Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

This study reports a new species of Culicoides(Avaritia)isolated from Xunke County, Heilongjiang Province, China. The new species, Culicoides(Avaritia)dongshanensis Liu et Wang, sp. nov., was identified and illustrated based on female adults. Its diagnostic characteristics are as follows: eyes contiguous over a short distance, with short interfacetal hair, antennal ratio(AR)of 1.20, palpal ratio(PR)of 2.16, wing length of 0.83 mm, mandible with 15 teeth, one pale spot in base cell M1, one pale spot in cell M4, two pale spots in cell A, and two unequal spermathecae. Type specimens were deposited at the Center for Disease Control and Prevention of the Northern Theater Command.

Objective To construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

With the rapid advancement and iterative development of new artificial intelligence technologies, there remains a regulatory vacuum in corresponding governance measures among governments worldwide. Simultaneously, a technological and governance gap exists between developing countries and developed economies. In response, the World Health Organization (WHO) has released "Ethics and Governance of Artificial Intelligence for Health: Guidance on Large Multi-Modal Models" to assist governments in strengthening governance capabilities in this field. This paper provides an in-depth analysis of the Guidance, aiming to identify challenges and risks associated with the application of multimodal large models in healthcare. Guided by ethical principles for advancing health through artificial intelligence, the paper examines the three-tier governance framework and recommendations outlined in the Guidance. Additionally, it evaluates the current state of AI governance in China, offering insights and reference points for improving AI governance in China′s healthcare sector.

The construction of a medical safety system based on the medical core quality and safty systems is the foundation of the hospital. Multi-campus operation coordinated development is key to the high-quality development of public hospitals and the balanced distribution of high-quality medical resources. Building a medical safety system that comfoms to the specialized layout and operation of branch districts is very important the construction of multi-campus hospitals. In January 2023, Xidan Campus of Peking Union Medical College Hospital established a medical safety system that was compatible with its development, based on the construction of the medical core quality and safty system. The system covered four dimensions: early identification, early assessment, early intervention, and fast response. It included high-risk surgical evaluation and filing, early warning of nursing rooms, periodic medical safety rounds, and rapid response teams and cross hospital transportation of critical care rapid response teams. As of June 2024, the hospital had recorded 570 high-risk surgeries with no unplanned secondary surgeries or unplanned readmissions; Reported nursing warnings 68 times, initiated 93 emergency treatments and cross hospital transfers. All emergency patients received early warning assessments and completed graded and classified transfers and management, effectively ensuring patient safety. This practice could provide references for other multi-campus hospitals to promote the construction and development of medical safety systems.

Objective To explore the application value of intravoxel incoherent motion(IVIM)imaging parameters in the differential diagnosis of benign and malignant breast nodules and their correlation with the expression of Ki-67 receptor in breast cancer.Methods The data of 41 female patients who completed 3.0 T breast magnetic resonance imaging(MRI)with complete surgical pathology results in the Second Hospital of Jiaxing City from October 2022 to January 2025 were analysed and evaluated.Conventional images and diffusion-weighted images with 11 b values were collected.The IVIM imaging parameters of real diffusion coefficient(D),perfusion related diffusion coefficient(D*)and perfusion fraction(f)were measured and calculated in the region of interest of each lesion.The receiver operating characteristic curve were plotted to quantify the differential diagnostic efficacy of each parameter of IVIM imaging in benign and malignant breast nodules.The differences of parameters between benign and malignant breast nodules and between the groups with different expression levels of Ki-67 receptor in breast cancer were analysed,and the correlation between each parameter and the expression level of Ki-67 in breast cancer was counted.Results The D value of benign breast nodules group(benign groups)was significantly higher than that of malignant breast nodules group(malignant groups),and the D*value was significantly lower than that of malignant group,and the differences between benign group and malignant group were statistically significant(t=-4.773,t=2.063,P＜0.05);Thefvalue of benign group was slightly lower than that of malignant group,and the differences between two groups were not statistically significant(t=0.035,P＞0.05).Among the parameters of IVIM imaging,D value had the best differential diagnostic efficacy for benign and malignant breast nodules,with area under the curve(AUC)of 0.870(95％CI:0.755-0.985)and a specificity of 75.0％;D*value had the second best differential diagnostic efficacy after D value,with an AUC of 0.789(95％CI:0.658-0.920),but it had the highest sensitivity of 88.2％;And the differential diagnosis efficiency off value was the worst,much less than D and D*values.The D value in the high Ki-67 expression group of breast cancer was lower than that in the low expression group,while the D* and f values in the high expression group were higher than that in the low expression group,and the differences of each imaging parameter of IVIM were not statistically significant between two groups(t=-2.617,t=2.169,t=0.647,P＞0.05).There was a significant negative correlation between the expression of the Ki-67 receptor and the D value(r=-0.615,P＜0.05),and no significant correlation was seen with either D *or f value(r=0.223,r-0.031,P＞0.05).Conclusion The D and D*values of IVIM imaging parameters have great clinical value in the differential diagnosis of benign and malignant breast nodules.

Depression is a heterogeneous mental disorder in which the interaction between genetic susceptibility and environ-mental factors plays a key role in its pathogenesis.Although the specific mechanisms of the disease still need to be thoroughly studied and elucidated,there is now a broad consensus that epi-genetic markers have a central influence on its mechanism of ac-tion.DNA methylation of brain-derived neurotrophic factor(BD-NF)is not only regarded as a promising epigenetic biomarker of pathology,but may also help predict the efficacy of antidepres-sants.In this paper we reviewed the gene structure of BDNF and its DNA methylation regulation mechanism,and also analyzed the changes of DNA methylation of this factor in depression pa-tients and animal models,aiming to provide new ideas and theo-retical support for clinical research.

The wide application of assisted reproductive technology (ART) has brought the hope of fertility to infertile couples worldwide. However, with the gradual popularization of ART, the long-term health status of ART children has attracted extensive attention from society. Adolescence is a critical developmental period for individuals to transition from childhood to adulthood, with significant physical and psychological changes, so the health status of ART offspring during this period has a profound impact on their overall future health. This article reviews the existing studies, focusing on the effects of ART on multiple aspects of adolescent health, especially growth and development, cardiovascular health, endocrine function, fertility, cancer risk, atopic diseases, mental health, epigenetic changes and other aspects. The possible mechanisms leading to these health problems, including genetic factors, environmental exposures, and the long-term effects of early life interventions, were explored. Future research should continue to explore the long-term effects of ART on the health of offspring and further clarify the mechanisms of these effects, so as to provide a scientific basis for the development of effective prevention and intervention measures.