Functional Characterization of Resting and Adenovirus-Induced Reactive Astrocytes in Three-Dimensional Culture

Brain is a rich environment where neurons and glia interact with neighboring cells as well as extracellular matrix in three-dimensional (3D) space. Astrocytes, which are the most abundant cells in the mammalian brain, reside in 3D space and extend highly branched processes that form microdomains and contact synapses. It has been suggested that astrocytes cultured in 3D might be maintained in a less reactive state as compared to those growing in a traditional, two-dimensional (2D) monolayer culture. However, the functional characterization of the astrocytes in 3D culture has been lacking. Here we cocultured neurons and astrocytes in 3D and examined the morphological, molecular biological, and electrophysiological properties of the 3D-cultured hippocampal astrocytes. In our 3D neuron-astrocyte coculture, astrocytes showed a typical morphology of a small soma with many branches and exhibited a unique membrane property of passive conductance, more closely resembling their native in vivo counterparts. Moreover, we also induced reactive astrocytosis in culture by infecting with high-titer adenovirus to mimic pathophysiological conditions in vivo. Adenoviral infection induced morphological changes in astrocytes, increased passive conductance, and increased GABA content as well as tonic GABA release, which are characteristics of reactive gliosis. Together, our study presents a powerful in vitro model resembling both physiological and pathophysiological conditions in vivo, and thereby provides a versatile experimental tool for studying various neurological diseases that accompany reactive astrocytes.

Development of a System for Extracting the Information of Candidate Tumor Markers Reported in Biomedical Literatures / 대한진단검사의학회지

BACKGROUND: Since the human genome project was completed in 2003, there have been numerous reports on cancer and related markers. This study was aimed to develop a system to extract automatically information regarding the relationship between cancer and tumor markers from biomedical literatures. METHODS: Named entities of tumor markers were recognized by both a dictionary-based method and machine learning technology of the support vector machine. Named entities of cancers were recognized by the MeSH dictionary. RESULTS: Relational and filtering keywords were selected after annotating 160 abstracts from PubMed. Relational information was extracted only when one of the relational keywords was in an appropriate position along the parse tree of a sentence with both tumor marker and disease entities. The performance of the system developed in this study was evaluated with another set of 77 abstracts. With the relational and filtering keyword used in the system, precision was 94.38% and recall was 66.14%, while without the expert knowledge precision was 49.16% and recall was 69.29%. CONCLUSIONS: We developed a system that can extract relational information between a tumor and its markers by incorporating expert knowledge into the system. The system exploiting expert knowledge would serve as a reference when developing another information extraction system in various medical fields.

Development of a Web-based Program for the Identification of Human Leukocyte Antigen Antibody Specificities / 대한진단검사의학회지

BACKGROUND: Panel reactive antibody (PRA) test is used to determine whether a patient awaiting transplantation is previously sensitized. Tail analysis algorithm is widely used to identify antibody specificities, but it is very difficult to perform manually. METHODS: To develop a web-based program, PHP (5.1.2), Apache (2.0.55), and MySQL (5.0.22) were used. Tail analysis algorithm was applied to identify specificities, which analyzed statistically 2 x 2 tables representing reactivities to broad antigens, splits and cross reactive groups (CREG). Exploiting two CREG classifications of Rodey (R) and Takemoto (T), antibody specificities were identified by 3 methods (ABC, R-ABC, T-ABC) simultaneously. Performance of the system was evaluated using 159 samples that showed > or =6 PRA% by a lymphocytotoxicity assay. RESULTS: A web-based system that can identify HLA antibody specificities was implemented on www.koreanhla.com. Among 159 samples tested, antibody specificities were identified in 151 (95.0 %), but not in 8 samples with PRA >97%. Among the 151 samples, 110 showed broad or split specificities and 41 CREG specificities. CONCLUSIONS: We developed a web-based computer program for the identification of HLA antibody specificities. Accessible to everyone on the internet, this program should be of help in sharing PRA results among laboratories.

Development of a Web-based Program to Calculate Sample Size for Evaluating the Performance of In Vitro Diagnostic Kits / 대한진단검사의학회지

BACKGROUND: Many studies evaluating the performance of in vitro diagnostic kits have been criticized for the lack of reliability. To attain reliability those evaluation studies should be preceded by sample size calculation ensuring statistical power. This study was intended to develop a web-based system to estimate the sample size, which was often neglected because it would require expert knowledge in statistics. METHODS: For sample size calculation, we extracted essential parameters from the performance studies on the 3rd generation anti-hepatitis C virus (HCV) kits reported in the literature. We developed a system with PHP web-script language and MySQL. The statistical models used in this system were as follows; one sample without power consideration (model 1), one sample with power consideration (model 2), and two samples with power consideration (model 3). RESULTS: Among the articles published between 1989 and 2005, 13 articles that evaluated the performance of anti-HCV kits were identified by searching with Medical Subject Headings (MeSH). The diagnostic sensitivity was 83-100% with a median of 145 samples (range; 12-1,091) and the specificity was 97-100% with a median of 1,025 samples (range; 33-4,381). The estimated sample size would be 280 in the model 1, 817 in the model 2, and 1,510 in the model 3, when we set 2% prevalence of HCV infection, 95% sensitivity of a conventional kit, 97% sensitivity of a new kit , 95% significance level (two-sided test), 2% allowable error, and 80% power. CONCLUSIONS: Our study indicates that an insufficient sample size is still a problem in performance evaluation. Our system should be helpful in increasing the reliability of performance evaluation by providing an appropriate sample size.