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.

With the rapid advancement of medical technology and the increasing complexity of clinical environments, competence in clinical ethical decision-making has become an indispensable core competency for exemplary physicians. However, traditional medical ethics education has long been confronted with the persistent challenges of theory-practice dissociation and the disconnect between pedagogical settings and clinical realities. Thus, how to construct a "Clinical Ethics" curriculum that aligns with the objectives of training high-caliber medical professionals has emerged as a critical and challenging issue in current medical education reform. To effectively address this challenge, the Office of Education at Peking University Third Hospital, since 2021, has assembled a multidisciplinary "Clinical Ethics" teaching and management team comprising faculty from Peking University School of Humanities and key clinical specialists from the hospital. In 2022, the "Clinical Ethics" elective course was formally launched for fourth-year students in the eight-year MD program who had completed coursework in "Medical Ethics" and organ-system-based curricula, with the aim of exploring and operationalizing a pre-clinical ethics education model tailored for senior medical students. The course employs a modular instructional design encompassing "theoretical review-case-based deliberation-clinical workshop", which effectively facilitates the deep integration of medical humanities with clinical practice.Following four years of iterative refinement through the "plan-act-observe-reflect" cycle, the course has demonstrated positive outcomes in enhancing students' ethical awareness and decision-making capabilities, and has preliminarily established a sustainable collaborative mechanism among the multidisciplinary faculty team. This article systematically delineates the course development background, pedagogical model and methodological innovations, and the multidisciplinary collaborative framework, alongside reflections and summaries based on implementation outcomes, with the intent of providing references for the future development of "Clinical Ethics" curricula.

The present study delves into the cellular mechanisms underlying the antiviral effects of dehydrodiisoeugenol(DEH) by focusing on the transcription factor EB(TFEB)/autophagy-lysosome pathway. The cell counting kit-8(CCK-8) was utilized to assess the impact of DEH on the viability of human non-small cell lung cancer cells(A549). The inhibitory effect of DEH on the replication of influenza A virus(H1N1) was determined by real-time quantitative polymerase chain reaction(RT-qPCR). Western blot was employed to evaluate the influence of DEH on the expression level of the H1N1 virus nucleoprotein(NP). The effect of DEH on the fluorescence intensity of NP was examined by the immunofluorescence assay. A mouse model of H1N1 virus infection was established via nasal inhalation to evaluate the therapeutic efficacy of 30 mg·kg~(-1) DEH on H1N1 virus infection. RNA sequencing(RNA-seq) was performed for the transcriptional profiling of mouse embryonic fibroblasts(MEFs) in response to DEH. The fluorescent protein-tagged microtubule-associated protein 1 light chain 3(LC3) was used to assess the autophagy induced by DEH. Western blot was employed to determine the effect of DEH on the autophagy flux of LC3Ⅱ/LC3Ⅰ under viral infection conditions. Lastly, the role of TFEB expression in the inhibition of DEH against H1N1 infection was evaluated in immortalized bone marrow-derived macrophage(iBMDM), both wild-type and TFEB knockout. The results revealed that the half-maximal inhibitory concentration(IC_(50)) of DEH for A549 cells was(87.17±0.247)μmol·L~(-1), and DEH inhibited H1N1 virus replication in a dose-dependent manner in vitro. Compared with the H1N1 virus-infected mouse model, the treatment with DEH significantly improved the body weights and survival time of mice. DEH induced LC3 aggregation, and the absence of TFEB expression in iBMDM markedly limited the ability of DEH to counteract H1N1 virus replication. In conclusion, DEH exerts its inhibitory activity against H1N1 infection by activating the TFEB/autophagy-lysosome pathway.
Influenza A Virus, H1N1 Subtype/genetics* ; Animals ; Autophagy/drug effects* ; Humans ; Mice ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Influenza, Human/metabolism* ; Lysosomes/metabolism* ; Orthomyxoviridae Infections/genetics* ; Eugenol/pharmacology* ; Antiviral Agents/pharmacology* ; Virus Replication/drug effects* ; A549 Cells ; Male

Salvia miltiorrhiza (Danshen) is a traditional Chinese herb that is commonly known for its cardiovascular and hepatoprotective benefits. Recent studies have confirmed that Danshen and its bioactive components can influence gut microbial homeostasis, thereby affecting Helicobacter pylori (HP) colonization in the human stomach. HP is a bacterial pathogen associated with various gastrointestinal diseases. Current HP treatments mainly involve antibiotics and proton pump inhibitors. However, their efficacy is strongly compromised by the rapid emergence of antibiotic resistance in HP and genetic heterogeneity among patients. The interaction between Danshen and gut microbial status provides a novel perspective for HP treatment. Understanding the medical properties of Danshen in altering gut microbiota and eliminating HP, as well as the underlying mechanisms, is important for improving human gastrointestinal healthcare. This review investigates the interaction between Danshen and gut microbiota and its impact on HP infection using databases including Web of Science, PubMed, and Google Scholar. We explored the unconventional intersection between Danshen, gut microbiota, and HP infection, shedding light on their intricate interplay and potential therapeutic implications. A comprehensive understanding of this interaction provides valuable insights into developing novel therapeutic strategies that target the gut microbiota to mitigate HP-associated gastrointestinal disorders. Please cite this article as: Li SJ, Miao JX, Wang F, Wang HY, Ma YW, Jiang Y, Xue X. Salvia miltiorrhiza components and gut microbiota interactions in Helicobacter pylori infection. J Integr Med. 2025; 23(5):462-470.
Salvia miltiorrhiza/chemistry* ; Gastrointestinal Microbiome/drug effects* ; Humans ; Helicobacter Infections/microbiology* ; Helicobacter pylori/drug effects* ; Drugs, Chinese Herbal/therapeutic use*

Hematologic malignancies,such as lymphoma,myeloma,and myeloid neoplasms,can occur in extramedullary tissues.Traditional histopathological morphology and immunohistochemical staining have lim-itations,including time-consuming specimen processing,prolonged reporting cycles,and relatively low sensi-tivity in cases of limited cell numbers.Flow cytometry offers significant advantages in detecting tissue sam-ples,such as rapid processing,shorter reporting cycles,and high accuracy and sensitivity,making it an effective complement to histopathological and immunohistochemical methods.However,the application of flow cytome-try in tissue sample detection currently lacks standardized protocols for sample collection and preservation,single-cell suspension preparation,antibody panel design for limited samples,data analysis,and result repor-ting.To promote the standardized application of flow cytometry in detecting hematologic tumor cells in tissue samples,the Cell Analysis Professional Committee of the Chinese Society of Biotechnology organized experts to develop the Chinese Expert Consensus on Flow Cytometry for Detecting Hematologic Tumor Cells in Tis-sue Samples(hereinafter referred to as the Consensus).This Consensus elaborates on the technical aspects of flow cytometry for tissue sample detection,covering sample processing,antibody panel design,data analysis,reporting content,and quality management.It particularly emphasizes recommended antibody panels and data analysis methods for flow cytometry when tissue sample cell counts are low.This article aims to interpret the key points of the Consensus to facilitate its better application in clinical practice.

Objective:To evaluate the diagnostic value of non-targeted detection of metabolic fingerprinting in pulmonary nodules and to analyze the clinical effective model of multi-omics for assessing the malignant risk of pulmonary nodules.Methods:A total of 73 patients who underwent chest CT and completed pathological diagnosis and non-targeted detection of metabolic fingerprinting at Shandong Provincial Hospital Affiliated to Shandong First Medical University from November 2021 to October 2024 were selected as the research subjects. According to the postoperative histopathological diagnosis, the patients were divided into the lung malignant nodule group (61 cases) and the lung benign nodule group (12 cases). General clinical data of the patients, including sex, age, smoking history, and family history of tumors, as well as imaging data, including nodule density, nodule size, nodule location, nodule number, and special imaging manifestations (spiculation, lobulation, vacuole sign, vascular convergence sign, etc.), and non-targeted detection of metabolic fingerprinting results were collected. The above data were compared between the two groups of patients, and the receiver operator characteristic (ROC) curve was drawn to evaluate the predictive value of each model. Results:There were statistically significant differences in age ( t=4.41, P<0.001), nodule size ( Z=2.67, P=0.008), nodule density ( χ2=4.64, P=0.031), and spiculation ( χ2=7.67, P=0.006) between the lung malignant nodule group and the lung benign nodule group. There were no statistically significant differences in sex, smoking history, family history of lung cancer, nodule number, nodule location, lobulation, vacuole sign, vascular convergence sign, pleural indentation sign, calcification sign, bronchial truncation sign, vascular supply sign, and bronchial air sign (all P>0.05). The number of non-targeted detection of metabolic fingerprinting high-risk patients in the lung malignant nodule group (36 cases) was significantly higher than that in the lung benign nodule group (0 case) ( χ2=13.97, P<0.001). ROC curve analysis showed that the area under the curve of the Brock model combined with non-targeted detection of metabolic fingerprinting was 0.930 (95% CI: 0.872-0.988), which was greater than that of the Brock model (0.856, 95% CI: 0.769-0.942, Z=0.27, P=0.040) and non-targeted detection of metabolic fingerprinting (0.768, 95% CI: 0.650-0.887, Z=0.30, P=0.004) alone. Conclusions:Non-targeted detection of metabolic fingerprinting risk assessment may serve as a non-invasive method to assist the Brock model in the diagnosis of pulmonary nodules and has good application value. The combination of the Brock model and non-targeted detection of metabolic fingerprinting can more accurately distinguish the benign and malignant nature of pulmonary nodules.

Objective To explore the effect of hydrogen molecules on the psychological state of submariners after long voyage.Methods A total of 197 submariners who had participated in a long-voyage mission were selected as the research objects by cluster sampling.They were randomly assigned to observation group or control group.The observation group was given hydrogen inhalation and hydrogen-enriched drinking water for 30 days,while the control group was given air inhalation and purified water.Before and after the intervention,mental health status was assessed by the Symptom Checklist 90(SCL-90),Self-rating Anxiety Scale(SAS),and Self-rating Depression Scale(SDS).The cognitive ability,such as digit conversion,visual memory,tracking goal,and number span were tested.Results After the intervention,the score of each dimension and positive items of SCL-90,as well as the total scores of SAS and SDS were decreased in both groups(P<0.05 or P<0.01),and the scores of depression and anxiety and positive items of SCL-90,as well as the total scores of SAS and SDS in the observation group were lower than those in the control group(P<0.01).The single correct response time for digit conversion in the observation group was shorter than that in the control group(P<0.01).Conclusion Hydrogen molecule can improve mental health and cognitive performance of submariners after long voyage.

Objective To establish an expert consensus on the management of mini-midline catheters(hereinafter referred to as the'consensus')to guide nurses in standardizing the insertion and maintenance of mini-midline catheters.Methods Evidence was systematically retrieved,scientifically evaluated,and synthesized using evidence-based methods to draft the initial version of the consensus.From December 2023 to July 2024,totally 2 rounds of expert correspondence and 2 rounds of expert panel discussions were conducted to revise the content,resulting in the final version.Results There were 17 experts from tertiary A general hospitals in Beijing,Shanghai,Hunan,Hubei,Sichuan,Jiangsu,Hainan,Guangxi Zhuang Autonomous Region,and Shandong participating in the consultation,with a 100％response rate.In the 2 rounds of expert correspondence,the authority coefficients were 0.947 and 0.962,respectively.The mean importance scores of all items exceeded 4.00 points.The coefficients of variation(CV)were 0-0.32(first round)and 0-0.15(second round).Kendall's concordance coefficients were 0.097 and 0.101(both P＜0.001).The consensus covers 11 sections,including definition,indications,contraindications,qualification training,pre-insertion preparation,catheter insertion,catheter use,catheter maintenance,catheter removal,prevention and management of common complications,and health education.Conclusion The Consensus demonstrates scientific rigor and comprehensively addresses key procedures before,during,and after the insertion of mini-midline catheters,providing actionable guidance for nurses in catheter insertion and maintenance.