Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Objective: It has been 1 year since the start of the worldwide coronavirus disease-19 (COVID-19) pandemic. This study analyzed the indirect effects of COVID-19 on treating patients with non-infectious diseases by comparing the incidence of complicated appendicitis before and after the pandemic. Methods: The target group included patients aged at least 16 years diagnosed with acute appendicitis between February 23 and July 31, 2020. Patients diagnosed during the same period in 2019 were selected as the control group. The differences in the incidence of complicated appendicitis before and after COVID-19 were investigated, and the association with various variables was analyzed using the odds ratios and 95% confidence intervals (CIs). Results: The study included 120 subjects in 2019 (pre-COVID group) and 119 cases in 2020 (post-COVID group). The pre-COVID group included 25 cases (20.8%) of complicated appendicitis, while the post-COVID group included 48 cases (40.3%). The median time from symptom onset to visit (pre-hospital time) increased from 15 to 22 hours, and the median time from the visit to surgery (in-hospital time) increased from 7 to 11 hours. Multivariate regression analysis of the three variables revealed odds ratios (95% CIs) of pre-hospital time, erythrocyte sedimentation rate, and inclusion in the post-COVID group of 1.02 (1.01-1.02), 2.07 (1.11-3.86), and 2.15 (1.12-4.11), respectively. Conclusion The incidence of complicated appendicitis increased after the COVID-19 pandemic. Therefore, a healthcare system that can minimize the delay in treating non-infectious emergency patients is needed.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Objective: It has been 1 year since the start of the worldwide coronavirus disease-19 (COVID-19) pandemic. This study analyzed the indirect effects of COVID-19 on treating patients with non-infectious diseases by comparing the incidence of complicated appendicitis before and after the pandemic. Methods: The target group included patients aged at least 16 years diagnosed with acute appendicitis between February 23 and July 31, 2020. Patients diagnosed during the same period in 2019 were selected as the control group. The differences in the incidence of complicated appendicitis before and after COVID-19 were investigated, and the association with various variables was analyzed using the odds ratios and 95% confidence intervals (CIs). Results: The study included 120 subjects in 2019 (pre-COVID group) and 119 cases in 2020 (post-COVID group). The pre-COVID group included 25 cases (20.8%) of complicated appendicitis, while the post-COVID group included 48 cases (40.3%). The median time from symptom onset to visit (pre-hospital time) increased from 15 to 22 hours, and the median time from the visit to surgery (in-hospital time) increased from 7 to 11 hours. Multivariate regression analysis of the three variables revealed odds ratios (95% CIs) of pre-hospital time, erythrocyte sedimentation rate, and inclusion in the post-COVID group of 1.02 (1.01-1.02), 2.07 (1.11-3.86), and 2.15 (1.12-4.11), respectively. Conclusion The incidence of complicated appendicitis increased after the COVID-19 pandemic. Therefore, a healthcare system that can minimize the delay in treating non-infectious emergency patients is needed.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Objective: It has been 1 year since the start of the worldwide coronavirus disease-19 (COVID-19) pandemic. This study analyzed the indirect effects of COVID-19 on treating patients with non-infectious diseases by comparing the incidence of complicated appendicitis before and after the pandemic. Methods: The target group included patients aged at least 16 years diagnosed with acute appendicitis between February 23 and July 31, 2020. Patients diagnosed during the same period in 2019 were selected as the control group. The differences in the incidence of complicated appendicitis before and after COVID-19 were investigated, and the association with various variables was analyzed using the odds ratios and 95% confidence intervals (CIs). Results: The study included 120 subjects in 2019 (pre-COVID group) and 119 cases in 2020 (post-COVID group). The pre-COVID group included 25 cases (20.8%) of complicated appendicitis, while the post-COVID group included 48 cases (40.3%). The median time from symptom onset to visit (pre-hospital time) increased from 15 to 22 hours, and the median time from the visit to surgery (in-hospital time) increased from 7 to 11 hours. Multivariate regression analysis of the three variables revealed odds ratios (95% CIs) of pre-hospital time, erythrocyte sedimentation rate, and inclusion in the post-COVID group of 1.02 (1.01-1.02), 2.07 (1.11-3.86), and 2.15 (1.12-4.11), respectively. Conclusion The incidence of complicated appendicitis increased after the COVID-19 pandemic. Therefore, a healthcare system that can minimize the delay in treating non-infectious emergency patients is needed.

Objectives: Presenteeism is known to be a much more economically damaging social cost than disease rest while going to work despite physical pain. Since COVID-19, social discussions on the sickness benefit have been taking place as a countermeasure against presenteeism, and in particular, farmers and fishermen do not have an institutional mechanism for livelihood support when a disease other than work occurs. This study attempted to examine the relationship between agricultural, fishing, and forestry workers and presenteeism using the 6th Korean Work Conditions Survey. Methods: From October 2020 to January 2021, data from the 6th working conditions survey conducted on 17 cities and provinces in Korea were used, and a total of 34,981 people were studied. Control variables were gender, age, self-health assessment, education level, night work, shift work, monthly income, occupation, working hours per week, and employment status. Results: As a result of the analysis, farmers and fishermen showed the characteristics of the self-employed and the elderly, and as a result of the regression analysis, when farmers and fishermen analyzed the relationship with presenteeism tendency compared to other industry workers, farmers and fishermen increased by 23% compared to other industry groups. Conclusion This study is significant in that it has representation by utilizing the 6th working conditions survey and objectively suggests the need for a sickness benefit for farmers and fishermen who may be overlooked in the sickness benefit.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.