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.

This study was designed to compare diagnostic categories of thyroid fine needle aspiration cytology (FNAC) and incidence of thyroid tumors in the multi-institutional Asian series with a special focus on diagnostic category IV (suspicious for a follicular neoplasm) and follicular thyroid carcinomas (FTCs). Methods: Distribution of FNAC categories, incidence of thyroid tumors in resection specimens and cytologic diagnoses of surgically confirmed follicular adenomas (FAs) and FTCs were collected from 10 institutes from five Asian countries and were compared among countries and between FAs and FTCs. Results: The frequency of category IV diagnoses (3.0%) in preoperative FNAC were significantly lower compared to those in Western countries (10.1%). When comparing diagnostic categories among Asian countries, category IV was more frequent in Japan (4.6%) and India (7.9%) than in Taiwan (1.4%), Korea (1.4%), and China (3.6%). Similarly, incidence of FAs and FTCs in surgical resection specimens was significantly higher in Japan (10.9%) and India (10.1%) than in Taiwan (5.5%), Korea (3.0%), and China (2.5%). FTCs were more commonly diagnosed as category IV in Japan (77.5%) than in Korea (33.3%) and China (35.0%). Nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were more common in FTCs compared with FAs. Conclusions: Our study highlighted the difference in FNAC diagnostic categories of FTCs among Asian countries, which is likely related to different reporting systems and thyroid cancer incidence. Cytologic features such as nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were found to be useful in diagnosing FTCs more effectively.

This study was designed to compare diagnostic categories of thyroid fine needle aspiration cytology (FNAC) and incidence of thyroid tumors in the multi-institutional Asian series with a special focus on diagnostic category IV (suspicious for a follicular neoplasm) and follicular thyroid carcinomas (FTCs). Methods: Distribution of FNAC categories, incidence of thyroid tumors in resection specimens and cytologic diagnoses of surgically confirmed follicular adenomas (FAs) and FTCs were collected from 10 institutes from five Asian countries and were compared among countries and between FAs and FTCs. Results: The frequency of category IV diagnoses (3.0%) in preoperative FNAC were significantly lower compared to those in Western countries (10.1%). When comparing diagnostic categories among Asian countries, category IV was more frequent in Japan (4.6%) and India (7.9%) than in Taiwan (1.4%), Korea (1.4%), and China (3.6%). Similarly, incidence of FAs and FTCs in surgical resection specimens was significantly higher in Japan (10.9%) and India (10.1%) than in Taiwan (5.5%), Korea (3.0%), and China (2.5%). FTCs were more commonly diagnosed as category IV in Japan (77.5%) than in Korea (33.3%) and China (35.0%). Nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were more common in FTCs compared with FAs. Conclusions: Our study highlighted the difference in FNAC diagnostic categories of FTCs among Asian countries, which is likely related to different reporting systems and thyroid cancer incidence. Cytologic features such as nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were found to be useful in diagnosing FTCs more effectively.

This study was designed to compare diagnostic categories of thyroid fine needle aspiration cytology (FNAC) and incidence of thyroid tumors in the multi-institutional Asian series with a special focus on diagnostic category IV (suspicious for a follicular neoplasm) and follicular thyroid carcinomas (FTCs). Methods: Distribution of FNAC categories, incidence of thyroid tumors in resection specimens and cytologic diagnoses of surgically confirmed follicular adenomas (FAs) and FTCs were collected from 10 institutes from five Asian countries and were compared among countries and between FAs and FTCs. Results: The frequency of category IV diagnoses (3.0%) in preoperative FNAC were significantly lower compared to those in Western countries (10.1%). When comparing diagnostic categories among Asian countries, category IV was more frequent in Japan (4.6%) and India (7.9%) than in Taiwan (1.4%), Korea (1.4%), and China (3.6%). Similarly, incidence of FAs and FTCs in surgical resection specimens was significantly higher in Japan (10.9%) and India (10.1%) than in Taiwan (5.5%), Korea (3.0%), and China (2.5%). FTCs were more commonly diagnosed as category IV in Japan (77.5%) than in Korea (33.3%) and China (35.0%). Nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were more common in FTCs compared with FAs. Conclusions: Our study highlighted the difference in FNAC diagnostic categories of FTCs among Asian countries, which is likely related to different reporting systems and thyroid cancer incidence. Cytologic features such as nuclear pleomorphism, nuclear crowding, microfollicular pattern, and dyshesive cell pattern were found to be useful in diagnosing FTCs more effectively.

Objectives:To develop a novel prediction model for mitral valve repair failure based on machine learning algorithms.Methods:Clinical and echocardiographic data were analyzed on patients,who underwent mitral valve repair in Fuwai Hospital from 2009 January 1st to 2022 December 31st.End points included immediate mitral valve repair failure (mitral replacement secondary to mitral repair failure) and recurrence regurgitation (moderate or severe mitral regurgitation before discharge).Risk factors of mitral valve repair failure were analyzed by XGBoost and shapley additive explanation (SHAP),and a machine learning model was established based on mixture of experts (MoE) as a risk prediction model and compared with conventional mitral valve repair complexity scores.Results:A total of 2314 patients were included in this study.Mitral repair was unsuccessful in 4.2％ (98 of 2314) of patients.Patient factors such as tricuspid regurgitation pressure gradient,A3 and A3P3 lesions,left ventricular end-systolic volume,and left atrium anterior and posterior diameter are associated with mitral valve repair failure;in addition,surgeon factors,such as cumulative repair failure rate,cumulative repair volume,and surgeon seniority,are also risk factors for mitral valve repair failure.The MoE model has an AUC value of 0.79,and the prediction performance is significantly better than traditional complexity scores.Conclusions:The MoE based machine learning model can predict the risk of mitral valve repair failure well.This evaluation system can effectively assist surgeons in assessing the risk of mitral valve repair failure and in selecting suitable treatment options for patients.

Objectives:To develop a novel prediction model for mitral valve repair failure based on machine learning algorithms.Methods:Clinical and echocardiographic data were analyzed on patients,who underwent mitral valve repair in Fuwai Hospital from 2009 January 1st to 2022 December 31st.End points included immediate mitral valve repair failure (mitral replacement secondary to mitral repair failure) and recurrence regurgitation (moderate or severe mitral regurgitation before discharge).Risk factors of mitral valve repair failure were analyzed by XGBoost and shapley additive explanation (SHAP),and a machine learning model was established based on mixture of experts (MoE) as a risk prediction model and compared with conventional mitral valve repair complexity scores.Results:A total of 2314 patients were included in this study.Mitral repair was unsuccessful in 4.2％ (98 of 2314) of patients.Patient factors such as tricuspid regurgitation pressure gradient,A3 and A3P3 lesions,left ventricular end-systolic volume,and left atrium anterior and posterior diameter are associated with mitral valve repair failure;in addition,surgeon factors,such as cumulative repair failure rate,cumulative repair volume,and surgeon seniority,are also risk factors for mitral valve repair failure.The MoE model has an AUC value of 0.79,and the prediction performance is significantly better than traditional complexity scores.Conclusions:The MoE based machine learning model can predict the risk of mitral valve repair failure well.This evaluation system can effectively assist surgeons in assessing the risk of mitral valve repair failure and in selecting suitable treatment options for patients.

BackgroundBeing complex and highly heterogeneous with regard to the etiology and clinical manifestations of depression， neuroimaging studies make a breakthrough for exploring the biological subtypes of depression， while the current data-driven approach for the identification of subtyping depression using structural magnetic resonance imaging （MRI） data is insufficient. ObjectiveTo explore the biological subtypes of depression using diffusion tensor imaging （DTI） and machine learning methods. MethodsA total of 127 patients with depression who attended Beijing Anding Hospital from September 2017 to August 2021 and met the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） diagnostic criteria were included， and another 80 healthy individuals matched for gender and age were recruited through advertisements in surrounding communities during the same period. DTI findings， demographic characteristics and clinical data were collected from all participants. Tract-based spatial statistics （TBSS） and the Johns Hopkins University （JHU） white matter probability maps were used to extract fractional anisotropy （FA） values of white matter tracts. A semi-supervised machine learning technique was used to identify the subtypes， and the FA values for whole brain white matter of patients and controls were compared. ResultsPatients with depression were classified into two biological subtypes. FA values in multiple tracts including corpus callosum and corona radiata of subtype I patients were smaller than those of healthy controls （P<0.01， FDR corrected）， and FA values in middle cerebellar peduncle， left superior cerebellar peduncle and left cerebral peduncle of subtype II patients were larger than those of healthy controls （P<0.01， FDR-corrected）. Baseline Hamilton Depression Scale-17 item （HAMD-17） score yielded no statistical difference between subtype I and subtype II patients （P>0.05）， while subtype I patients scored lower on HAMD-17 than subtype II patients after 12 weeks of treatment （t=2.410， P<0.05）. ConclusionDepression patients exhibit two biological subtypes with distinct patterns of white matter damage. Furthermore， the subtypes respond differently to the medication treatment. ［Funded by the National Key Research and Development Program of China （number， 2016YFC1307200）， the Scientific Research and Cultivation Program of Beijing Municipal Hospitals （number，PX2023066）， Beijing Anding Hospital， Capital Medical University （number，YJ201904， YJ201911）； www.chictr.org.cn number： ChiCTR-OOC-17012566］

Objective:This study aimed to investigate the effect of lipohypertrophy induced by insulin injection on blood glucose fluctuation in patients with type 1 diabetes mellitus.Methods:A total of 80 patients with type 1 diabetes mellitus were recruited between June 2021 and December 2021 from the First Affiliated Hospital of Nanjing Medical University. And these patients all received insulin injection more than six months. Lipohypertrophy was assessed by ultrasound scanning, and blood glucose fluctuation was evaluated using the flash glucose monitoring system(FGM). Univariate analysis and multivariate linear regression were used to analyze the relationship of lipohypertrophy and and core indicators of blood glucose fluctuation.Results:Compared with patients without lipohypertrophy, patients with lipohypertrophy had higher mean amplitude of glycemic excursions(MAGE), coefficient of variation(CV), mean of daily differences(MODD), standard deviation(SD) of blood glucose, time above range(TAR), and high blood glucose index(HBGI; all P<0.05), while time in range(TIR) of glucose markedly become lower( P<0.01). Moreover, multivariate linear regression analysis showed that lipohypertrophy detected by ultrasound was an independent influencing factor of TIR( β=-9.423, P=0.032), MAGE( β=1.114, P=0.039), CV( β=4.304, P=0.041), MODD( β=0.717, P=0.046) after adjusting for age at diagnosis, duration of insulin injection, fasting C-peptide, and daily dose of insulin per unit weight. Conclusion:Lipohypertrophy increases glycemic variability and imposes negative impact on glycemic control rate in patients type 1 diabetes mellitus.

Objective:To investigate the clinical effectiveness and significance of special fixing cartilaginous support structure on nasal tip to prevent and correct alar rim retraction.Methods:Special shaped tip extension support structure was composed of two parts of type Ⅲ of septum extension graft (SEG) and two pieces of wedge graft fixed on either side of the cephalic end near the top of support structure. After the alar cartilage vault was fixed to the nasal tip cartilage support structure, the lower lateral cartilage (LLC) cephalic was fixed to both sides of this nasal tip support structure. The LLC received support from the cartilaginous support structure to counter and correct the lower lateral cartilage cephalic retraction. From January 2017 to January 2020, this surgical procedure was used in 34 patients (aged from 20 to 46 years, with mean 32.6 years) with rhinoplasty who had a nasal tip support structure but still had a space between the LLC and the stent intraoperativly. Preoperativly, 4 cases had normal relation of alar columella and alar rim, 18 cases had mild alar rim retraction, and 12 cases had moderate alar rim retraction. The patients were followed up for 6 to 18 months to observe the correction effect and patient satisfaction.Results:Among the 34 patients, 8 patients received alar edge graft, 2 patients received lateral foot support graft, and 2 patients received alar rim graft combined with lateral foot support graft. All patients were followed up for 6-18 months, 30 patients with alar rim retraction were completely corrected, and 4 patients with normal alar and nasal columella relationship did not have alar rim retraction after surgery. No complications such as infection, necrosis, contracture or respiratory dysfunction were found in all patients. 28 cases (82.4%) were very satisfied; 6 cases (17.6%) were satisfied; the satisfactory rate was 100%.Conclusions:The special shaped nasal tip cartilage support structure combined with type Ⅲ SEG and its cephalic wedge grafts could achieve satisfactory clinical results in the prevention and correction of alar rim retraction.

Objective:To explore the feasibility and advantages of integrated prosthesis of expanded polytetra-fluoroethylene (e-PTFE) in eyebrow arch augmentation.Methods:The clinical data of 45 patients with low or flat brow arch and glabellar zone from June 2019 to October 2020 in Chengdu High-tech Zone Xinyuerong Medical Aesthetic Clinic were analyzed retrospectively, in which it included 45 women, whose ages ranged from 20 to 39 years with average 29.8 years. Forty-three cases underwent primary surgery, and 2 cases underwent repair. The e-PTFE was sculpted to be personalized integrated prosthesis according to the shape of the patient's eyebrow arch and glabellar zone. The incision was designed on the medial and lateral sides of the lower margin of the bilateral eyebrow to avoid the supraorbital foramen, and the lacunae were striped under the frontal periosteum, and the two sides were connected to cover the glabellar zone and inverted triangle area between the eyebrows. The carved e-PTFE was implanted into one side and pulled out from the other side. The prosthesis was smoothed by Venn pliers of the ventral and dorsal sides.Results:The 45 patients in this group were followed up for 6-18 months. The incisions of all the patients were healed Ⅰ/A, and the scar of the incisions was concealed. Slight scalp numbness occurred in 4 patients and returned to normal 3 months later. The prosthesis in the glabellar zone appeared in 1 case 3 months after operation and returned to normal after reoperation. The symmetry, radian, fullness, convexity and tactility of bilateral eyebrow arch were all satisfactory in 45 cases. 39 cases were very satisfied, accounting for 86.7%; 6 cases (13.3%) were satisfactory. The sagittal distance of the anterior surface of the cornea to the soft tissues overlying the supraorbital rims was (2.02±1.72) mm preoperatively and (6.5±1.19) mm in the last follow-up. The difference was statistically significant ( t=14.49, P<0.01). Conclusions:This design of integral e-PTFE in eyebrow arch augmentation is safe, effective and easy to operate. It can significantly increase the bony beauty and stereoscopic sense of the eyebrow arch and glabellar zone, effectively deepen the eye socket, improve the eye protrusion, and reduce the risk of asymmetry and prosthesis displacement, and therefore it is one of the ideal methods for eyebrow arch augmentation.