51 research outputs found

    The Future is Now

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    No abstract available DOI: http://dx.doi.org/10.5564/mjia.v0i5.361 The Mongolian Journal of International Affairs; Number 5, 1998, Pages 3-1

    Gene Therapy in a Humanized Mouse Model of Familial Hypercholesterolemia Leads to Marked Regression of Atherosclerosis

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    Familial hypercholesterolemia (FH) is an autosomal codominant disorder caused by mutations in the low-density lipoprotein receptor (LDLR) gene. Homozygous FH patients (hoFH) have severe hypercholesterolemia leading to life threatening atherosclerosis in childhood and adolescence. Mice with germ line interruptions in the Ldlr and Apobec1 genes (Ldlr(-/-)Apobec1(-/-)) simulate metabolic and clinical aspects of hoFH, including atherogenesis on a chow diet.In this study, vectors based on adeno-associated virus 8 (AAV8) were used to deliver the gene for mouse Ldlr (mLDLR) to the livers of Ldlr(-/-)Apobec1(-/-) mice. A single intravenous injection of AAV8.mLDLR was found to significantly reduce plasma cholesterol and non-HDL cholesterol levels in chow-fed animals at doses as low as 3×10(9) genome copies/mouse. Whereas Ldlr(-/-)Apobec1(-/-) mice fed a western-type diet and injected with a control AAV8.null vector experienced a further 65% progression in atherosclerosis over 2 months compared with baseline mice, Ldlr(-/-)Apobec1(-/-) mice treated with AAV8.mLDLR realized an 87% regression of atherosclerotic lesions after 3 months compared to baseline mice. Immunohistochemical analyses revealed a substantial remodeling of atherosclerotic lesions.Collectively, the results presented herein suggest that AAV8-based gene therapy for FH may be feasible and support further development of this approach. The pre-clinical data from these studies will enable for the effective translation of gene therapy into the clinic for treatment of FH

    Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

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    Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

    Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

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    Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification

    Leveraging Self-Report, Electronic Health Record and Human Resource Data to Estimate the Impact of Diabetes Mellitus on Worker Productivity

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    Background/Aims: The economic burden of diabetes mellitus is high in the United States, increasing health care utilization and reducing workforce participation. Worker productivity is adversely impacted by complications related to diabetes. Estimating rates of absenteeism, presenteeism and other productivity measures can quantify the impact of diabetes in the U.S. workforce. Methods: We used data from the Value-Based Benefit Design Health and Wellness Study Phase II (VBD), a multiyear prospective study of employees surveyed from Group Health Cooperative and Kaiser Permanente Colorado from Jan. 1, 2010, to Dec. 31, 2013. The VBD survey questionnaire includes self-reported data on physical activity at work and at home, the SF-12® Health Survey, and self-reported data on absenteeism, presenteeism and lost productivity. These data were linked to the Virtual Data Warehouse (VDW) from both sites to determine whether respondents were diagnosed with diabetes. We applied the standardized relative resource cost algorithm to the VDW utilization data to calculate total health care costs per respondent. Results: Across both sites 3,891 respondents to the baseline survey, all of whom provided consent to have their data included in the study, were analyzed. Of these, 286 (7.4%) were identified as having diabetes. Compared to respondents without diabetes, respondents with diabetes had lower rates of positive overall health status (74% vs. 92%), higher mean days worked while not feeling well (1.6 days vs. 0.9 days) and lower average physical health composite scale scores (46 vs. 52.6). Respondents with diabetes reported higher rates of presenteeism (1.1 vs. 0.7 hours per week), absenteeism (1.4 vs. 1.1 hours per week) and productivity due to illnesses (2.5 vs. 1.8 hours per week) compared to respondents without diabetes. Crude odds ratios for respondents with diabetes were higher for absenteeism (1.35, 95% confidence interval [CI]: 0.97–1.87), presenteeism (1.63, 95% CI: 1.27–2.08) and lost productivity (1.51, 95% CI: 1.18–1.92). Average total health care costs were $1,222.98 higher for respondents with diabetes. Conclusion: Our preliminary results suggest employees with diabetes experience higher rates of presenteeism and lost productivity compared to employees without diabetes. Linking patient-reported outcomes to VDW and human resources data provides a detailed understanding of patient experience in the workforce
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