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 assess the prognostic impact of the thoracic aorta and aortic valve calcification volume (TAC, AVC) score based on CT measurementsin patients undergoing transcatheter aortic valve implantation (TAVI).Methods:We retrospectively analyzed 102 patients who underwent TAVI for severe aortic stenosis from March 2018 to April 2022 at Fuwai Central China Cardiovascular Hospital. The patients were stratified into low TAC and AVC group (TAC low, AVC low) and high TAC and AVC group (TAC high, AVC high) based on median TAC and AVC. The independent risk factors affecting the prognosis of TAVI patients were analyzed using univariate and multivariate Cox proportional risk regression, and the independent risk factors affecting the prognosis of TAVI were analyzed by survival curve. Results:A total of 102 patients were included with a median follow-up of 695 (602, 923) days, during which 9 (8.8%) all-cause deaths and 33 (32.4%) composite end-point events occurred. Univariate Cox risk regression analysis found that TAC was a risk factor for all-cause mortality events in TAVI patients ( P=0.039), TAC and AVC were risk factors for composite endpoint events in TAVI patients ( P=0.047, 0.035).TAC was an independent predictor of all-cause mortality after TAVI in multivariate analysis ( HR=8.971, 95% CI 1.121-71.790, P=0.039), and TAC and AVC were independent risk factors for composite endpoint events after TAVI ( HR=2.243, 95% CI 1.099-4.578, P=0.026; HR=2.346, 95% CI 1.146-4.804, P=0.020). Kaplan-Meier survival curves showed that high TAC and AVC scores increased the risk of end-point events ( P<0.05). Conclusion:CT-quantified TAC and AVC volume scores are independent prognostic markers in TAVI patients, with greater calcification burden portending poorer clinical outcomes.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

In order to solve the problems of difficult test, high cost and long cycle in the development of large-scale airborne negative pressure isolation system, the simulation analysis of negative pressure response characteristics is carried out around various aviation conditions such as aircraft ascending, leveling and descending, especially rapid decompression, based on the computational fluid dynamics (CFD) method. The results showed that the isolation cabin could achieve -50 Pa pressure difference environment and form a certain pressure gradient. The exhaust air volume reached the maximum value in the early stage of the aircraft's ascent, and gradually decreased with the increase of altitude until it was level flying. In the process of aircraft descent, the exhaust fan could theoretically maintain a pressure difference far below -50 Pa without working; Under the special condition of rapid pressure loss, it was difficult to deal with the rapid change of low pressure only by the exhaust fan, so it was necessary to design safety valve and other anti-leakage measures in the isolation cabin structure. Therefore, the initial stage of aircraft ascent is the key stage for the adjustment and control of the negative pressure isolation system. By controlling the exhaust air volume and adjusting parameters, it can adapt to the change of low pressure under normal flight conditions, form a relatively stable negative pressure environment, and meet the needs of biological control, isolation and transport.
Aircraft ; Computer Simulation ; Aviation/instrumentation* ; Humans ; Hydrodynamics ; Air Pressure ; Equipment Design ; Pressure

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Idiopathic pulmonary fibrosis (IPF) is a progressive disease lacking effective therapy. Metformin, an antidiabetic medication, has shown promising therapeutic properties in preclinical fibrosis models; however, its precise cellular targets and associated mechanisms in fibrosis resolution remain incompletely defined. Most research on metformin's effects has focused on mesenchymal and inflammatory responses with limited attention to epithelial cells. In this study, we utilized Sftpc lineage-traced and Fgfr2b conditional knockout mice, along with BMP2/PPARγ and AMPK inhibitors, to explore metformin's impact on alveolar epithelial cells in a bleomycin-induced pulmonary fibrosis model and cell culture. We found that metformin increased the proliferation and differentiation of alveolar type 2 (AT2) cells, particularly the recently identified injury-activated alveolar progenitors (IAAPs)-a subpopulation characterized by low SFTPC expression but enriched for PD-L1. Single-cell RNA sequencing revealed a reduction in apoptosis among mature AT2 cells. Interestingly, metformin's therapeutic effects were not significantly affected by BMP2 or PPARγ inhibition, which blocked the lipogenic differentiation of myofibroblasts. However, Fgfr2b deletion in Sftpc lineage cells significantly impaired metformin's ability to promote fibrosis resolution, a process linked to AMPK signaling. In conclusion, metformin alleviates fibrosis by directly activating AT2 cells, especially the IAAPs, through a mechanism that involves AMPK and FGFR2b signaling, but is largely independent of BMP2/PPARγ pathways.

Objective To enhance the mechanical properties of trichiral honeycomb sandwich structures and satisfy the design criteria for vertebral implant structures.Methods A chiral-like honeycomb sandwich structure with an auxiliary support structure was constructed for optimal design.The finite element method was used to study the influence of the auxiliary support structure on the chiral-like honeycomb sandwich structure and the relationship between the support position and mechanical property parameters.Furthermore,the influence of the deformation mechanism of different structures on mechanical properties was discussed.Results All chiral-like honeycomb sandwich structures exhibited enhanced mechanical properties in comparison to trichiral honeycomb sandwich structures.The mechanical properties of the chiral-like dCW honeycomb sandwich structure with the auxiliary support structure positioned perpendicular to the ligament were optimal,and this position represented the optimal support position.When the volume was used as a control variable,the compressive stiffness,stiffness-to-mass ratio,and transverse strain of the chiral-like honeycomb sandwich structure in the x1 direction were significantly correlated with the change of the support position,and all of them were positively correlated.Conclusions As a novel chiral-like honeycomb structure,it provides a biomechanical basis for the optimal design and clinical application of honeycomb sandwich structures as vertebral implant structures.

Objective:To examine the safety and effectiveness of a novel domestic transcatheter aortic valve system in addressing severe aortic valve stenosis.Methods:This prospective, multicenter, single-arm target-value clinical trial enrolled patients with severe aortic stenosis meeting inclusion criteria from 13 Chinese centers between July 2021 and April 2022. The primary endpoint was all-cause mortality at 1-year post-procedure. Secondary endpoints included safety outcomes (30-day all-cause mortality, 1-year major adverse cardiovascular events, device success) and efficacy parameters (transvalvular pressure gradient, paravalvular leak severity, New York Heart Association(NYHA)class improvement, and quality of life). Survival analysis was performed using the Kaplan-Meier analysis.Results:The study included 134 patients, 85 males and 49 females, with an age of (73.6±5.6)years (range: 65.1 to 91.8 years). Bicuspid aortic valve morphology was present in 59.7% (80/134). Device success rate was 99.3%, with one case converted to open surgery due to coronary obstruction. All-cause mortality was 0.8% (95% CI: 0.1% to 5.3%) at both 30-day and 1-year follow-up, significantly lower than the 25% target value ( P<0.01). Permanent pacemaker implantation rates remained 2.2% (3/134) at both timepoints. Stroke incidence was 0.7% (1/134) at 30 days and 1.5% (2/134) at 1 year. Myocardial infarction rates were 0.7% (1/134) at both intervals. The postoperative transvalvular pressure gradient of the aortic valve was (6.6±3.1) mmHg(1 mmHg=0.133 kPa) (range: 4 to 8 mmHg). Among the patients, 32 cases (23.9%) had mild paravalvular leakage, 4 cases (3.0%) had moderate paravalvular leakage, and no severe paravalvular leakage was observed. NYHA class Ⅰ and Ⅱ patients increased from 18.7% preoperatively to 99.3% postoperatively. Conclusion:The novel domestic transcatheter aortic valve system demonstrates satisfactory 1-year safety and efficacy outcomes in treating severe aortic stenosis.

Objective:To investigate the current status of nutritional support specialist nurses' knowledge, attitude and practice about nutrition nursing practice and analyze their influencing factors, so as to provide reference for optimizing and improving the level of nutritional support specialist nurses' knowledge, attitude and practice, and constructing a training program for nutritional support specialist nurses.Methods:From October to November 2023, 557 nutritional support specialist nurses in 28 provinces, autonomous regions, and municipalities directly under the central government of China were selected for the survey using the convenience sampling method. General information questionnaire and Nutrition Nursing Practice Knowledge, Attitude and Practice Questionnaire were used to conduct the survey. Multiple linear regression was used to explore the influencing factors of knowledge, attitude and practice.Results:A total of 557 questionnaires were distributed and 507 questionnaires were effectively recovered, with an effective recovery rate of 91.0%. The nutrition nursing practice knowledge dimension scores, attitude dimension scores, and practice dimension scores of 507 nutritional support specialist nurses were 30.00 (28.00, 31.00) , 47.00 (41.00, 50.00) , (22.65±6.77) , respectively. Multiple linear regression analyses showed that education was an influencing factor in the knowledge dimension of nutrition nursing practice among nutritional support nurse specialists ( P<0.05) ; title, hospital level, and years of experience as a nutritional support nurse specialist were influencing factors in the attitude dimension of nutrition nursing practice ( P<0.05) . Conclusions:Nutritional support specialist nurses have a good knowledge base of nutrition nursing practice and a positive attitude, but their practices need to be further improved. Knowledge, attitude, and practice are affected by multiple factors such as education, title, hospital level, and number of years in the professional field. In the process of nurse specialist training, managers should pay attention to the learning needs of nurses at different levels, carry out targeted training, establish a standard workflow for nurse specialists, and emphasize the construction of talents in primary hospitals, so as to promote the high-quality development of nutrition support specialist nurses.