• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.123-123
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• 2006

• Journal of radiological science and technology
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• v.45 no.6
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• pp.553-560
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• 2022

The purpose of this study is to evaluate the clinical risk according to the applicator heterogeneity, mislocation, and tissue heterogeneity correction through a dose verification program during brachytherapy of cervical cancer. We performed image processing with MATLAB on images acquired with CT simulator. The source was modeled and stochiometric calibration and Monte-Carlo algorithm were applied based on dwell time and location to calculate the dose, and the secondary cancer risk was evaluated in the dose verification program. The result calculated by correcting for applicator and tissue heterogeneity showed a maximum dose of about 25% higher. In the bladder, the difference in excess absolute risk according to the heterogeneity correction was not significant. In the rectum, the difference in excess absolute risk was lower than that calculated by correcting applicator and tissue heterogeneity compared to the water-based calculation. In the femur, the water-based calculation result was the lowest, and the result calculated by correcting the applicator and tissue heterogeneity was 10% higher. A maximum of 14% dose difference occurred when the applicator mislocation was 20 mm in the Z-axis. In a future study, it is expected that a system that can independently verify the treatment plan can be developed by automating the interface between the treatment planning system and the dose verification program.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.32-49
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• 1998

For estimation of regional myocardial blood flow with O-15 water PET, a few modifications considering partial volume effect based on single compartment model have been proposed. In this study, we attempted to quantify the degree of heterogeneity and to show the effect of tissue flow heterogeneity on partition coefficient(${\lambda}$) and to find the relation between perfusable tissue index(PTI) and ${\lambda}$ by computer simulation using two modified models. We simulated tissue curves for the regions with homogeneous and heterogeneous blood flow over a various flow range(0.2-4.0ml/g/min). Simulated heterogeneous tissue composed of 4 subregions of the same or different size of block which have different homogeneous flow and different degree of slope of distribution of blood flow. We measured the index representing heterogeneity of distribution of blood flow for each heterogeneous tissue by the constitution heterogeneity(CH). For model I, we assumed that tissue recovery coefficient ($F_{MME}$) was the product of partial volume effect($F_{MMF}$) and PTI. Using model I, PTI, flow, and $F_{MM}$ were estimated. For model II, we assumed that partition coefficient was another variable which could represent tissue characteristics of heterogeneity of flow distribution. Using model II, PTI, flow and ${\lambda}$ were estimated. For the simulated tissue with homogeneous flow, both models gave exactly the same estimates, of three parameters. For the simulated tissue with heterogeneous flow distribution, in model I, flow and $F_{MM}$ were correctly estimated as CH was increased moderately. In model II, flow and ${\lambda}$ were decreased curvi-linearly as CH was increased. The degree of underestimation of ${\lambda}$ obtained using model II, was correlated with CH. The degree of underestimation of flow was dependent on the degree of underestimation of ${\lambda}$. PTI was somewhat overestimated and did not change according to CH. We conclude that estimated ${\lambda}$ reflect the degree of tissue heterogeneity of flow distribution. We could use the degree of underestimation of ${\lambda}$ to find the characteristic heterogeneity of tissue flow and use ${\lambda}$ to recover the underestimated flow.

• Journal of Preventive Medicine and Public Health
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• v.49 no.2
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• pp.97-107
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• 2016

Objectives: Research on how the risk of gastric cancer increases with Epstein-Barr virus (EBV) infection is lacking. In a systematic review that investigated studies published until September 2014, the authors did not calculate the summary odds ratio (SOR) due to heterogeneity across studies. Therefore, we include here additional studies published until October 2015 and conduct a meta-analysis with meta-regression that controls for the heterogeneity among studies. Methods: Using the studies selected in the previously published systematic review, we formulated lists of references, cited articles, and related articles provided by PubMed. From the lists, only case-control studies that detected EBV in tissue samples were selected. In order to control for the heterogeneity among studies, subgroup analysis and meta-regression were performed. Results: In the 33 case-control results with adjacent non-cancer tissue, the total number of test samples in the case and control groups was 5280 and 4962, respectively. In the 14 case-control results with normal tissue, the total number of test samples in case and control groups was 1393 and 945, respectively. Upon meta-regression, the type of control tissue was found to be a statistically significant variable with regard to heterogeneity. When the control tissue was normal tissue of healthy individuals, the SOR was 3.41 (95% CI, 1.78 to 6.51; I-squared, 65.5%). Conclusions: The results of the present study support the argument that EBV infection increases the risk of gastric cancer. In the future, age-matched and sex-matched case-control studies should be conducted.

• Molecules and Cells
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• v.47 no.2
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• pp.100031.1-100031.13
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• 2024

It is now well-accepted that obesity-induced inflammation plays an important role in the development of insulin resistance and type 2 diabetes. A key source of the inflammation is the murine epididymal and human visceral adipose tissue. The current paradigm is that obesity activates multiple proinflammatory immune cell types in adipose tissue, including adipose-tissue macrophages (ATMs), T Helper 1 (Th1) T cells, and natural killer (NK) cells, while concomitantly suppressing anti-inflammatory immune cells such as T Helper 2 (Th2) T cells and regulatory T cells (Tregs). A key feature of the current paradigm is that obesity induces the anti-inflammatory M2 ATMs in lean adipose tissue to polarize into proinflammatory M1 ATMs. However, recent single-cell transcriptomics studies suggest that the story is much more complex. Here we describe the single-cell genomics technologies that have been developed recently and the emerging results from studies using these technologies. While further studies are needed, it is clear that ATMs are highly heterogeneous. Moreover, while a variety of ATM clusters with quite distinct features have been found to be expanded by obesity, none truly resemble classical M1 ATMs. It is likely that single-cell transcriptomics technology will further revolutionize the field, thereby promoting our understanding of ATMs, adipose-tissue inflammation, and insulin resistance and accelerating the development of therapies for type 2 diabetes.

• IMMUNE NETWORK
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• v.10 no.4
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• pp.115-119
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• 2010

Lymphoid tissue inducer (LTi) cells have been characterized in mouse as a key cell when secondary lymphoid tissues are organized during development and memory T cells are formed after birth. In addition to their involvement in adaptive immune responses, recent studies show that they contribute to innate immune responses by producing large amount of interleukin (IL)-22 against microbial attack. Here, we compare IL-22-producing LTi and LTi-like cells in human and mouse and discuss their heterogeneity in different tissues.

• IMMUNE NETWORK
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• v.15 no.4
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• pp.167-176
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• 2015

Macrophages are the main effector cells of innate immunity and are involved in inflammatory and anti-infective processes. They also have an essential role in maintaining tissue homeostasis, supporting tissue development, and repairing tissue damage. Until few years ago, it was believed that tissue macrophages derived from circulating blood monocytes, which terminally differentiated in the tissue and unable to proliferate. Recent evidence in the biology of tissue macrophages has uncovered a series of immune and ontogenic features that had been neglected for long, despite old observations. These include origin, heterogeneity, proliferative potential (or self-renewal), polarization, and memory. In recent years, the number of publications on tissue resident macrophages has grown rapidly, highlighting the renewed interest of the immunologists for these key players of innate immunity. This minireview aims to summarizing the new current knowledge in macrophage immunobiology, in order to offer a clear and immediate overview of the field.

• Tuberculosis and Respiratory Diseases
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• v.87 no.1
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• pp.52-64
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• 2024

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.

• Genomics & Informatics
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• v.15 no.1
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• pp.48-50
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• 2017

Tumor tissues from biopsies or surgery are major sources for the next generation sequencing (NGS) study, but these procedures are invasive and have limitation to overcome intratumor heterogeneity. Recent studies have shown that driver alterations in tumor tissues can be detected by liquid biopsy which is a less invasive technique capable of both capturing the tumor heterogeneity and overcoming the difficulty in tissue sampling. However, it is still unclear whether the driver alterations in liquid biopsy can be detected by targeted NGS and how those related to the tissue biopsy. In this study, we performed whole-exome sequencing for a breast cancer tissue and identified PTEN p.H259fs*7 frameshift mutation. In the plasma DNA (liquid biopsy) analysis by targeted NGS, the same variant initially identified in the tumor tissue was also detected with low variant allele frequency. This mutation was subsequently validated by digital polymerase chain reaction in liquid biopsy. Our result confirm that driver alterations identified in the tumor tissue were detected in liquid biopsy by targeted NGS as well, and suggest that a higher depth of sequencing coverage is needed for detection of genomic alterations in a liquid biopsy.

• Genomics & Informatics
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• v.17 no.1
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• pp.2.1-2.12
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• 2019

Chronic obstructive pulmonary disease (COPD) is a type of progressive lung disease, featured by airflow obstruction. Recently, a comprehensive analysis of the transcriptome in lung tissue of COPD patients was performed, but the heterogeneity of the sample was not seriously considered in characterizing the mechanistic dysregulation of COPD. Here, we established a new transcriptome analysis pipeline using a deconvolution process to reduce the heterogeneity and clearly identified that these transcriptome data originated from the mild or moderate stage of COPD patients. Differentially expressed or co-expressed genes in the protein interaction subnetworks were linked with mitochondrial dysfunction and the immune response, as expected. Computational protein localization prediction revealed that 19 proteins showing changes in subcellular localization were mostly related to mitochondria, suggesting that mislocalization of mitochondria-targeting proteins plays an important role in COPD pathology. Our extensive evaluation of COPD transcriptome data could provide guidelines for analyzing heterogeneous gene expression profiles and classifying potential candidate genes that are responsible for the pathogenesis of COPD.