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.

Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

ObjectiveTo investigate the association between insulin resistance （IR） and cardiovascular metabolic indicators， including blood pressure， blood lipids， and serum uric acid， in a middle-aged population. MethodsBased on the baseline survey of the Hong Sifang cohort of China National Salt Industry Group， a total of 575 participants were included. According to the homeostasis model assessment of insulin resistance， the participants were divided into an IR group （n=116） and a non-IR group （n=459）. Differences between the two groups were compared using the t-test and chi-square test. Multivariate logistic regression analysis was performed to evaluate the associations between IR and abnormalities in metabolic indicators. ResultsA total of 575 participants were included， including 390 men and 185 women， with a mean age of （48.58 ± 5.14） years and a mean body mass index （BMI） of （24.16 ± 2.97） kg/m². Blood pressure， serum uric acid， and blood lipid levels were significantly higher in the IR group than in the non-IR group （P<0.001）. After adjusting for potential confounders including age， sex， and BMI， IR was independently associated with hypertension， dyslipidemia， and hyperuricemia， with odds ratios （OR） and 95% confidence intervals （CI） of 2.57 （1.61-4.09）， 3.81 （2.36-6.17）， and 2.68 （1.53-4.71）， respectively （all P<0.001）. ConclusionInsulin resistance is significantly associated with multiple cardiovascular metabolic risk factors in the middle-aged population. Monitoring IR may contribute to the early prevention and control of cardiovascular diseases.

Bariatric and metabolic surgery currently grapples with multifaceted challenges due to the global surge in obesity. The application of artificial intelligence (AI) technologies presents transformative potential to address these complex dilemmas. The authors review the application of AI in the perioperative period of bariatric and metabolic surgery, indicate the promising prospects of the integration of AI and bariatric and metabolic surgery. Meanwhile, in the process of its extensive application, pertinent ethical concerns should be duly considered. At present, the in-depth application ability of AI by doctors remains relatively low. In the future, the combination of AI with internet of things, robotic surgery, surgical education, and genomics will become the core direction of bariatric and metabolic surgery development.

The biological characteristics of hepatocellular carcinoma(HCC)lead to a high incidence of portal vein tumor thrombus.It progresses rapidly,and the opportunity for radical surgical resection can be lost in a short term,resulting in poor prognosis.Reasonable down-staging treatment is a research focus for patients with unresectable HCC complicated with portal vein tumor thrombus to achieve a resectable range.This article reviews the potential population of HCC complicated with portal vein tumor thrombus with conversion therapy for HCC,analyzes the application of hepatic artery infusion chemotherapy,transcatheter arterial chemoembolization,radiotherapy,regional and systemic drug therapy in conversion therapy,and points out that the combination of multidisciplinary comprehensive treatments is the key to improve the prognosis of HCC patients with portal vein tumor thrombus.

Objective:To establish a rapid method for urinary iodine determination based on arsenic-cerium catalytic spectrophotometry using semiconductor water bath rapid cooling digestion technology (rapid cooling method) and an automated iodine analyzer.Methods:Urine samples were collected from three staff members randomly selected at the Gansu Provincial Center for Disease Control and Prevention. The samples were mixed and divided into three equal portions. Using rapid cooling method instead of traditional natural cooling method, the mixed urine sample was lowered from 100 ℃ to the measurement temperature (30 ℃), and then the urine iodine was determined by arsenic cerium catalytic spectrophotometry using a fully automatic iodine analyzer. The differences between the two cooling methods were compared. Additionally, the rapid cooling-arsenic-cerium catalytic spectrophotometry method was validated in terms of the linear equation of the standard curve, precision, accuracy (using urinary iodine reference materials GBW09110e and GBW09109m, and spike recovery experiments), and detection limit.Results:Using the rapid cooling method, the temperature of urine samples reached 30 ℃ in 40 minutes, while the natural cooling method required 120 minutes to reach the same temperature. Urinary iodine levels determined by the rapid cooling method in the three samples were (158.3 ± 1.9), (133.7 ± 2.7), and (219.2 ± 3.1) μg/L, respectively, while those determined by the natural cooling method were (155.5 ± 2.7), (136.2 ± 2.3), and (215.1 ± 3.9) μg/L, respectively. There was no statistically significant difference between the results of the two methods ( t = 1.43, P = 0.192). In the validation experiments for the rapid cooling method, the linear equations for the low-concentration (0 - 300 μg/L) and high-concentration (300 - 1 200 μg/L) iodine standard series were y = - 0.003 0 x + 0.117 5 ( r = - 0.999 7) and y = - 0.001 5 x + 0.649 3 ( r = - 0.999 8), respectively. The precision experiments showed that the relative deviation values of the repeated tests for two different iodine concentrations (300 and 600 μg/L) were 1.99% and 1.90%, respectively. The accuracy experiments demonstrated that the repeated test results for the national urinary iodine reference materials (GBW09110e and GBW09109m) were 216.8 and 134.7 μg/L, respectively, with relative standard deviations of 1.04% and 1.35%, respectively, all within the reference ranges[(218 ± 15) and (135 ± 10) μg/L]. The detection limit was 1.20 μg/L. The spike recovery rate ranged from 92.90% to 99.10%, with an average recovery rate of 96.77%. Conclusions:The rapid cooling-arsenic-cerium catalytic spectrophotometry method not only shortens the time required for urinary iodine determination and improves the speed of measurement, but also provides accurate results, which can be applied when a large number of urine samples need to be measured in a short period of time.

To evaluate the clinical application value of magnetic bead sorting technology (MBS) using the T-cell select kit combined with an automatic cell sorter for isolating peripheral blood mononuclear cells (PBMCs) to realize automated specimen pre-processing and process optimization in T-SPOT.TB assay. A cross-sectional study was conducted involving 300 patients recruited from the first affiliated hospital of Air Force Medical University from March 2023 to July 2024. Among them, there were 167 males and 133 females. The age range of the patients was 18 to 65 years, with a median age of 49.0 (33.3, 59.0) years and a mean age of (46.4±13.9) years. 4 ml of anticoagulated whole blood samples in duplicate were collected from each patient. One fresh sample (0-4 h) was processed immediately using density gradient centrifugation (DGC) for PBMC isolation, while the other was processed using MBS method at either 0-4 h or 34-54 h post-collection. The cycles for cell enrichment step of the automatic cell sorter were adjusted from the conventional 4 cycles to 2 cycles. Statistical analysis was performed using Cohen′s Kappa test to evaluate the concordance of T-SPOT.TB results across all processing groups. The results showed that for fresh samples (0-4 h), the T-SPOT.TB results for samples processed with 4-cycle and 2-cycle MBS enrichment steps demonstrated positive concordance rates of 91.7% and 93.1%, negative concordance rates of 100% for both, overall concordance rates of 98.0% and 97.9%, and Kappa values of 0.94 and 0.95, respectively, compared with the reference results for paired samples processed using DGC. Correspondingly, the results for samples processed with the 4-cycle and 2-cycle MBS methods at 34-54 h post-collection yielded positive concordance rates of 90.0% and 81.3%, negative concordance rates of 95.1% and 100%, overall concordance rates of 93.0% and 82.9%, and Kappa values of 0.86 and 0.43, respectively, compared with the reference results for fresh samples processed using DGC. In conclusion,for 0-4 h samples, the T-SPOT.TB results from both 4-cycle and 2-cycle MBS enrichment protocols were highly consistent with the reference results from conventional DGC methods. However, for 34-54 h stored samples, results from the 4-cycle MBS method rather than the 2-cycle protocol exhibited significantly superior concordance with the reference results. The MBS method using T-Cell Select kit achieves automated sample pre-processing for T-SPOT.TB assay, reduces hands-on time, and provides a viable alternative with reliable results for long-stored specimens.

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 empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective:To study the effects of epidermal growth factor(EGF)on the coordinated motor behaviors and changes of nigrostriatal dopaminergic system under the impact of EGF in middle-aged rats.Methods:Healthy aged Sprague Dawley(SD)rats were subcutaneously administered EGF(0.1 mg/ml)in the dorsal region for 7 days.Adhe-sive removal test,tapered beam walking test and descending a wire mesh pole test were performed to detect the changes in the coordinated motor behaviors of rats as well as changes in the expression of tyrosine hydroxylase(TH)and dopa-mine transporter(DAT)of nigrostriatal dopaminergic system in rats.Results:Middle-aged rats showed reduced behav-ioral parameters of adhesive removal test,tapered beam walking test and descending a wire mesh pole test compared with those of adult rats(P<0.05),which were improved after treatment with EGF(P<0.05).The expression of TH and DAT in nigrostriatal dopaminergic system was down-regulated in middle-aged rats compared with that in adult rats(P<0.01),however,which were up-regulated after treatment with EGF(P<0.01).Conclusion:EGF can amelio-rate the decline in coordinated motor behaviors and increases the activity of nigrostriatal dopaminergic system in middle-aged rats.