• International Journal of Stem Cells
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• v.15 no.1
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• pp.26-40
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• 2022

Region specific brain organoids are brain organoids derived by patterning protocols using extrinsic signals as opposed to cerebral organoids obtained by self-patterning. The main focus of this review is to discuss various region-specific brain organoids developed so far and their application in modeling neurodevelopmental disease. We first discuss the principles of neural axis formation by series of growth factors, such as SHH, WNT, BMP signalings, that are critical to generate various region-specific brain organoids. Then we discuss various neurodevelopmental disorders modeled so far with these region-specific brain organoids, and findings made on mechanism and treatment options for neurodevelopmental disorders (NDD).

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.68-73
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• 2015

Purpose The purpose of this study was to evaluate image quality change by truncated region in field of view (FOV) of attenuation correction computed tomography (AC-CT) in brain PET/CT. Materials and Methods Biograph Truepoint 40 with TrueV (Siemens) was used as a scanner. $^{68}Ge$ phantom scan was performed with and without applying brain holder using brain PET/CT protocol. PET attenuation correction factor (ACF) was evaluated according to existence of pallet in FOV of AC-CT. FBP, OSEM-3D and PSF methods were applied for PET reconstruction. Parameters of iteration 4, subsets 21 and gaussian 2 mm filter were applied for iterative reconstruction methods. Window level 2900, width 6000 and level 4, 200, width 1000 were set for visual evaluation of PET AC images. Vertical profiles of 5 slices and 20 slices summation images applied gaussian 5 mm filter were produced for evaluating integral uniformity. Results Patient pallet was not covered in FOV of AC-CT when without applying brain holder because of small size of FOV. It resulted in defect of ACF sinogram by truncated region in ACF evaluation. When without applying brain holder, defect was appeared in lower part of transverse image on condition of window level 4200, width 1000 in PET AC image evaluation. With and without applying brain holder, integral uniformities of 5 slices and 20 slices summation images were 7.2%, 6.7% and 11.7%, 6.7%. Conclusion Truncated region by small FOV results in count defect in occipital lobe of brain in clinical or research studies. It is necessary to understand effect of truncated region and apply appropriate accessory for brain PET/CT.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.343-344
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• 2009

The aim in this paper is to show how to extract scalp of a series of brain MR images by using region growing segmentation algorithm. Most researches are all forces on the segmentation of skull, gray matter, white matter and CSF. Prior to the segmentation of these inner objects in brain, we segmented the scalp and the brain from the MR images. The scalp mask makes us to quickly exclude background pixels with intensities similar those of the skull, while the brain mask obtained from our brain surface. We make use of connected threshold method (CTM) and confidence connected method (CCM). Both of them are two implementations of region growing in Insight Toolkit (ITK). By using these two methods, the results are displayed contrast in the form of 2D and 3D scalp images.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• BMB Reports
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• v.56 no.3
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• pp.172-177
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• 2023

BEST family is a class of Ca²⁺-activated Cl- channels evolutionary well conserved from bacteria to human. The human BEST paralogs (BEST1-BEST4) share significant amino acid sequence homology in the N-terminal region, which forms the transmembrane helicases and contains the direct calcium-binding site, Ca²⁺-clasp. But the cytosolic C-terminal region is less conserved in the paralogs. Interestingly, this domain-specific sequence conservation is also found in the BEST1 orthologs. However, the functional role of the C-terminal region in the BEST channels is still poorly understood. Thus, we aimed to understand the functional role of the C-terminal region in the human and mouse BEST1 channels by using electrophysiological recordings. We found that the calcium-dependent activation of BEST1 channels can be modulated by the C-terminal region. The C-terminal deletion hBEST1 reduced the Ca²⁺-dependent current activation and the hBEST1-mBEST1 chimera showed a significantly reduced calcium sensitivity to hBEST1 in the HEK293 cells. And the C-terminal domain could regulate cellular expression and plasma membrane targeting of BEST1 channels. Our results can provide a basis for understanding the C-terminal roles in the structure-function of BEST family proteins.

• Journal of KIISE
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• v.43 no.1
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• pp.54-60
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• 2016

Brain gene expression information is closely related to the structural and functional characteristics of the brain. Thus, extensive research has been carried out on the relationship between gene expression patterns and the brain's structural organization. In this study, Principal Component Analysis was used to extract features of gene expression patterns, and genes were automatically classified by spatial distribution. Voxels were then clustered with classified specific region expressed genes. Finally, we visualized the clustering results for mouse hippocampal region gene expression with the Allen Brain Atlas. This experiment allowed us to classify the region-specific gene expression of the mouse hippocampal region and provided visualization of clustering results and a brain atlas in an integrated manner. This study has the potential to allow neuroscientists to search for experimental groups of genes more quickly and design an effective test according to the new form of data. It is also expected that it will enable the discovery of a more specific sub-region beyond the current known anatomical regions of the brain.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.525-528
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• 1999

Abstract - In this paper, a segmentation method for brain Magnetic Resonance(MR) image using region clustering technique with statistical distribution of gradient image and fuzzy rules is described. The brain MRI consists of gray matter and white matter, cerebrospinal fluid. But due to noise, overlap, vagueness, and various parameters, segmentation of MR image is a very difficult task. We use gradient information rather than intensity directly from the MR images and find appropriate thresholds for region classification using gradient approximation, rayleigh distribution function, region clustering, and merging techniques. And then, we propose the adaptive fuzzy rules in order to extract anatomical structures and diseases from brain MR image data. The experimental results shows that the proposed segmentation algorithm given better performance than traditional segmentation techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.247-250
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• 2003

This paper describes the extraction method for brain region using cellular automata from the brain MR image. In the first removing the background from the brain MR image, and then extracting the brain region by applying the cellular automata rule obtained from histogram analysis information. The results on some experimental results showed that the PSNR is 42.11(dB) on image quality and also the correlation factor is estimated 98.46%. The result of this study can be used as the auto-diagnostics system.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.83.1-83.1
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• 2003

The heterotrimeric G protein subunits (G ) are region-specifically expressed in brain such as hypothalamus and pituitary gland in abundant, suggesting that is may be associated with “stress-axis”. This study was designed to examine the effect of stress on the region-specific expression of various G subunits in rat brain. The localization of mRNAs encoding seven of G and striking region-specific patterns of expression were observed in 12 different regions of both non-stressed and stressed rat brain; (1) frontal cortex area, (2) cerebral cortex area, (3) striatum, (4) hippocampus area, (5) thalamus, (6) brain stem, (7) cerebellum area, (8) hypothalamus, (9) septum, (10) amygdala, (11) preoptic area, and (12) pituitary gland. (omitted)

• Journal of Microbiology and Biotechnology
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• v.12 no.3
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• pp.508-513
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• 2002

Human endogenous retroviral long terminal repeats (LTRs) have been found to be coexpressed with sequences of genes located nearby. It has been suggested that the LTR elements have contributed to the structural change or genetic variation of human genome connected to various diseases. The HERV-W family has been identified in the cerebrospinal fluids and brains of individuals with schizophrenia. Using a cDNA library derived from a human brain, the HERV-W LTR elements were examined and five new LTR elements were identified. These elements were examined using a YAC clone panel from the Xq21.3 region linked to psychosis that was replicated on the Y chromosome after the separation of the chimpanzee and human lineages. Fourteen elements of the HERV-W LTR were identified in that region. Those LTR elements showed a high degree of sequence similarity ($91.8-99.5\%$) with previously reported HERV-W LTR. A phylogenetic tree obtained from the neighbor-joining method revealed that new HERV-W LTR elements were closely related to the AXt000960, AF072504, and AF072506 from the GenBank database. The data indicates that several copy numbers of the HERV-W LTR elements exist on the Xq21.3 region and are also expressed in the human brain. These LTR elements need to be further investigated as potential leads to neuropsychiatric diseases.