Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

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 explore the related factors of college students social network addiction based on problem behavior theory, so as to provide a basis for improving social networking addiction in this population. Methods: From May to June 2023, a method combining convenient sampling and cluster random sampling was used to select 1 768 college students from five universities in Shanghai for a questionnaire survey on social networking addiction, self esteem, loneliness, depressive symptoms, social support, interpersonal needs, sense of distress and frustration; at the same time, the physical exercise, smoking and drinking of college students were investigated. Multivariate Logistic regression analysis was applied to explore the association between the three systems of the problem behavior theory (personality, behavior, and social environment) and social networking addiction among college students. Results: The score on the Social Network Addiction Tendency Scale was (21.08±6.29) among college students, and the detection rate of social networking addiction was 66.29%. After adjusting for gender, family economic status, parental divorce status, and whether being an only child, multivariate Logistic regression analysis showed that in the personality system, higher loneliness ( OR =1.66) and higher depressive symptoms ( OR =2.18) were associated with increased risk of social networking addiction among college students; in the behavior system, alcohol consumption ( OR =1.42) was associated with higher risk of soical networking addiction compared to non drinkers; and in the social environment system, low social support ( OR =1.43) was associated with increased risk of social networking addiction (all P <0.05). Conclusions The rate of social networking addiction among college students is relatively high, and the systems of personality, behavior, and social environment are all related to social network addiction. Providing social support, cultivating healthy lifestyle habits, and increasing interpersonal interactions may help reduce excessive dependence on social networking among college students.

Metabolic associated fatty liver disease （MAFLD） is a highly prevalent chronic liver disease worldwide， and the mechanism underlying its progression to metabolic associated steatohepatitis and liver fibrosis remain unclear. Endoplasmic reticulum stress （ERS） and ferroptosis （Fer） are deeply involved in the pathological evolution of MAFLD. This article systematically reviews the core regulatory mechanisms of ERS and its role in regulating lipid metabolism， inflammation response， and cell apoptosis in MAFLD. It also analyzes the core mechanism of Fer and discusses the predisposing factors for Fer in the pathological microenvironment of MAFLD， as well as the role of Fer in exacerbating hepatocyte death and activating the progression of liver fibrosis. This article proposes that the crosstalk between ERS and Fer is a key driver for the progression of MAFLD， which provides new references and ideas for the clinical intervention of MAFLD.

ObjectiveThe quality of fresh Gastrodiae Rhizoma directly determines the efficacy of its terminal products. According to the theory of excellent shape， high quality， and superior effect of authentic medicinal materials， this study aimed to develop a novel quality evaluation system for fresh Gastrodiae Rhizoma by systematically quantifying and integrating appearance traits with bioactive components. MethodsFresh Gastrodiae Rhizoma samples were collected from four major producing regions. After herbal textural research and a literature review， tuber weight， width， length， and aspect ratio were selected as quantitative indicators of appearance， and they were measured by an electronic balance and a digital vernier caliper. Key active components， including gastrodin， p-hydroxybenzyl alcohol， parishins， and total polysaccharides， were quantified via ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） and the phenol-sulfuric acid method. Descriptive statistics and K-means clustering analysis were employed to establish the threshold ranges for the excellent shape and high quality indicators. ResultsTwo specific quantitative evaluation systems for characterizing the excellent shape and high quality of fresh Gastrodiae Rhizoma were established. System 1： tuber weight > 83.90 g， tuber width > 3.50 cm， total gastrodin and p-hydroxybenzyl alcohol content > 0.277%， and total parishin content > 0.561%. System 2： tuber length < 9.89 cm， aspect ratio < 3.41， and total polysaccharide content > 195.274 mg·g^-1. The verification results showed that the systems effectively identified fresh Gastrodiae Rhizoma samples with both excellent appearance features and stable bioactive components. ConclusionThis study establishes a multi-dimensional evaluation and grading system for fresh Gastrodiae Rhizoma based on the correlation between shape and quality. This framework provides a scientific basis for the quality control and resource grading of fresh Gastrodiae Rhizoma and lays a methodological foundation for the efficient utilization of both the medicinal and edible value of this herbal medicine.

Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective To study the correlation between Periostin, interleukin-33 (IL-33), and chronic cough after thoracoscopic lobectomy in patients with coronary artery bypass grafting (CABG) combined with lung cancer. Methods A total of 102 lung cancer and coronary heart disease patients at Tianjin Chest Hospital from January 2022 to January 2024 were prospectively enrolled, and they were divided into a chronic cough group (n=42) and a non-chronic cough group (n=60) based on whether chronic cough occurred after surgery. Serum levels of Periostin and IL-33 were measured on the 1st, 7th, and 14th days post-lobectomy. The Pearson method was employed to analyze the correlation between Periostin and IL-33 levels and the severity of cough. Univariate and multivariate logistic regression analyses were conducted to identify factors influencing the occurrence of chronic cough. Additionally, receiver operating characteristic (ROC) curve analysis was utilized to assess the potential value of serum Periostin and IL-33 levels in predicting postoperative chronic cough. Results In patients with chronic cough, the peripheral blood Periostin and IL-33 levels measured on days 7 and 14 were significantly higher than those in patients with non-chronic cough, and the interactions between the two groups and at different time points were significant (P<0.001). The degree of cough was positively correlated with the levels of Periostin and IL-33 on days 7 and 14 (P<0.05), but had no significant correlation with the levels on day 1 (P>0.05). In patients with lung cancer, after thoracoscopic lobectomy, Periostin [OR=1.619, 95%CI (1.295, 2.025)] and IL-33 [OR=1.831, 95%CI (1.216, 2.758)] on day 7 and Periostin [OR=1.952, 95%CI (1.306, 2.918)] and IL-33 [OR=1.742, 95%CI (1.166, 2.603)] on day 14 were identified as risk factors for chronic cough. ROC curve analysis showed that the sensitivity of Periostin on day 7 was 69.05%, the specificity was 71.67%, and the area under the curve (AUC) was 0.756 [95%CI (0.616, 0.893)]. The sensitivity of Periostin on day 14 increased to 71.43% and the specificity was 76.67%, AUC was 0.762 [95%CI (0.633, 0.898)]. At the same time, the critical value of IL-33 on day 7 was 45.03 pg/mL, the sensitivity and specificity were both 83.33%, the AUC was 0.884 [95%CI (0.789, 0.980)], and the critical value of IL-33 on day 14 was 56.01 pg/mL, the sensitivity was 85.71%, the specificity was 80.00%, and the AUC was 0.899 [95%CI (0.799, 0.999)]. Joint logistic regression analysis of Periostin and IL-33 levels on days 7 and 14 showed showed that the sensitivity was 95.24%, the specificity was 95.00%, and the AUC reached 0.993 [95%CI (0.979, 1.000)]. Conclusion Periostin and IL-33 levels, measured at various time points, are abnormally elevated following thoracoscopic lobectomy in patients with combined CABG and lung cancer. These levels significantly correlate with cough severity. Given their predictive potential for chronic cough, these markers are deemed valuable biomarkers.

Esophageal squamous cell carcinoma is the main histological type of esophageal cancer in China, which seriously threatens the health of people. The application of immunotherapy, mainly immune checkpoint inhibitors, has greatly improved the prognosis of patients with esophageal squamous cell carcinoma, but the efficacy of treatment is still limited. Tertiary lymphoid structure (TLS) is an ectopic organized lymphoid structure that accumulates in non-lymphoid organs. Previous studies have found that TLS in esophageal squamous cell carcinoma is associated with better patient outcomes and enhanced immunotherapy efficacy. Based on current researches about TLS in esophageal squamous cell carcinoma, this paper reviews the relationship between TLS and the prognosis and immunotherapy of patients. We hope to provide reference for the precise immunotherapy of esophageal squamous cell carcinoma.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

Liver fibrosis is caused by various factors such as viral infection， alcohol intake， and metabolism-related damage， leading to the replacement of normal tissue by fibrous scars. As a regulatory factor for cell proliferation， insulin-like growth factor 1 （IGF-1） participates in the regulation of cell cycle， the promotion of cell proliferation and differentiation， and the inhibition of cell apoptosis by binding to its receptor insulin-like growth factor-1 receptor （IGF-1R）. Studies have shown that the IGF-1/IGF-1R signaling pathway can regulate the process of liver fibrosis by affecting the senescence and apoptosis of hepatocytes， the activation and proliferation of hepatic stellate cells， and the dysfunction of endothelial cells. In addition， the IGF-1/IGF-1R signaling system can also regulate multiple mechanisms such as DNA damage repair， cell proliferation， lipid metabolism， cell senescence， and oxidative stress， thereby providing new strategies and potential targets for the prevention and treatment of liver fibrosis. This article summarizes the mechanism of action of IGF-1/IGF-1R and its signal transduction system in mediating liver fibrosis by regulating DNA damage repair in different cells， in order to provide a theoretical basis for the treatment of liver fibrosis.