Search

BackgroundSocial networks play an important role in smoking. Provision of social support during cessation is a cornerstone of treatment. Online social networks for cessation are ubiquitous and represent a promising modality for smokers to receive and provide the support necessary for cessation. There are no existing measures specific to online social support for smoking cessation. ObjectiveThe objective was to develop a measure of social support to be used in online smoking cessation treatment research. MethodsInitial items for the Online Social Support for Smokers Scale (OS4) were based on existing theory and scales delineated in various taxonomies. Preliminary field analysis (N = 73) was conducted on 23 initial items to optimize the scale. Further development was conducted on a refined 15-item scale in the context of a large randomized trial of Internet and telephone cessation treatment with follow-ups at 3, 6, 12, and 18 months. In all, 1326 participants were randomized to an enhanced Internet arm that included a large online social network; psychometric analyses employed 3-month follow-up data from those reporting use of the enhanced Internet intervention at least once (n = 873). Items were subjected to a factor analysis, and the internal consistency reliability of the scale was examined along with construct and criterion validity. Other measures used in the study included demographics, nicotine dependence, partner support for cessation, general social support, social integration, stress, depression, health status, online community use, Internet use behaviors, intervention satisfaction, and 30-day point prevalence abstinence. ResultsThe final 12-item OS4 scale demonstrated high internal consistency reliability (Cronbach alphas .86-.89) across demographic and smoking strata of interest. The OS4 also demonstrated good construct and criterion validity, with the directionality of the observed associations providing support for most a priori hypotheses. Significant Pearson correlations were observed between the OS4 and the Partner Interaction Questionnaire (PIQ) Positive subscale (ρ = .24, P < .001). As hypothesized, participants with the highest OS4 scores were more likely to have actively participated in the enhanced Internet community and to have high levels of satisfaction with the enhanced Internet intervention. In logistic regression analyses, the OS4 was highly predictive of 30-day point-prevalence abstinence at 6, 12, and 18 months (all P values

We evaluated the associations of subjective (self-reported everyday cognition [ECog]) and objective cognitive measures with regional amyloid-β (Aβ) and tau accumulation in 86 clinically normal elderly subjects from the Alzheimer's Disease Neuroimaging Initiative. Regression analyses were conducted to identify whether individual ECog domains (Memory, Language, Organization, Planning, Visuospatial, and Divided Attention) were equally or differentially associated with regional [18F]florbetapir and [18F]flortaucipir uptake and how these associations compared to those obtained with objective cognitive measures. A texture analysis, the weighted 2-point correlation, was used as an additional approach for estimating the whole-brain tau burden without positron emission tomography intensity normalization. Although the strongest models for ECog domains included either tau (planning and visuospatial) or Aβ (memory and organization), the strongest models for all objective measures included Aβ. In Aβ-negative participants, the strongest models for all ECog domains of executive functioning included tau. Our results indicate differential associations of individual subjective cognitive domains with Aβ and tau in clinically normal adults. Detailed characterization of ECog may render a valuable prescreening tool for pathological prediction.

Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC) into estimating FC. In our proposed approach, SC based on DTI data is used to construct an informative prior for FC based on resting-state fMRI data through the Cholesky decomposition. Simulation studies showed that incorporating the two data produced significantly reduced mean squared errors compared to the standard approach of separately analyzing the two data from different modalities. We applied our model to analyze the resting state DTI and fMRI data collected to estimate FC between the brain regions that were hypothetically important in the origination and spread of temporal lobe epilepsy seizures. Our analysis concludes that the proposed model achieves smaller false positive rates and is much robust to data decimation compared to the conventional approach.

The endocrine and exocrine compartments of the pancreas are spatially related but functionally distinct. Multiple diseases affect both compartments, including type 1 diabetes (T1D), pancreatitis, cystic fibrosis, and pancreatic cancer. To better understand how the exocrine pancreas changes with age, obesity, and diabetes, we performed a systematic analysis of well-preserved tissue sections from the pancreatic head, body, and tail of organ donors with T1D (n = 20) or type 2 diabetes (T2D) (n = 25) and donors with no diabetes (ND; n = 74). Among ND donors, we found that the incidence of acinar-to-ductal metaplasia (ADM), angiopathy, and pancreatic adiposity increased with age, and ADM and adiposity incidence also increased with BMI. Compared with age- and sex-matched ND organs, T1D pancreata had greater rates of acinar atrophy and angiopathy, with fewer intralobular adipocytes. T2D pancreata had greater rates of ADM and angiopathy and a higher total number of T lymphocytes, but no difference in adipocyte number, compared with ND organs. Although total pancreatic fibrosis was increased in both T1D and T2D, the patterns were different, with periductal and perivascular fibrosis occurring more frequently in T1D pancreata and lobular and parenchymal fibrosis occurring more frequently in T2D. Thus, the exocrine pancreas undergoes distinct changes as individuals age or develop T1D or T2D. Article Highlights: We performed a systematic histologic analysis of 119 well-preserved pancreata from deceased organ donors: 74 without diabetes, 20 with type 1 diabetes, and 25 with type 2 diabetes. In donors without diabetes, patterns of pancreatic metaplasia, angiopathy, fibrosis, and adiposity varied across a broad range of ages and BMIs. In type 1 diabetes, the pancreata had greater rates of acinar atrophy, ductal/vascular fibrosis, and angiopathy, with less frequent adiposity, compared with age- and sex-matched control donors. In type 2 diabetes, there were greater rates of acinar-to-ductal metaplasia, lobular fibrosis, and angiopathy, with no change in pancreatic adipocyte number. The pancreata in type 2 diabetes also had a minimally higher number of exocrine T lymphocytes, with no change in exocrine endothelial cell or macrophage number. [ABSTRACT FROM AUTHOR]

BackgroundSemiquantitative methods such as the standardized uptake value ratio (SUVR) require normalization of the radiotracer activity to a reference tissue to monitor changes in the accumulation of amyloid-β (Aβ) plaques measured with positron emission tomography (PET). The objective of this study was to evaluate the effect of reference tissue normalization in a test-retest (18)F-florbetapir SUVR study using cerebellar gray matter, white matter (two different segmentation masks), brainstem, and corpus callosum as reference regions.MethodsWe calculated the correlation between (18)F-florbetapir PET and concurrent cerebrospinal fluid (CSF) Aβ1-42 levels in a late mild cognitive impairment cohort with longitudinal PET and CSF data over the course of 2 years. In addition to conventional SUVR analysis using mean and median values of normalized brain radiotracer activity, we investigated a new image analysis technique-the weighted two-point correlation function (wS2)-to capture potentially more subtle changes in Aβ-PET data.ResultsCompared with the SUVRs normalized to cerebellar gray matter, all cerebral-to-white matter normalization schemes resulted in a higher inverse correlation between PET and CSF Aβ1-42, while the brainstem normalization gave the best results (high and most stable correlation). Compared with the SUVR mean and median values, the wS2 values were associated with the lowest coefficient of variation and highest inverse correlation to CSF Aβ1-42 levels across all time points and reference regions, including the cerebellar gray matter.ConclusionsThe selection of reference tissue for normalization and the choice of image analysis method can affect changes in cortical (18)F-florbetapir uptake in longitudinal studies.

OBJECTIVE: This multicenter prospective cohort study compared pancreas volume as assessed by MRI, metabolic scores derived from oral glucose tolerance testing (OGTT), and a combination of pancreas volume and metabolic scores for predicting progression to stage 3 type 1 diabetes (T1D) in individuals with multiple diabetes-related autoantibodies. RESEARCH DESIGN AND METHODS: Pancreas MRI was performed in 65 multiple autoantibody-positive participants enrolled in the Type 1 Diabetes TrialNet Pathway to Prevention study. Prediction of progression to stage 3 T1D was assessed using pancreas volume index (PVI), OGTT-derived Index60 score and Diabetes Prevention Trial–Type 1 Risk Score (DPTRS), and a combination of PVI and DPTRS. RESULTS: PVI, Index60, and DPTRS were all significantly different at study entry in 11 individuals who subsequently experienced progression to stage 3 T1D compared with 54 participants who did not experience progression (P < 0.005). PVI did not correlate with metabolic testing across individual study participants. PVI declined longitudinally in the 11 individuals diagnosed with stage 3 T1D, whereas Index60 and DPTRS increased. The area under the receiver operating characteristic curve for predicting progression to stage 3 from measurements at study entry was 0.76 for PVI, 0.79 for Index60, 0.79 for DPTRS, and 0.91 for PVI plus DPTRS. CONCLUSIONS: These findings suggest that measures of pancreas volume and metabolism reflect distinct components of risk for developing stage 3 type 1 diabetes and that a combination of these measures may provide superior prediction than either alone. [ABSTRACT FROM AUTHOR]