• Tuberculosis and Respiratory Diseases
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• v.61 no.1
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• pp.54-59
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• 2006

Background: Although there have been several studies regarding the clinical value of an automated TB-PCR study using sputum, bronchial washing, and other body fluid samples for the detection of pulmonary tuberculosis, there are only a few reports on the use of fresh tissue samples. Materials and methods: The acid-fast bacilli stain(AFB), tuberculosis culture, automated TB-PCR study, and histopathology examination were performed in 42 fresh tissue samples. Results: Among the 42 cases, 18 cases were diagnosed with tuberculosis based on the clinical findings. Sixteen of the 18 cases were TB-PCR positive and of these 16 cases, only 2 cases were positive in the AFB stain or culture study. However, all 18 cases showed the histopathology findings of chronic granulomatous inflammation that was compatible with tuberculosis. Based on the clinical findings, the sensitivity, specificity, positive predictability, and negative predictability of the automated TB-PCR study were 88.9%, 100%, 100%, and 92.3% respectively. Conclusion: An automated TB-PCR assay is an important diagnostic tool for diagnosing tuberculosis in fresh tissue samples.

• The Journal of the Korean bone and joint tumor society
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• v.10 no.2
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• pp.113-119
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• 2004

Purpose: To determine the utility of sonographically guided percutaneous core needle biopsy to diagnose musculoskeletal soft tissue masses. Methods: A prospective study was performed in 55 patients referred for image-guided needle biopsy of primary or recurrent soft tissue masses and bone lesion or suspected solitary metastasis with extraosseous masses. Tissue samples were obtained with a 14-gauge or 18-gauge cutting needle coupled to an automated biopsy device under local anesthesia and sonographic guidance. Statistical analysis was based on 49 biopsies confirmed by successful clinical treatment (11 cases) or surgical resection (38 cases). Results: An accurate diagnosis was obtained in 47 (97%) of 49 biopsies; sensitivity was 95%, and specificity was 100%. The method did not yield sufficient tissue to establish a diagnosis in 6 cases. Considering all 55 biopsies, high-quality specimens were obtained in 87%. There were no serious complications. Conclusions: Sonographically guided core needle biopsy is accurate and safe, in soft tissue masses and bone tumors with extraosseous masses in the appendicular skeleton. In such patients, the sonographically guided procedure is the most prompt and effective method for obtaining tissue samples.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.34 no.s01
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• pp.33-39
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• 1989

Ethylene gas classified as one of five major plant hormones plays an important role in various plant metabolism. The precise analysis of ethylene production of plants or plant parts is a valuable research procedure because knowledge of ethylene production facilitates measures of the physiological activity within the tissue. This paper describes procedures for analyzing ethylene from plant tissues by gas chromatography and discusses problems associated with extracting gas samples either by introducing a vacuum to plant samples or by using a hypodermic syringe. Introduced are a continuous flow system for efficient analysis and an automated system for sampling, analyzing, calculating and recording ethylene production data.

• Journal of the korean veterinary medical association
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• v.29 no.3
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• pp.160-164
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• 1993

In order to clarify the cadmium contents of normal dogs, tissue samples including liver, kidney, muscle, skin and hair were collected from 50 dogs which were slaughtered in Dae Gu area. All samples were dry ashed and analyzed for cadmium content by atomic

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7597-7602
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• 2014

Background: Amplification and overexpression of human epidermal growth factor receptor 2 (HER2/neu) oncogene has considerable prognostic value in breast and gastric cancers. This study aimed to evaluate the frequency, overexpression pattern, clinical significance, and concordance between the results for protein expression and gene amplification of HER-2/neu in gastric and gastro-esophageal junction carcinomas. Materials and Methods: In this study, 101 gastric tissue samples which were included in tissue microarray were immunohistochemically examined for overexpression of HER2/neu. Chromogenic in situ hybridization (CISH) was used for HER-2/neu amplification. The correlation of HER2/neu amplification with clinicopathological parameters was also assessed. In addition, concordance between CISH and IHC was detected. Results: This study demonstrated a significant difference in the overexpression of HER2/neu in gastric tumors. The overexpression of HER2/neu was significantly higher in intestinal type, poorly differentiated grade, large size ($5cm{\leq}$) and positive nodal involvement tumors (p-value=0.041, 0.015, 0.038 and 0.071, respectively). Also, amplification of HER2/neu according to CISH test, had a significant positive correlation with tumor size and tumor type (p-value=0.018 and 0.058, respectively).Concordance between CISH and IHC was 76.9% in 101 evaluable samples. Conclusions: IHC/CISH differences were attributed to basolateral membranous immunoreactivity of glandular cells resulting in incomplete membranous reactivity and/or a higher rate of tumor heterogeneity in gastric cancers compared to breast cancers. Therefore, this can be a potential marker for targeted therapy of malignant gastric tumors.

• Mass Spectrometry Letters
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• v.5 no.1
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• pp.16-23
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• 2014

Liquid chromatography based mass spectrometry (LC-MS) is a key technology for analyzing highly complex and dynamic proteome samples. With highly accurate and sensitive LC-MS analysis of complex proteome samples, efficient data processing is another critical issue to obtain more information from LC-MS data. A typical proteomic data processing starts with protein database search engine which assigns peptide sequences to MS/MS spectra and finds proteins. Although several search engines, such as SEQUEST and MASCOT, have been widely used, there is no unique standard way to interpret MS/MS spectra of peptides. Each search engine has pros and cons depending on types of mass spectrometers and physicochemical properties of peptides. In this study, we describe a novel data process pipeline which identifies more peptides and proteins by correcting precursor ion mass numbers and unifying multi search engines results. The pipeline utilizes two open-source software, iPE-MMR for mass number correction, and iProphet to combine several search results. The integrated pipeline identified 25% more proteins in mouse epididymal adipose tissue compared with the conventional method. Also the pipeline was validated using control and colitis induced colon tissue. The results of the present study shows that the integrated pipeline can efficiently identify increased number of proteins compared to the conventional method which can be a breakthrough in identification of a potential biomarker candidate.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1129-1133
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• 2015

Background: The tissue microarray (TMA) is widely accepted as a fast and cost-effective research tool for in situ tissue analysis in modern pathology. However, the current automated and manual TMA techniques have some drawbacks restricting their productivity. Our study aimed to introduce an improved manual tissue miniarray (TmA) technique that is simple and readily applicable to a broad range of tissue samples. Materials and Methods: In this study, a conventional TV/radio telescopic antenna was used to punch tissue cores manually from donor paraffin embedded tissue blocks which were pre-incubated at $40^{\circ}C$. The cores were manually transferred, organized and attached to a standard block mould, and filled with liquid paraffin to construct TmA blocks without any use of recipient paraffin blocks. Results: By using a conventional TV/radio antenna, it was possible to construct TmA paraffin blocks with variable formats of array size and number ($2-mm{\times}42$, $2.5-mm{\times}30$, $3-mm{\times}24$, $4-mm{\times}20$ and $5-mm{\times}12$ cores). Up to $2-mm{\times}84$ cores could be mounted and stained on a standard microscopic slide by cutting two sections from two different blocks and mounting them beside each other. The technique was simple and caused minimal damage to the donor blocks. H&E and immunostained slides showed well-defined tissue morphology and array configuration. Conclusions: This technique is easy to reproduce, quick, inexpensive and creates uniform blocks with abundant tissues without specialized equipment. It was found to improve the stability of the cores within the paraffin block and facilitated no losses during cutting and immunostaining.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.30-36
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• 2006

Tissue microarray (TMA) is an array-based technology allowing the examination of hundreds of tissue samples on a single slide. To handle, exchange, and disseminate TMA data, we need standard representations of the methods used, of the data generated, and of the clinical and histopathological information related to TMA data analysis. This study aims to create a comprehensive data model with flexibility that supports diverse experimental designs and with expressivity and extensibility that enables an adequate and comprehensive description of new clinical and histopathological data elements. We designed a Tissue Microarray Object Model (TMA-OM). Both the Array Information and the Experimental Procedure models are created by referring to Microarray Gene Expression Object Model, Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE), and the TMA Data Exchange Specifications (TMA DES). The Clinical and Histopathological Information model is created by using CAP Cancer Protocols and National Cancer Institute Common Data Elements (NCI CDEs). MGED Ontology, UMLS and the terms extracted from CAP Cancer Protocols and NCI CDEs are used to create a controlled vocabulary for unambiguous annotation. We implemented a web-based application for TMA-OM, supporting data export in XML format conforming to the TMA DES or the DTD derived from TMA-OM. TMA-OM provides a comprehensive data model for storage, analysis and exchange of TMA data and facilitates model-level integration of other biological models.

• Parasites, Hosts and Diseases
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• v.45 no.2 s.142
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• pp.139-144
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• 2007

We investigated a small-scale serological survey to screen tissue-parasitic helminthiases of North Koreans as one of research programs for re-unification of Korea. Soil-transmitted helminthiases were found highly prevalent among North Korean residents at the border with China. ELISA using 4 tissue-parasitic helminth antigens was applied to 137 residents living in Cheongjin-shi, Hamgyeongbuk-do, North Korea and 133 female refugees in South Korea in 2004-2005. Among a total of 270 samples, 31 (11.5%), 25 (9.3%), and 11 (4.1%) were positive for specific IgG antibodies to antigens of Clonorchis sinensis, Taenia solium metacestode, and sparganum, respectively. The overall positive rate was 21.5%; 38.2% in males and 15.8% in females. The present finding suggests that tissue parasites, such as C. sinensis, T. solium metacestode and sparganum are highly prevalent in some limited areas of North Korea. These foodborne tissue-parasitic helminthiases should be considered for future control measures of parasitic diseases in North Korea.

• Current Optics and Photonics
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• v.6 no.1
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• pp.92-103
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• 2022

The development of midinfrared (mid-IR) quantum cascade lasers (QCLs) has enabled rapid high-contrast measurement of the mid-IR spectra of biological tissues. Several studies have compared the differences between the mid-IR spectra of colon cancer and noncancerous colon tissues. Most mid-IR spectrum classification studies have been proposed as machine-learning-based algorithms, but this results in deviations depending on the initial data and threshold values. We aim to develop a process for classifying colon cancer and noncancerous colon tissues through a deep-learning-based convolutional-neural-network (CNN) model. First, we image the midinfrared spectrum for the CNN model, an image-based deep-learning (DL) algorithm. Then, it is trained with the CNN algorithm and the classification ratio is evaluated using the test data. When the tissue microarray (TMA) and routine pathological slide are tested, the ML-based support-vector-machine (SVM) model produces biased results, whereas we confirm that the CNN model classifies colon cancer and noncancerous colon tissues. These results demonstrate that the CNN model using midinfrared-spectrum images is effective at classifying colon cancer tissue and noncancerous colon tissue, and not only submillimeter-sized TMA but also routine colon cancer tissue samples a few tens of millimeters in size.