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.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective:To construct a training program for nurses in shared-decision making of breast cancer surgery based on core competence, and to provide reference for clinical training.Methods:From February to May 2023, through literature review, qualitative interview, group discussion, Delphi and analytic hierarchy process, the training program were determined.Results:Among 18 experts, there were 3 males and 15 females, aged (44.67±9.24) years old. The final training program included 6 first-level indicators(admission criteria, training content (theory + practice), training format, training hours, training instructors, training evaluation), 17 second-level indicators, and 57 third-level indicators. The effective response rates of 2 rounds of expert consultations were both 18/18, and the expert authority coefficients were both 0.933. The Kendall coordination coefficients of the first and second round were 0.160, 0.213 (both P<0.05). Conclusions:The training program of decision aid nurses in breast cancer surgery is scientific, practical and clinically valuable, and can provide reference for the development of standardized training for nurses.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

BACKGROUND:In the process of intervening in the development of osteoarthritis,platelet-rich plasma plays an important role by intervening in autophagy,apoptotic cytokines and signal transduction pathways.OBJECTIVE:To summarize the structure of cytokines and signaling pathways involved in the diagnosis of osteoarthritis by platelet-rich plasma in recent years,as well as its correlation with chondrocyte apoptosis and autophagy,in order to provide effective targets for the future treatment of osteoarthritis.METHODS:Literature search was conducted in CNKI,WanFang Data,VIP,PubMed,Web of Science,and Medline databases using "platelet-rich plasma,chondrocyte,apoptosis,autophagy,osteoarthritis,cytokines,signaling pathway" as Chinese and English search terms.A systematic summary and induction were made for the 66 included articles.RESULTS AND CONCLUSION:Current research has shown that platelet-rich plasma can promote cartilage repair and assist bone tissue healing through various pathways,mainly divided into three aspects:(1) Platelet-rich plasma regulates the extension,closure,and maturation of microautophagosomes,promotes chondrocyte megaautophagy and molecular chaperone-mediated cell autophagy under specific conditions,enhances the expression of autophagy-related factors such as LC3Ⅱ/Ⅰ and Beclin1,inhibits the expression of P62/SQSTM1.Currently,there is no clear research directly exploring the specific effect of platelet-rich plasma on heat shock proteins,and further research is needed in this field in the future.(2) The various growth factors released by platelet-rich plasma inhibit the expression of pro-apoptotic factors Caspase,interleukin-1β,and tumor necrosis factor alpha,promote the expression of anti-apoptotic factor Bcl-2,and prevent chondrocyte apoptosis and degeneration.(3) By activating the PI3K/AKT/mTOR signaling pathway,NF-κB signal transduction pathway,death receptor pathway,mitochondrial stress pathway and other pathways,platelet-rich plasma inhibits the expression of Bax and Caspase,and prevents the release of cytochrome c,thereby inhibiting the death and necrotic apoptosis of chondrocytes.In general,platelet-rich plasma promotes cartilage repair,supports cartilage regeneration,and plays an anti-inflammatory role,and its biological effect in chondrocytes usually depends on the regulation of autophagy and apoptosis-related cytokines and signaling pathways.

Objective This study investigated feasible cases and their significance in promoting the"generalized"development of inspection through digital-intelligent equipment.Methods A qualitative research approach was used,involving interviews conducted between February 2025 and March 2025 with experts in traditional Chinese medicine diagnostics,clinical research methodology,medical engineering integration,and related disciplines,using both online and offline methods.In accordance with the Consolidated Criteria for Reporting Qualitative Research,feasible cases involving the specific application of digital equipment in various parts of observation were collected through item enrichment.The significance of extending observation capabilities via these cases was analyzed,along with the overall implications of integrating digital technologies with traditional inspection method.Results Interviews were completed with 11 experts from domestic universities and research institutes in the fields of traditional Chinese medicine diagnosis,medical engineering integration,and related disciplines.A total of 78 feasible cases of digital-intelligent inspection were identified,along with 69 insights regarding the significance of enhancing the inspection capabilities.These insights were synthesized into two dimensions and 23 holistic meanings.The first dimension is to expand the scope of inspection,including obtaining internal environmental characteristics,observing external environmental characteristics,expanding thermodynamic characteristic data,and crossing time and space.The second dimension is to improve the quality of observation and diagnosis information collection and analysis,including 19 specific meanings,such as standardized collection environment,objective quantification,and refined observation.Conclusion Digital-intelligent equipment plays a significant role in expanding the scope of inspection content and achieving high-quality acquisition and analysis of extensive inspection information.These advancements extend and enrich the capabilities of traditional inspection method in traditional Chinese medicine.

Objective To explore the role and mechanism of RNA m6A methyltransferase Wilms'tumor 1-associated protein(WTAP)in epithelial-mesenchymal transition(EMT)of glioblastoma cells and its association with transcription factor JUNB.Methods(1)Based on the Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)databases,the expression levels of transforming growth factor β(TGF-β),WTAP,and JUNB in glioblastoma multiforme(GBM)and normal brain tissues were analyzed,as well as their diagnostic and prognostic values for GBM.The correlation of TGF-β,WTAP,and JUNB with gliomas of different WHO grades was analyzed using the Chinese Glioma Genome Atlas(CGGA)database.Spearman correlation analysis was performed to assess the correlation between TGF-β and m6A methyltransferases.(2)An EMT model was established in human astrocytoma U87-MG cells through TGF-β1 induction.qRT-PCR and Western blotting were employed to detect the expression levels of WTAP,JUNB,matrix metalloproteinase 2(MMP2),and N-cadherin.The migration capacity of U87-MG cells was evaluated by wound-healing and Transwell assays.An m6A RNA methylation quantification kit(colorimetric)was used to detect RNA m6A methylation modification levels.A stable cell line with low expression of WTAP was constructed to investigate the effects of WTAP knockdown on the migration ability of U87-MG cells,as well as the expression of JUNB.(3)A protein-protein interaction network was constructed using STRING database and GeneMANIA database,followed by gene ontology(GO)and KEGG pathway enrichment analyses to explore the biological processes,molecular functions,cellular components,and signaling pathways potentially involved in TGF-β/WTAP/JUNB.Gene set enrichment analysis(GSEA)was performed on JUNB-related genes to investigate their potential downstream signaling pathways.Results(1)The expression levels of TGF-β,WTAP,and JUNB were significantly higher in GBM(P<0.001),positively correlated with WHO grades of glioma(P<0.001).Glioma patients with high expression of all three genes had shorter overall and disease-free survival(P<0.001).Spearman analysis showed that the expression of TGF-β in GBM was positively correlated with WTAP(r=0.175,P=0.023),but no significant correlation with other m6A methyltransferases(P>0.05).(2)After TGF-β1 treatment,the level of m6A methylation modification of total RNA in U87-MG cells significantly increased(P<0.001).Wound-healing assay and Transwell assay results showed that the migration ability of U87-MG cells was significantly increased after TGF-β1 treatment(P<0.01),while WTAP knockdown significantly reduced the migration ability of U87-MG cells(P<0.01).qRT-PCR and Western blotting results showed that the mRNA and protein expression levels of WTAP,N-Cadherin,MMP2,and JUNB in U87-MG cells were significantly increased after 48 h of TGF-β1 induction(P<0.001),while WTAP knockdown significantly reduced the mRNA and protein expression of JUNB(P<0.001).(3)The TGF-β/WTAP/JUNB-related protein-protein interaction network was constructed,which was primary involved in mRNA modification and EMT.GSEA results showed that JUNB-related signaling pathways were closely associated with glioma malignant progression.Conclusions TGF-β,WTAP,and JUNB are all associated with GBM malignant progression and poor patient prognosis.TGF-β may enhance total RNA m6A modification by promoting the expression of m6A methyltransferase WTAP,and WTAP subsquentaly upregulates transcription factor JUNB,thereby promoting EMT and malignant progression of GBM.

Objective To investigate and compare the epidemiological characteristics of common respiratory viruses among influenza-like illness(ILI)and severe acute respiratory infection(SARI)cases in Huzhou,Zhejiang Province before and after the COVID-19 pandemic,so as to provide a basis for formulating and adjusting the prevention and control strategies for viral respiratory infectious diseases.Methods ILI and SARI cases at two influenza surveillance sentinel hospitals in Huzhou and had throat swab samples collected during Nov 2017 to Feb 2020(pre-COVID-19 pandemic period)and Dec 2022 to Apr 2024(post-COVID-19 mitigation phase)were selected as the participants.Seven common viral respiratory pathogens were tested,including influenza A virus(H1N1 and H3N2 subtypes),influenza B virus(Victoria lineage,FluB),respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),and severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The positive rates of respiratory pathogens before and after the COVID-19 pandemic were compared across different age groups and different time.Results A total of 7 948 ILI samples and 2 294 SARI samples were included.The overall positive rate of ILI samples increased from 33.6%to 47.1%,primarily due to the increase in influenza and COVID-19 infections;the overall positive rate of SARI samples decreased from 31.4%to 24.8%,mainly due to the reduction in HRV and ADV infections.During the post-COVID-19 mitigation phase,SARS-CoV-2(22.1%),H3N2(12.7%),and FluB(6.0%)were the primary pathogens in ILI samples,while RSV(7.1%),H3N2(5.3%),and HRV(4.5%)dominated in SARI samples.During the post-COVID-19 mitigation phase,the influenza virus circulation period was shortened.Before the COVID-19 pandemic,RSV was mainly detected in autumn and winter,while during the post-COVID-19 mitigation phase,out-of-season RSV epidemics were observed in spring and summer.Co-infection rate in ILI cases increased significantly in the post-COVID-19 mitigation phase,predominantly consisting of co-infections of COVID-19 and influenza A virus,while co-infection rate in SARI cases showed a decline.Conclusion We found important epidemiological changes in respiratory viruses in Huzhou during the post-COVID-19 mitigation phase compared to pre-COVID-19 period,including increased positive rates of influenza and COVID-19,and disruptions to the seasonal patterns of influenza and RSV.The prevention and control strategies should be adjusted in a timely manner based on the monitoring data.