Fucoxanthin is a pigment found in plants and animals such as algae， marine plankton and aquatic shellfish， and holds significant potential for development in the pharmaceutical field. This review introduces the anti-inflammatory， antioxidant， anticancer， anti-obesity， and other pharmacological effects of fucoxanthin， as well as recent advances in drug design research. It was found that fucoxanthin can exert anti-inflammatory and antioxidant effects through mechanisms such as activating AMP- activated protein kinase related signaling pathways， regulating the expression of inflammatory factors， altering microbial stability， thereby improving conditions such as metabolic associated fatty liver disease and colitis. It can exert selective antitumor effects through multi-target synergistic actions； and it was also found that it can exert anti-obesity effects by regulating the intestinal microbiota. Its characteristic functional groups （such as hydroxyl and epoxy groups） possess target specificity and reversible inhibitory properties， making it a suitable template for guiding the design and development of novel drugs， thereby providing new insights for breaking through the limitations of traditional drug design.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

Objective To summarize the imaging characteristics of occult rib fracture(ORF),analyze the causes of missed diagnosis and misdiagnosis of ORF,and explore strategies to improve the detection rate of ORF.Methods A total of 142 patients with rib fractures who underwent multi spiral computed tomography(MSCT)were selected.The initial examination was conducted within 1 week after the injury,and follow-up examinations were performed at multiple time points after 1 week post-injury.A retrospective analysis was conducted to review the fracture detection and locations during the follow-up period.The time of fracture edge sclerosis or callus growth was observed in the young group(17 cases),middle-aged group(64 cases),and elderly group(61 cases).Results The anterior segment of the ribs was the predilection site for occult fractures,with 199 cases(53.4％).The missed diagnosis rates of fracture were higher for fractures near the costal cartilage segment and the posterior segment of the ribs,with missed diagnosis rates of 49.4％and 58.8％,respectively.Compared with the number of rib fractures identified in the initial examination,there was a statistically significant difference in the number of rib fractures at 3-6 weeks after injury(P＜0.05).The time of local sclerosis or callus growth in the young,middle-aged and elderly groups was(18.76±3.849)d,(26.14±6.597)d,and(37.69±5.726)d,respectively,with statistically significantl differences between the groups(P＜0.05).Conclusion MSCT has certain limits in diagnosing ORF in the short term after injury.Primarily observing the predilection sites and missed sites of occult fractures,systematically recognizing the imaging characteristics of ORF,and adopting the optimal detection-time window for patients of different age groups can reduce the missed diagnosis rate and misdiagnosis rate of ORF and improve the detection rate of fractures.This provides accurate and objective basis for clinical and forensic identification,with significant clinical importance and application value.

Objective To explore the change of nucleoplasm distribution of glucocorticoid receptor alpha(GRα)in peripheral blood of children with primary nephrotic syndrome(PNS)during the course of the disease,aiming at evaluating the correlation between nuclear transport abnormality and different GC responses.Methods A total of 45 children with PNS were enrolled as subjects in this prospective study,and divided into steroid-sensitive nephrotic syndrome(SSNS,n=36)and steroid-resistant nephrotic syndrome(SRNS,n=9)groups,according to their response to GC.The SSNS group was further subclassified into non-frequently relapsing nephrotic syndrome(NFRNS,n=21)and frequently relapsing nephrotic syndrome(FRNS,n=15)based on relapse frequency during 12-month follow-up.Peripheral blood samples were collected before GC treatment,6-week and 6-month after GC treatment.GRα nuclear localization was detected by immunofluorescence assay,and their correlations with clinical-laboratory indicators were analyzed.Results Before the GC treatment,the average fluorescence intensity showed no significantly difference among different groups(P＞0.05),the GRαin the three groups were localized mainly in cytoplasm,and the nucleocytoplasmic ratio showed no significantly difference among the three groups(P＞0.05).6-week after the GC treatment,the average fluorescence intensity showed no significantly difference among the three groups(P＞0.05),the GRα in SSNS group were localized mainly in nucleus,while those in SRNS group were localized mainly in cytoplasm.Furthermore,nucleocytoplasmic ratio in NFRNS group and SRNS group demonstrated significant differences,while those in NFRNS group and FRNS group showed no significant difference(P＞0.05).6-month after the GC treatment,the average fluorescence intensity in NFRNS group and FRNS group showed no significant difference(P＞0.05),GRα in the two groups were localized mainly in nucleus,and their nucleocytoplasmic ratio had significantly differences(P＜0.05).The GRα nucleocytoplasmic ratio in children with PNS was negatively correlated with 24-hour urine protein(24 h-UTP),TNF-α,while positively correlated with serum albumin(Alb).Conclusion There are differences in nuclear transport ability among PNS children of SRNS,NFRNS and FRNS groups,and these differences are correlated with the differency of GC responses.

Objective:To explore the effect of psoas muscle index (PMI) and construct a machine learning model to validate the 180-day prognosis in patients with decompensated liver cirrhosis.Methods:Retrospective data were collected from patients with decompensated liver cirrhosis at Henan Provincial People's Hospital from January 2022 to November 2022. The area of the psoas muscle index (PMI) at the level of the third lumbar vertebra was measured and calculated based on the abdominal X-ray computed tomography images stored in the Eastern China Hospital Information System (HIS). Patients were divided into low PMI and normal PMI groups according to the receiver operating characteristic curve. Patients clinical data and complication status were collected.The general conditions of both groups were compared using a t-test, chi-square test, and Mann-Whitney U test. The Kaplan-Meier method was applied for survival analysis. The outcome variable was 180-day mortality, and variables were selected using Cox and LASSO regression. The dataset was divided into training and testing sets in a 7∶3 ratio. Machine learning algorithms were used to build models in the training set, and model performance was validated by the test set. The model for MELD-Na score was compared with the model for End-Stage Liver Disease score. Results:A total of 298 patients with decompensated liver cirrhosis were included.The MELD scores, Child-Pugh classification, and NRS2002 scores, along with the incidence rate of complications such as ascites, hepatic encephalopathy, infections, and gastrointestinal bleeding, were significantly higher in the low PMI than the normal PMI group, with statistically significant differences ( P<0.05). The area under a receiver operating characteristic curve for the extreme gradient boosting model was higher than traditional clinical scores (MELD score 0.658, MELD_Na score 0.719) in the machine learning model. Furthermore, the application of SHAP results model indicated that PMI, hemoglobin, NRS2002 score, direct bilirubin, and blood ammonia were important factors in predicting the prognosis of patients with decompensated liver cirrhosis. Conclusion:A low PMI is closely related to poorer survival rates and the development of complication rates in patients with decompensated liver cirrhosis. The machine learning prediction model based on this construction, especially extreme gradient boosting, has favorable predictive performance, which is superior to the traditional clinical scoring system and can provide patients with the most accurate risk assessment and individualized treatment plan.

Objective To explore the change of nucleoplasm distribution of glucocorticoid receptor alpha(GRα)in peripheral blood of children with primary nephrotic syndrome(PNS)during the course of the disease,aiming at evaluating the correlation between nuclear transport abnormality and different GC responses.Methods A total of 45 children with PNS were enrolled as subjects in this prospective study,and divided into steroid-sensitive nephrotic syndrome(SSNS,n=36)and steroid-resistant nephrotic syndrome(SRNS,n=9)groups,according to their response to GC.The SSNS group was further subclassified into non-frequently relapsing nephrotic syndrome(NFRNS,n=21)and frequently relapsing nephrotic syndrome(FRNS,n=15)based on relapse frequency during 12-month follow-up.Peripheral blood samples were collected before GC treatment,6-week and 6-month after GC treatment.GRα nuclear localization was detected by immunofluorescence assay,and their correlations with clinical-laboratory indicators were analyzed.Results Before the GC treatment,the average fluorescence intensity showed no significantly difference among different groups(P＞0.05),the GRαin the three groups were localized mainly in cytoplasm,and the nucleocytoplasmic ratio showed no significantly difference among the three groups(P＞0.05).6-week after the GC treatment,the average fluorescence intensity showed no significantly difference among the three groups(P＞0.05),the GRα in SSNS group were localized mainly in nucleus,while those in SRNS group were localized mainly in cytoplasm.Furthermore,nucleocytoplasmic ratio in NFRNS group and SRNS group demonstrated significant differences,while those in NFRNS group and FRNS group showed no significant difference(P＞0.05).6-month after the GC treatment,the average fluorescence intensity in NFRNS group and FRNS group showed no significant difference(P＞0.05),GRα in the two groups were localized mainly in nucleus,and their nucleocytoplasmic ratio had significantly differences(P＜0.05).The GRα nucleocytoplasmic ratio in children with PNS was negatively correlated with 24-hour urine protein(24 h-UTP),TNF-α,while positively correlated with serum albumin(Alb).Conclusion There are differences in nuclear transport ability among PNS children of SRNS,NFRNS and FRNS groups,and these differences are correlated with the differency of GC responses.

A method was developed for determination of dilauryl thiodipropionate(DLTDP)in fried foods by coupling solid-phase extraction(SPE)pretreatment with reverse-phase liquid chromatography-tandem mass spectrometry(RPLC-MS/MS)detection.Samples were extracted with n-hexane as the solvent,purified using a neutral alumina SPE cartridge,and finally analyzed by RPLC-MS/MS.Quantitative analysis was performed using matrix-matched calibration curves combined with an external standard method under optimal experimental conditions.The results showed that DLTDP exhibited good linearity in the range of 2.0-50.0 μg/L,with a correlation coefficient(R2)≥0.999.The limit of detection(LOD)and the limit of quantification(LOQ)of the method were 0.15 mg/kg and 0.5 mg/kg,respectively.The mean recoveries at three fortification levels(0.5,1.0,and 200 mg/kg)in different samples ranged from 84.8%to 96.8%,with the relative standard deviations(RSDs)all less than 8.0%.The developed method was highly sensitive,accurate and reliable,and easy to operate,making it well suited for the routine quantitative analysis of DLTDP in fried foods.

Objective To summarize the imaging characteristics of occult rib fracture(ORF),analyze the causes of missed diagnosis and misdiagnosis of ORF,and explore strategies to improve the detection rate of ORF.Methods A total of 142 patients with rib fractures who underwent multi spiral computed tomography(MSCT)were selected.The initial examination was conducted within 1 week after the injury,and follow-up examinations were performed at multiple time points after 1 week post-injury.A retrospective analysis was conducted to review the fracture detection and locations during the follow-up period.The time of fracture edge sclerosis or callus growth was observed in the young group(17 cases),middle-aged group(64 cases),and elderly group(61 cases).Results The anterior segment of the ribs was the predilection site for occult fractures,with 199 cases(53.4％).The missed diagnosis rates of fracture were higher for fractures near the costal cartilage segment and the posterior segment of the ribs,with missed diagnosis rates of 49.4％and 58.8％,respectively.Compared with the number of rib fractures identified in the initial examination,there was a statistically significant difference in the number of rib fractures at 3-6 weeks after injury(P＜0.05).The time of local sclerosis or callus growth in the young,middle-aged and elderly groups was(18.76±3.849)d,(26.14±6.597)d,and(37.69±5.726)d,respectively,with statistically significantl differences between the groups(P＜0.05).Conclusion MSCT has certain limits in diagnosing ORF in the short term after injury.Primarily observing the predilection sites and missed sites of occult fractures,systematically recognizing the imaging characteristics of ORF,and adopting the optimal detection-time window for patients of different age groups can reduce the missed diagnosis rate and misdiagnosis rate of ORF and improve the detection rate of fractures.This provides accurate and objective basis for clinical and forensic identification,with significant clinical importance and application value.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

Objective:To explore the effect of psoas muscle index (PMI) and construct a machine learning model to validate the 180-day prognosis in patients with decompensated liver cirrhosis.Methods:Retrospective data were collected from patients with decompensated liver cirrhosis at Henan Provincial People's Hospital from January 2022 to November 2022. The area of the psoas muscle index (PMI) at the level of the third lumbar vertebra was measured and calculated based on the abdominal X-ray computed tomography images stored in the Eastern China Hospital Information System (HIS). Patients were divided into low PMI and normal PMI groups according to the receiver operating characteristic curve. Patients clinical data and complication status were collected.The general conditions of both groups were compared using a t-test, chi-square test, and Mann-Whitney U test. The Kaplan-Meier method was applied for survival analysis. The outcome variable was 180-day mortality, and variables were selected using Cox and LASSO regression. The dataset was divided into training and testing sets in a 7∶3 ratio. Machine learning algorithms were used to build models in the training set, and model performance was validated by the test set. The model for MELD-Na score was compared with the model for End-Stage Liver Disease score. Results:A total of 298 patients with decompensated liver cirrhosis were included.The MELD scores, Child-Pugh classification, and NRS2002 scores, along with the incidence rate of complications such as ascites, hepatic encephalopathy, infections, and gastrointestinal bleeding, were significantly higher in the low PMI than the normal PMI group, with statistically significant differences ( P<0.05). The area under a receiver operating characteristic curve for the extreme gradient boosting model was higher than traditional clinical scores (MELD score 0.658, MELD_Na score 0.719) in the machine learning model. Furthermore, the application of SHAP results model indicated that PMI, hemoglobin, NRS2002 score, direct bilirubin, and blood ammonia were important factors in predicting the prognosis of patients with decompensated liver cirrhosis. Conclusion:A low PMI is closely related to poorer survival rates and the development of complication rates in patients with decompensated liver cirrhosis. The machine learning prediction model based on this construction, especially extreme gradient boosting, has favorable predictive performance, which is superior to the traditional clinical scoring system and can provide patients with the most accurate risk assessment and individualized treatment plan.