Objective:To investigate the interventional effect of Rhizoma Corydalis on mice with ulcerative colitis(UC)induced by dextran sulfate sodium(DSS),as well as the potential mechanism of Rhizoma Corydalis in the treatment of UC based on metabolomics and inflammation biomarkers.Methods:A mouse model of UC was established,and then the mice were divided into model group,high-dose group(1.517 g/kg crude drug),middle-dose group(0.986 g/kg crude drug),low-dose group(0.455 g/kg crude drug),and positive drug group(5-aminosalicylic acid at a dose of 718.8 mg/kg),while the mice without modeling were selected as normal group(0.9%NaCl by gavage).The mice in each group were administered for 7 consecutive days,and phenotypic parameters were dynamically moni-tored,such as body weight change,disease activity index(DAI),mean daily food intake,and daily water intake.The mice were sacri-ficed after 7 days to collect serum and colon tissue samples;ELISA was used to measure the serum levels of the proinflammatory fac-tors interleukin-6(IL-6),interleukin-17A(IL-17A),C-reactive protein(CRP),and tumor necrosis factor-α(TNF-α),and ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF/MS)was used to perform the non-targeted metabolomics analysis and compare the differences in se-rum metabolite profiles between groups.The mice were selected for modeling and validation with the same method,and glutathione(GSH)was selected as the positive drug.Colon length and mucosal damage were assessed,and quantitative real-time PCR was used to measure the relative mRNA expression levels of the key genes in the glutathione synthesis pathway(γ-glutamylcysteine synthetase[γ-GCS]and oxidative stress regulators yap1p and skn7)and mito-chondrial GSH transporter protein(Slc25a39)in colonic tissue.Results:Rhizoma Corydalis significantly improved weight loss,DAI,and colon length in a dose-dependent manner in the model animals,and there were reductions in the serum levels of IL-6,CRP,and TNF-α,while it had no significant effect on IL-17A.The metabolomics analysis revealed 21 potential biomarkers associated with amino acid and lipid metabolism,which were significantly regulated by Rhizoma Corydalis.In the verification experiment,both Rhi-zoma Corydalis and GSH exerted a significant protective effect against colonic mucosal damage without affecting colon length.Rhizoma Corydalis upregulated the expression of genes associated with glutathione synthesis,especially γ-GCS,suggesting that Rhizoma Co-rydalis could enhance intestinal antioxidant defenses.Conclusion:Rhizoma Corydalis has a therapeutic potential in a mouse model of DSS-induced UC and can alleviate symptoms,reduce the serum levels of inflammatory markers,and regulate metabolic pathways,and upregulation of the genes associated with glutathione synthesis suggests that the drug can enhance intestinal antioxidant defenses.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To explore the development process of family resilience in children with congenital pseudarthrosis of the tibia (CPT) and to understand the long-term challenges and coping strategies that CPT imposes on the families of affected children.Methods:This study combined purposive sampling and theoretical sampling. It selected 15 caregivers of CPT children from Hunan Children's Hospital for semi-structured interviews. Grounded theory was used to analyze the interview results.Results:The development of family resilience in CPT children's families occurred in three stages: pre-formation stage, formation stage, and maintenance stage. In facing negative emotions and family challenges, caregivers first needed to rebuild their inner beliefs. They then adjusted the family organizational model, adopted open and inclusive communication, and actively sought external support to foster the development of family resilience. Ultimately, caregivers were able to self-regulate their emotions, accumulate caregiving experience, and begin to shift their life perspective.Conclusions:The development of family resilience in CPT children's families is a dynamic, multi-stage process with interactions of multiple factors. Healthcare providers should offer professional health guidance according to the different stages of family development. Moreover, the government and schools should increase their attention and support, working together with families and healthcare providers to enhance family resilience for children with CPT.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To explore the development process of family resilience in children with congenital pseudarthrosis of the tibia (CPT) and to understand the long-term challenges and coping strategies that CPT imposes on the families of affected children.Methods:This study combined purposive sampling and theoretical sampling. It selected 15 caregivers of CPT children from Hunan Children's Hospital for semi-structured interviews. Grounded theory was used to analyze the interview results.Results:The development of family resilience in CPT children's families occurred in three stages: pre-formation stage, formation stage, and maintenance stage. In facing negative emotions and family challenges, caregivers first needed to rebuild their inner beliefs. They then adjusted the family organizational model, adopted open and inclusive communication, and actively sought external support to foster the development of family resilience. Ultimately, caregivers were able to self-regulate their emotions, accumulate caregiving experience, and begin to shift their life perspective.Conclusions:The development of family resilience in CPT children's families is a dynamic, multi-stage process with interactions of multiple factors. Healthcare providers should offer professional health guidance according to the different stages of family development. Moreover, the government and schools should increase their attention and support, working together with families and healthcare providers to enhance family resilience for children with CPT.

Purpose To explore the clinicopathological features and molecular characteristics of primary CD5+diffuse large B cell lymphoma(DLBCL).Methods Immunohisto-chemistry and next-generation sequencing(NGS)were used to compare the pathological features,immunophenotypes,and mo-lecular characteristics between primary CD5+DLBCL and CD5-DLBCL,and to analyze their relationship with prognosis and clinical characteristics of patients.Results Among 311 DLBCL patients,there were 46 cases(14.7％)of CD5+DLBCL.There were no statistically significant differences in patient gen-der,clinical staging,international prognostic index between CD5+DLBCL and CD5-DLBCL,and between CD5+DLBCL with and without MYD88 L265P mutation(P＞0.05).Immuno-phenotypically,the overexpression of BCL2(69.5％vs 49.4％,P=0.003)and the co-expression of BCL2 and C-MYC(26％vs 14％,P=0.04)were higher in the CD5+DLBCL group than those in the CD5-DLBCL group;the expression of C-MYC(53％vs 20％),BCL6(93.3％vs 61.3％),Ki67(93.3％vs 64.5％),and co-expression(46.7％vs 20.8％)were higher in the CD5+with MYD88 L265P mutation group than those in the CD5+without MYD88 L265P mutation group(P＜0.05).Survival analysis showed that the disease progres-sion-free survival time of patients in the CD5+DLBCL group tended to be shorter than that of patients in the CD5-DLBCL group(P=0.09).Furthermore,the disease progression-free survival time of patients in the CD5+without MYD88 L265P mutation group was significantly longer than that of patients in the CD5+with MYD88 L265P mutation group(P=0.04).NGS detection found differences in the distribution of accompan-ying mutated genes between CD5+DLBCL and CD5-DLBCL groups.ConclusionCD5 expression and CD5+with MYD88 L265P mutation may be potential indicators of poor prognosis in DLBCL patients.

Objective:To evaluate the endometrial implantation window in patients with recurrent implantation failure using endometrial receptive array(ERA)sequencing or endometrial histological detection methods,and to explore the effectiveness and cost-effectiveness analysis of two technologies for improving clinical outcomes in such patients.Methods:A retrospective cohort study was conducted on clinical data of 125 patients diagnosed with repeated implantation failure in Gansu Maternal and Child Health Hospital from January 2018 to December 2022.According to whether endometrial receptivity testing was accepted and different detection techniques were used,they were divided into a control group(n=36),a genomic group(n=35),and a histological group(n=54).The clinical data and pregnancy outcomes of the three groups were compared.Results:①The results of one-way ANOVA showed that the embryo implantation rate in the genomic group and histological group was significantly higher than that in the control group,and the difference was statistically significant(P＜0.05).There was no sta-tistically significant difference in embryo implantation rate between genomic and histological groups(P=0.48).②There was no statistically significant difference in clinical pregnancy rate and live birth rate among the three groups(P＞0.05).③Log rank test showed:The time for 50％of patients to reach live labor was significantly shorter than that of the control group,and the difference was statistically significant(P＜0.05);There was no sta-tistically significant difference in the time to live birth in 50％of patients between the genomic and histological groups of 50％of patients(P＞0.05).④The average number of embryos transferred in the control group was significantly higher than that in the genomic and histological groups,with statistical significance(P＜0.05).The cost of genomic patients was significantly higher than that of histology group,and the difference was statistically significant(P＜0.05).Conclusions:①Endometrial implantation window detection is feasible for patients with re-peated implantation failure,which can effectively shorten the time to live birth and reduce the number of transplan-ted embryos;②Both ERA sequencing and endometrial histology detection have limitations as methods to evaluate endometrial implantation window,and it is not clear which detection method has more advantages in accuracy and practicability.

Objective:To evaluate the endometrial implantation window in patients with recurrent implantation failure using endometrial receptive array(ERA)sequencing or endometrial histological detection methods,and to explore the effectiveness and cost-effectiveness analysis of two technologies for improving clinical outcomes in such patients.Methods:A retrospective cohort study was conducted on clinical data of 125 patients diagnosed with repeated implantation failure in Gansu Maternal and Child Health Hospital from January 2018 to December 2022.According to whether endometrial receptivity testing was accepted and different detection techniques were used,they were divided into a control group(n=36),a genomic group(n=35),and a histological group(n=54).The clinical data and pregnancy outcomes of the three groups were compared.Results:①The results of one-way ANOVA showed that the embryo implantation rate in the genomic group and histological group was significantly higher than that in the control group,and the difference was statistically significant(P＜0.05).There was no sta-tistically significant difference in embryo implantation rate between genomic and histological groups(P=0.48).②There was no statistically significant difference in clinical pregnancy rate and live birth rate among the three groups(P＞0.05).③Log rank test showed:The time for 50％of patients to reach live labor was significantly shorter than that of the control group,and the difference was statistically significant(P＜0.05);There was no sta-tistically significant difference in the time to live birth in 50％of patients between the genomic and histological groups of 50％of patients(P＞0.05).④The average number of embryos transferred in the control group was significantly higher than that in the genomic and histological groups,with statistical significance(P＜0.05).The cost of genomic patients was significantly higher than that of histology group,and the difference was statistically significant(P＜0.05).Conclusions:①Endometrial implantation window detection is feasible for patients with re-peated implantation failure,which can effectively shorten the time to live birth and reduce the number of transplan-ted embryos;②Both ERA sequencing and endometrial histology detection have limitations as methods to evaluate endometrial implantation window,and it is not clear which detection method has more advantages in accuracy and practicability.

Objective:To evaluate the endometrial implantation window in patients with recurrent implantation failure using endometrial receptive array(ERA)sequencing or endometrial histological detection methods,and to explore the effectiveness and cost-effectiveness analysis of two technologies for improving clinical outcomes in such patients.Methods:A retrospective cohort study was conducted on clinical data of 125 patients diagnosed with repeated implantation failure in Gansu Maternal and Child Health Hospital from January 2018 to December 2022.According to whether endometrial receptivity testing was accepted and different detection techniques were used,they were divided into a control group(n=36),a genomic group(n=35),and a histological group(n=54).The clinical data and pregnancy outcomes of the three groups were compared.Results:①The results of one-way ANOVA showed that the embryo implantation rate in the genomic group and histological group was significantly higher than that in the control group,and the difference was statistically significant(P＜0.05).There was no sta-tistically significant difference in embryo implantation rate between genomic and histological groups(P=0.48).②There was no statistically significant difference in clinical pregnancy rate and live birth rate among the three groups(P＞0.05).③Log rank test showed:The time for 50％of patients to reach live labor was significantly shorter than that of the control group,and the difference was statistically significant(P＜0.05);There was no sta-tistically significant difference in the time to live birth in 50％of patients between the genomic and histological groups of 50％of patients(P＞0.05).④The average number of embryos transferred in the control group was significantly higher than that in the genomic and histological groups,with statistical significance(P＜0.05).The cost of genomic patients was significantly higher than that of histology group,and the difference was statistically significant(P＜0.05).Conclusions:①Endometrial implantation window detection is feasible for patients with re-peated implantation failure,which can effectively shorten the time to live birth and reduce the number of transplan-ted embryos;②Both ERA sequencing and endometrial histology detection have limitations as methods to evaluate endometrial implantation window,and it is not clear which detection method has more advantages in accuracy and practicability.

Objective:To evaluate the endometrial implantation window in patients with recurrent implantation failure using endometrial receptive array(ERA)sequencing or endometrial histological detection methods,and to explore the effectiveness and cost-effectiveness analysis of two technologies for improving clinical outcomes in such patients.Methods:A retrospective cohort study was conducted on clinical data of 125 patients diagnosed with repeated implantation failure in Gansu Maternal and Child Health Hospital from January 2018 to December 2022.According to whether endometrial receptivity testing was accepted and different detection techniques were used,they were divided into a control group(n=36),a genomic group(n=35),and a histological group(n=54).The clinical data and pregnancy outcomes of the three groups were compared.Results:①The results of one-way ANOVA showed that the embryo implantation rate in the genomic group and histological group was significantly higher than that in the control group,and the difference was statistically significant(P＜0.05).There was no sta-tistically significant difference in embryo implantation rate between genomic and histological groups(P=0.48).②There was no statistically significant difference in clinical pregnancy rate and live birth rate among the three groups(P＞0.05).③Log rank test showed:The time for 50％of patients to reach live labor was significantly shorter than that of the control group,and the difference was statistically significant(P＜0.05);There was no sta-tistically significant difference in the time to live birth in 50％of patients between the genomic and histological groups of 50％of patients(P＞0.05).④The average number of embryos transferred in the control group was significantly higher than that in the genomic and histological groups,with statistical significance(P＜0.05).The cost of genomic patients was significantly higher than that of histology group,and the difference was statistically significant(P＜0.05).Conclusions:①Endometrial implantation window detection is feasible for patients with re-peated implantation failure,which can effectively shorten the time to live birth and reduce the number of transplan-ted embryos;②Both ERA sequencing and endometrial histology detection have limitations as methods to evaluate endometrial implantation window,and it is not clear which detection method has more advantages in accuracy and practicability.