ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

Objective To explore the value of machine learning(ML)models based on ultrasonic texture features(TF)of coronary artery for predicting incomplete Kawasaki disease(IKD)in children.Methods Forty-eight children with IKD and 48 children without KD(non-KD)were enrolled with propensity score matching and divided into training set(n=67,34 cases of IKD and 33 cases of non-KD)and test set(n=29,14 of IKD and 15 of non-KD)at the ratio of 7∶3.Based on clinic-laboratory indicators(C-L)in training set and TF obtained with texture analysis of coronary artery ultrasound images,the optimal C-L-related features and TF were selected.Based on the optimal C-L correlated features,TF and their combinations,6 ML models,including random forest(RF),support vector machine(SVM),logistic regression(LR),gradient boosting decision tree(GBDT),decision tree(DT)and eXtreme gradient boosting(XGBoost)were respectively constructed for predicting IKD in children.The models were then trained in training set and validated in test set,and the best C-L ML,TF ML and C-L-TF ML models were selected.The area under the curve(AUC)of the best ML models were compared,and the clinical value of the best TF ML model was observed with decision curve analysis(DCA).Results Totally 3 optimal C-L related features and 8 optimal TF were selected.Among the constructed C-L ML,TF ML and C-L-TF ML models,C-L-LR model,TF-LR model and C-L-TF-SVM model were the optimal ones,with AUC in training set of 0.891,0.985 and 0.965,while in test set of 0.676,0.971 and 0.948,respectively.No significant difference of AUC was found between TF-LR model and C-L-TF-SVM model in both training set and test set(both P＞0.05),which were both greater than those of C-L-LR model(all P＜0.05).TF-LR model achieved higher clinical benefits in both training set and test set.Conclusion Ultrasound TF-LR model of coronary artery could be used to effectively predict IKD in children.

Objective:To evaluate the effect of Bu-Zhong-Yi-Qi-Tang (BZYQT) combined with low molecular weight heparin (LMWH) on lower limb deep vein thrombosis (DVT) after fracture fixation in aged rabbits.Methods:Thirty-two elderly New Zealand rabbits of either sex, aged 36 months, weighing 3.5-4.0 kg, were divided into 4 groups ( n=8 each) using the random number table method: control group (C group), fracture fixation group (F group), low molecular weight heparin group (L group) and BZYQT combined with LMWH group (BL group). A model of fixation surgery for right femoral shaft fracture was established in anesthetized rabbits in F, L and BL groups. Starting from postoperative day 1, BL group received BZYQT at 3.6 ml/kg via gavage, F and L groups received normal saline at 3.6 ml/kg via gavage, L and BL groups received subcutaneous injection of LMWH at 200 IU/kg, and all the administrations were performed daily at 08: 00 for 7 consecutive days. On postoperative day 7, ultrasound examination was performed to assess lower limb DVT. Blood samples were collected from the marginal ear vein for determination of the serum concentrations of cortisol (COR), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and endothelin-1 (ET-1) by enzyme-linked immunosorbent assay. Femoral vein specimens were obtained under anesthesia for microscopic examination of the pathological changes of the femoral vein lumen and endothelial tissues (by HE staining) and of the morphology of vascular endothelial cells (by the transmission electron microscopy). Results:Compared with C group, the concentrations of serum COR, TNF-α, IL-6 and ET-1 were significantly increased in F, L and BL groups, and the incidence of lower limb DVT within 7 days after surgery was significantly increased in F and L groups ( P<0.05). Compared with F group, the incidence of lower limb DVT within 7 days after surgery was significantly decreased in L and BL groups, and the concentrations of serum COR, TNF-α, IL-6 and ET-1 were significantly decreased ( P<0.05), and the pathological damage was significantly reduced in BL group. Compared with L group, the incidence of lower limb DVT and concentration of IL-6 were significantly decreased ( P<0.05), and pathological damage was significantly alleviated in BL group. Conclusions:BZYQT combined with LMWH can prevent the occurrence of lower limb DVT after fracture fixation in aged rabbits.

Objective:To explore the current status of perceived vulnerability and its influencing factors among parents of children with type 1 diabetes mellitus (T1DM) .Methods:A convenience sampling method was used to select 220 parents of children with T1DM from the diabetes care and consultation outpatient clinic at Beijing Children's Hospital, Capital Medical University, from June to November 2023. The parents were surveyed using a general information questionnaire, the Parental Perceived Vulnerability Scale, the Family Care Index, and the Parental Illness Uncertainty Scale.Results:A total of 220 questionnaires were distributed, with 192 valid responses. The total score on the Parental Perceived Vulnerability Scale was (13.91±5.39), the total score on the Family Care Index was (5.39±2.73), and the total score on the Parental Illness Uncertainty Scale was (75.36±17.34). Multiple linear regression analysis showed that whether the child was an only child, family monthly income per capita, parents' religious beliefs, family care level, and illness uncertainty were significant influencing factors for perceived vulnerability ( P<0.05), explaining 36.5% of the variance. Conclusions:Healthcare professionals should pay more attention to parents who have only children, have lower family income, and do not have religious beliefs. Interventions aimed at improving family care levels and reducing illness uncertainty may help decrease the perceived vulnerability among parents of children with T1DM.

Objective:To evaluate the effect of Bu-Zhong-Yi-Qi-Tang (BZYQT) combined with low molecular weight heparin (LMWH) on lower limb deep vein thrombosis (DVT) after fracture fixation in aged rabbits.Methods:Thirty-two elderly New Zealand rabbits of either sex, aged 36 months, weighing 3.5-4.0 kg, were divided into 4 groups ( n=8 each) using the random number table method: control group (C group), fracture fixation group (F group), low molecular weight heparin group (L group) and BZYQT combined with LMWH group (BL group). A model of fixation surgery for right femoral shaft fracture was established in anesthetized rabbits in F, L and BL groups. Starting from postoperative day 1, BL group received BZYQT at 3.6 ml/kg via gavage, F and L groups received normal saline at 3.6 ml/kg via gavage, L and BL groups received subcutaneous injection of LMWH at 200 IU/kg, and all the administrations were performed daily at 08: 00 for 7 consecutive days. On postoperative day 7, ultrasound examination was performed to assess lower limb DVT. Blood samples were collected from the marginal ear vein for determination of the serum concentrations of cortisol (COR), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and endothelin-1 (ET-1) by enzyme-linked immunosorbent assay. Femoral vein specimens were obtained under anesthesia for microscopic examination of the pathological changes of the femoral vein lumen and endothelial tissues (by HE staining) and of the morphology of vascular endothelial cells (by the transmission electron microscopy). Results:Compared with C group, the concentrations of serum COR, TNF-α, IL-6 and ET-1 were significantly increased in F, L and BL groups, and the incidence of lower limb DVT within 7 days after surgery was significantly increased in F and L groups ( P<0.05). Compared with F group, the incidence of lower limb DVT within 7 days after surgery was significantly decreased in L and BL groups, and the concentrations of serum COR, TNF-α, IL-6 and ET-1 were significantly decreased ( P<0.05), and the pathological damage was significantly reduced in BL group. Compared with L group, the incidence of lower limb DVT and concentration of IL-6 were significantly decreased ( P<0.05), and pathological damage was significantly alleviated in BL group. Conclusions:BZYQT combined with LMWH can prevent the occurrence of lower limb DVT after fracture fixation in aged rabbits.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

Objective:To explore the current status of perceived vulnerability and its influencing factors among parents of children with type 1 diabetes mellitus (T1DM) .Methods:A convenience sampling method was used to select 220 parents of children with T1DM from the diabetes care and consultation outpatient clinic at Beijing Children's Hospital, Capital Medical University, from June to November 2023. The parents were surveyed using a general information questionnaire, the Parental Perceived Vulnerability Scale, the Family Care Index, and the Parental Illness Uncertainty Scale.Results:A total of 220 questionnaires were distributed, with 192 valid responses. The total score on the Parental Perceived Vulnerability Scale was (13.91±5.39), the total score on the Family Care Index was (5.39±2.73), and the total score on the Parental Illness Uncertainty Scale was (75.36±17.34). Multiple linear regression analysis showed that whether the child was an only child, family monthly income per capita, parents' religious beliefs, family care level, and illness uncertainty were significant influencing factors for perceived vulnerability ( P<0.05), explaining 36.5% of the variance. Conclusions:Healthcare professionals should pay more attention to parents who have only children, have lower family income, and do not have religious beliefs. Interventions aimed at improving family care levels and reducing illness uncertainty may help decrease the perceived vulnerability among parents of children with T1DM.

Objective To explore the value of machine learning(ML)models based on ultrasonic texture features(TF)of coronary artery for predicting incomplete Kawasaki disease(IKD)in children.Methods Forty-eight children with IKD and 48 children without KD(non-KD)were enrolled with propensity score matching and divided into training set(n=67,34 cases of IKD and 33 cases of non-KD)and test set(n=29,14 of IKD and 15 of non-KD)at the ratio of 7∶3.Based on clinic-laboratory indicators(C-L)in training set and TF obtained with texture analysis of coronary artery ultrasound images,the optimal C-L-related features and TF were selected.Based on the optimal C-L correlated features,TF and their combinations,6 ML models,including random forest(RF),support vector machine(SVM),logistic regression(LR),gradient boosting decision tree(GBDT),decision tree(DT)and eXtreme gradient boosting(XGBoost)were respectively constructed for predicting IKD in children.The models were then trained in training set and validated in test set,and the best C-L ML,TF ML and C-L-TF ML models were selected.The area under the curve(AUC)of the best ML models were compared,and the clinical value of the best TF ML model was observed with decision curve analysis(DCA).Results Totally 3 optimal C-L related features and 8 optimal TF were selected.Among the constructed C-L ML,TF ML and C-L-TF ML models,C-L-LR model,TF-LR model and C-L-TF-SVM model were the optimal ones,with AUC in training set of 0.891,0.985 and 0.965,while in test set of 0.676,0.971 and 0.948,respectively.No significant difference of AUC was found between TF-LR model and C-L-TF-SVM model in both training set and test set(both P＞0.05),which were both greater than those of C-L-LR model(all P＜0.05).TF-LR model achieved higher clinical benefits in both training set and test set.Conclusion Ultrasound TF-LR model of coronary artery could be used to effectively predict IKD in children.