes in SUVmax between baseline and the fraction 21 timepoint were statistically significant. Significant correlations were observed between multiple imaging parameters, both anatomical and functional; 20 correlations between baseline to the fraction 11 timepoint; 12 correlations between baseline and the fraction 21 timepoints; and 4 correlations between the fraction 11 and fraction 21 timepoints. Conclusions: Multi-modality imaging during radiotherapy treatment demonstrates early changes (by fraction 11) in both anatomic and functional imaging parameters. All functional imaging modalities are potentially complementary and should be considered in combination to provide multi-parametric tumour assessment, to guide potential treatment adaptation strategies. Trial Registration: ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015

A Large Linked Study to Evaluate the Future Burden of Cancer in Australia Attributable to Current Modifiable Behaviours

Introduction The cancer burden preventable through modifications to risk factors can be quantified by calculating their population attributable fractions (PAFs). PAF estimates require large, prospective data to inform risk estimates and contemporary population-based prevalence data to inform the current exposure distributions, including among population subgroups. Objectives and Approach We provide estimates of the preventable future cancer burden in Australia using large linked datasets. We pooled data from seven Australian cohort studies (N=367,058) and linked them to national registries to identify cancers and deaths. We estimated the strength of the associations between behaviours and cancer risk using a proportional hazards model, adjusting for age, sex, study and other behaviours. Exposure prevalence was estimated from contemporary National Health Surveys. We harmonised risk factor data across the data sources, and calculated PAFs and their 95% confidence intervals using a novel method accounting for competing risk of death and risk factor interdependence. Results During the first 10-years follow-up, there were 3,471 incident colorectal cancers, 640 premenopausal and 2,632 postmenopausal breast cancers, 2,025 lung cancers and 22,078 deaths. The leading preventable causes were current smoking (53.7% of lung cancers), body fatness or BMI ≥ 25kg/m2 (11.1% of colorectal cancers, 10.9% of postmenopausal breast cancers), and regular alcohol consumption (12.2% of premenopausal breast cancers). Three in five lung cancers, but only one in four colorectal cancers and one in five breast cancers, were attributable to modifiable factors, when we also considered physical inactivity, dietary and hormonal factors. The burden attributable to modifiable factors was markedly higher in certain population subgroups, including men (colorectal, lung), people with risk factor clustering (colorectal, breast, lung), and individuals with low educational attainment (breast, lung). Conclusion/Implications Estimating PAFs for modifiable risk factors across cancers using contemporary exposure prevalence data can inform timely public health action to improve health and health equity. Testing PAF effect modification may identify population subgroups with the most to gain from programs that support behaviour change and early detection

PDE-based spatial smoothing: a practical demonstration of impacts on MRI brain extraction, tissue segmentation and registration

Spatial smoothing is typically used to denoise magnetic resonance imaging (MRI) data. Gaussian smoothing kernels, associated with heat equations or isotropic diffusion (ISD), are widely adopted for this purpose because of their easy implementation and efficient computation, but despite these advantages, Gaussian smoothing kernels blur the edges, curvature and texture of images. To overcome these issues, researchers have proposed anisotropic diffusion (ASD) and non-local means [i.e., diffusion (NLD)] kernels. However, these new filtering paradigms are rarely applied to MRI analyses. In the current study, using real degraded MRI data, we demonstrated the effect of denoising using ISD, ASD and NLD kernels. Furthermore, we evaluated their impact on three common preprocessing steps of MRI data analysis: brain extraction, segmentation and registration. Results suggest that NLD-based spatial smoothing is most effective at improving the quality of MRI data preprocessing and thus should become the new standard method of smoothing in MRI data processing. (C) 2011 Elsevier Inc. All rights reserved