Anticancer activities of Licochalcone D (LCD) in human colorectal cancer (CRC) cells HCT116 and oxaliplatin-resistant HCT116 (HCT116-OxR) were determined. Cell viability assay and soft agar assay were used to analyze antiproliferative activity of LCD.Flow cytometry was performed to determine effects of LCD on apoptosis, cell cycle distribution, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) dysfunction, and multi-caspase activity in CRC cells. Western blot analysis was used to monitor levels of proteins involved in cell cycle and apoptosis signaling pathways. LCD suppressed the growth and anchorageindependent colony formation of both HCT116 and HCT116-OxR cells. Cell cycle analysis by flow cytometry indicated that LCD induced cell cycle arrest and increased cells in sub-G1 phase. In parallel with the antiproliferative effect of LCD, LCD up-regulated levels of p21 and p27 while downregulating cyclin B1 and cdc2. In addition, phosphorylation levels of JNK and p38 mitogen-activated protein kinase (MAPK) were increased by LCD. Inhibition of these kinases somehow prevented the antiproliferative effect of LCD. Moreover, LCD increased ROS and deregulated mitochondrial membrane potential, leading to the activation of multiple caspases. An ROS scavenger N-acetyl-cysteine (NAC) or pan-caspase inhibitor Z-VAD-FMK prevented the antiproliferative effect of LCD, supporting that ROS generation and caspase activation mediated LCD-induced apoptosis in CRC cells. In conclusion, LCD exerted antitumor activity in CRC cells by inducing ROS generation and phosphorylation of JNK and p38 MAPK. These results support that LCD could be further developed as a chemotherapeutic agent for treating CRC.

Anticancer activities of Licochalcone D (LCD) in human colorectal cancer (CRC) cells HCT116 and oxaliplatin-resistant HCT116 (HCT116-OxR) were determined. Cell viability assay and soft agar assay were used to analyze antiproliferative activity of LCD.Flow cytometry was performed to determine effects of LCD on apoptosis, cell cycle distribution, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) dysfunction, and multi-caspase activity in CRC cells. Western blot analysis was used to monitor levels of proteins involved in cell cycle and apoptosis signaling pathways. LCD suppressed the growth and anchorageindependent colony formation of both HCT116 and HCT116-OxR cells. Cell cycle analysis by flow cytometry indicated that LCD induced cell cycle arrest and increased cells in sub-G1 phase. In parallel with the antiproliferative effect of LCD, LCD up-regulated levels of p21 and p27 while downregulating cyclin B1 and cdc2. In addition, phosphorylation levels of JNK and p38 mitogen-activated protein kinase (MAPK) were increased by LCD. Inhibition of these kinases somehow prevented the antiproliferative effect of LCD. Moreover, LCD increased ROS and deregulated mitochondrial membrane potential, leading to the activation of multiple caspases. An ROS scavenger N-acetyl-cysteine (NAC) or pan-caspase inhibitor Z-VAD-FMK prevented the antiproliferative effect of LCD, supporting that ROS generation and caspase activation mediated LCD-induced apoptosis in CRC cells. In conclusion, LCD exerted antitumor activity in CRC cells by inducing ROS generation and phosphorylation of JNK and p38 MAPK. These results support that LCD could be further developed as a chemotherapeutic agent for treating CRC.

Anticancer activities of Licochalcone D (LCD) in human colorectal cancer (CRC) cells HCT116 and oxaliplatin-resistant HCT116 (HCT116-OxR) were determined. Cell viability assay and soft agar assay were used to analyze antiproliferative activity of LCD.Flow cytometry was performed to determine effects of LCD on apoptosis, cell cycle distribution, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) dysfunction, and multi-caspase activity in CRC cells. Western blot analysis was used to monitor levels of proteins involved in cell cycle and apoptosis signaling pathways. LCD suppressed the growth and anchorageindependent colony formation of both HCT116 and HCT116-OxR cells. Cell cycle analysis by flow cytometry indicated that LCD induced cell cycle arrest and increased cells in sub-G1 phase. In parallel with the antiproliferative effect of LCD, LCD up-regulated levels of p21 and p27 while downregulating cyclin B1 and cdc2. In addition, phosphorylation levels of JNK and p38 mitogen-activated protein kinase (MAPK) were increased by LCD. Inhibition of these kinases somehow prevented the antiproliferative effect of LCD. Moreover, LCD increased ROS and deregulated mitochondrial membrane potential, leading to the activation of multiple caspases. An ROS scavenger N-acetyl-cysteine (NAC) or pan-caspase inhibitor Z-VAD-FMK prevented the antiproliferative effect of LCD, supporting that ROS generation and caspase activation mediated LCD-induced apoptosis in CRC cells. In conclusion, LCD exerted antitumor activity in CRC cells by inducing ROS generation and phosphorylation of JNK and p38 MAPK. These results support that LCD could be further developed as a chemotherapeutic agent for treating CRC.

Purpose: There is a high possibility of trauma patients being referred to an unsuitable medical institution for their rehabilitation treatment since the decision is made by them. This study sought to develop a standardized scale to evaluate the need for specialized rehabilitation in patients with multiple traumas and evaluate the effectiveness of the developed scale. Methods: This study employed a systematic review of existing literature to inform the development of a specialized rehabilitation evaluation scale. An expert panel consisting of trauma surgeons, orthopedic surgeons, and rehabilitation medicine physicians collaborated to create a discharge-planning checklist by assessing the need for specialized rehabilitation. The checklist was validated using retrospective data from trauma patients treated at Seoul National University Hospital. Results: We identified 12 studies, providing factors influencing the discharge location and rehabilitation needs of trauma patients. The checklist was developed through expert consensus and comprised 3 criteria: discharge feasibility to specialized rehabilitation facilities, diagnostic eligibility for specialized rehabilitation, and functional assessment. Validation of the checklist demonstrated that the percentage agreement, likelihood ratio of a positive test, and Cohen’s kappa value were 82.1%, 5.21, and 0.375, respectively when comparing whether the checklist was met and the actual discharge location, indicating its effectiveness. Conclusion This study established standardized criteria for assessing the need for specialized rehabilitation in trauma patients, offering a practical tool for clinical use. Implementation of this assessment scale has the potential to improve the trajectory of trauma survivors by facilitating access to appropriate rehabilitation services.

Purpose: There is a high possibility of trauma patients being referred to an unsuitable medical institution for their rehabilitation treatment since the decision is made by them. This study sought to develop a standardized scale to evaluate the need for specialized rehabilitation in patients with multiple traumas and evaluate the effectiveness of the developed scale. Methods: This study employed a systematic review of existing literature to inform the development of a specialized rehabilitation evaluation scale. An expert panel consisting of trauma surgeons, orthopedic surgeons, and rehabilitation medicine physicians collaborated to create a discharge-planning checklist by assessing the need for specialized rehabilitation. The checklist was validated using retrospective data from trauma patients treated at Seoul National University Hospital. Results: We identified 12 studies, providing factors influencing the discharge location and rehabilitation needs of trauma patients. The checklist was developed through expert consensus and comprised 3 criteria: discharge feasibility to specialized rehabilitation facilities, diagnostic eligibility for specialized rehabilitation, and functional assessment. Validation of the checklist demonstrated that the percentage agreement, likelihood ratio of a positive test, and Cohen’s kappa value were 82.1%, 5.21, and 0.375, respectively when comparing whether the checklist was met and the actual discharge location, indicating its effectiveness. Conclusion This study established standardized criteria for assessing the need for specialized rehabilitation in trauma patients, offering a practical tool for clinical use. Implementation of this assessment scale has the potential to improve the trajectory of trauma survivors by facilitating access to appropriate rehabilitation services.

Purpose: There is a high possibility of trauma patients being referred to an unsuitable medical institution for their rehabilitation treatment since the decision is made by them. This study sought to develop a standardized scale to evaluate the need for specialized rehabilitation in patients with multiple traumas and evaluate the effectiveness of the developed scale. Methods: This study employed a systematic review of existing literature to inform the development of a specialized rehabilitation evaluation scale. An expert panel consisting of trauma surgeons, orthopedic surgeons, and rehabilitation medicine physicians collaborated to create a discharge-planning checklist by assessing the need for specialized rehabilitation. The checklist was validated using retrospective data from trauma patients treated at Seoul National University Hospital. Results: We identified 12 studies, providing factors influencing the discharge location and rehabilitation needs of trauma patients. The checklist was developed through expert consensus and comprised 3 criteria: discharge feasibility to specialized rehabilitation facilities, diagnostic eligibility for specialized rehabilitation, and functional assessment. Validation of the checklist demonstrated that the percentage agreement, likelihood ratio of a positive test, and Cohen’s kappa value were 82.1%, 5.21, and 0.375, respectively when comparing whether the checklist was met and the actual discharge location, indicating its effectiveness. Conclusion This study established standardized criteria for assessing the need for specialized rehabilitation in trauma patients, offering a practical tool for clinical use. Implementation of this assessment scale has the potential to improve the trajectory of trauma survivors by facilitating access to appropriate rehabilitation services.

Background/Aims: Shifts in the gut microbiota and metabolites are interrelated with liver cirrhosis progression and complications. However, causal relationships have not been evaluated comprehensively. Here, we identified complication-dependent gut microbiota and metabolic signatures in patients with liver cirrhosis. Methods: Microbiome taxonomic profiling was performed on 194 stool samples (52 controls and 142 cirrhosis patients) via V3-V4 16S rRNA sequencing. Next, 51 samples (17 controls and 34 cirrhosis patients) were selected for fecal metabolite profiling via gas chromatography mass spectrometry and liquid chromatography coupled to timeof-flight mass spectrometry. Correlation analyses were performed targeting the gut-microbiota, metabolites, clinical parameters, and presence of complications (varices, ascites, peritonitis, encephalopathy, hepatorenal syndrome, hepatocellular carcinoma, and deceased). Results: Veillonella bacteria, Ruminococcus gnavus, and Streptococcus pneumoniae are cirrhosis-related microbiotas compared with control group. Bacteroides ovatus, Clostridium symbiosum, Emergencia timonensis, Fusobacterium varium, and Hungatella_uc were associated with complications in the cirrhosis group. The areas under the receiver operating characteristic curve (AUROCs) for the diagnosis of cirrhosis, encephalopathy, hepatorenal syndrome, and deceased were 0.863, 0.733, 0.71, and 0.69, respectively. The AUROCs of mixed microbial species for the diagnosis of cirrhosis and complication were 0.808 and 0.847, respectively. According to the metabolic profile, 5 increased fecal metabolites in patients with cirrhosis were biomarkers (AUROC >0.880) for the diagnosis of cirrhosis and complications. Clinical markers were significantly correlated with the gut microbiota and metabolites. Conclusions Cirrhosis-dependent gut microbiota and metabolites present unique signatures that can be used as noninvasive biomarkers for the diagnosis of cirrhosis and its complications.