Objective Based on the visualization graph analysis of the research hotspots of Angelica sinensis, predict the future research trends, and provide references for the next step of Angelica sinensis research. Methods Chinese and English literatures on Angelica sinensis collected from CNKI, WanFang, VIP and Web of Science from 2012 to 2022 were retrieved. CiteSpace 6.1.R6 software was used to perform visualization econometrics analysis on the number of publications, authors, institutions, journals, keywords and other topics. Results 3490 Chinese literatures and 409 English literatures were included. Visual knowledge map analysis showed that Gansu University of Chinese Medicine and Nanjing University of Chinese Medicine were the research institutions with the largest number of literature publications in Chinese and English respectively. Journals published mainly include Shizhen Traditional Chinese Medicine and Materia medica, Evidence-based Complementary and Alternative Medicine. Current research hotspots include the effects of Angelica sinensis polysaccharides, volatile oils, and ferulic acid on the hematopoietic system, chronic diseases, and cognitive impairment, as well as clinical efficacy evaluations of classic prescriptions containing Angelica sinensis and their modified formulations. The research trend was characterized by a focus on the pharmacological study of Danggui Buxue Tang,employing various experimental approaches such as network pharmacology, serum pharmacology, and metabolomics to elucidate the mechanisms of Angelica sinensis. Conclusion The pharmacological effects of Angelica sinensis and its compound were extensive, which should be further researched.

Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

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.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Babesiosis is a zoonotic parasitic disease caused by tick-borne Babesia species. Currently, more than 100 species of Babesia have been characterized, including at least 4 species that may infect humans. Babesiosis is prevalent across the world, and humans are commonly susceptible to babesiosis. The incidence of babesiosis appears an obvious seasonal distribution, and peaks in summer and autumn. Recently, the number of reported babesiosis cases has increased year by year with the improvement of diagnostic and monitoring capabilities, and the range of animal hosts has continued to expand. However, effective prevention and control of babesiosis remain challenging because of the lack of highly effective specific drugs and available vaccines. This review summarizes the pathogenic characteristics, epidemiological characteristics, epidemic process of babesiosis, and influencing factors of its epidemic, with an emphasis on natural and social factors, so as to provide the scientific evidence for risk assessment of babesiosis and formulation of babesiosis control strategy.

Objective: To study the efficacy of photosensitizer 8- methoxsalen (8-MOP) combined with ultraviolet radiation A (UVA) in inducing ferroptosis in mouse melanoma B16 cells, and to assess the resultant changes in immunogenicity, and their impact on subsequent immune activation after treatment. Methods: 1) Mouse melanoma B16 cells were cultured and treated with 8-MOP (100 ng/mL) and UVA (4 J/cm ), and then cultured in a constant temperature incubator (37℃, 5%CO ) for 24 hours after irradiation. 2) CCK8 (cell proliferation and toxicity) detection kit was used to detect the death rate of tumor cells. 3) LPO (lipid peroxide) and GSH (glutathione) detection kits were used to detect the degree of oxidative damage of tumor cells; Changes of Fe , mitochondrial membrane potential (JC-1) and BODIPY 581/591 C11 (lipid peroxidation detection kit) in tumor cells were detected by confocal microscope. Western blotting (WB) was performed to detect GPX4, SLC7A11 and NCOA4 to confirm ferroptosis. 4) The expression of HMGB1 (high mobility group protein 1), ATP and CRT (calreticulin) in the supernatant of tumor cell culture was detected by ELISA kit to evaluate the immunogenicity of tumor cells. 5) 1×10 B16 cells were injected subcutaneously into the skin of the back and neck of mice at a dose of 100 μL to construct a mouse melanoma model. Spleen mononuclear cells of tumor-bearing mice were extracted and immediately co-cultured with irradiated tumor cells for 48 h. Changes of dendritic cell (DC) maturity were detected by MHC-II, CD11c, CD80 and CD83 flow cytometry. Results: After UVAP, the survival rate of B16 cells decreased significantly (61.39±6.823 vs 84.81±7.026 vs 100.0±3.996, P<0.000 1, P<0.01). UVAP effectively induced ferroptosis in B16 cells, characterized by increased LPO and C11-bodipy lipid peroxidation, GSH depletion, Fe accumulation, mitochondrial membrane depolarization, decreased GPX4 and SLC7A11 protein expression, and increased NCOA4 expression, all in line with the trend of ferroptosis. UVAP also enhanced tumor cell immunogenicity, evidenced by elevated release of ATP, CRT, and HMGB1. The immunogenicity of B16 cells increased, the expressions of ATP, CRT and HMGB1 increased, and the DC maturity increased (CD80: 31.92±4.071 vs 19.77±3.177; CD83: 21.40±4.787 vs 12.19±1.487, P<0.001, P<0.01). Conclusion: The combined action of 8-MOP and UVA can induce ferroptosis in B16 tumor cells, enhance the immunogenicity of tumor cells, release more tumor antigens, promote the maturation of DC, present antigens better, thereby facilitating subsequent immune activation.

TFIIB-related factor 1 (BRF1) is an important transcription factor. It specifically regulates the transcription of RNA polymerase III-dependent genes (RNA Pol III genes). The products of these genes are some small non-coding RNAs, including transfer RNAs (tRNAs) and 5S ribosomal RNAs (5S rRNA). The transcription levels of tRNAs and 5S rRNA vary with changes in intracellular BRF1 amounts. tRNAs and 5S rRNA play a crucial role in determining protein synthesis. Studies have demonstrated that dysregulation of tRNAs and 5S rRNA is closely related to cell growth, proliferation, transformation, and even tumorigenesis. BRF1 is a key factor determining the generation of tRNAs and 5S rRNA. Increasing BRF1 expression enhances cell proliferation and transformation, promoting tumor development. In contrast, repressing BRF1 activity decreases the rates of cell proliferation and transformation, and inhibits tumor growth. High levels of BRF1 are found in the samples of patients suffering from hepatocellular carcinoma, breast cancer, gastric carcinoma, lung cancer, prostate carcinoma, and other cancers. It indicates that high levels of BRF1 are closely related to the occurrence of human cancer and may be a common landmark of tumors. But there is discrepancy in the regulatory mechanisms and signaling pathways of BRF1 overexpression in different cancers. In general, high levels of BRF1 in patients suffering from cancer show short survival period and poor prognosis. However, there is one exception, namely breast cancer. Approximate 80% of cases of breast cancer are estrogen receptor-positive (ER+) and 20% are ER-. The cases with high levels of BRF1 reveal longer survival period and better prognosis after they accepted the hormone treatment by Tamoxifen (Tam), compared to the cases with low level BRF1. It seems like a contradiction. Most of the cases with high levels of BRF1 belong to ER+ status. Tam has been used to treat ER+ cases of breast cancer after diagnosis and surgery. Thus, hormone therapy, such as Tam, is more effective on these patients. This is because, on one hand, that Tam competes with E2 (17β-estradiol) to bind to estrogen receptor α (ERα), but does not dissociate to occupy the receptors, blocking E2 binding to this receptor and inhibiting its biological effects. On other hand, Tam can inhibit the expression of BRF1, leading to a decline of intracellular BRF1 levels. Therefore, the actual levels of BRF1 are lower in the patients with ER+ breast cancer. It appears the prognosis of the high BRF1 expression cases better than that of the low BRF1 expression cases. Myocardial hypertrophy manifests magnification of cardiomyocyte volume rather than number increasing in the postnatal heart. Myocardial hypertrophy is a critical risk factor underlying cardiovascular diseases. No matter how myocardial hypertrophy occur, it will ultimately lead to myocardial dysfunction and heart failure. Hypertrophic growth of cardiomyocytes requires a large amount of protein synthesis to meet its needs of cardiomyocyte growth. Animal models and cell experiments have shown that myocardial hypertrophy stimulates a significant increase in BRF1 expression and transcription of tRNAs and 5S rRNA. Interestingly, elevated levels of BRF1 are found in the myocardium tissues of patients with myocardial hypertrophy. These studies demonstrate that BRF1 indeed plays a critical role in myocardial hypertrophy. In summary, high levels of BRF1 are found in patients suffering from different cancers and myocardial hypertrophy. It implies that BRF1 is a promising biological target of cancer and cardiomyopathy. BRF1 is expected to become a common biomarker for early diagnosis and prognostic observation of different human cancers. It is also an important biomarker for the diagnosis and treatment of cardiomyopathy. BRF1 not only holds an important position in the field of basic medical research but also has great prospects for translational medicine. In the present article, we summarize the progress on studies of BRF1 expressions in cancer and cardiomyopathy, proposes future research directions. It is a new research area. Here, we emphasize the significancy of BRF overexpression in the two huge diseases of human, cancer and cardiomyopathy to raise people's attention to this field.

BACKGROUND: Renal osteodystrophy (ROD) is a skeletal pathology associated with chronic kidney disease-mineral and bone disorder (CKD-MBD) that is characterized by aberrant bone mineralization and remodeling. ROD increases the risk of fracture and mortality in CKD patients. The underlying mechanisms of ROD remain elusive, partially due to the absence of an appropriate animal model. To address this gap, we established a stable mouse model of ROD using an optimized adenine-enriched diet and conducted exploratory analyses through ribonucleic acid sequencing (RNA-seq). METHODS: Eight-week-old male C57BL/6J mice were randomly allocated into three groups: control group ( n = 5), adenine and high-phosphate (HP) diet group ( n = 20), and the optimized adenine-containing diet group ( n = 20) for 12 weeks. We assessed the skeletal characteristics of model mice through blood biochemistry, microcomputed tomography (micro-CT), and bone histomorphometry. RNA-seq was utilized to profile gene expression changes of ROD. We elucidated the functions of differentially expressed genes (DEGs) using gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). DEGs were validated via quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: By the fifth week, adenine followed by an HP diet induced rapid weight loss and high mortality rates in the mouse group, precluding further model development. Mice with optimized adenine diet-induced ROD displayed significant abnormalities in serum creatinine and blood urea nitrogen levels, accompanied by pronounced hyperparathyroidism and hyperphosphatemia. The femur bone mineral density (BMD) of the model mice was lower than that of control mice, with substantial bone loss and cortical porosity. ROD mice exhibited substantial bone turnover with an increase in osteoblast and osteoclast markers. Transcriptomic profiling revealed 1907 genes with upregulated expression and 723 genes with downregulated expression in the femurs of ROD mice relative to those of control mice. Pathway analyses indicated significant enrichment of upregulated genes in the sphingolipid metabolism pathway. The significant upregulation of alkaline ceramidase 1 ( Acer1 ), alkaline ceramidase 2 ( Acer2 ), prosaposin-like 1 ( Psapl1 ), adenosine A1 receptor ( Adora1 ), and sphingosine-1-phosphate receptor 5 ( S1pr5 ) were successfully validated in mouse femurs by qRT-PCR. CONCLUSIONS Optimized adenine diet mouse model may be a valuable proxy for studying ROD. RNA-seq analysis revealed that the sphingolipid metabolism pathway is likely a key player in ROD pathogenesis, thereby providing new avenues for therapeutic intervention.
Animals ; Mice ; Chronic Kidney Disease-Mineral and Bone Disorder/genetics* ; Male ; Disease Models, Animal ; Mice, Inbred C57BL ; Sphingolipids/metabolism* ; Transcriptome/genetics* ; Signal Transduction/genetics* ; X-Ray Microtomography ; Adenine