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.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To compare the periodontally accelerated osteogenic orthodontics(PAOO)effects of corticotomy with full mu-coperiosteal flap(flapped corticotomy)and corticotomy-only on accelerating orthodontic tooth movement.Methods A total of 60 healthy male SD rats(weighing 180-200 g)were selected and randomly divided into three groups.There were 20 rats each in the flapped corticotomy group,the corticotomy-only group,and the control group.After applying orthodontic instruments,5 rats each in the surgical group and the control group were killed by excessive anesthesia on 0,1,3,and 7 days after tooth movement.The tooth move-ment distances of the rats in the control group and the experimental group were counted,and immunohistochemical staining was per-formed to observe the corresponding molecular biological changes.Results There was no significant difference in accelerating ortho-dontic tooth movement between the flapped corticotomy group and the corticotomy-only group.Compared with traditional orthodontic tooth movement,both the flapped corticotomygroup and the corticotomy-only group could bring an increase in the expression of RANKL on the pressed periodontal side while there was no significant difference between the two experimental groups.Both the flapped corticot-omy and non-flapped corticotomy could enlarge the area of tissue formation in the periodontal tension zone,and still there was no signif-icant difference between the two surgical methods.Compared with traditional orthodontic tooth movement,both the flapped corticotomy group and the corticotomy-only group could lead to an increase in ALP,OCN and OPN expression on the periodontal tension zone.Conclusion Both flapped corticotomy and corticotomy play a significant role in accelerating orthodontic tooth movement and promoting alveolar bone formation in the early stage.Both surgical methods of PAOO can provide more efficient and stable biological support for orthodontic treatment.

Objective:To investigate disease characteristics of patients with psoriatic arthritis (PsA) based on the PsA cohort in West China Hospital, so as to provide a reference for clinicians in its diagnosis, treatment, and evaluation strategy formulation.Methods:A cross-sectional study was carried out, and a descriptive analysis was conducted on clinical data from PsA patients who were treated at the Department of Dermatology, West China Hospital, Sichuan University between April 2, 2020, and January 21, 2025. Demographic characteristics, clinical manifestations, laboratory and imaging findings, and treatment modalities were analyzed.Results:A total of 530 PsA patients were included, of whom 332 (62.6%) were males and 198 (37.4%) were females, with ages of 44.1 ± 12.4 years. Skin lesions preceded joint symptoms in 452 patients (85.3%), with time intervals ( M [ Q1, Q3]) of 8.0 (3.0, 15.0) years. Overweight or obesity was observed in 319 patients (60.2%), and 188 (35.5%) had comorbid fatty liver. Peripheral joint involvement was common (485 cases, 91.5%), with the proximal interphalangeal joints being most frequently affected by tenderness (172 cases, 35.5%) and swelling (119 cases, 24.5%) ; the number of enthesitis cases identified by ultrasonography (116 cases, 23.9%) was significantly higher than that by clinical examination (82 cases, 15.5%) ; axial joint involvement was observed in 258 patients (48.7%), with the sacroiliac joints most commonly affected (201 cases, 77.9%). Regarding treatment, conventional systemic drugs were predominant in the treatment of psoriasis prior to the diagnosis of PsA; after the diagnosis of PsA, the number of patients receiving targeted therapies increased to 334 (63.0%), with interleukin-17 inhibitors being the most common (140 cases, 26.4%), followed by tumor necrosis factor-α inhibitors (106 cases, 20.0%) and Janus kinase inhibitors (39 cases, 7.4%) . Conclusions:PsA predominantly affects males over 40 years old and is characterized by preceding skin lesions, delayed diagnosis, and multiple comorbidities. High-frequency ultrasound has advantages in the early detection of peripheral enthesitis. Further attention is needed for managing comorbidities such as fatty liver and obesity-related metabolic conditions.

Objective:To investigate disease characteristics of patients with psoriatic arthritis (PsA) based on the PsA cohort in West China Hospital, so as to provide a reference for clinicians in its diagnosis, treatment, and evaluation strategy formulation.Methods:A cross-sectional study was carried out, and a descriptive analysis was conducted on clinical data from PsA patients who were treated at the Department of Dermatology, West China Hospital, Sichuan University between April 2, 2020, and January 21, 2025. Demographic characteristics, clinical manifestations, laboratory and imaging findings, and treatment modalities were analyzed.Results:A total of 530 PsA patients were included, of whom 332 (62.6%) were males and 198 (37.4%) were females, with ages of 44.1 ± 12.4 years. Skin lesions preceded joint symptoms in 452 patients (85.3%), with time intervals ( M [ Q1, Q3]) of 8.0 (3.0, 15.0) years. Overweight or obesity was observed in 319 patients (60.2%), and 188 (35.5%) had comorbid fatty liver. Peripheral joint involvement was common (485 cases, 91.5%), with the proximal interphalangeal joints being most frequently affected by tenderness (172 cases, 35.5%) and swelling (119 cases, 24.5%) ; the number of enthesitis cases identified by ultrasonography (116 cases, 23.9%) was significantly higher than that by clinical examination (82 cases, 15.5%) ; axial joint involvement was observed in 258 patients (48.7%), with the sacroiliac joints most commonly affected (201 cases, 77.9%). Regarding treatment, conventional systemic drugs were predominant in the treatment of psoriasis prior to the diagnosis of PsA; after the diagnosis of PsA, the number of patients receiving targeted therapies increased to 334 (63.0%), with interleukin-17 inhibitors being the most common (140 cases, 26.4%), followed by tumor necrosis factor-α inhibitors (106 cases, 20.0%) and Janus kinase inhibitors (39 cases, 7.4%) . Conclusions:PsA predominantly affects males over 40 years old and is characterized by preceding skin lesions, delayed diagnosis, and multiple comorbidities. High-frequency ultrasound has advantages in the early detection of peripheral enthesitis. Further attention is needed for managing comorbidities such as fatty liver and obesity-related metabolic conditions.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.