Compared to traditional suturing, lung stapling using automatic staplers offers advantages such as smaller trauma, faster wound healing, ease of operation, and lower complication rates, making it widely used in clinical practice. However, there are significant differences in bronchial tissue thickness at different anatomical locations, and the market is flooded with various types of staplers. Currently, there is a lack of recommended stapling schemes for bronchial staplers at different anatomical locations. This article reviews the development and application of automatic staplers and summarizes some types of staplers that are currently used in clinical practice, with the aim of promoting the formation of individualized stapler selection protocols for minimally invasive thoracic surgery based on the Chinese population.

AIM To investigate the stability of salvianolic acid B.METHODS HPLC was adopted in the content determination of salvianolic acid B,after which the chemical stability in different pH of buffer solutions,oxidation stability in different concentrations of H2O2,and biological stability in artificial gastric fluid,artificial intestinal fluid and biological matrices were analyzed,and its degradation kinetics was fitted.RESULTS Salvianolic acid B was stable in acidic and weakly acidic buffer solutions and artificial gastric fluid,which demonstrated poor stability in neutral and alkaline buffer solutions,artificial intestinal fluid,H2O2 and biological matrices.The degradation process of this constituent accorded with the first-order kinetic model in ileum homogenate,and the second-order kinetic model in pH 7.4 buffer solution,artificial intestinal fluid,H2O2 and stomach,duodenum,jejunum,colon homogenates.CONCLUSION Biological matrices,oxidants and alkaline environment can affect the stability of salvianolic acid B.This experimental exhibits important significance for the development and application of salvianolic acid B-related products.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

Objective:This study aims to initially establish a scoring system for comprehensively reflecting the severity of intracranial atherosclerotic lesions and to explore the correlation between this score and atherosclerotic risk factors as well as stroke events.Methods:This study retrospectively analyzed patients who underwent head and neck computer tomography angiography(CTA)examinations and had head MRI examinations within one month before or after the CTA examination from January 2021 to August 2024 in Beijing Hospital.An intracranial atherosclerosis disease score(ICADS)system was constructed based on the degree and number of vascular stenosis.The relationship between ICADS and atherosclerotic risk factors was explored by grouping patients according to the quartile of ICADS.Patients were divided into acute stroke group and non-acute stroke group to compare differences in ICADS and cerebrovascular disease risk factors between the two groups, and to investigate the correlation between stroke events and ICADS.Results:There were statistically significant differences in the proportions of patients with hypertension and diabetes among different ICADS groups.Multiple linear regression analysis showed that hypertension( B=1.17, 95% CI: 0.20-2.14, P<0.05)and diabetes( B=2.75, 95% CI: 1.85-3.64, P<0.001)were risk factors for higher ICADS.The ICADS was higher in the acute stroke group than in the non-acute stroke group(9 vs.6, P<0.001), and a higher ICADS was identified as a risk factor for stroke( OR=1.10, 95% CI: 1.07-1.14, P<0.001). Conclusions:ICADS can comprehensively reflect the severity of intracranial atherosclerotic lesions and is correlated with stroke events, making it useful for clinical screening of high-risk patients for stroke.

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

One of the key mechanisms underlying resistance against immunotherapy is the reduction in the abundance and functional capacity of immune cells within the tumor microenvironment (TME). Accordingly, the development of novel antibodies and small-molecule agents that target multiple co-inhibitory molecules—whether employed as monotherapies or in combination—holds promise for reinvigorating exhausted T cells and restoring antitumor immune responses. In addition, exploring agonists targeting co-stimulatory molecules represents a promising strategy to enhance the secondary signals necessary for T cell activation and thereby facilitates tumor eradication. However, careful attention must be given to potential toxicities associated with these agents. Furthermore, this review highlights the emerging therapeutic potential of cancer vaccines, oncolytic viruses, diverse cellular therapies, and other innovative strategies designed to augment the efficacy of immunotherapy in non-small cell lung cancer (NSCLC). Moreover, we discuss therapeutic strategies targeting non-proliferating TME components, including cancer-associated fibroblasts (CAFs) and the extracellular matrix (ECM), and hypoxia-alleviating agents and immune homeostasis-supporting probiotics, all aimed at enhancing anti-tumor immunity. In summary, this article emphasizes the critical importance of integrating therapeutics with complementary mechanisms of action while maintaining the balance between efficacy and tolerability in the advancement of precise and effective immunotherapy in NSCLC to an unprecedented level.

AIM To investigate the stability of salvianolic acid B.METHODS HPLC was adopted in the content determination of salvianolic acid B,after which the chemical stability in different pH of buffer solutions,oxidation stability in different concentrations of H2O2,and biological stability in artificial gastric fluid,artificial intestinal fluid and biological matrices were analyzed,and its degradation kinetics was fitted.RESULTS Salvianolic acid B was stable in acidic and weakly acidic buffer solutions and artificial gastric fluid,which demonstrated poor stability in neutral and alkaline buffer solutions,artificial intestinal fluid,H2O2 and biological matrices.The degradation process of this constituent accorded with the first-order kinetic model in ileum homogenate,and the second-order kinetic model in pH 7.4 buffer solution,artificial intestinal fluid,H2O2 and stomach,duodenum,jejunum,colon homogenates.CONCLUSION Biological matrices,oxidants and alkaline environment can affect the stability of salvianolic acid B.This experimental exhibits important significance for the development and application of salvianolic acid B-related products.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.