ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

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.

Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.

Objective To investigate the clinical effect of posterior femoral composite tissue flap pedicled with inferior gluteal artery for repair of huge sacrococcygeal pressure injuries.Methods The clinical data of 11 patients with huge sacrococcygeal pressure injuries admitted to our hospital were retrospectively analyzed,with a mean wounds area of(205.3±15.3)cm2,and the depth of the wounds all reached the sacrococcygeal bone surface with partial sacrococcygeal necrosis.The inferior gluteal artery and its perforating branch were investigated with ultrasonic Doppler flow detector before operation,the posterior femoral composite tissue flap pedicled with inferior gluteal artery was designed according to the wound surface,and then the chronic sacrococcygeal wound was repaired.The operation time,intraoperative blood loss,wound healing,postoperative skin flap survival and occurrence of complications were recorded.The skin flap color,temperature and two-point discernability were monitored to evaluate skin flap sensory sensitivity.The visual analog scale(VAS)was used to evaluate the satisfaction of appearance.Results The operation time of patients was(2.8±0.1)hours and the intraoperative blood loss was(235.4±10.2)mL.The posterior femoral composite tissue flap pedicled with inferior gluteal artery of all the 11 patients survived.The distal part of the flap was necrotic in 1 case,which healed well after local debridement and suturing by amplification;other wounds healed well in the first stage without complications such as infection,fat liquefaction or hematoma.The skin flap has good color,soft texture,and good elasticity,with good healing in the donor area.There were significant differences in the skin flap temperature,two-point discernability and VAS score of appearance satisfaction between 12 months after operation and other time points(P＜0.05).Conclusion The posterior femoral composite tissue flap pedicled with inferior gluteal artery has a constant blood supply,without damage to the main blood vessels.It can be transposed at anterograde or retrograde direction,with simple operation and less damage,which can reconstruct flap sense,and has significant clinical efficacy in repairing huge sacrococcygeal pressure injuries.

Objective:To retrieve, evaluate, and summarize the evidence on fertility management for cervical cancer patients of childbearing age, providing a basis for clinical medical and nursing staff to carry out fertility management for cervical cancer patients.Methods:The evidence on fertility in cervical cancer patients included clinical decision-making, guidelines, summary of evidence, expert consensus, and systematic review, which were systematically searched on domestic and international evidence-based medicine databases, clinical decision-making systems, guideline websites, professional association websites, medical literature service websites, and databases such as UpToDate, Cochrane Library, British Medical Journal (BMJ) Best Practice, China Guidelines Network, China National Knowledge Infrastructure, WanFang Med Online, China Biology Medicine disc, and VIP. The search period was from database establishment to March 1, 2023. Two researchers who received evidence-based nursing knowledge training independently conducted literature screening and quality evaluation, and jointly discussed with clinical experts on the literature that met the requirements to complete evidence extraction and summary.Results:A total of 11 articles were included, including three clinical decision-making, four guidelines, three expert consensus, and one systematic review. A total of 30 pieces of best evidence were summarized from six aspects, including fertility assessment and safety, fertility preservation methods, fertility preservation surgery and anti-tumor treatment, fertility timing, pregnancy management and follow-up, and special treatment for pregnancy with cervical cancer.Conclusions:The evidence on fertility management for cervical cancer patients of childbearing age provides a basis for clinical medical and nursing staff to provide fertility guidance for cervical cancer patients. In clinical application, factors such as patient willingness and condition should be fully considered, and personalized treatment plans should be provided to maximize patient benefits.

Objective To construct a machine learning model for predicting benign and malignant pulmonary nodules based on CT features.Methods A total of 129 patients with single solid nodules on CT from January 2021 to January 2023 in Hai'an People's Hospital were selected.All of them underwent chest CT scan,and the quantitative parameters,morphological features and radiomics features were recorded.The differentiation of benign and malignant pulmonary nodules was carried out according to relevant diagnostic criteria.The cases were divided into the training set and the internal test set.The constructed models included radiomics labels,morphological model,CT model and combined model.Results There were 98 cases in the training set(27 malignance and 71 benign)and 31 cases in the internal test set(7 malignance and 24 benign).Univariate analysis showed that there were significant differences in age,lesion diameter,mean density,burr sign,pleural depression sign,vacuole sign and air bronchial sign between malignant group and benign group(P<0.05).Compared with benign group,malignant group had higher proportions of burr sign,pleural depression sign,vacuole sign,air bronchial sign,and larger lesion diameter and mean density(P<0.05).LinkDocAI intelligent diagnosis system for pulmonary nodules was used to outline regions of interest and from which 1 000 radiomics features were extracted.The feature selection was performed in 98 cases,and 20 features were screened out after standardized treatment and correlation testing,excluding missing features,low importance feature values and highly correlated features.Through LASSO regression and 10-fold cross validation,λ1se was selected as the optimal λ to construct radiomics labels,and the two most meaningful features(LBP_Glszm_ZoneEntropy and Gradient_Shape_MinorAxis)were enrolled.CT model was considered as the optimal model in this study,and it had an area under receiver operating characteristic curve of 0.912 and 0.889 in the training set and the internal testing set,respectively.Conclusion The machine learning model to predict benign and malignant lung nodules based on CT features has good predictive efficiency,and it can realize the differential diagnosis of benign and malignant pulmonary nodules.

Objective To study the diagnostic value of miR-571 for liver fibrosis by detecting miR-571 expression in the peripheral blood of patients with liver fibrosis.Methods From December 2022 to September 2023,40 patients with liver fibrosis,40 patients with chronic hepatitis,and 40 healthy controls were chosen as research subjects.The expression level of miR-571 in peripheral blood was detected using a real-time quantitative polymerase chain reaction,and the relative expression of miR-571 in each group was evaluated.The Spearman correlation method was utilized to examine the relationship between miR-571 and clinical detection indices.To assess the capacity of miR-571 and the multivariate diagnostic model to identify liver fibrosis,binary logistic regression was used to create a multivariate diagnostic model,and ROC curves were generated.Results The expression of miR-571 was significantly higher in the liver fibrosis group than in the healthy control and hepatitis groups,and the difference was statistically significant(P<0.001).The expression level of miR-571 was positively connected with ALT,APRI score,and FIB-4 index(r = 0.23,0.30,0.22,P<0.05)and negatively correlated with PLT(r =-0.19,P<0.05)according to Spearman correlation analysis.Logistic regression research revealed that miR-571 and the FIB-4 index were independent risk factors for liver fibrosis.The AUC for miR-571 to diagnose fibrosis was 0.91(95%CI:0.85～0.96),while the AUC for miR-571 paired with the FIB-4 index was 0.94(95%CI:0.90～0.98).Conclusion MiR-571 expression was shown to be considerably higher in the peripheral blood of hepatic fibrosis patients,and the combined FIB-4 index offers some clinical diagnostic value for hepatic fibrosis.

Objective To investigate the value of computer-assisted quantification of pulmonary embolism volume(PEV)in identifying mild-to-high-risk acute pulmonary embolism(APE).Methods We retrospectively enrolled 143 patients with suspected APE confirmed by computed tomography pulmonary angiography(CTPA)at Yan'an University Affiliated Hospital from January 2017 to December 2020.According to the 2018 Chinese Guidelines for Diagnosis,Treatment and Prevention of Pulmonary Thromboembolism,all the patients were divided into low-risk group(n=88)and mild-to-high-risk group(n=55).We collected the patients'basic demographic data,clinical manifestations,and serum levels of N-terminal-B type natriuretic peptide precursor(NT-proBNP)and D-dimer.Based on CTPA images,the degree of pulmonary thromboembolism was artificially evaluated to obtain the pulmonary artery occlusion index(PAOI).The thrombus was segmented using the pulmonary embolism detection tool based on digital lung,and PEV was calculated.We compared the differences in clinical and laboratory indicators and PAOI and PEV between the two risk groups.We analyzed the value of PAOI and PEV in identifying mild-to-high-risk APE using receiver operating characteristic(ROC)curves,and used Logistic regression analysis to identify independent risk factors in predicting mild-to-high-risk APE.Different models were established.Results Compared with the low-risk group,APE patients in the mild-to-high-risk group were older(P＜0.05),had lower diastolic blood pressure(P＜0.05),higher levels of D-dimer and NT-proBNP(P＜0.05),lower levels of platelet count,arterial oxygen partial pressure and arterial carbon dioxide partial pressure(P＜0.05),and higher levels of PAOI and PEV(P＜0.001).ROC curve analysis showed that the area under the curve for PEV in identifying mild-to-high-risk APE was 0.809(95％CI:0.734-0.884),while that for PAOI was 0.753(95％CI:0.667-0.839).Logistic regression analysis showed that PEV and NT-proBNP were independent risk factors for mild-to-high-risk APE(P＜0.05).Conclusion PEV and NT-proBNP are independent risk factors for mild-to-high-risk APE.

[Objective] In view of the crucial role of indole propionic acid in the treatment of tumor immune checkpoint blockade and further revealing its mechanism, our study intended to design and synthesize 1-[¹⁸F]-fluoroethyl-indole propionic acid (1-[¹⁸F]-IPA), and evaluate it as a tumor PET imaging agent. [Methods] The precursor 1-(2-p-toluenesulfonic acid oxygen ethyl)-methyl indole propionate underwent nucleophilic substitution reaction with ¹⁸F^-. The crude product was separated and purified by high-performance liquid chromatography and the intermediates were collected. Finally, 1-[¹⁸F]-IPA was obtained by hydrolysis. The clarity of the product was measured by visual inspection, the pH value was determined by precision test paper, and the radiochemical purity and stability were determined by high-performance liquid chromatography. In order to determine the biodistribution of 1-[¹⁸F]-IPA in normal mice, ICR mice were intravenously injected with 1-[¹⁸F]-IPA (0.2 mL, 7 MBq), and sacrificed at 5, 15, 25, 45, 75 and 120 min and dissected. Micro-PET imaging was performed and analyzed in BxPC-3 tumor-bearing nude mice. Student t test was used to compare the biodistribution of tissues and organs at different time points. [Results] The total preparation time of 1-[¹⁸F]-IPA was 35-40 min, the radiochemical yield was (45±5)%, and the radiochemical purity was more than 95%. The product solution was clear without particles, and the pH value was 6.5, which had good stability in vitro and in vivo. The results of biodistribution in healthy ICR mice showed that except for the brain, 1-[¹⁸F]-IPA had a certain uptake in all major organs, with the most obvious uptake in the liver, gallbladder and kidneys. The radioactivity in the gallbladder gradually increased with time and reached (39.86±6.56)%ID/g at 120 min, but bone uptake did not change significantly with time. Micro-PET/CT showed that there was radioactive uptake at the tumor 30 min after injection of 1-[¹⁸F]-IPA in Dutch BxPC-3 nude mice, but it was not obvious. At this time, SUVmax was about 55.18±14.62. Consistent with the results of biodistribution, the brain uptake was low at each time point. [Conclusion] In summary, 1-[¹⁸F]-IPA with short preparation time and high yield is expected to be a tool to probe tryptophan indole metabolism pathway and further reveal tumor immune resistance.