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.

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.

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.

Centralized monitoring is a risk-based remote monitoring mode that can effectively improve monitoring efficiency and quality. From July to September 2023, this study developed a centralized monitoring scheme for investigator initiated trials(IIT). This scheme utilized electronic data collection system and clinical research document management system, using programming techniques to compare the consistency of key project processes and data, monitor data filling, distribution trends, logical relationships, as well as documents such as informed consent forms, protocol violation records, and adverse event reports. It could timely identify problems in clinical trials and develop targeted response measures. From October to December 2023, 6 experts conducted centralized monitoring for 153 IIT projects using this scheme and found common issues in program execution(86 projects), ethical approvals(68 projects), and informed consent forms(67 projects), and so on. At the scome time, corresponding measures were developed. The process took a total of 20 days, with an average time of 6.27 hours per project. Compared with traditional on-site monitoring, the centralized monitoring scheme developed in this study had shown certain advantages in terms of timeliness, which could help guide the efficient implementation of on-site monitoring work and provide references for tertiary public hospitals to improve the quality of clinical trials.

Centralized monitoring is a risk-based remote monitoring mode that can effectively improve monitoring efficiency and quality. From July to September 2023, this study developed a centralized monitoring scheme for investigator initiated trials(IIT). This scheme utilized electronic data collection system and clinical research document management system, using programming techniques to compare the consistency of key project processes and data, monitor data filling, distribution trends, logical relationships, as well as documents such as informed consent forms, protocol violation records, and adverse event reports. It could timely identify problems in clinical trials and develop targeted response measures. From October to December 2023, 6 experts conducted centralized monitoring for 153 IIT projects using this scheme and found common issues in program execution(86 projects), ethical approvals(68 projects), and informed consent forms(67 projects), and so on. At the scome time, corresponding measures were developed. The process took a total of 20 days, with an average time of 6.27 hours per project. Compared with traditional on-site monitoring, the centralized monitoring scheme developed in this study had shown certain advantages in terms of timeliness, which could help guide the efficient implementation of on-site monitoring work and provide references for tertiary public hospitals to improve the quality of clinical trials.

Colloidal gold immunochromatographic strip is a fast, sensitive and accurate solid-phase labeling detection technology, which has the advantages of low price, easy operation, rapid detection and high specificity, with the potential to qualitatively detect the relevant viruses in a short time with desired sensitivity and accuracy. It effectively addresses the disadvantages of long detection time, equipment inconvenience and professionalism requirement of the traditional detection methods used in the medical, veterinary, animal, plant virus detection, pesticide residue detection and other areas. Presently, the technology has been applied in the detection of bacterial diseases, viral diseases and prevention of extensive spread of infectious diseases, and has sufficient room for further development. This review summarizes the application of colloidal gold immunochromatography strip for biological virus detection, followed by prospecting future perspectives.
Animals ; Antibodies, Monoclonal/chemistry* ; Chromatography, Affinity ; Gold Colloid/chemistry* ; Pesticide Residues ; Sensitivity and Specificity

AIMTo study the thermodynamics of precipitation reaction and kinetics between berberine and rheinic acid. The former is the main compound in rhubarb root or corktree bark, the latter is a representation of anthraquinone compounds that are the main kind compound in coptis rhizome. The precipitate produced in preparation of complex prescription of Chinese herbal medicines Xiexin decoction and Shaoyao decoction had made an appeal. The work should build a good basement for two decoctions research and development.

METHODSCapillary electrophoresis (CE) and front analysis methods are used for determining two compounds' equilibrium concentration at different precipitate conditions to calculate the constants of thermodynamics and kinetics.

RESULTSThe molar ratio of berberine and rheinic acid in precipitate is 1:1. The solubility product constant Ksp = [B] [R] = (3.29 +/- 0.19) x 10(-9) mol2.L-2. The precipitate reaction is an endotherm process and Ksp shows less effect by temperature. The reaction occurred immediately even though the precipitate cannot be observed in time. The precipitate process in experiments is practically just an aging or grown process of the precipitate particles. High temperature can quicken the aging.

CONCLUSIONThe precipitate in Chinese herbal medicines Xiexin decoction and Shaoyao decoction should be resulted from anthraquinone compounds and alkaloids. The reproductivity of capillary electrophoresis can be improved for simple sample by combining peak height measurement.

Anthraquinones ; analysis ; chemistry ; Berberine ; analysis ; chemistry ; Chemical Precipitation ; Drug Interactions ; Electrophoresis, Capillary ; Solubility