Changes in plasma levels of N-arachidonoyl ethanolamine and N-palmitoylethanolamine following bariatric surgery in morbidly obese females with impaired glucose homeostasis

Aim: We examined endocannabinoids (ECs) in relation to bariatric surgery and the association between plasma ECs and markers of insulin resistance. Methods: A study of 20 participants undergoing bariatric surgery. Fasting and 2-hour plasma glucose, lipids, insulin, and C-peptide were recorded preoperatively and 6 months postoperatively with plasma ECs (AEA, 2-AG) and endocannabinoid-related lipids (PEA, OEA). Results: Gender-specific analysis showed differences in AEA, OEA, and PEA preoperatively with reductions in AEA and PEA in females postoperatively. Preoperatively, AEA was correlated with 2-hour glucose (r = 0.55, P = 0.01), HOMA-IR (r = 0.61, P = 0.009), and HOMA %S (r = -0.71, P = 0.002). OEA was correlated with weight (r = 0.49, P = 0.03), waist circumference (r = 0.52, P = 0.02), fasting insulin (r = 0.49, P = 0.04), and HOMA-IR (r = 0.48, P = 0.05). PEA was correlated with fasting insulin (r = 0.49, P = 0.04). 2-AG had a negative correlation with fasting glucose (r = -0.59, P = 0.04). Conclusion: Gender differences exist in circulating ECs in obese subjects. Females show changes in AEA and PEA after bariatric surgery. Specific correlations exist between different ECs and markers of obesity and insulin and glucose homeostasis

Comparison of Parkinson’s Disease Patients’ Characteristics by Indication for Deep Brain Stimulation: Men Are More Likely to Have DBS for Tremor

Background: We investigated whether the characteristics of Parkinson’s disease (PD) patients differ based on the primary indication for deep brain stimulation (DBS). Methods: We reviewed data for 149 consecutive PD patients who underwent DBS at the University of Virginia. Patients were categorized based on primary surgical indication, and clinical characteristics were compared between groups. Results: Twenty-nine (93.5%) of 31 PD patients who underwent DBS for medication refractory tremor were men, and 66 (62.3%) of 106 PD patients who underwent DBS for motor fluctuations were men (p = 0.001). Other primary indications for DBS were tremor and fluctuations (n = 5), medication intolerance (n = 5), and dystonia (n = 2). Discussion: Patients who underwent DBS for medication refractory tremor were predominantly men, while patients who had DBS for motor fluctuations approximated the gender distribution of PD. Possible explanations are that men with PD are more likely to develop medication refractory tremor or undergo surgery for medication refractory tremor in PD compared to women

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment