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 To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Objective To target at the NKG2A-HLA-E inhibitory axis,a pluripotent stem cell(iPSC)-derived geneti-cally engineered natural killer cells(NK cells)with NKG2A knockout(NKG2A KO-iNK)were prepared and then their tumor-killing efficacy was evaluated in vitro.Methods NKG2A was knocked out in iPSCs using gene-editing technology.These cells were then differentiated into NKG2A KO-iNK cells.Surface markers at each differentiation stage were analyzed by flow cytometry.Western blot confirmed NKG2A knockout,and flow cytometry assessed expres-sion of activating receptors(NKG2D)and natural cytotoxicity receptors(NKp30,NKp44,NKp46)in NKG2A KO-iNK cells.Cytotoxic activity against tumor cell lines with varying human leukocyte antigen E(HLA-E)expression level was evaluated via lactate dehydrogenase(LDH)release assay.Results Co-transfection of iPSCs with Cas9 pro-tein and three small-guide RNAs(sgRNAs)targeting at exons 1 and 2 of the KLRC1 gene(encoding NKG2A)suc-cessfully generated monoclonal NKG2A-knockout iPSCs(NKG2A KO-iPSCs)with a single T-base insertion in exon 1.During iPSC differentiation into NK cells,CD34 expression reached 30％-50％at the embryoid body(EB)stage(day 8),while CD56 and CD 16 expression exceeded 80％by day 28.Western blot confirmed complete NKG2A knockout in NKG2A KO-iNK cells.Flow cytometry revealed comparable expression level of activating receptor NKG2D and cytotox-icity receptors(NKp30,NKp44,NKp46)between NKG2A KO-iNK and wild-type iNK(WT-iNK)cells.The LDH assay results indicated that the cytotoxic activity of NKG2A KO-iNK cells against the HLA-E highly-expressed B-cell precursor leukemia cell line Nalm6 cells was significantly higher than that of WT-iNK cells,while there was no signif-icant difference between them and human myeloma cell line H929 cells with low HLA-E expression and human hepa-tocellular carcinoma cell line HepG2 cells with almost no HLA-E expression.Interferon-γ(IFN-γ)pretreatment up regulated HLA-E expression in Nalm6 cells,further amplifying NKG2A KO-iNK-mediated cytotoxicity.Conclusions By disrupting the NKG2A-HLA-E inhibitory axis,NKG2A KO-iNK cells exhibit markedly enhanced in vitro cytotoxic-ity against HLA-E-high tumor cells.This result highlights their potential function as a novel adoptive cell therapy strategy for cancers reliant on HLA-E-mediated immune evasion.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

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 investigate the long-term outcome of deep brain stimulation (DBS) in patients with KMT2B gene-related dystonia. Methods:Seven patients with KMT2B gene-related dystonia who were treated at Peking Union Medical College Hospital from April 2018 to December 2020 were enrolled. Whole-exome sequencing was used to detect genetic variations, and clinical phenotypes were summarized. All patients underwent DBS surgery and were followed up at 6 months, 3 years, and 5 years post-surgery. The therapeutic effects of DBS were evaluated by Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS), including BFMDRS Motor Subscale (BFMDRS-M) and Disability Subscale (BFMDRS-D). Results:The preoperative BFMDRS-M and BFMDRS-D scores were 60.43±27.12 and 17.00±6.24, respectively. The most significant improvements were observed at 6 months post-surgery, with the BFMDRS-M and BFMDRS-D scores being 20.64±5.50 and 9.57±1.72, reflecting improvements of 65.8% and 43.7%, respectively, both with statistically significant differences ( t=4.342, P=0.005; t=2.828, P=0.030). At 3 years post-surgery, the BFMDRS-M and BFMDRS-D scores were 26.20±8.68 and 10.50±2.74, representing improvements of 56.7% ( t=3.045, P=0.029) and 38.2% ( t=2.012, P=0.100), respectively. At 5 years post-surgery, the BFMDRS-M and BFMDRS-D scores were 27.80±14.87 and 11.00±2.83, with improvements of 54.0% ( t=1.824, P=0.142) and 35.3% ( t=1.933, P=0.125), respectively. At the 5-year postoperative follow-up, the patients′ cervical dystonia improved by 78.9%, while the upper limbs, lower limbs, and trunk dystonia improved by 57.8%, 56.6%, and 58.0%, respectively. However, only 1 patient showed significant improvement in the language function. Conclusions:DBS showed good therapeutic effects on KMT2B gene-related dystonia, but the efficacy declined over time. Significant improvements were observed in patients′ cervical, limb and trunk dystonia, but the improvement in language function was not significant.

Objective:To investigate the clinical characteristics of patients with multiple myeloma(MM)complicated by bone lesions and the risk factors associated with bone lesions.Methods:The clinical data of 294 newly diagnosed MM patients in Gansu Provincial Hospital from January 2017 to June 2021 were retrospectively analyzed.The patients were divided into the bone lesion group(154 cases)and the non-bone lesions group(140 cases)based on the presence of absence of bone lesions at diagnosis.The general data and laboratory parameters were compared between the two groups.The risk factors for bone lesions in MM patients were analyzed by logistic regression analysis,and the characteristic(ROC)curves were plotted to assess the predictive value of each risk factor for the occurrence of bone lesions in MM patients.Results:Compared to the non-bone lesion group,the bone lesion group had significantly higher serum calcium levels and significantly greater proportions of patients with Durie-Salmon(DS)stage Ⅲ,and bone pain(all P＜0.05).Logistic regression analysis showed that elevated serum calcium(OR=5.135,95％CI:1.931-13.653,P=0.001),DS stage Ⅲ(OR=1.841,95％CI:1.019-3.328,P=0.043),and bone pain(OR=8.208,95％CI:4.761-14.151,P＜0.001)were independent risk factors for bone lesions in MM patients.ROC curve analysis showed that serum calcium(AUC=0.619,95％CI:0.555-0.683,P＜0.001)and bone pain(AUC=0.743,95％CI:0.692-0.793,P＜0.001)had predictive value for bone lesions in MM patients.Conclusion:MM patients have a high incidence of bone lesions,and active monitoring and management of risk factors may improve treatment outcomes and prognosis.