Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and increased inflammation, leading to respiratory symptoms. This study aimed to identify the traits for COPD progression from mild to severe stages. Additionally, we explored the correlation between coronavirus disease-2019 (COVID-19) and COPD to uncover overlapping respiratory patterns. Materials and Methods: Bulk RNA sequencing was conducted on data from 43 healthy individuals and 39 COPD patients across one dataset (GSE239897) to distinguish COPD characteristics. Single-cell RNA analysis was then performed on samples from seven mild patients, seven moderate patients, and three severe patients from three datasets (GSE167295, GSE173896, and GSE227691) to analyze disease progression. Finally, single-nuclei RNA analysis was applied to data from seven healthy individuals and 20 COVID-19 patients from one dataset (GSE171524) to compare the two conditions. Results: Bulk RNA sequencing revealed enhanced inflammatory pathways in COPD patients, indicating increased inflammation.Single-cell RNA sequencing showed a stronger inflammatory response from mild to moderate COPD with a decrease from moderate to severe stages. COVID-19 displayed similar biological patterns to moderate COPD, suggesting that stage-specific COPD analysis could enhance COVID-19 management. Conclusion The analysis found that immune responses increased from mild to moderate stages but declined in severe cases, marked by reduced pulmonary T cell activation. The overlap between moderate COPD and COVID-19 suggests shared therapeutic strategies, warranting further investigation.

Modern drug discovery is driven by high demand in the pharmaceutical industry to test growing libraries of compounds against potential targets. High-throughput screening (HTS) is characterized by fully automated experimentation that leverages robotic liquid handling systems, analytical techniques, and advanced computing and statistics, including the recent integration of artificial intelligence. To align with this trend, it is crucial to develop and implement new HTS platforms that offer improved predictivity and physiological relevance. In recent years, microphysiological systems, commonly known as organ-on-chip (OoC) systems, have progressed from a theoretical concept to a powerful alternative to conventional in vitro and animal models. High-throughput OoC (HT-OoC) systems could represent the disruptive technology sought by pharmaceutical companies to address their enormous research and development (R&D) expenses. In this study, we provide a brief overview of commercial products utilizing modern HT-OoC systems in drug discovery and development. Additionally, we discuss recent trends in R&D aimed at industrialization.

Modern drug discovery is driven by high demand in the pharmaceutical industry to test growing libraries of compounds against potential targets. High-throughput screening (HTS) is characterized by fully automated experimentation that leverages robotic liquid handling systems, analytical techniques, and advanced computing and statistics, including the recent integration of artificial intelligence. To align with this trend, it is crucial to develop and implement new HTS platforms that offer improved predictivity and physiological relevance. In recent years, microphysiological systems, commonly known as organ-on-chip (OoC) systems, have progressed from a theoretical concept to a powerful alternative to conventional in vitro and animal models. High-throughput OoC (HT-OoC) systems could represent the disruptive technology sought by pharmaceutical companies to address their enormous research and development (R&D) expenses. In this study, we provide a brief overview of commercial products utilizing modern HT-OoC systems in drug discovery and development. Additionally, we discuss recent trends in R&D aimed at industrialization.

Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and increased inflammation, leading to respiratory symptoms. This study aimed to identify the traits for COPD progression from mild to severe stages. Additionally, we explored the correlation between coronavirus disease-2019 (COVID-19) and COPD to uncover overlapping respiratory patterns. Materials and Methods: Bulk RNA sequencing was conducted on data from 43 healthy individuals and 39 COPD patients across one dataset (GSE239897) to distinguish COPD characteristics. Single-cell RNA analysis was then performed on samples from seven mild patients, seven moderate patients, and three severe patients from three datasets (GSE167295, GSE173896, and GSE227691) to analyze disease progression. Finally, single-nuclei RNA analysis was applied to data from seven healthy individuals and 20 COVID-19 patients from one dataset (GSE171524) to compare the two conditions. Results: Bulk RNA sequencing revealed enhanced inflammatory pathways in COPD patients, indicating increased inflammation.Single-cell RNA sequencing showed a stronger inflammatory response from mild to moderate COPD with a decrease from moderate to severe stages. COVID-19 displayed similar biological patterns to moderate COPD, suggesting that stage-specific COPD analysis could enhance COVID-19 management. Conclusion The analysis found that immune responses increased from mild to moderate stages but declined in severe cases, marked by reduced pulmonary T cell activation. The overlap between moderate COPD and COVID-19 suggests shared therapeutic strategies, warranting further investigation.

Modern drug discovery is driven by high demand in the pharmaceutical industry to test growing libraries of compounds against potential targets. High-throughput screening (HTS) is characterized by fully automated experimentation that leverages robotic liquid handling systems, analytical techniques, and advanced computing and statistics, including the recent integration of artificial intelligence. To align with this trend, it is crucial to develop and implement new HTS platforms that offer improved predictivity and physiological relevance. In recent years, microphysiological systems, commonly known as organ-on-chip (OoC) systems, have progressed from a theoretical concept to a powerful alternative to conventional in vitro and animal models. High-throughput OoC (HT-OoC) systems could represent the disruptive technology sought by pharmaceutical companies to address their enormous research and development (R&D) expenses. In this study, we provide a brief overview of commercial products utilizing modern HT-OoC systems in drug discovery and development. Additionally, we discuss recent trends in R&D aimed at industrialization.

Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and increased inflammation, leading to respiratory symptoms. This study aimed to identify the traits for COPD progression from mild to severe stages. Additionally, we explored the correlation between coronavirus disease-2019 (COVID-19) and COPD to uncover overlapping respiratory patterns. Materials and Methods: Bulk RNA sequencing was conducted on data from 43 healthy individuals and 39 COPD patients across one dataset (GSE239897) to distinguish COPD characteristics. Single-cell RNA analysis was then performed on samples from seven mild patients, seven moderate patients, and three severe patients from three datasets (GSE167295, GSE173896, and GSE227691) to analyze disease progression. Finally, single-nuclei RNA analysis was applied to data from seven healthy individuals and 20 COVID-19 patients from one dataset (GSE171524) to compare the two conditions. Results: Bulk RNA sequencing revealed enhanced inflammatory pathways in COPD patients, indicating increased inflammation.Single-cell RNA sequencing showed a stronger inflammatory response from mild to moderate COPD with a decrease from moderate to severe stages. COVID-19 displayed similar biological patterns to moderate COPD, suggesting that stage-specific COPD analysis could enhance COVID-19 management. Conclusion The analysis found that immune responses increased from mild to moderate stages but declined in severe cases, marked by reduced pulmonary T cell activation. The overlap between moderate COPD and COVID-19 suggests shared therapeutic strategies, warranting further investigation.

Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and increased inflammation, leading to respiratory symptoms. This study aimed to identify the traits for COPD progression from mild to severe stages. Additionally, we explored the correlation between coronavirus disease-2019 (COVID-19) and COPD to uncover overlapping respiratory patterns. Materials and Methods: Bulk RNA sequencing was conducted on data from 43 healthy individuals and 39 COPD patients across one dataset (GSE239897) to distinguish COPD characteristics. Single-cell RNA analysis was then performed on samples from seven mild patients, seven moderate patients, and three severe patients from three datasets (GSE167295, GSE173896, and GSE227691) to analyze disease progression. Finally, single-nuclei RNA analysis was applied to data from seven healthy individuals and 20 COVID-19 patients from one dataset (GSE171524) to compare the two conditions. Results: Bulk RNA sequencing revealed enhanced inflammatory pathways in COPD patients, indicating increased inflammation.Single-cell RNA sequencing showed a stronger inflammatory response from mild to moderate COPD with a decrease from moderate to severe stages. COVID-19 displayed similar biological patterns to moderate COPD, suggesting that stage-specific COPD analysis could enhance COVID-19 management. Conclusion The analysis found that immune responses increased from mild to moderate stages but declined in severe cases, marked by reduced pulmonary T cell activation. The overlap between moderate COPD and COVID-19 suggests shared therapeutic strategies, warranting further investigation.

Purpose: Chronic obstructive pulmonary disease (COPD) is characterized by alveolar destruction and increased inflammation, leading to respiratory symptoms. This study aimed to identify the traits for COPD progression from mild to severe stages. Additionally, we explored the correlation between coronavirus disease-2019 (COVID-19) and COPD to uncover overlapping respiratory patterns. Materials and Methods: Bulk RNA sequencing was conducted on data from 43 healthy individuals and 39 COPD patients across one dataset (GSE239897) to distinguish COPD characteristics. Single-cell RNA analysis was then performed on samples from seven mild patients, seven moderate patients, and three severe patients from three datasets (GSE167295, GSE173896, and GSE227691) to analyze disease progression. Finally, single-nuclei RNA analysis was applied to data from seven healthy individuals and 20 COVID-19 patients from one dataset (GSE171524) to compare the two conditions. Results: Bulk RNA sequencing revealed enhanced inflammatory pathways in COPD patients, indicating increased inflammation.Single-cell RNA sequencing showed a stronger inflammatory response from mild to moderate COPD with a decrease from moderate to severe stages. COVID-19 displayed similar biological patterns to moderate COPD, suggesting that stage-specific COPD analysis could enhance COVID-19 management. Conclusion The analysis found that immune responses increased from mild to moderate stages but declined in severe cases, marked by reduced pulmonary T cell activation. The overlap between moderate COPD and COVID-19 suggests shared therapeutic strategies, warranting further investigation.

Purpose: The purpose of this study was to identify the predictors influencing fear of falling in community-dwelling elderly women with mild cognitive impairment (MCI). Methods: A secondary data analysis was performed using data of 65 years or older elderly women with MCI participating in the 7th Korea Longitudinal Study of Ageing of the Korea Employment Information Service. The study subjects included 368 elderly women with MCI. For data analysis, descriptive statistics and logistic regression with complex samples were performed using IBM SPSS ver. 23.0. Results: 89.9% of the elderly women with MCI had fear of falling. There were significant factors such as religion (OR=8.85, 95% CI: 3.39~23.15), restriction of activity (OR=6.84, 95% CI: 2.14~21.90), depression (OR=0.75, 95% CI: 0.62~0.90), and MMSE (OR=1.30, 95% CI: 1.03~1.63), predicting fear of falling in community-dwelling elderly women with MCI. Conclusion Differentiated strategies should be developed for elderly women with MCI to decrease fear of falling and prevent falls with understanding of contributing factors. This study will provide fundamental information on programming and a policy proposal related to fear of falling for elderly women with MCI.