Intraflagellar transport (IFT) particles, a multi-protein apparatus composed of complex A and B, are known to be involved in homeostasis of flagella formation. IFT particles have recently become an interesting topic in Giardia lamblia, which has 4 pairs of flagella. In this experiment, we examined the function of giardial IFT components. When 7 components (IFT121, 140, 20, 46, 52, 81, and 88) of IFT were expressed in Giardia trophozoites as a tagged form with mNeonGreen, all of them were found in both flagella pores and cytoplasmic axonemes. In addition, motor proteins for IFT particles (kinesin-13 and kinesin-2b), were localized to a median body and cytoplasmic flagella, respectively. The CRISPRi-mediated knockdown of IFT88 significantly affected the lengths of all 4 flagella compared to the control cells, Giardia expressing dead Cas9 using control guide RNA. Decreased expression of kinesin-2b also resulted in shortening of flagella, excluding the ventral flagella. Live Giardia cells expressing IFT88-mNeonGreen clearly demonstrated fluorescence in flagella pores and cytoplasmic axonemes. These results on IFT88 and kinesin-2b indicate that IFT complex plays a role in maintenance of G. lamblia flagella.

Intraflagellar transport (IFT) particles, a multi-protein apparatus composed of complex A and B, are known to be involved in homeostasis of flagella formation. IFT particles have recently become an interesting topic in Giardia lamblia, which has 4 pairs of flagella. In this experiment, we examined the function of giardial IFT components. When 7 components (IFT121, 140, 20, 46, 52, 81, and 88) of IFT were expressed in Giardia trophozoites as a tagged form with mNeonGreen, all of them were found in both flagella pores and cytoplasmic axonemes. In addition, motor proteins for IFT particles (kinesin-13 and kinesin-2b), were localized to a median body and cytoplasmic flagella, respectively. The CRISPRi-mediated knockdown of IFT88 significantly affected the lengths of all 4 flagella compared to the control cells, Giardia expressing dead Cas9 using control guide RNA. Decreased expression of kinesin-2b also resulted in shortening of flagella, excluding the ventral flagella. Live Giardia cells expressing IFT88-mNeonGreen clearly demonstrated fluorescence in flagella pores and cytoplasmic axonemes. These results on IFT88 and kinesin-2b indicate that IFT complex plays a role in maintenance of G. lamblia flagella.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Intraflagellar transport (IFT) particles, a multi-protein apparatus composed of complex A and B, are known to be involved in homeostasis of flagella formation. IFT particles have recently become an interesting topic in Giardia lamblia, which has 4 pairs of flagella. In this experiment, we examined the function of giardial IFT components. When 7 components (IFT121, 140, 20, 46, 52, 81, and 88) of IFT were expressed in Giardia trophozoites as a tagged form with mNeonGreen, all of them were found in both flagella pores and cytoplasmic axonemes. In addition, motor proteins for IFT particles (kinesin-13 and kinesin-2b), were localized to a median body and cytoplasmic flagella, respectively. The CRISPRi-mediated knockdown of IFT88 significantly affected the lengths of all 4 flagella compared to the control cells, Giardia expressing dead Cas9 using control guide RNA. Decreased expression of kinesin-2b also resulted in shortening of flagella, excluding the ventral flagella. Live Giardia cells expressing IFT88-mNeonGreen clearly demonstrated fluorescence in flagella pores and cytoplasmic axonemes. These results on IFT88 and kinesin-2b indicate that IFT complex plays a role in maintenance of G. lamblia flagella.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

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.

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.

Intraflagellar transport (IFT) particles, a multi-protein apparatus composed of complex A and B, are known to be involved in homeostasis of flagella formation. IFT particles have recently become an interesting topic in Giardia lamblia, which has 4 pairs of flagella. In this experiment, we examined the function of giardial IFT components. When 7 components (IFT121, 140, 20, 46, 52, 81, and 88) of IFT were expressed in Giardia trophozoites as a tagged form with mNeonGreen, all of them were found in both flagella pores and cytoplasmic axonemes. In addition, motor proteins for IFT particles (kinesin-13 and kinesin-2b), were localized to a median body and cytoplasmic flagella, respectively. The CRISPRi-mediated knockdown of IFT88 significantly affected the lengths of all 4 flagella compared to the control cells, Giardia expressing dead Cas9 using control guide RNA. Decreased expression of kinesin-2b also resulted in shortening of flagella, excluding the ventral flagella. Live Giardia cells expressing IFT88-mNeonGreen clearly demonstrated fluorescence in flagella pores and cytoplasmic axonemes. These results on IFT88 and kinesin-2b indicate that IFT complex plays a role in maintenance of G. lamblia flagella.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.