Risk Factors for Progression of Barrett’s Esophagus to High Grade Dysplasia and Esophageal Adenocarcinoma

Barrett’s esophagus (BE) is the only known precursor to esophageal adenocarcinoma (EAC). Methods of identifying BE patients at high risk for progression to high-grade dysplasia (HGD) or EAC are needed to improve outcomes and identify who will benefit most from intensive surveillance or ablative therapy. Clinical predictors of BE progression to HGD or EAC are poorly understood, with multiple contradictory studies. We performed a retrospective study included 460 patients at Johns Hopkins Hospital who underwent at least 2 upper endoscopies 6 months apart showing biopsy-documented BE between 1992 and 2013. Patients with EAC or HGD at the initial endoscopy were excluded. Demographic, clinicopathological, and endoscopic data were collected. Univariate and multivariate Cox proportional hazards analyses with time to progression to HGD and EAC were performed. Among 460 patients included in the study, 132 BE patients ultimately progressed to HGD and 62 developed EAC. Two hundreds and seventy two (272) BE patients did not progress to dysplasia or EAC. Significant EAC risk factors included age, abdominal obesity, caffeine intake, and the presence of HGD. Risk factors for HGD or EAC included age, caffeine intake, and low-grade dysplasia while colonic adenomas trended towards significance. Notably, a history of statin or SSRI usage reduced the risk of EAC or HGD by 49% or 61%, respectively. In sum, our study validated several known and identified several novel risk factors, including a history of colonic adenomas or caffeine usage. Low-grade dysplasia (LGD) was a risk factor for progression but various endoscopic characteristics were not, suggesting that screening strategies should focus on histology instead. We identified SSRIs as a new potential chemoprotective medication

Statistical dependence estimation for object interaction and matching

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 97-103).This dissertation shows how statistical dependence estimation underlies two key problems in visual surveillance and wide-area tracking. The first problem is to detect and describe interactions between moving objects. The goal is to measure the influence objects exert on one another. The second problem is to match objects between non-overlapping cameras. There, the goal is to pair the departures in one camera with the arrivals in a different camera so that the resulting distribution of relationships best models the data. Both problems have become important for scaling up surveillance systems to larger areas and expanding the monitoring to more interesting behaviors. We show how statistical dependence estimation generalizes previous work and may have applications in other areas. The two problems represent different applications of our thesis that statistical dependence estimation underlies the learning of the structure of probabilistic models. First, we analyze the relationship between Bayesian, information-theoretic, and classical statistical methods for statistical dependence estimation. Then, we apply these ideas to formulate object interaction in terms of dependency structure model selection.(cont.) We describe experiments on simulated and real interaction data to validate our approach. Second, we formulate the matching problem in terms of maximizing statistical dependence. This allows us to generalize previous work on matching, and we show improved results on simulated and real data for non-overlapping cameras. We also prove an intractability result on exact maximally dependent matching.by Kinh Tieu.Ph.D

Silencing of the Pink1 gene expression by conditional RNAi does not induce dopaminergic neuron death in mice.

Transgenic RNAi, an alternative to the gene knockout approach, can induce hypomorphic phenotypes that resemble those of the gene knockout in mice. Conditional transgenic RNAi is an attractive choice of method for reverse genetics in vivo because it can achieve temporal and spatial silencing of targeted genes. Pol III promoters such as U6 are widely used to drive the expression of RNAi transgenes in animals. Tested in transgenic mice, a Cre-loxP inducible U6 promoter drove the broad expression of an shRNA against the Pink1 gene whose loss-of-functional mutations cause one form of familial Parkinson\u27s disease. The expression of the shRNA was tightly regulated and, when induced, silenced the Pink1 gene product by more than 95% in mouse brain. However, these mice did not develop dopaminergic neurodegeneration, suggesting that silencing of the Pink1 gene expression from embryo in mice is insufficient to cause similar biochemical or morphological changes that are observed in Parkinson\u27s disease. The results demonstrate that silencing of the PINK1 gene does not induce a reliable mouse model for Parkinson\u27s disease, but that technically the inducible U6 promoter is useful for conditional RNAi in vivo

Identifying Computer-Translated Paragraphs using Coherence Features

We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corpus containing 2000 human-created and 2000 machine-translated paragraphs. The result showed that our method achieved the best performance (accuracy = 72.3%, equal error rate = 29.8%) when it is compared with previous methods on various computer-generated text including translation and paper generation (best accuracy = 67.9%, equal error rate = 32.0%). Experiments on Dutch, another rich resource language, and a low resource one (Japanese) attained similar performances. It demonstrated the efficiency of the coherence features at distinguishing computer-translated from human-created paragraphs on diverse languages.Comment: 9 pages, PACLIC 201

Local anesthetics induce autophagy in young permanent tooth pulp cells

Pulp cells are essential for tooth development, and dentin repair and regeneration. In addition these cells have been identified as an important stem cell source. Local anesthetics are widely used in dental clinics, as well as the other clinical disciplines and have been suggested to interfere with human permanent tooth development and induce tooth agenesis through unknown mechanisms. Using pig model and human young permanent tooth pulp cells, our research has identified that the local anesthetics commonly used in clinics can affect cell proliferation. Molecular pathway profiling suggested that LC3II is one of the earliest molecules induced by the agents and p62 is the only common downstream target identified for all the drugs tested. The effect of the drugs could be partially recovered by V-ATPase inhibitor only if early intervention is performed. Our results provide novel evidence that local anesthetics could affect tooth cell growth that potentially can have impacts on tooth development

Asymmetric Cold Rolling of Thin Strip with Roll Edge Kiss

Asymmetric rolling can reduce the thickness of rolled strip and rolling load significantly. In this paper, the asymmetric cold rolling of thin strip with roll edge kiss was analysed theoretically and the rolling pressure, intermediate force between the work roll and backup roll, the work roll edge kiss force, the strip profile after rolling are obtained for this special asymmetric rolling. The rolling pressure, intermediate force, roll edge kiss force and the strip profile are compared for various roll speed ratios, reduction and friction coefficients. Simulation result shows that the roll speed ratio and reduction have significant influence on the profile of rolled strip, and the calculated rolling forces are consistent with the measured values. The effect of friction in the roll bite on mechanics of the asymmetric cold rolling of thin strip with roll edge kiss is also discussed

Infrequent HIV Testing and Late HIV Diagnosis Are Common Among a Cohort of Black Men Who Have Sex With Men in 6 US Cities

Objective: US guidelines recommend at least annual HIV testing for those at risk. This analysis assessed frequency and correlates of infrequent HIV testing and late diagnosis among black men who have sex with men (BMSM). Methods: HIV testing history was collected at enrollment from participants in HPTN 061, an HIV prevention trial for at-risk US BMSM. Two definitions of late HIV diagnosis were assessed: CD4 cell count <200 cells per cubic millimeter or <350 cells per cubic millimeter at diagnosis. Results: HPTN 061 enrolled 1553 BMSM. HIV testing questions were completed at enrollment by 1284 (98.7%) of 1301 participants with no previous HIV diagnosis; 272 (21.2%) reported no HIV test in previous 12 months (infrequent testing); 155 of whom (12.1% of the 1284 with testing data) reported never testing. Infrequent HIV testing was associated with: not seeing a medical provider in the previous 6 months (relative risk [RR]: 1.08, 95% confidence interval [CI]: 1.03 to 1.13), being unemployed (RR: 1.04, CI: 1.01 to 1.07), and having high internalized HIV stigma (RR: 1.03, CI: 1.0 to 1.05). New HIV diagnoses were more likely among infrequent testers compared with men tested in the previous year (18.4% vs. 4.4%; odds ratio: 4.8, 95% CI: 3.2 to 7.4). Among men with newly diagnosed HIV, 33 (39.3%) had a CD4 cell count <350 cells per cubic millimeter including 17 (20.2%) with CD4 <200 cells per cubic millimeter. Conclusions: Infrequent HIV testing, undiagnosed infection, and late diagnosis were common among BMSM in this study. New HIV diagnoses were more common among infrequent testers, underscoring the need for additional HIV testing and prevention efforts among US BMSM. Infrequent HIV Testing and Late HIV Diagnosis Are Common Among a Cohort of Black Men Who Have Sex With Men in 6 US Cities. Available from: https://www.researchgate.net/publication/265419180_Infrequent_HIV_Testing_and_Late_HIV_Diagnosis_Are_Common_Among_a_Cohort_of_Black_Men_Who_Have_Sex_With_Men_in_6_US_Cities [accessed Feb 4, 2016]

Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector

Making computer-generated (CG) images more difficult to detect is an interesting problem in computer graphics and security. While most approaches focus on the image rendering phase, this paper presents a method based on increasing the naturalness of CG facial images from the perspective of spoofing detectors. The proposed method is implemented using a convolutional neural network (CNN) comprising two autoencoders and a transformer and is trained using a black-box discriminator without gradient information. Over 50% of the transformed CG images were not detected by three state-of-the-art spoofing detectors. This capability raises an alarm regarding the reliability of facial authentication systems, which are becoming widely used in daily life.Comment: Accepted to be Published in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2018, San Diego, US