italic>Sophora flavescens is a traditional Chinese medicine rich in flavonoids and has wide application potential in drug development and clinical practice. In this study, a total of 227 flavonoids were detected among five tissues of S. flavescens during anthesis using widely targeted metabolomics techniques. There were 137 flavonoids shared by five S. flavescens tissues and 18 root-specific flavonoids. There were 156, 155, 156 and 150 differentially accumulated metabolites identified in stem, leaf, flower, and young pod, respectively, compared with root. Forty-seven potentially active flavonoid components in S. flavescens were identified using the PubChem and SwissADME databases. The 58 potential target proteins for these potentially active components were predicted to be important in the treatment of type 2 diabetes mellitus (T2DM) based on the SwissTargetPrediction and GeneCards database. These 58 target proteins were used to construct a protein-protein interaction network through the STRING database, from which we performed GO and KEGG functional enrichment analysis. The mechanisms by which S. flavescens flavonoids may be useful in the treatment of T2DM was further explored in a multi-level and systematic way based on a "component-target-pathway" network. Finally, ten key potentially effective components were identified and found to be mainly distributed in the roots, flowers, and pods, and their content varied significantly between tissues. The results predict that the key targets of S. flavescens flavonoids in the treatment of T2DM are AKT1, ESR1, EGFR, PIK3R1, TNF and PTGS2, and that they play a hypoglycemic role through the regulation of endocrine resistance, AGE-RAGE, the PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance and other signaling pathways. This analysis of the tissue distribution and network pharmacology of S. flavescens flavonoids provides a theoretical basis for further studies on S. flavescens metabolites, the rational development and utilization of the S. flavescens aboveground parts, and initiates a comprehensive exploration of the mechanisms by which S. flavescens can be used in the treatment of T2DM.

ObjectiveTo explore the correlation between the content of 4 functional components in Codonopsis pilosula roots from different areas and soil factors， and thereby to lay a theoretical basis for soil ecological regulation and improvement of quality of C. pilosula roots. MethodThe content of lobetyolin， atractylenolide Ⅲ， alcohol extract， and polysaccharides， as well as soil fertility and 16 soil factors in 24 batches of samples from different producing areas were determined. Principal component analysis （PCA） and Pearson's correlation analysis were used to explore the key soil factors leading to the variation of chemical component content in C. pilosula roots. ResultThe content of lobetyolin and atractylenolide Ⅲ in samples from Longxi was the highest， and the content of polysaccharides peaked in samples from Huguan. The content of lobetyolin was in positive correlation with soil total nitrogen， total phosphorus， total potassium， alkali-hydrolyzable nitrogen， and available potassium （P<0.01）， as well as soil organic matter， pH， available manganese， and available zinc （P<0.05）. There was a positive correlation between pH and atractylenolide Ⅲ content （P<0.05）. Soil total potassium was in positive correlation with alcohol extract and polysaccharide content （P<0.01）. Soil available zinc was positively correlated with alcohol extract and the polysaccharide content （P<0.05）. Sample sites with higher PCA scores were Pingshun， Huguan， and Longxi， which were significantly positively correlated with the content of polysaccharides in C. pilosula roots in different habitats. ConclusionThe content of functional components in C. pilosula roots can be improved by raising soil organic matter content and applying specific fertilizers.

Objective: To investigate the clinicopathological characteristics of pancreatic lesions in children. Methods: The clinicopathological data of pancreatic lesions in children were analyzed including 42 cases of pancreatic tumors diagnosed from January 2000 to May 2021 in Guangzhou Women's and Children's Medical Center, Guangzhou, China. Histological and immunohistochemical assessments were performed . Related literature was reviewed. Results: The 42 pediatric patients with pancreatic lesions aged 1 day to 12 years (mean, 4.25 years). There were 23 males and 19 females. Clinical presentations included abdominal masses, abdominal pain, vomiting and persistent hypoglycemia after birth. Ultrasound and computerized tomography examination showed space-occupying pancreatic lesions in 31 cases, but no detectable pancreatic lesions in 11 cases. Histologically, among the 42 cases, 22 cases (52.4%) were neoplastic, including 18 cases of epithelial origin. Nine cases of pancreatoblastoma showed that the epithelial tumor cells were arranged in a trabecular pattern, with squamous nests. Six cases of solid-pseudopapillary tumors revealed hemorrhagic and necrotic cysts and monomorphic epithelioid cells arranged in solid sheets, nests or pseudopapillae. Two cases of neuroendocrine tumors showed tumor cells arranged in cords or nests; one case had a mitotic count of about 3/10 high power field, and a Ki-67 index of about 5%, which was consistent with G2 neuroendocrine tumor; the other case showed tumor cells with cytological atypia, brisk mitoses, about 25/10 HPF and a Ki-67 index of about 80%, consistent with small-cell type neuroendocrine carcinoma. The case of acinar cell carcinoma showed high cellularity, tumor cells in solid, cord-like or acinar-like arrangement with little stroma, and monotonous tumor cells with single distinct nucleolus. There were 4 cases of mesenchymal tumors, including 3 cases of Kaposi's hemangioendothelioma and 1 case of inflammatory myofibroblastic tumor. Among the 20 cases (47.6%) of non-neoplastic lesions, there were 11 cases of hyperinsulinism with ATP-sensitive potassium channel abnormality (HAPCA). Severn cases of diffuse type HAPCA in which the islets scattered between the pancreatic acinar tissue, enlarged, and prominent nuclei. Three cases of focal type HAPCA showed pancreatic islet hyperplasia in the form of nested nodules (0.6-1.5 cm). One case of atypical type HAPCA had extensive islet hyperplasia in pancreatic tissue, and scattered proliferation of nest-like nodules was noted. There were also 7 cases of pseudocyst and 2 cases of congenital cyst. Immunohistochemically, pancreatoblastomas were diffusely positive for CKpan, CK8/18, and β-catenin (nuclear staining of squamous nests only). Solid-pseudopapillary tumors expressed CD10, cyclin D1, CD99, vimentin, CD56, and β-catenin (nuclear staining). Neuroendocrine tumors were positive for CK, Syn, NSE, CgA, CD56, and β-catenin (membranous staining). The acinar cell carcinoma was positive for CK8/18, trypsin, and β-catenin (membranous staining). Conclusions: Pancreatic lesions in children have a wide range of histopathological types. HAPCA is the most common lesion of newborns. Pediatric pancreatic tumors are rare and mostly malignant. It is important to recognize them and make correct pathological diagnoses.
Carcinoma, Acinar Cell/pathology* ; Carcinoma, Squamous Cell ; Child ; Female ; Humans ; Hyperplasia ; Infant, Newborn ; Ki-67 Antigen ; Male ; Neuroendocrine Tumors ; Pancreatic Neoplasms/metabolism* ; beta Catenin/analysis*

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

"The Expert Group on Tumor Ablation Therapy of Chinese Medical Doctor Association, The Tumor Ablation Committee of Chinese College of Interventionalists, The Society of Tumor Ablation Therapy of Chinese Anti-Cancer Association and The Ablation Expert Committee of the Chinese Society of Clinical Oncology" have organized multidisciplinary experts to formulate the consensus for thermal ablation of pulmonary subsolid nodules or ground-glass nodule (GGN). The expert consensus reviews current literatures and provides clinical practices for thermal ablation of GGN. The main contents include: (1) clinical evaluation of GGN, (2) procedures, indications, contraindications, outcomes evaluation and related complications of thermal ablation for GGN and (3) future development directions.
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