ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

The working principle and development of flexible semiconductor devices based on organic field effect transistor(OFET)technology were introduced.The current research status of OFET-based wearable flexible monitoring devices were reviewed,including biomechanical monitoring devices,tattoo biomonitoring devices and cellular detection devices and etc.The deficiencies of OFET-based wearable flexible monitoring devices were analyzed,and it's pointed out that miniaturization,personalization and diversification were the directions for the development of the future OFET-based wearable flexible moni-toring devices.[Chinese Medical Equipment Journal,2024,45(1):93-100]

Objective:To describe and analyze suicide risk of patients with schizophrenia,major depressive disorder,and bipolar disorder.Methods:A total of 2 016 patients with schizophrenia,903 patients with major de-pressive disorder,and 381 patients with bipolar disorder from inpatients,clinics,or communities who met the diag-nostic criteria of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition were recruited.All patients were interviewed by psychiatrists using the Mini International Neuropsychiatric Interview to diagnose mental disor-ders and assess suicide risk,as well as Clinical-Rated Dimensions of Psychosis Symptom Severity(CRDPSS)to as-sess symptoms.Differences and risk factors of suicide risk among three types of mental disorders were explored u-sing multivariate logistic regression analysis.Results:In the past one month,37 patients with schizophrenia(1.8％),516 patients with major depressive disorder(57.1％),and 102 patients with bipolar disorder(26.8％)had suicide risk.Compared with patients with schizophrenia,suicide risk in patients with major depressive disorder(OR=36.50)and bipolar disorder(OR=20.10)increased.Female(OR=1.87),smoking(OR=1.76),family history of suicide(OR=5.09),higher score of CRDPSS hallucination(OR=1.80),and higher score of CRDPSS depression(OR=1.54)were risk factors of suicide risk of patients.Conclusions:Suicide risk of patients with ma-jor depressive disorder and bipolar disorder is higher than that of patients with schizophrenia.In clinical practice,it is important to regularly assess suicide risk of patients.Patients who experience symptoms of hallucination and de-pression should be paid more attention to.

Objective:To evaluate direct and indirect costs for schizophrenia,major depressive disorder(MDD)and bipolar disorder,and to compare their differences of cost composition,and to explore the drivers of the total costs.Methods:A total of 3 175 inpatients with schizophrenia,MDD,and bipolar disorder were recruited.In-patient's self-report total direct of medical costs outpatient and inpatient,out-of-pocket costs,and direct non-medical costs were regarded as direct costs.Productivity loss and other loss caused by damaging properties were defined as indirect costs.The perspectives of this study included individual and societal levels.Multivariate regression analysis was applied for detecting the factors influencing disease costs.Results:The total cost of schizophrenia was higher than those of MDD and bipolar disorder at individual and societal levels.The indirect costs of three mental disorders were higher than the direct costs,and the indirect cost ratio of bipolar disorder was higher than those of schizophre-nia and MDD.Age,gender,working condition and marital status(P＜0.05)were the important drivers of total costs.Conclusion:The economic burden of the three mental disorders is relatively heavy.Schizophrenia has heaviest disease burden,and the productivity loss due to mental disorders is the driving force of the soaring disease cost

Objective:To explore the clinical characteristics and related socio-demographic factors of schizo-phrenia patients with different ages of onset.Methods:Totally 2 016 patients with schizophrenia aged 15 to 70 were selected according to the diagnostic criteria for schizophrenia in the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition.All of the patients were interviewed by psychiatrists using the Mini International Neuropsy-chiatric Interview to diagnose schizophrenia,Clinical-Rated Dimensions of Psychosis Symptom Severity(CRDPSS)and the Positive and Negative Syndrome Scale(PANSS)to assess symptoms.The cut-off points were 18 and 25 years old for three age groups,i.e.early onset(EOS),youth onset(YOS)and adult onset(AOS).Statistical analy-ses were performed by analysis of variance Pearson correlation analysis,and multivariate linear regression.Results:The early-onset patients had the highest total PANSS score(73.8±28.0)and CRDPSS score(11.7±5.4).Fe-male gender,high education level,Han ethnicity,early onset age,and slower onset of illness were negatively corre-lated with the total and dimension score of PANSS scale and CRDPSS scale(standardized regression coefficient:0.04-0.47),and income level and smoking were negatively correlated with those score(standardized regression coefficient:-0.04--0.14).Conclusion:Early-onset schizophrenia patients have more severe symptoms,and fe-male,high education level,early-onset disease,and chronic onset are the risk factors of symptom severity in patients with schizophrenia.

Objective:To describe demographic,clinical and physiological characteristics,treatment between first-episode major depressive disorder(MDD)and relapse MDD,and to explore characteristics of relapse MDD.Methods:Totally 858 patients who met the diagnostic criteria for depression of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),were included by using the Mini International Neuropsychiatric Interview(MINI),Clinician-Rated Dimensions of Psychosis Symptom Severity,and Hamilton Depression Scale etc.Among them,529(58.6％)were first-episode depression and 329(36.0％)were relapsed.The differences of demographic characteristics,clinical and physiological characteristics,treatment were compared byx2test and Kruskal-Wallis rank sum test.Multivariate logistic regression was used to explore the characteristics of MDD recur-rence.Results:Compared to first-episode MDD,relapse MDD had more comorbidity(OR=2.11,95％CI:1.00-4.44),more days out of role(OR=1.26,95％CI:1.01-1.56),more history of using psychiatric drug more than one month(OR=1.41,95％CI:1.02-1.97)and electroconvulsive therapy(OR=3.23,95％CI:1.42-7.36),and higher waist-hip ratio(OR=33.88,95％CI:2.88-399.32).Conclusion:Relapse MDD has positive as-sociation with comorbidity of mental disorders,out of role,and higher waist-hip ratio.

Objective:To compare demographic characteristics,clinical characteristics,therapeutic characteris-tics and physiological indicators of patients with bipolar Ⅰ disorder and bipolar Ⅱ disorder.Methods:A total of 381 patients with bipolar disorder(BD)diagnosed by the Diagnostic and Statistical Manual of Mental Disorders 5 th Edi-tion(DSM-5)were selected,including 302 patients with BD-Ⅰ(79.27％),74 patients with BD-Ⅱ(19.42％)and 5 patients with other specific and related disorders(1.31％).Demographic and clinical characteristics were collected with self-designed clinical information questionnaire.Multivariate logistic regression and multivariate linear regres-sion analysis were used for analysis.Results:Compared with patients with BD-Ⅱ,patients with BD-Ⅰ had more risk to have psychotic features(OR=5.75,95％CI:2.82-11.76),longer disease duration,and more repeated transcra-nial magnetic therapy(OR=3.09,95％CI:1.02-9.35),higher uric acid,total cholesterol and high-density lipo-protein.BD-Ⅰ in Han nationality was more common(OR=11.50,95％CI:1.76-75.30),and had lower education level(OR=10.22,95％CI:1.16-89.77),and less family history of psychosis(OR=2.34,95％CI:1.01-5.42).Conclusion:There are significant differences between BD-Ⅰ and BD-Ⅱ in demographic and clinical charac-teristics,treatment status,and physiological indicators,which could provide clues for exploring the pathogenesis of bipolar disorder.

AIM To evaluate the quality of Beidougen Formula Granules.METHODS Fifteen batches of standard decoctions and three batches of formula granules were prepared,after which paste rate and contents,transfer rates of magnoflorine,daurisoline,dauricine were determined.HPLC specific chromatograms were established,and cluster analysis was adopted in chemical pattern recognition.RESULTS For three batches of formula granules,the paste rates were 15.1%-16.6%,the contents of magnoflorine,daurisoline,dauricine were 18.93-19.39,9.42-9.60,6.79-6.85 mg/g with the transfer rates of 34.42%-35.25%,43.81%-44.65%,27.27%-27.51%from decoction pieces to formula granules,respectively,and there were seven characteristic peaks in the specific chromatograms with the similarities of more than 0.95,which demonstrated good consistence with those of standard decoctions and accorded with related limit requirements.Fifteen batches of standard decoctions were clustered into two types,and the medicinal materials produced from Jilin,Hebei,Shangdong could be used for the preparation of formula granules.CONCLUSION This reasonable and reliable method can provide references for the quality control and clinical application of Beidougen Formula Granules.

Objective:To compare clinical characteristics,treatment patterns and physiological indicators in bipolar disorder(BD)patients with different age of onset.Methods:Totally 380 patients with DSM-5 BD were se-lected in this study.Psychiatrists diagnosed the patients using the Mini International Neuropsychiatric Interview.The clinical information questionnaire and the Global Assessment of Functioning scale were utilized to collected clinical characteristics,treatment status,and physiological indicators.The onset age of BD was divided into 21 and 35 years as cut-off points.Multivariate logistic regression and linear regression were used to analyze related factors.Results:Among the 380 patients with BD,199 cases were early-onset group(52.4％),121 cases were middle-onset group(31.8％),and 60 cases were late-onset group(15.8％).There were 26.6％of patients in the early-onset group in-itially diagnosed as depression,23.1％in the middle-onset group,and 11.7％in the late-onset group.Multivariate analysis revealed that compared to the early-onset group of BD,the middle-onset(OR=2.22)and late-onset(OR=4.99)groups had more risk to experience depressive episodes,and the late-onset group(OR=6.74)had 6.74 times of risk to suffer from bipolar Ⅱ disorder.Additionally,patients in the middle-onset(β=-1.52)and late-on-set(β=-4.29)groups had shorter durations of delayed treatment,and those in the middle-onset(β=-1.62)and late-onset(β=-3.14)groups had fewer hospitalizations.Uric acid levels were lower in both the middle-onset(β=-28.39)and late-onset(β=-31.47)groups,and total cholesterol level was lower in the middle-onset group(β=-0.23).Conclusion:Patients with BD in different age of onset show significant differences in clinical charac-teristics,treatment conditions and physiological indicators.