ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome patterns among postmenopausal women with dyslipidemia， and to examine the correlations of lipid parameters with bone mineral density （BMD） and bone metabolism markers across common TCM syndrome patterns， thereby providing a clinical reference for individualized integrative traditional Chinese and western medicine interventions stratified according to TCM syndrome patterns. MethodsA multi-center cross-sectional study was conducted among postmenopausal women aged 45-64 years with dyslipidemia. TCM syndromes were determined using a scale-based scoring method. BMD measurements were collected， and fasting venous blood samples were assayed for lipid parameters including total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C）， and bone metabolism biomarkers including osteocalcin （OST）， total procollagen type Ⅰ N-terminal propeptide （P1NP）， alkaline phosphatase （ALP）， bone-specific alkaline phosphatase （BALP）， β-isomerized C-terminal telopeptide of type Ⅰ collagen （β-CTX）， 25-hydroxyvitamin D ［25（OH）D］， and thyroid-stimulating hormone （TSH）. Chi-square tests were used to compare the distribution of dyslipidemia across different TCM syndromes. Spearman's rank correlation analysis was performed to evaluate the correlations between TCM syndrome patterns and dyslipidemia， as well as the correlations of lipid parameters with BMD and bone metabolism markers within each syndrome pattern. ResultsA total of 506 postmenopausal women with dyslipidemia were included， comprising 172 cases of spleen-kidney yang deficiency syndrome （33.99%）， 163 cases of phlegm-turbidity obstruction syndrome （32.21%）， 118 cases of liver-kidney yin deficiency syndrome （23.32%）， 33 cases of qi stagnation and blood stasis syndrome （6.52%）， and 20 cases of yin deficiency and yang hyperactivity syndrome （3.95%）. Phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120， P=0.007） and positively correlated with TG abnormality （r=0.246， P＜0.001）. Spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were both negatively correlated with TG abnormality （r=-0.101， P=0.023； r=-0.116， P=0.009， respectively）. Further correlation analysis confirmed that phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120） and significantly positively correlated with TG abnormality （r=0.246）. Both the spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were negatively correlated with TG abnormality （r=-0.101 and r=-0.116， respectively）. In patients with phlegm-turbidity obstruction syndrome， HDL-C was negatively correlated with BMD at the left femoral neck （r=-0.178， P=0.023） and at left total hip （r=-0.190， P=0.015）. In patients with liver-kidney yin deficiency syndrome， TG was positively correlated with BMD at the lumbar spine （L1-L4） and left total hip （r=0.214， P=0.020； r=0.221， P=0.016， respectively）. More significant correlations were observed in patients with spleen-kidney yang deficiency syndrome， TG was positively correlated with ALP （r=0.210， P=0.006）； TC was positively correlated with TSH and 25（OH）D （r=0.153， P=0.045； r= 0.231， P=0.002， respectively）； HDL-C was positively correlated with OST and 25（OH）D （r=0.156， P=0.040； r=0.228， P=0.003， respectively）； and LDL-C was positively correlated with TSH and 25（OH）D （r=0.156， P= 0.041； r=0.182， P=0.017， respectively）. In patients with liver-kidney yin deficiency syndrome， HDL-C was negatively correlated with TSH （r=-0.204， P=0.027）. ConclusionThe association between dyslipidemia and skeletal health in postmenopausal women varies across TCM syndromes. Lipid abnormalities in women with phlegm-turbidity obstruction syndrome or liver-kidney yin deficiency syndrome are accompanied primarily by site-specific alterations in BMD， whereas those in women with spleen-kidney yang deficiency syndrome are reflected mainly in changes in bone metabolism markers. These findings suggest that targeted intervention strategies should be developed according to TCM syndrome characteristics for postmenopausal women with dyslipidemia.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome patterns among postmenopausal women with dyslipidemia， and to examine the correlations of lipid parameters with bone mineral density （BMD） and bone metabolism markers across common TCM syndrome patterns， thereby providing a clinical reference for individualized integrative traditional Chinese and western medicine interventions stratified according to TCM syndrome patterns. MethodsA multi-center cross-sectional study was conducted among postmenopausal women aged 45-64 years with dyslipidemia. TCM syndromes were determined using a scale-based scoring method. BMD measurements were collected， and fasting venous blood samples were assayed for lipid parameters including total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C）， and bone metabolism biomarkers including osteocalcin （OST）， total procollagen type Ⅰ N-terminal propeptide （P1NP）， alkaline phosphatase （ALP）， bone-specific alkaline phosphatase （BALP）， β-isomerized C-terminal telopeptide of type Ⅰ collagen （β-CTX）， 25-hydroxyvitamin D ［25（OH）D］， and thyroid-stimulating hormone （TSH）. Chi-square tests were used to compare the distribution of dyslipidemia across different TCM syndromes. Spearman's rank correlation analysis was performed to evaluate the correlations between TCM syndrome patterns and dyslipidemia， as well as the correlations of lipid parameters with BMD and bone metabolism markers within each syndrome pattern. ResultsA total of 506 postmenopausal women with dyslipidemia were included， comprising 172 cases of spleen-kidney yang deficiency syndrome （33.99%）， 163 cases of phlegm-turbidity obstruction syndrome （32.21%）， 118 cases of liver-kidney yin deficiency syndrome （23.32%）， 33 cases of qi stagnation and blood stasis syndrome （6.52%）， and 20 cases of yin deficiency and yang hyperactivity syndrome （3.95%）. Phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120， P=0.007） and positively correlated with TG abnormality （r=0.246， P＜0.001）. Spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were both negatively correlated with TG abnormality （r=-0.101， P=0.023； r=-0.116， P=0.009， respectively）. Further correlation analysis confirmed that phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120） and significantly positively correlated with TG abnormality （r=0.246）. Both the spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were negatively correlated with TG abnormality （r=-0.101 and r=-0.116， respectively）. In patients with phlegm-turbidity obstruction syndrome， HDL-C was negatively correlated with BMD at the left femoral neck （r=-0.178， P=0.023） and at left total hip （r=-0.190， P=0.015）. In patients with liver-kidney yin deficiency syndrome， TG was positively correlated with BMD at the lumbar spine （L1-L4） and left total hip （r=0.214， P=0.020； r=0.221， P=0.016， respectively）. More significant correlations were observed in patients with spleen-kidney yang deficiency syndrome， TG was positively correlated with ALP （r=0.210， P=0.006）； TC was positively correlated with TSH and 25（OH）D （r=0.153， P=0.045； r= 0.231， P=0.002， respectively）； HDL-C was positively correlated with OST and 25（OH）D （r=0.156， P=0.040； r=0.228， P=0.003， respectively）； and LDL-C was positively correlated with TSH and 25（OH）D （r=0.156， P= 0.041； r=0.182， P=0.017， respectively）. In patients with liver-kidney yin deficiency syndrome， HDL-C was negatively correlated with TSH （r=-0.204， P=0.027）. ConclusionThe association between dyslipidemia and skeletal health in postmenopausal women varies across TCM syndromes. Lipid abnormalities in women with phlegm-turbidity obstruction syndrome or liver-kidney yin deficiency syndrome are accompanied primarily by site-specific alterations in BMD， whereas those in women with spleen-kidney yang deficiency syndrome are reflected mainly in changes in bone metabolism markers. These findings suggest that targeted intervention strategies should be developed according to TCM syndrome characteristics for postmenopausal women with dyslipidemia.

Objective: To explore the relationship between socio ecological risk factors (SERF), physical activity (PA) developmental trajectories, and depressive symptoms among junior and senior high school students in Tianjin, in order to provide theoretical support for comprehensive interventions for adolescent depression. Methods: A longitudinal follow up design was adopted. In September 2022, a baseline survey was conducted using a stratified cluster random sampling method in two junior high schools and two senior high schools in Tianjin, collecting data on students basic information, SERF, PA, and depressive symptoms. Two follow up surveys were conducted in September 2023 and 2024, yielding 588 valid participants. Latent class growth analysis (LCGA) was used to identify PA developmental trajectory categories among junior and senior high school students. Logistic regression was applied to examine the associations between depressive symptoms and SERF as well as PA trajectories. Results: The detection rates of depressive symptoms among Tianjin junior and senior high school students over the three years were 26.53%, 20.24%, and 21.26 %, respectively. Depressive symptoms were positively correlated with SERF ( OR=1.04, 95%CI=1.03-1.05, P <0.05). The highest risks were observed in the individual dimension and family dimension ( OR =1.28, 1.21, both P <0.05). LCGA identified three PA trajectory groups:persistently low level (80.65%), persistently high level (4.58%), and slowly increasing group ( 14.77 %). Multivariate regression analysis showed that compared with the persistently low level PA, the slowly increasing PA significantly reduced the risk of depressive symptoms ( OR=0.44, 95%CI =0.20-0.88), while SERF still increased the risk of depressive symptoms ( OR=1.04, 95%CI =1.03-1.05) (both P <0.05). Conclusion SERF are risk factors for depression symptoms among junior and senior high school students, whereas slowly increasing PA development trajectory demonstrates a protective effect.

Objective To observe the value of pituitary radiomics and MRI features combined model for predicting growth hormone(GH)status in pediatric short stature.Methods Totally 300 children with short stature were enrolled as training set,while other 73 cases were taken as external validation set.Based on growth hormone stimulation test,the children were divided into GH deficiency(GHD)group(n=228)and non-GHD group(n=145).The training set included 196 cases in GHD subgroup and 104 cases in non-GHD subgroup,while the validation set included 32 cases in GHD subgroup and 41 cases in non-GHD subgroup.Radiomics features of pituitary were extracted from T1WI.The key features were selected using least absolute shrinkage and selection operator(LASSO)regression,and machine learning models were subsequently constructed using support vector machine(SVM),logistic regression(LR),naive Bayes(NB)and K-nearest neighbor(KNN),respectively.Then combined models were constructed combining with MRI features,and the efficacy of each model was evaluated.Results The area under the curve(AUC)of SVM,LR,NB,and KNN radiomics model for predicting GH status in pediatric short stature was 0.860,0.831,0.838 and 0.901 in training set,0.788,0.829,0.823 and 0.770 in validation set,while of the relative combined SVM,LR,NB and KNN model was 0.924,0.903,0.859 and 0.920 in training set,and 0.827,0.881,0.836 and 0.718 in validation set.LRcombined model had the best overall performance,with sensitivity of 84.94％,specificity of 80.56％and accuracy of 83.61％in training set,and 80.95％,72.22％and 80.00％in validation set,respectively.Conclusion Pituitary radiomics and MRI features combined model could effectively predict GH status in pediatric short stature.

[Purpose]To analyze the incidence and mortality rates of female breast cancer in Henan Province in 2020 and the trends from 2010 to 2020.[Methods]Breast cancer incidence and mor-tality data stratified by urban and rural areas and age groups were collected from Henan Provincial tumor registry,and the province's household population statistics were used.The crude incidence/mortality rate,age-standardized incidence/mortality rate by Chinese standard population(ASIRC/ASMRC)and world standard population(ASIRW/ASMRW),cumulative rate(0～74 year old)were calculated.The annual percentage change(APC),average annual percentage change(AAPC)and 95％confidence interval(CI)were calculated using Joinpoint software to analyze the trends of the incidence and mortality from 2010 to 2020.[Results]In 2020,24 744 new cases and 4 989 deaths of female breast cancer were documented in Henan Province,with a crude incidence rate of 46.96/105,ASIRC of 38.43/105 and ASIRW of 35.71/105;a crude mortality rate of 9.47/105,ASMRC of 6.80/105 and ASMRW of 6.72/105,respectively.The above indicators in urban areas were signifi-cantly higher than those in rural areas.The highest incidence was observed in the age group of 50～54 years old,while the highest mortality reached in the age group of 85 years old and above.From 2010 to 2020,the overall incidence of female breast cancer showed a slow upward trend(AAPC=2.09％,95％CI:0.62％～3.58％,P=0.010),while the mortality rate exhibited a signif-icant downward trend(AAPC=-3.49％,95％CI:-5.62％～-1.30％,P=0.005).[Conclusion]The incidence and mortality rates of female breast cancer in Henan Province are still at a high level,and corresponding preventive measures and control strategies are needed to effectively reduce the health hazards of breast cancer to women.

Objective To observe hierarchical differences in brain functional networks in unilateral mesial temporal lobe epilepsy(mTLE)patients with different outcomes after surgery.Methods A total of 69 unilateral mTLE patients who underwent resection of epileptogenic lesion on the affected side were retrospectively enrolled.Based on Engel classification 1 year after surgery,the patients were divided into seizure free(SF)group and non-seizure free(NSF)group.Functional connectivity gradient analysis was employed to extract principal gradient explaining the highest variance on preoperative resting-state functional MRI(rs-fMRI),then the whole-brain gradient characteristics and principal gradient values within specific functional networks were compared between groups.Results Principal gradient connected default mode network(DMN)with sensorimotor network(SMN)along a continuous axis.Compared to SF group,NSF group showed a contracted gradient range at both ends(DMN and SMN)of the functional network and weakened hierarchical differentiation,and principal gradient value of DMN was higher,while that of SMN was lower than those in SF group(both P＜0.05).Conclusion Hierarchical differences in brain functional networks in unilateral mTLE patients with different outcomes after surgery mainly present as enhanced DMN and weakened SMN in NSF ones,and the latter two might serve as important neuroimaging markers for evaluating postoperative seizure recurrence.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.

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.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.