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The sol–gel nanoporous capturing technology represents a powerful approach where the sol–gel matrix constrains the motion of the encapsulated biomolecules (proteins, peptides, chemicals, antibodies, nucleotides, etc.) without physical adsorption or any modifications. This technology can be applied to multiplex immunoassay platform because several disease markers can be immobilized and tested at once. In this study, we have tested several thousand specimens using Hi3-1 Multiplex human immunodeficiency virus (HIV) 1/2 and hepatitis C virus (HCV) antibody detection kit at two clinical trials institutes. These results showed a highest sensitivity (100%, n = 500 HIV-positive specimens and n = 400 HCV-positive) and specificity (99.99% for HIV and 99.83% for HCV, n = 7706 negative specimens) by using Hi3-1 kit, which screens HIV1/2 and HCV antibodies simultaneously. Finally, we suggested that our screening technology was successfully utilized as a multiplex HIV and HCV diagnostic tool for blood bank screening.

Silver–tin oxide (Ag–SnO2) is considered to be an effective alternative to silver–cadmium oxide (Ag–CdO), which is carcinogenic and, therefore, toxic to the human body. In this study, Ag–SnO2 powder was prepared through a combined oxidation and ball-milling process using gas-atomized Ag–Sn powder. During oxidation, the Ag3Sn phase disappeared at 800°C and SnO2 was formed without Ag oxidation; this SnO2 formed a layer structure that covered the Ag matrix. The thickness of the oxide layer increased after the composite was subjected to a second oxidation process. Owing to the resultant core (Ag)-shell (SnO2) structure, the electrical conductivity of the fabricated composite was considerably lower than that of commercially available materials. However, the electrical conductivity increased remarkably after ball milling of the samples, which allowed the SnO2 surface layer to be peeled off and crushed. Following high-pressure magnetic pulsed compaction, the SnO2 was found to be homogeneously distributed in the Ag matrix, which exhibited a lamellar structure.

Automated white matter hyperintensity (WMH) segmentation on magnetic resonance imaging is greatly advantageous for various clinical studies using large-sample data. Accurate localization of WMH can provide more beneficial information for clinical studies, as differences of regional WMH existence may be linked to clinical symptoms. We suggest a fully automated method for WMH quantification and localization without human interaction using T1-weighted and fluid-attenuated inversion-recovery (FLAIR) images. The known sources of false-positive results in the subarachnoid space and brain-cerebrospinal fluid (CSF) interface were removed by applying a WMH candidate-region mask. WMH segmentation was performed based on the Markov random field model. The intensity-substitution method was developed for the accurate localization of WMH, with proper tissue classification and nonlinear registration. The performance of the method was evaluated via comparison with manual delineation; the similarity index and the overlap ratio were 89.94 and 81.90, respectively. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 193–200, 2011 (This work was supported by the Global Science experimental Data hub Center (GSDC) funded by the Korea Institute of Science and Technology Information (KISTI) (N-10-NM-IR05), in which main calculations were performed by using the supercomputing resource of the KISTI.)

BACKGROUND AND PURPOSE Patients with small vessel disease show high-signal intensity on T2-weighted magnetic resonance (MR) images that represent ischemic cell damage. However, despite a similar degree of ischemic change, the amount and the severity of clinical presentations may vary. We investigated the clinical correlations of ischemic changes using voxel-based morphometric analyses of diffusion tensor imaging (DTI). METHODS Twenty-seven MCI and 34 dementia patients were included who all had significant small vessel disease on magnetic resonance imaging (MRI). In all patients, neuropsychological tests, a rating on the Pyramidal and Extrapyramidal scale (PEPS) for motor deficits, and 3-Tesla MRI including DTI scans were performed. Voxel-based analysis of the fractional anisotropy and mean diffusivity maps were computed. RESULTS Cognitive scores correlated with the DTI abnormalities in supratentorial areas with regional specificity according to each cognitive test. Unexpectedly, cognitive deficits in most neuropsychological tests, even in some frontal tasks, were associated with disruption of posterior white matter integrities. Motor deficits correlated with both supra- and infratentorial lesions. CONCLUSION Our findings suggest that in patients with small vessel disease who show cognitive and motor impairments, a specific distribution of fiber tract damage is more related with clinical deficits than is the severity of the total ischemia.

carriers had lower volumes at bilateral presubiculum, left hippocampus & left subiculum. Among controls none of the hippocampal subfields were differing between ApoE4 carrier status. Conclusions: Study validates previous observations of hippocampal atrophy including the sub-regions in AD. There is a modest association between ApoE4 carrier status and alterations in white-matter microstructural integrity at medial temporal and hippocampus. ApoE4 associated changes are more pronounced in AD with atrophy of subicular complex, which is the main information router from hippocampus to subcortical structures.

including d, were regressed onto VBM data, in order to identify the neural substrates associated with our latent dementia proxy. In a base model, we constructed two latent factors: “g” 1⁄4 Spearman’s g, i.e., the shared variance in cognition derived from the cognitive battery; and “f”, i.e., the shared variance in functional status, derived from Physical Performance Test (PPT) and Alzheimer’s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) items. In the final model, we added a third latent variable “d”, representing the shared variance between cognitive test scores and PPT /ADC-ADL items. Results: In the base model, g correlated r 1⁄4 0.643 with CDR sum of boxes (CDRSOB). f correlated r 1⁄4 0.562. Together, g and f explained 72.9% of CDRSOB variance. In the final model, d correlated strongly with CDRSOB (r 1⁄4 0.816). g’s association was attenuated (r 1⁄4 0.300), as was f’s (r 1⁄4 0.245). Together, g, f and d explained 82.7% of CDRSOB variance. Lower gray matter volumes in the regions associated with d and g were associated with higher CDR scores. After adjusting for age and gender, d was significantly and positively associated with grey matter volume in bilateral cingulate (BA 31), left posterior cingulate, (BA 31), right inferior parietal lobe (BA 40), and right middle temporal gyrus (BA 21). Conclusions: This study confirms in a third cohort that a latent variable can be constructed from readily available cognitive and functional status measures that is strongly associated with dementia severity. As we hypothesized, d is specifically associated with elements of the DMN.