The prescription of Qidong Yixin oral liquid is derived from the experience of national medical master Ren Jixue in treating viral myocarditis （VMC）. It has the functions of tonifying Qi， nourishing the heart，calming the mind， and relieving palpitations. It is used to treat VMC and angina pectoris of coronary heart disease caused by deficiency of both Qi and Yin. However，the understanding of its efficacy evidence， advantageous aspects， dosage and administration， and medication safety remains insufficient in clinical practice. Therefore，the development of the Expert Consensus on the Clinical Application of Qidong Yixin Oral Liquid （hereinafter referred to as consensus） was initiated. Consensus strictly followed the process and methods of the expert consensus on the clinical application of Chinese patent medicines of the China Association of Chinese Medicine，successively completing multiple tasks such as the consensus project initiation，determination of clinical problems，evidence search and evaluation，formation of recommendation opinions and consensus suggestions，solicitation of opinions，peer review， submission for review and release， and so on. Consensus formed a total of 10 recommendation opinions and 12 consensus suggestions，clarifying the clinical positioning，efficacy advantages，syndrome differentiation，dosage and administration，combination therapy，timing of medication，adverse reactions，contraindications， and precautions of Qidong Yixin oral liquid，indicating that it has good clinical advantages and safety in the treatment of VMC and angina pectoris of coronary heart disease，providing norms and references for physicians to safely and rationally apply Qidong Yixin oral liquid. Consensus was reviewed and approved for release by the Standardization Office of the China Association of Chinese Medicine on December 23， 2024. Standard number：GSCACM-376-2024.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Purpose: The aim of this study is to determine the impact of solute carrier family 3 member 2 (SLC3A2) on the malignant phenotype of gliomas and its role in regulating ferroptosis sensitivity. Materials and Methods: The malignant phenotype of glioma was assessed by cell proliferation assay, colony formation assay, EdU assay, wound healing, and Transwell experiments. We further validated the impact of reduced SLC3A2 expression on the sensitivity to ferroptosis in glioma cells through Cell Counting Kit-8 assays, flow cytometry, western blotting, and transmission electron microscopy. Western blot was used to explore how SLC3A2 affects glioma sensitivity to ferroptosis through the AKT/NF-E2-related factor 2 (NRF2)/glutathione peroxidase 4 (GPX4) axis. By establishing a subcutaneous xenograft tumor model in BALB/c-nude mice, we investigated the growth of tumors following the knockout of SLC3A2 in glioma cells. Results: Downregulation of SLC3A2 suppressed the malignant phenotype of glioma by blocking the cell cycle and epithelial-mesenchymal transition processes. On the other hand, loss of SLC3A2 not only downregulated SLC7A11 but also prevented the activation of the AKT/NRF2/GPX4 axis. These lead to increased accumulation of reactive oxygen species and lipid peroxides, ultimately enhancing the susceptibility of glioma to ferroptosis. Conclusion Our findings suggest that SLC3A2 is an oncogene in gliomas, promoting their occurrence and development. It plays a critical role in ferroptosis resistance through the AKT/NRF2/GPX4 axis.

ObjectiveFlavonoids are clinically significant natural products, yet their oxygen-glycosylation in aqueous environments relies heavily on expensive nucleotide-activated sugar donors such as UDP-glucose. Liquid-liquid phase separation (LLPS) creates specialized, membraneless physicochemical microenvironments capable of modulating enzymatic functions and overcoming mass transfer limitations. This study aims to investigate whether the gut microbiota-derived DgpB/C complex—a multienzyme system traditionally recognized for cleaving stable C-glycosidic bonds and facilitating isomerization—can undergo functional remodeling within phase-separated condensates. Our core objective is to elucidate the role of phase separation in expanding enzymatic catalytic plasticity and to provide a non-canonical, highly cost-effective biocatalytic mechanism for the direct utilization of free sugars in the synthesis of O-glycosylated natural products. MethodsAn artificial phase-separation platform was constructed utilizing the multivalent arginine-glycine-glycine motif (RGG)-repeat domain derived from the Caenorhabditis elegans LAF-1 protein. To ensure precise spatial compartmentalization, the DgpB/C complex was specifically recruited into the RGG condensates via a high-affinity SZ1/SZ2 heterodimerization tag system. Condensate formation and substrate partitioning were visualized using light and confocal fluorescence microscopy. The chemical structures and regioselectivity of the reaction products were rigorously characterized using high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS)/MS systems. Furthermore, molecular docking and 20-ns molecular dynamics (MD) simulations were performed via the Hermite platform and Uni-GBSA pipeline to elucidate the structural and thermodynamic basis underlying the phase-transition-induced functional shift. ResultsWe observed that the condensates formed by RGG proteins selectively recruited and significantly enriched hydrophobic flavonoid substrates. Strikingly, within the LLPS microenvironment, the DgpB/C complex—which typically exhibits only degradative or isomerase activities—underwent a profound functional remodeling, transforming into an efficientO-glycosyltransferase. Diverging from canonical pathways that require high-energy donors, the sequestered DgpB/C complex directly utilized unactivated free glucose to catalyze the formation of new O-glycosidic bonds. This remodeled activity was found to be evolutionarily conserved across DgpB/C homologs from diverse gut microbiota strains, such as P581a and W974-1. LC-MS/MS analysis further revealed that the phase-separated environment reduced the regioselectivity constraints of the enzyme, enabling catalytic action on multiple hydroxyl positions of the flavonoid scaffold. MD simulations further indicated that the low-water-activity microenvironment of the condensates reconfigured the conformational dynamics of the catalytic pocket, favoring a spatial orientation highly conducive to dehydration condensation. ConclusionThis study demonstrates that LLPS drives the functional remodeling of the gut microbiota enzyme DgpB/C through the reconfiguration of the physicochemical microenvironment. These findings challenge traditional perceptions regarding the functional boundaries of metabolic enzymes and reveal a novel biocatalytic pathway that bypasses the requirement for nucleotide-activated sugars. Consequently, this provides a highly promising artificial compartmentalization strategy for the green manufacturing of complex, high-value-added natural products.

Objective To analyze the factors affecting the prognosis of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy and construct an individualized prognostic nomogram prediction model. Methods A retrospective analysis was conducted on the clinical data of 385 patients with driver gene-negative, locally advanced or metastatic NSCLC who received first-line immune checkpoint inhibitors. Univariate and multivariate Cox regression analyses were used to identify prognostic risk factors, and a prognostic nomogram model was established. The predictive performance of the model was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC), and calibration curves. The cutoff value of the nomogram was calculated to stratify patients by risk. Survival curves were calculated by Kaplan-Meier analysis. Results Age (HR=1.775, 95%CI: 1.265-2.490), degree of differentiation (HR=0.365, 95%CI: 0.257-0.519), low PD-L1 expression (HR=0.661, 95%CI: 0.455-0.960), high PD-L1 expression (HR=0.423, 95%CI: 0.297-0.603), SCC-Ag (HR=1.549, 95%CI: 1.109-2.163), and CONUT score (HR=2.527, 95%CI: 1.797-3.554) were independent risk factors affecting overall survival (OS) of patients with NSCLC undergoing immunotherapy. The nomogram prediction model constructed on the basis of these factors had a C-index of 0.767. Time-dependent ROC curves for survival showed that the AUCs for 1-, 2-, and 3-year OS were 0.830, 0.853, and 0.886, respectively. Calibration curves indicated that the nomogram-predicted survival rates were in good agreement with the actual outcomes. The cutoff value for the study’s nomogram prediction model was 136.60 points, and survival curves showed statistically significant differences between different risk groups (P<0.05). Conclusion The nomogram model established in this study can effectively predict the prognosis of patients with driver gene-negative locally advanced or metastatic NSCLC treated with first-line immunosuppressive therapy. It provides a new tool for assessing prognosis and aids clinicians in formulating individualized treatment plans.

Morinda officinalis is one of the “Four Great Southern Medicines” and is commonly used in clinical practice to treat erectile dysfunction and nocturnal emissions caused by kidney yang deficiency， uterine cold infertility， menstrual disorders， low abdominal pain， rheumatism， and muscle and bone weakness. Based on the principle of “treating raw and cooked differently”， this article summarizes the effects of different processing methods on the chemical constituents and pharmacological effects of M. officinalis . Research has found that processing can affect the content and structure of sugars， iridoids， and anthraquinones in M. officinalis ， thereby regulating its pharmacological effects such as anti-osteoporosis， immune regulation， anti-fatigue， and anti-depression. Among them， salt M. officinalis shows outstanding performance in anti-osteoporosis and enhancing immunity. Although previous studies have preliminarily elucidated the major chemical constituents of M. officinalis and their pharmacological characteristics， the dynamic transformation paths of constituents during the processing remain to be further clarified， especially the es tablishment of a quality marker system associated with the processing technology， to achieve the precision and intelligent development of the processing.

Morinda officinalis is one of the “Four Great Southern Medicines” and is commonly used in clinical practice to treat erectile dysfunction and nocturnal emissions caused by kidney yang deficiency， uterine cold infertility， menstrual disorders， low abdominal pain， rheumatism， and muscle and bone weakness. Based on the principle of “treating raw and cooked differently”， this article summarizes the effects of different processing methods on the chemical constituents and pharmacological effects of M. officinalis . Research has found that processing can affect the content and structure of sugars， iridoids， and anthraquinones in M. officinalis ， thereby regulating its pharmacological effects such as anti-osteoporosis， immune regulation， anti-fatigue， and anti-depression. Among them， salt M. officinalis shows outstanding performance in anti-osteoporosis and enhancing immunity. Although previous studies have preliminarily elucidated the major chemical constituents of M. officinalis and their pharmacological characteristics， the dynamic transformation paths of constituents during the processing remain to be further clarified， especially the es tablishment of a quality marker system associated with the processing technology， to achieve the precision and intelligent development of the processing.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

Objective: To develop a modified calculation formula for renal tumor volume and tumor contact surface area (CSA) based on the modeling results of 3D Slicer software, and to create a webpage of the calculation formula for use. Methods: The general information and tumor anatomical data of 98 patients who underwent partial nephrectomy during Jan.2021 and Jul.2023 in the Second Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed.The imaging data were input into 3D Slicer software in the form of Dicom files for tumor and ipsilateral kidney modeling to obtain tumor anatomical data.The relationship between tumor anatomical parameters and tumor volume and CSA was analyzed using multifactorial linear regression.The initial modified formulas (V2, C2) and the optimized modified formulas (V3, C3) for tumor volume over CSA were established, respectively, after insignificant variables were eliminated.The mean square error (MSE) and Akaike information criterion (AIC) of the modified and traditional formulas (V1, C1) were compared, and the formula with the smallest MSE and AIC was selected as the optimal tumor volume and CSA calculation formula.The median tumor volume and CSA obtained from 3D modeling were used as the cutoff values.The optimal formula and conventional formula were applied to calculate tumor volume and CSA for all patients, and risk stratification was performed for all patients based on these cutoff values, and the perioperative indicators of patients in the upper and lower groups were compared.Finally, an online calculation tool was developed based on HTML. Results: Based on multifactorial linear regression analysis, we obtained the modified tumor volume calculation formula: V=0.382abc+2.488a+2.372b－4.146c+1.948（V2）, V=0.469abc－4.586c+13.816（V3）; the modified tumor CSA calculation formula CSA=2.469a －2.262L －19.23a+6.206b+1.212c+18.017L+1.616h－3.97h －2.185h/h －0.388（C2）, CSA=2.376a －2.144L －20.157a+5.024b+1.128c+17.578L+2.525h－2.634（C3）.Both of the modified volume formula (MSE=151.298 vs. 127.807 vs. 104.106) and modified CSA formula (MSE=309.878 vs.23.556 vs.30.388) had smaller errors compared to the conventional formula.The modified volume calculation formula showed that bleeding was more and thermal ischemia time was longer in patients with larger tumor volumes than in patients with smaller tumor volumes (P<0.05); and the modified CSA calculation formula showed that bleeding was more, surgery and thermal ischemia time were longer in patients with high CSA than in patients with low CSA (P＜0.05).Finally, V3 and C3 are selected as the best calculation formula, and a web page (https://lizihao-bot.github.io/RCC-Calculate/) was established for easy use. Conclusion: This study combined data from a medical information technology platform with numerical modeling methods to provide a faster and more accurate method to calculate the renal tumor volume and CSA.Meanwhile, a webpage version of the tool was developed to enhance its practicability.

ObjectiveBased on modern analytical techniques and a depressed mouse model established by chronic unpredictable mild stress（CUMS）， to evaluate the quality marker（Q-Marker） and pharmacodynamic difference of Baihe Dihuangtang prepared by different processes. MethodsHigh performance liquid chromatography（HPLC） was used to establish the characteristic profiles of Baihe Dihuangtang， and determine the content of Q-Marker in the samples prepared by ancient and modern processes. Seventy C57BL/6J mice were randomly divided into the normal group， model group， fluoxetine group（3 mg·kg^-1）， low and high dose groups of ancient process（6.5， 26 g·kg^-1）， and low and high dose groups of modern process（6.5， 26 g·kg^-1）， with 10 mice in each group. Except for the normal group， CUMS was used to induce depression in mice from the other groups for 28 d. After successful modeling， administration groups were given the corresponding drugs by gavage every day， and the normal and model groups were given an equal volume of pure water by gavage for 21 consecutive days. Change in body mass of mice was recorded， tail suspension test and open field test were used to evaluate the depressive behavior of mice， and enzyme-linked immunosorbent assay（ELISA） was employed to determine the contents of tumor necrosis factor-α（TNF-α）， interleukin（IL）-1β and IL-6 in serum. ResultsCharacteristic profiles of Baihe Dihuangtang prepared by the two processes were established， the similarity between the two was 0.951， and 8 characteristic peaks were recognized with the reference peak of regaloside A. The results of quantitative analysis showed that the Q-Marker content was similar in Baihe Dihuangtang prepared by ancient and modern processes. The results of pharmacodynamics showed that， compared with the normal group， the model group showed increased immobility time in the tail suspension test， reduced total movement distance in the open field test， and elevated IL-1β， IL-6 and TNF-α levels in the serum（P<0.01）. Compared with the model group， the behavioral indicators of mice in the Baihe Dihuangtang treatment group were significantly improved in terms of tail suspension time and open field exercise， and the levels of IL-1β， IL-6 and TNF-α in serum were significantly reduced（P<0.05， P<0.01）. Baihe Dihuangtang prepared by the two processes both had antidepressant effects， and the difference between the two was not statistically significant in improving depressive symptoms. ConclusionQ-Marker of Baihe Dihuangtang prepared by modern and ancient methods are equivalent in content， and the pharmacological effects are consistent， indicating that dried Lilii Bulbus can replace fresh products in the preparation of Baihe Dihuangtang. This study provides a scientific basis for the development of new drugs of Baihe Dihuangtang and a reference for its rational application and clinical use.