The spine is the most common site of skeletal metastasis in lung cancer, which frequently leads to severe complications such as pathological fracture and neurological compromise and is associated with poor prognosis. The development and progression of spinal metastasis from lung cancer are linked to the unique local microenvironment and tumor microenvironment (TME) of the vertebral column. During metastatic evolution, the dense vascular network of the spine and a plethora of signaling molecules, together with the complex cellular constituents and their intricate interactions within the TME, all cooperate to facilitate the tumor invasion and colonization of the vertebral compartment. Mechanistic studies delineating the role of the TME in spinal metastasis from lung cancer have markedly expanded, fostering the emergence of innovative therapeutic strategies—including nanomedicines, sono-photodynamic therapy, gene therapy, and combination regimens. These strategies demonstrate remarkably potential for clinical translation and offer new directions for the precision management of spinal metastasis from lung cancer.

Breviscapine （Bre）， the effective flavonoid fraction extracted from Erigeron breviscapus ， contains more than 90% scutellarin. It exerts pharmacological effects including cardiovascular protection， neuroprotection， anti-tumor activity and immunomodulation. Nevertheless， Bre has several drawbacks such as low solubility， low permeability， poor stability and short half-life， which greatly restrict its clinical application. Novel drug delivery systems （NDDS） are carriers that integrate multi-dimensional technologies including solubilization， penetration enhancement， sustained/controlled release and targeted delivery to achieve efficient drug delivery. This paper systematically summarizes the research progress of Bre-NDDS， which mainly covers oral preparations （sustained/controlled-release drug delivery systems， immediate-release drug delivery systems）， injectable preparations （liposomes， solid lipid nanoparticles， lipid emulsions， polymeric nanoparticles， polymeric micelles）， mucosal delivery systems （nasal mucosal drug delivery systems， buccal mucosal drug delivery systems， pulmonary mucosal drug delivery systems） and transdermal delivery systems. The preparation routes as well as in vitro and in vivo performances of various Bre-NDDS are analyzed. The design principles for NDDS based on pharmacokinetics/pharmacodynamics are put forward， which can provide scientific evidence for the research， development and industrialization of high-efficiency and safe new Bre preparations.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

By systematically analyzing the bottlenecks in current traditional Chinese medicine （TCM） efficacy evaluation， this study addresses the limitations of TCM efficacy assessment methods in terms of individualization， holism， and complexity representation. Drawing on the concepts and methodologies of evidence-based medicine and systems biology， this paper proposes a new evaluation path by integrating multidisciplinary technologies such as big data， artificial intelligence （AI）， omics techniques， and bioinformatics， and encompassing from foundational data， individualized evaluation， and mechanistic analysis to evidence translation. The path first integrates real-world data， multi-omics profiling， and dynamic monitoring via smart devices to construct a high-dimensional dynamic data foundation. Subsequently， leveraging this foundation， it combines digital twins， dynamic symptom networks， and reinforcement learning to develop a dynamic efficacy evaluation method based on individual self-reference， enabling a shift from group mean comparisons to individual potential outcome comparisons. Furthermore， adopting the systems biology paradigm， it employs dynamic omics monitoring and deep learning models to dissect the synergistic mechanisms of TCM compound prescriptions from network regulation， emergent effects， and dynamic evolution dimensions. Finally， it enhances real-world evidence strength through target trial emulation and causal inference， achieving model iteration via incremental learning. This path aims to advance efficacy evaluation from "point validation" to "systematic characterization" and from "outcome assessment" to "process mechanism elucidation，" providing methodological support for the modernization of TCM.

Objective:To explore the association between sublingual microcirculatory perfusion vessel proportion (PPV), high mobility group protein B1 (HMGB1), and sepsis-induced coagulopathy (SIC), and to identify early predictive markers for clinical intervention.Methods:A total of 66 septic patients admitted to the Respiratory Intensive Care Unit (RICU) between November 2021 and May 2024 were enrolled. Based on SIC diagnosis within 24 hours of admission, patients were categorized into SIC ( n=36) and non-SIC ( n=30) groups. Clinical parameters, including prothrombin time (PT), activated partial thromboplastin time (APTT), sublingual PPV, and serum HMGB1 levels (measured at 0 h and 6 h), were analyzed. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors. Results:Compared with the non-SIC group, the SIC group demonstrated significantly prolonged PT ( P<0.05) and APTT ( P<0.05), elevated 0 h lactate levels, and increased 6 h HMGB1. Spearman analysis revealed a positive correlation between 6 h PPV and platelet count ( P<0.05), while an inverse correlation was observed with 6 h PT ( P<0.05). Multivariate regression identified APTT, 6 h PPV, and 6 h HMGB1 as independent predictors of SIC. ROC analysis yielded AUC values of 0.732 for APTT, 0.802 for 6 h PPV, and 0.765 for 6 h HMGB1. The combination of 6 h PPV and HMGB1 further improved predictive accuracy (AUC=0.873). Conclusions:Prolonged APTT, decreased 6 h PPV, and elevated 6h HMGB1 are key indicators of SIC. Integrated assessment of these markers enhances early risk stratification in septic patients, facilitating timely clinical intervention.

In the case of acute radiation-induced damage, rapidly and accurately assessing the exposure dose using biomarkers is crucial to medical treatment. In recent years, with the application of technologies such as metabolomics, immunomics, and genomics, more radiation biomarkers have emerged based on gene transcription markers and radiation metabolites. MicroRNAs (miRNAs), a type of molecular biomarkers, have demonstrated great potential in radiation damage assessment due to their simplicity of tests and high throughput. This review summarized the biological characteristics of miRNAs and advances in research on peripheral blood miRNAs as biomarkers of radiation-induced damage.

Imprinted genes play a key role in regulating mammalian placental and embryonic development. Here, we generated glutaminyl-peptide cyclotransferase-knockout (Qpct^-/-) mice utilizing the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) platform and identified Qpct as a novel anti-angiogenic factor in regulating mouse placentation. Compared with Qpct^+/+ mice, placentae and embryos (Qpct^-/+ and Qpct^-/-) showed significant overgrowth at embryonic Day 12.5 (E12.5), E15.5, and E18.5. Using single-cell transcriptome analysis of 32 309 cells from Qpct^+/+ and Qpct^-/- mouse placentae, we identified 13 cell clusters via single-nucleus RNA sequencing (snRNA-seq) (8880 Qpct^+/+ and 13 577 Qpct^-/- cells) and 20 cell clusters via single-cell RNA sequencing (scRNA-seq) (6567 Qpct^+/+ and 3285 Qpct^-/- cells). Furthermore, we observed a global up-regulation of pro-angiogenic genes in the Qpct^-/- background. Immunohistochemistry assays revealed a notable increase in the number of blood vessels in the decidual and labyrinthine layers of E15.5 Qpct^-/+ and Qpct^-/- mice. Moreover, the elevation of multiple pairs of ligand-receptor interactions was observed in decidual cells, endothelial cells, and macrophages, promoting angiogenesis and inflammatory response. Our findings indicate that loss of maternal Qpct leads to altered phenotypic characteristics of placentae and embryos and promotes angiogenesis in murine placentae.
Animals ; Female ; Pregnancy ; Mice ; Placentation/genetics* ; Single-Cell Analysis ; Gene Expression Profiling ; Mice, Knockout ; Transcriptome ; Placenta/blood supply* ; Neovascularization, Pathologic/genetics* ; Genomic Imprinting ; Single-Cell Gene Expression Analysis ; Angiogenesis

Objective:To explore the clinical, imaging, and pathological features of glottic squamous cell carcinoma of the larynx and their relationship with prognosis. Methods:A retrospective analysis was conducted on the clinical, imaging, and pathological data of 130 patients with glottic squamous cell carcinoma of the larynx who were treated at the First People's Hospital of Yinchuan and the General Hospital of Ningxia Medical University from January 2018 to March 2023. Imaging examinations （CT and MRI） were used to evaluate the lesion boundary clarity, density, enhancement nature, and enhancement degree. Postoperative pathological examination was used to determine the pathological nature, immunohistochemistry, etc. Statistical methods such as χ² test, Spearman correlation analysis, multivariate logistic regression analysis, and Kaplan-Meier method were used to analyze the data. Results:Among the 130 patients, 127 were male and 3 were female, with an average age of （61.92±9.595） years. There was a correlation between clinical, imaging, and pathological features. Multivariate analysis showed that heterogeneous MRI density （OR=12.414;P=0.019） and squamous cell carcinoma as a subtype were correlated. The initial symptom of non-hoarseness （HR=6.045;P=0.010） and unclear MRI boundary （HR=12.559; P=0.029） were independent risk factors for poor prognosis in patients with glottic squamous cell carcinoma of the larynx. Conclusion:There is a correlation between the clinical, imaging, and pathological features of patients with glottic squamous cell carcinoma of the larynx, and they can affect prognosis. The initial symptom of non-hoarseness and unclear MRI boundary of the tumor are independent risk factors for poor prognosis.
Humans ; Laryngeal Neoplasms/diagnosis* ; Prognosis ; Male ; Female ; Retrospective Studies ; Middle Aged ; Carcinoma, Squamous Cell/diagnosis* ; Magnetic Resonance Imaging ; Glottis/pathology* ; Tomography, X-Ray Computed ; Aged

Objective:To investigate the clinical characteristics and major allergens of patients with pollen-food allergy syndrome（PFAS） and their correlation with the severity of symptoms, and to provide a basis for identifying high-risk patients, optimizing the allergen testing process and developing individualized dietary management strategies. Methods:The clinical data of 166 patients with PFAS admitted to our hospital from January 2021 to July 2023 were retrospectively analyzed. The clinical symptoms, pollen types and food allergy of the patients were analyzed by questionnaire survey and serum specific IgE detection. phi coefficient, Apriori algorithm modeling and multivariate logistic regression analysis were used to evaluate the association between allergen and symptom severity. Results:Artemisia pollen was the most common allergen in this area, with a positive rate of 96.39%. Peach and mango were the most common food allergens, which caused allergic reactions in 24.10% and 22.89% of patients, respectively. Oral mucosal symptoms were the main symptoms. Correlation analysis showed that there was a correlation between pollen allergens and allergenic food. Association rule analysis showed that when the patient was allergic to the combination of peanuts and trees, the probability of high severity of symptoms was 82.35%. Multivariate analysis showed that ragweed allergy was significantly positively correlated with the severity of PFAS symptoms. Conclusion:Artemisia pollen and related food allergens play an important role in the pathogenesis of PFAS. Association rule mining and network map analysis revealed direct associations between peanut and tree combination allergy and symptom severity, as well as potential links between other inhaled allergens and specific food allergies. Ragweed and peach allergy are independent risk factors for the aggravation of PFAS symptoms, which can be used as early warning indicators. These results help to improve the screening of high-risk patients and the construction of regional allergen databases.
Humans ; Food Hypersensitivity/immunology* ; Allergens/immunology* ; Retrospective Studies ; Pollen/immunology* ; Cross Reactions ; Immunoglobulin E/blood* ; Rhinitis, Allergic, Seasonal/immunology* ; Artemisia/immunology* ; Male ; Female ; Adult ; Prunus persica/immunology* ; Arachis/immunology* ; Middle Aged ; Surveys and Questionnaires ; Oral Allergy Syndrome