ObjectiveThis paper aims to clarify the material basis of Gualou Niubangtang and establish a quantitative analysis method for its main constituents， providing a reference for the overall quality control of this preparation. MethodsThe constituents in the formula were systematically characterized based on ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. Identification was performed by matching with the UNIFI 9.6 software and utilizing database platforms such as PubChem， ChemicalBook， and ChemSpider， combined with relevant literature reports. A quantitative analysis method for the seven main constituents in Gualou Niubangtang was established by using high performance liquid chromatography （HPLC）. ResultsUPLC-Q-TOF-MS/MS analysis identified 155 constituents， including 69 flavonoids， 36 terpenoids， 23 phenylpropanoids， 8 phenylethanoid glycosides， and 19 other types of constituents. In the established quantitative analysis method， the seven main constituents showed good linearity within their respective linear ranges. The precision， repeatability， stability， and spike recovery all met the required standards. The results showed that the content ranges of geniposide， liquiritin， hesperidin， arctiin， baicalin， oroxylin A-7-O-β-D-glucuronide， and wogonoside in 15 batches of Gualou Niubangtang were 13.67-21.25， 1.20-7.64， 5.45-7.45， 22.97-33.51， 29.95-39.07， 2.58-4.80， and 6.56-9.31 mg·g^-1， respectively. ConclusionThis study successfully characterizes and attributes multi-category constituents in Gualou Niubangtang， clarifying that its material basis is primarily composed of flavonoids， terpenoids， phenylethanoid glycosides， and phenylpropanoids. Furthermore， it enables the quantification of seven constituents within the formula. This work lays a foundation for research on the quality control， action mechanism， and clinical application of this formula.

ObjectiveTo investigate the effects of metformin on the immune functions of immature dendritic cells （imDCs） and the underlying mechanisms. MethodsMouse bone marrow-derived imDCs were treated with different concentrations of metformin. The working concentration and treatment time of metformin in this study were determined based on the results of cell apoptosis and cell viability assays. The effects of metformin on the phagocytic capacity of imDCs was evaluated using an antigen endocytosis assay. The expression of cluster of differentiation 205 （CD205）， the polymerization of filamentous actin （F-actin）， and the underlying regulatory mechanisms were investigated through flow cytometry， laser confocal fluorescence microscopy， and Western blot. ResultsThe working concentrations of metformin were 1， 2， 4 mmol/L for 24 h determined by the apoptosis and cell viability assays.Metformin significantly suppressed the phagocytic capacity of imDCs， down-regulated the expression of the mannose receptor CD205 on the cell surface， which was closely associated with phagocytic function； metformin inhibited the RhoA-ROCK1-LIMK1-Cofilin signaling pathway， which inhibited the polymerization of F-actin and disturbed its dynamic remodeling of imDCs. ConclusionMetformin can inhibit the expression of CD205 and disrupt the remodeling of F-actin， thereby suppressing the antigen-capturing capacity of imDCs.

Armeniacae Semen Amarum， the dried mature seeds of plants such as Prunus armeniaca var. ansu （Rosaceae）， have a long history for medicinal use. Modern research indicates that the core active compounds of Armeniacae Semen Amarum， such as amygdalin， fatty acids， and volatile oils， exhibit multiple pharmacological effects including antitussive， bronchodilatory， anti-inflammatory， antioxidant， antitumor， antifibrotic， and immunomodulatory effects. Consequently， their potential applications in treating respiratory diseases， tumors， tissue injury， and metabolic disorders have garnered significant attention. However， a systematic integrated analysis of the relationship between the traditional efficacy， modern pharmacology， key material basis， and multi-pathway mechanisms of Armeniacae Semen Amarum remains lacking. Using bibliometric methods combined with CiteSpace visualization technology， this study systematically summarizes the research hotspots on Armeniacae Semen Amarum and its representative component amygdalin， including the key roles in inflammation regulation， apoptosis induction， cell cycle arrest， oxidative stress balance， and fibrosis modulation. This article reviews the research progress in Armeniacae Semen Amarum across from four major dimensions—traditional applications， visualization analysis， material basis， and modern pharmacological studies， providing a reference for the further basic and clinical studies of Armeniacae Semen Amarum in respiratory diseases， oncology， and immune-related disorders.

Objective To investigate the correlation between gut microbiota characteristics and immunotherapy efficacy in patients with advanced microsatellite stable (MSS) advanced gastrointestinal tumors. Methods Thirty patients with advanced MSS gastrointestinal tumors, including fourteen cases of gastric cancer and sixteen cases of colorectal cancer, who were admitted from November 1, 2022, to July 31, 2025 were enrolled. All patients underwent gut microbiota testing and received corresponding interventions on the basis of the results, followed by treatment with antiangiogenic agents combined with immunotherapy. Some patients additionally received probiotics or fecal microbiota transplantation. The primary endpoints were disease control rate (DCR) and objective response rate (ORR). The secondary endpoints were progression-free survival (PFS) and overall survival (OS). Univariate and multivariate Cox regression analyses were used to assess potential prognostic factors. Results Among the thirty patients, no complete response was observed. Two cases of partial response (PR), twelve cases of stable disease, and sixteen cases of progressive disease were recorded. The ORR was 6.7%, and the DCR was 46.7%. The median PFS was 6.4 months, and the median OS was 8.3 months. Both PR patients were classified as having a medium risk of gut microbiota dysbiosis and exhibited a Bacteroides-dominated enterotype. Multivariate analysis indicated that tumor type, liver metastasis, and bone metastasis were potential prognostic factors for PFS and OS. Conclusion Patients with a medium risk of gut dysbiosis may exhibit a relatively favorable response to immunotherapy, suggesting that gut microbiota status could serve as a potential biomarker for predicting treatment efficacy in advanced MSS gastrointestinal tumors.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

As people’s attention to health continues to increase, the market demand for traditional Chinese medicine (TCM) is growing steadily. The quality and safety of Chinese medicinal materials have attracted unprecedented social attention. In particular, the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society. The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM. This not only reflects China’s high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision. Basis on this study, by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detection standards in the Chinese Pharmacopoeia 2025 Edition, deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition. Moreover, it interprets the future development directions of the detection of exogenous residues in TCM, aiming to provide a reference for the formulation of TCM safety supervision policies.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

The Compilation Instructions for Expert Consensus on Clinical Application of Dieda Huoxue capsules systematically expound the development methods and evidence-based basis of this consensus. In view of the weak clinical application evidence and ambiguous indications of Dieda Huoxue capsules， the Institute of Basic Research in Clinical Medicine of the China Academy of Chinese Medical Sciences and Wangjing Hospital took the lead and collaborated with 33 experts from 28 medical institutions nationwide. They strictly followed the World Health Organization （WHO） guideline-making norms and the Grading of Recommendations Assessment， Development and Evaluations （GRADE） evidence-grading system and completed the compilation through multidisciplinary cooperation. The workflow included constructing clinical questions （19 items were screened by the nominal group technique）， retrieving evidence （from Chinese and English databases and grey literature）， assessing safety （integrating drug monitoring data and clinical investigations）， and forming recommendations and consensus suggestions （3 recommendations were reached via the GRADE grid method， and 16 consensus suggestions were reached by the majority vote rule）. The results indicate that the consensus clearly states that this medicine （Dieda Huoxue capsules） is applicable to conditions like traumatic injury， blood stasis-induced pain， and sudden lumbar sprains. The recommended dose is 6 capsules each time， twice a day. Combining oral administration with external application can enhance the efficacy， and elderly patients should take the medicine at intervals. Safety monitoring suggests that it should be used with caution in people with a bleeding tendency and those with an allergic constitution. The compilation process involved three rounds of reviews by internal and external experts. Literature analysis， the Delphi method， and clinical applicability tests were employed to ensure methodological rigor. The compilation instructions comprehensively present key aspects such as project approval and registration， conflict-of-interest statements， and evidence evaluation through 12 appendices， providing methodological support for the clinical translation of the consensus. In the future， it will be continuously improved through a dynamic revision mechanism.

Cancer represents a major worldwide disease burden marked by escalating incidence and mortality. While therapeutic advances persist, developing safer and precisely targeted modalities remains imperative. Nanomedicines emerges as a transformative paradigm leveraging distinctive physicochemical properties to achieve tumor-specific drug delivery, controlled release, and tumor microenvironment modulation. By synergizing passive enhanced permeation and retention effect-driven accumulation and active ligand-mediated targeting, nanoplatforms enhance pharmacokinetics, promote tumor microenvironment enrichment, and improve cellular internalization while mitigating systemic toxicity. Despite revolutionizing cancer therapy through enhanced treatment efficacy and reduced adverse effects, translational challenges persist in manufacturing scalability, longterm biosafety, and cost-efficiency. This review systematically analyzes cutting-edge nanoplatforms, including polymeric, lipidic, biomimetic, albumin-based, peptide engineered, DNA origami, and inorganic nanocarriers, while evaluating their strategic advantages and technical limitations across three therapeutic domains: immunotherapy, chemotherapy, and radiotherapy. By assessing structure-function correlations and clinical translation barriers, this work establishes mechanistic and translational references to advance oncological nanomedicine development.
Humans ; Neoplasms/radiotherapy* ; Immunotherapy/methods* ; Nanoparticles/chemistry* ; Animals ; Nanomedicine/methods* ; Drug Delivery Systems/methods* ; Drug Carriers/chemistry* ; Radiotherapy/methods*