• Journal of Physiology & Pathology in Korean Medicine
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• v.38 no.1
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• pp.16-21
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• 2024

Haepyoijin-tang and its main components have been used for phlegm, cough and dyspnea. Using a respiratory inflammation model, we intend to reveal the anti-inflammatory effect and pharmacological mechanism of Haepyoijin-tang. We induced the respiratory inflammation model by Aspergillus oryzae protease and ovalbumin administration. Female Balb/c mice (8 weeks old) were classified into four groups as follows: saline control group, aspergillus oryzae protease and ovalbumin induced respiratory inflammation group (vehicle), inflammation with Haepyoijin-tang (200 mg/kg) administration group, inflammation with dexamethasone (5 mg/kg) administration group (n=7). To identify the anti-inflammatory effects of Haepyoijin-tang water extracts, we measured the inflammatory cell number in bronchoalveolar lavage fluid (BALF) and total live lung cell number. In addition, we checked eosinophil ratio and number in BALF. And Interleukin (IL)-5 level was also measured in lung cell culture supernatant. To confirm the mechanism of anti-inflammatory effects, we analyzed the activated helper T cell (CD4⁺CD25⁺ cell) and Th2 cell (CD4⁺GATA3⁺ cell) ratio and number in lung by using flow cytometry. Finally, we attempted to confirm the immune mechanism by measuring the ratio and number of regulatory T cells (CD4⁺Foxp3⁺ cell). Haepyoijin-tang extracts treatment diminished inflammatory cell, especially, eosinophil number in BALF and total live lung cell number. Moreover, IL-5 level was reduced in Haepyoijin-tang treated group. Surprisingly, Haepyoijin-tang extracts administration not only decreased the activated helper T cell but also Th2 cell population in lung. Additionally, regulatory T cell population was increased in Haepyoijin-tang administration group. Our findings proved that Haepyoijin-tang extract have anti-inflammatory efficacy by suppressing Th2 cell activation and promoting regulatory T cell population.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1833-1840
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• 2013

Metastasis is one of the hallmarks of malignant neoplasms and is the leading cause of death in many cancer patients. A major challenge in cancer treatment is to find better ways to specifically target tumor metastasis. In this study, the anti-metastatic potential of the methanolic extract of Rhizophora apiculata (R.apiculata) was evaluated using the B16F-10 melanoma induced lung metastasis model in C57BL/6 mice. Metastasis was induced in C57BL/6 mice by injecting highly metastatic B16F-10 melanoma cells through the lateral tail vein. Simultaneous treatment with R.apiculata extract (10 mg/kg b.wt (intraperitoneal) significantly (p<0.01) inhibited pulmonary tumor nodule formation (41.1 %) and also increased the life span (survival rate) 107.3 % of metastatic tumor bearing animals. The administration of R.apiculata extract significantly (p<0.01) reduced biochemical parameters such as lung collagen hydroxyproline, hexosamine, uronic acid content, serum nitric oxide (NO), ${\gamma}$-glutamyl transpeptidase (GGT) and sialic acid levels when compared to metastasis controls. These results correlated with lung histopathology analysis of R.apiculata extract treated mice showing reduction in lung metastasis and tumor masses. Taken together, our findings support that R.apiculata extract could be used as a potential anti-metastasis agent against lung cancer.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.7-14
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• 2024

In this paper, we explore the application of RNA-sequencing data and ensemble machine learning to predict lung cancer and treatment strategies for lung cancer, a leading cause of cancer mortality worldwide. The research utilizes Random Forest, XGBoost, and LightGBM models to analyze gene expression profiles from extensive datasets, aiming to enhance predictive accuracy for lung cancer prognosis. The methodology focuses on preprocessing RNA-seq data to standardize expression levels across samples and applying ensemble algorithms to maximize prediction stability and reduce model overfitting. Key findings indicate that ensemble models, especially XGBoost, substantially outperform traditional predictive models. Significant genetic markers such as ADGRF5 is identified as crucial for predicting lung cancer outcomes. In conclusion, ensemble learning using RNA-seq data proves highly effective in predicting lung cancer, suggesting a potential shift towards more precise and personalized treatment approaches. The results advocate for further integration of molecular and clinical data to refine diagnostic models and improve clinical outcomes, underscoring the critical role of advanced molecular diagnostics in enhancing patient survival rates and quality of life. This study lays the groundwork for future research in the application of RNA-sequencing data and ensemble machine learning techniques in clinical settings.

• Journal of Preventive Medicine and Public Health
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• v.35 no.1
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• pp.13-23
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• 2002

Objectives : To investigate the therapeutic compliance and its related factors in lung cancer patients. Methods : The subjects of this study comprised 277 patients first diagnosed with lung cancer at Kyungpook National University Hospital between Jan 1999 and Sept 1999. Of these, 141(50.9%) participated in the study by properly replying to structured questionnaires. The data was analyzed using a simplified Health Decision Model. This model includes categories of variables covering therapeutic compliance, health beliefs, patient preferences, knowledge and experience, social interaction, sociodemographic and clinical characteristics. Results : The therapeutic compliance rate of the 141 study subjects was 78.0%. An analysis of health beliefs and patient preferences revealed health concern (p<0.05), dependency on medicine (p<0.05), perceived susceptibility and severity (p<0.05) as well as preferred treatment (p<0.01) as factors related to therapeutic compliance. Factors from the sociodemographic characteristics and clinical factors that were related to therapeutic compliance were age (p<0.01), monthly income (p<0.05), histological type (p<0.05) and clinical stage (p<0.05) of cancer. Conclusions : In order to improve therapeutic compliance in lung cancer patients it is necessary to educate the aged, low-income patients, or patients who have small cell lung cancer or lune cancer of an advanced stage for which surgery is not indicated. Additionally, it is essential for medical personnel to have a deep concern about patients who have poor lifestyles, a low dependency on medicine, or a high perceived susceptibility and severity. Practically, early diagnosis of lung cancer and thoughtful considerations of low-income patients are important. By means of population-based education in a community, we may promote attention to health and enhance the early diagnosis of lung cancer.

• Journal of Chest Surgery
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• v.57 no.5
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• pp.460-466
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• 2024

Background: Numerous studies have investigated methods of predicting postoperative pulmonary complications (PPCs) in lung cancer surgery, with chronic obstructive pulmonary disease (COPD) and low forced expiratory volume in 1 second (FEV₁) being recognized as risk factors. However, predicting complications in COPD patients with preserved FEV₁ poses challenges. This study considered various diffusing capacity of the lung for carbon monoxide (DL_CO) parameters as predictors of pulmonary complication risks in mild COPD patients undergoing lung resection. Methods: From January 2011 to December 2019, 2,798 patients undergoing segmentectomy or lobectomy for non-small cell lung cancer (NSCLC) were evaluated. Focusing on 709 mild COPD patients, excluding no COPD and moderate/severe cases, 3 models incorporating DL_CO, predicted postoperative DL_CO (ppoDL_CO), and DL_CO divided by the alveolar volume (DL_CO/VA) were created for logistic regression. The Akaike information criterion and Bayes information criterion were analyzed to assess model fit, with lower values considered more consistent with actual data. Results: Significantly higher proportions of men, current smokers, and patients who underwent an open approach were observed in the PPC group. In multivariable regression, male sex, an open approach, DL_CO <80%, ppoDL_CO <60%, and DL_CO/VA <80% significantly influenced PPC occurrence. The model using DL_CO/VA had the best fit. Conclusion: Different DL_CO parameters can predict PPCs in mild COPD patients after lung resection for NSCLC. The assessment of these factors using a multivariable logistic regression model suggested DL_CO/VA as the most valuable predictor.

• Journal of Korean Physical Therapy Science
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• v.31 no.3
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• pp.31-50
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• 2024

Background: The lung capacity prediction formula in Korea is an important judgment standard. Since there is no appropriate lung capacity prediction formula, various prediction formulas are used for foreigners such as Northeast Asians. The purpose of this study is to develop a lung capacity prediction equation by selecting data and setting the selection criteria for normal subjects in accordance with international standards through strict quality control, and to propose a new prediction model. Design: Preliminary feasibility study Methods: A total of 857 people who met the criteria for normal people were finally collected. The tester used for the lung capacity test was the V-Max Encore 22 (Carefusion, California, USA), which is a lung capacity tester proposed by the Korean Society of Tuberculosis and Respiratory Medicine and satisfies accuracy and precision. Among the indicators measured using spirometry, forced vital capacity (FVC), forced expiratory volume in 1 second (FEV₁), forced expiratory volume ratio in 1 second (FEV₁/FVC), forced mid-expiratory flow (Forced expiratory flow 25-75%, FEF25-75%) and peak expiratory flow (PEF) values were collected. Results: This study confirmed a significant correlation between age, height, weight, and pulmonary function indicators. Additionally, it found a correlation between body mass index, which considers the diversity of physical conditions, and pulmonary function indicators. Graphs depicting age-specific pulmonary function indicators by gender, presented as generalized additive model results from collected data, showed a pattern where both FVC and FEV1 increased until the mid-20s and then gradually decreased with aging. FEV1% and PEF exhibited a continuous decrease with aging. Conclusion: This study confirms that there is a significant correlation between weight and pulmonary function in the prediction formula for lung capacity. Additionally, it verifies the correlation between body mass index, which considers the diversity of physical conditions, and pulmonary function. The study suggests that the predicted values are relatively low due to factors such as aging and environmental influences like COVID-19. This preliminary study holds clinical significance for improving the diagnostic accuracy of respiratory symptoms in the elderly.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.373-381
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• 2021

In this paper, we propose a classification model based on convolutional neural network(CNN) for predicting 2-year recurrence in non-small cell lung cancer(NSCLC) patients using preoperative chest CT images. Based on the region of interest(ROI) defined as the tumor internal and external area, the input images consist of an intratumoral patch, a peritumoral patch and a peritumoral texture patch focusing on the texture information of the peritumoral patch. Each patch is trained through AlexNet pretrained on ImageNet to explore the usefulness and performance of various patches. Additionally, ensemble learning of network trained with each patch analyzes the performance of different patch combination. Compared with all results, the ensemble model with intratumoral and peritumoral patches achieved the best performance (ACC=98.28%, Sensitivity=100%, NPV=100%).

• The Journal of Pediatrics of Korean Medicine
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• v.22 no.2
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• pp.37-49
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• 2008

Objectives : Idiopathic pulmonary fibrosis (IPF) is chronic fibrotic interstitial pneumonia and the pathogenesis is unknown. Peucedani Radix is well-known for the treatment of respiratory diseases and pulmonary hypertension. This study was to evaluate the effectiveness of Peucedani Radix on the bleomycin-induced lung fibrosis model (BLFM) in mouse. Methods : We induced lung fibrosis by intratracheal instillation of bleomycin in C57BL/6J. We compared two groups BLFM without Peucedani Radix (group I) and BLFM with Peucedani Radix (group II). We performed bronchoalveolar lavages (BAL) and obtained lung specimens from both group I and II on the 7th (A) and 21st (B) day, and also for the normal group. We compared with group I and II to find BAL by using ANOVA test and to find pathologic symptoms by using semiquantitative histological index (SHI). Results : In BAL, total cell counts, lymphocytes, and neutrophils was increased in both group I and II comparing with normal group. However, lymphocyte level was decreased more in group IIB than group IB. It was statistically significant. In microscopic findings, scores of SHI in normal group, group IB and IIB were 0.33, 4.47, and 1.96 each. Conclusions : Peucedani Radix might have inhibitory effect on lung fibrosis by reducing inflammatory cells in bleomycin-induced lung fibrosis model in mouse.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.1067-1072
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• 2013

Hiwi, a human homologue of the Piwi family, plays an important role in stem cell self-renewal and is overexpressed in various human tumors. This study aimed to determine whether an RNA interference-based strategy to suppress Hiwi expression could inhibit tumor growth in a xenograft mouse model. A rare population of $SSC^{lo}\;Alde^{br}$ cells was isolated and identified as lung cancer stem cells in our previous study. Plasmids containing U6 promoter-driven shRNAs against Hiwi or control plasmids were successfully established. The xenograft tumor model was generated by subcutaneously inoculating with lung cancer stem cell $SSC^{lo}\;Alde^{br}$ cells. After the tumor size reached about 8 mm in diameter, shRNA plasmids were injected into the mice via the tail vein three times a week for two weeks, then xenograft tumor growth was assessed. In nude mice, intravenously delivery of Hiwi shRNA plasmids significantly inhibited tumor growth compared to treatment with control scrambled shRNA plasmids or the vehicle PBS. No mice died during the experiment and no adverse events were observed in mice administered the plasmids. Moreover, delivery of Hiwi shRNA plasmids resulted in a significant suppressed expression of Hiwi and ALDH-1 in xenograft tumor samples, based on immunohistochemical analysis. Thus, shRNA-mediated Hiwi gene silencing in lung cancer stem cells by an effective in vivo gene delivery strategy appeared to be an effective therapeutic approach for lung cancer, and may provide some useful clues for RNAi gene therapy in solid cancers.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4095-4099
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• 2014

The X-ray repair cross-complementing group 1 protein (XRCC1) plays important roles in the DNA base excision repair pathway which may influence the development of lung cancer. This study aimed to evaluate the potential association of the XRCC1 c.1178G>A genetic polymorphism with lung cancer risk. The created restriction site-polymerase chain reaction (CRS-PCR) and DNA sequencing methods were utilized to evaluate the XRCC1 c.1178G>A genetic polymorphism among 376 lung cancer patients and 379 controls. Associations between the genetic polymorphism and lung cancer risk were determined with an unconditional logistic regression model. Our data suggested that the distribution of allele and genotype in lung cancer patients was significantly different from that of controls. The XRCC1 c.1178G>A genetic polymorphism was associated with an increased risk of lung cancer (AA vs GG: OR=2.91, 95%CI 1.70-4.98, p<0.001; A vs G: OR=1.52, 95%CI 1.22-1.90, p<0.001). The allele A and genotype AA may contribute to risk of lung cancer. These preliminary results suggested that the XRCC1 c.1178G>A genetic polymorphism is statistically associated with lung cancer risk in the Chinese population.