Acute lung injury （ALI） is one of the most common and critical diseases in clinical practice， with extremely high morbidity and mortality， seriously threatening human life and health. The pathogenesis of ALI is complex， in which the inflammatory response is a key factor. Studies have shown that NOD-like receptor protein 3 （NLRP3） inflammasomes are involved in ALI through mechanisms such as inflammation induction， increased microvascular permeability， recruitment of neutrophils， oxidative stress， and pyroptosis， playing a key role in the occurrence and progression of ALI. Therefore， regulating NLRP3 inflammasomes and inhibiting the release of inflammatory factors can alleviate the damage in ALI. At present， ALI is mainly treated by mechanical ventilation and oxygen therapy， which have problems such as high costs and poor prognosis. In recent years， studies have shown that traditional Chinese medicine （TCM） can reduce the inflammatory response and the occurrence of oxidative stress and pyroptosis by regulating the NLRP3 inflammasome， thus alleviating the damage and decreasing the mortality of ALI. Based on the relevant literature in recent years， this article reviews the research progress in TCM treatment of ALI by regulating NLRP3 inflammasomes， discusses how NLRP3 inflammasomes participate in ALI， and summarizes the active ingredients， extracts， and compound prescriptions of TCM that regulate NLRP3 inflammasomes， aiming to provide new ideas for the clinical treatment of ALI and the development of relevant drugs.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.