Large language models (LLMs) offer a modern approach to help inherit traditional Chinese medicine (TCM). This article discussed the progress of LLM applications in TCM and proposed future development directions by reviewing the existing research. We have found that LLMs and related technologies have excellent applications and performance in the management of TCM knowledge and data. They are often applied in information extraction, knowledge graph construction, and data standardization processing. However, data quality and security issues need to be given more attention. In clinical diagnosis and treatment, LLMs can imitate the thinking of TCM by disassembling and reconstructing its diagnostic process and can achieve functions such as prescription recommendation and question and answer (Q&A). However, this approach involves LLMs making inferences and predictions based on existing corpora and thus may not flexibly handle complex environments and tasks. Moreover, the current evaluation criteria for TCM LLMs can be summarized into 3 categories: general evaluation metrics, technical framework evaluation, and evaluation criteria for the characteristics of TCM (such as consistency rates of prescriptions and diagnostic suggestions). However, the lack of a unified and standardized evaluation system hinders the clinical application of TCM LLMs. The future progress of TCM LLMs should focus on the 3 aforementioned critical aspects to achieve technological breakthroughs. In addition, we are promoting the research on vertical TCM LLMs and application terminals. We believe this will bring new ideas to the research on TCM LLMs.

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.

This narrative review examines the challenges, strategies, and future directions in the development of young teachers within the pathophysiology departments of Chinese medical colleges. A thorough review of 49 studies published between 2013 and 2024 was carried out using PubMed, Web of Science, and various Chinese databases. The primary challenges identified include teaching innovation (cited in 84.2% of the studies), research pressure (91.2%), disciplinary characteristics (87.7%), and career development (80.7%). Medical schools have responded by enhancing training systems (94.7%), innovating teaching methods (93.0%), and bolstering research support (96.5%). Looking ahead, trends are shifting toward the application of new technologies, interdisciplinary integration, and international collaboration. The focus on cultivating young teachers is increasingly geared towards personalization and diversification, which are essential for advancing education in pathophysiology. High-quality young teachers are pivotal in raising teaching standards, fostering research innovation, and facilitating interdisciplinary exchanges. Based on these insights, we recommend several practical measures to enhance the quality of pathophysiology education in China. These include establishing comprehensive training programs that integrate teaching innovation and research skills; developing structured mentorship systems with clear pathways for career advancement; creating platforms that support technology-enhanced teaching and international collaboration; and implementing systematic evaluation mechanisms to assess teaching effectiveness. These targeted interventions will require a coordinated effort from department heads, educational institutions, and policymakers to ensure a sustained improvement in the quality of pathophysiology education.

Objective To explore the value of radiomics model and deep learning model based on unenhanced MRI in predicting microvascular invasion(MVI)of hepatocellular carcinoma(HCC)preoperatively.Methods A total of 189 patients with postopera-tive pathologically confirmed HCC from two centers were retrospectively selected,of which 119 cases from Zhujiang Hospital of Southern Medical University were used as the training set[60 cases with negative MVI,59 cases with positive MVI],and 70 cases from Shenzhen People's Hospital were used as the external test set[38 cases with negative MVI and 32 cases with positive MVI].Clinical indicators were analyzed by univariate and multivariate logistic regression analysis and the independent predictors of positive MVI were screened.Deep transfer learning(DTL)and traditional radiomics methods were used to construct radiomics model and deep learning model based on unenhanced MRI.The predictive performances of each model were compared using receiver operating charac-teristic(ROC)curves and area under the curve(AUC).DeLong test was employed to compare statistical differences in performance of the models.Results Alkaline phosphatase(ALP)and prothrombin time(PT)were independent predictors of positive MVI(P<0.05).The deep learning model based on T2WI had the best predictive efficacy,with AUC of 0.779[95%confidence interval(CI)0.696-0.863]and 0.741(95%CI 0.620-0.861)in the training set and external test set,respectively,and there were statistically significant differences compared with the radiomics model and the clinical model based on T1WI(P<0.05).Conclusion Deep learning model based on T2WI has a certain application value in preoperative noninvasive prediction of MVI status in HCC patients.

OBJECTIVE: By analyzing the hormone secretion of the adenohypophysis, thyroid glands, gonads, and adrenal cortex in patients with hematological diseases before and after hematopoietic stem cell transplantation (HSCT), this study aims to preliminarily explore the effect of HSCT on patients' hormone secretion and glandular damage. METHODS: The baseline data of 209 hematological disease patients who underwent HSCT in our hospital from January 2019 to December 2023, as well as the data on the levels of hormones secreted by the adenohypophysis, thyroid glands, gonads and adrenal cortex before and after HSCT were collected, and the changes in hormone levels before and after transplantation were analyzed. RESULTS: After allogeneic HSCT, the levels of thyroid-stimulating hormone (TSH), triiodothyronine (T3), free triiodothyronine (FT3) and estradiol (E2) decreased, while the levels of luteinizing hormone (LH) and follicle- stimulating hormone (FSH) increased. The T3 level of patients with decreased TSH after transplantation was lower than that of those with increased TSH after transplantation. In female patients, the levels of prolactin (PRL), progesterone (Prog), and testosterone (Testo) decreased after HSCT. Testo and PRL decreased when there was a donor-recipient sex mismatch, and the levels of adrenocorticotropic hormone (ACTH) and cortisol (COR) decreased when the HLA matching was haploidentical. The levels of T3, FT3, and PRL decreased after autologous HSCT. In allogeneic HSCT patients, the levels of TSH, T4, T3, FT3, and ACTH in the group with graft-versus-host disease (GVHD) were significantly lower than those in the group without GVHD. Logistic regression analysis showed the changes in hormone levels after transplantation were not correlated with factors such as the patient's sex, age, or whether the blood types of the donor and the recipient are the same. CONCLUSION HSCT can affect the endocrine function of patients with hematological diseases, mainly affecting target glandular organs such as the thyroid, gonads, and adrenal glands, while the secretory function of the adenohypophysis is less affected.
Humans ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Hematologic Diseases/blood* ; Follicle Stimulating Hormone/blood* ; Triiodothyronine/blood* ; Luteinizing Hormone/blood* ; Thyroid Gland/metabolism* ; Estradiol/blood* ; Thyrotropin/blood* ; Gonads/metabolism* ; Adult ; Middle Aged ; Adrenocorticotropic Hormone/blood* ; Hormones/metabolism* ; Adrenal Cortex/metabolism* ; Prolactin

OBJECTIVES: To investigate the effects of periodontitis induced by Prevotella nigrescens (Pn) combined with ligation on cognitive functions in mice. METHODS: Twenty-four C57BL/6J mice were randomly divided into control group, ligation group, and ligation + Pn treatment (P+Pn) group. Experimental periodontitis was induced by silk ligation of the first molars followed by topical application of Pn for 6 weeks. After modeling, alveolar bone resorption was assessed using micro-CT and histological analysis. Learning and memory abilities of the mice were evaluated using open field test (OFT), novel object recognition test (NORT), and Morris water maze test (MWM). Seven weeks after the start of modeling, the mice were sacrificed for examining histopathological changes in the hippocampus using HE and Nissl staining. RESULTS: After 6 weeks of molar ligation, micro-CT revealed horizontal alveolar bone resorption and furcation exposure in the mice, and histological analysis showed apical migration of the junctional epithelium, epithelial ridge hyperplasia, and lymphocyte infiltration, and these changes were obviously worsened in P+Pn group. Alveolar bone height decreased significantly in both ligation groups compared to the control group. Cognitive tests showed that the mice in both of the ligation groups traveled shorter distances in OFT, showed reduced novel object preference in NORT, and exhibited longer escape latencies in MWM, and the mice in P+Pn group had significantly poorer performances in the tests. Histologically, obvious neuronal cytoplasmic degeneration, necrosis, nuclear pyknosis, vacuolation, and reduced Nissl bodies and viable neurons were observed in the hippocampal regions of the mice in the two ligation groups. CONCLUSIONS Pn infection aggravates alveolar bone destruction, accelerates necrosis and causes morphological abnormalities of neuronal cells in the hippocampus to reduce cognitive functions of mice with periodontitis.
Animals ; Periodontitis/microbiology* ; Mice ; Mice, Inbred C57BL ; Cognition ; Alveolar Bone Loss ; Hippocampus/pathology* ; Male ; Inflammation ; Maze Learning

OBJECTIVES: To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application. Methods and. RESULTS: Recommendations were formulated based on literature review and expert group discussion, and consensus was reached following expert consultation. The consensus recommendations are comprehensive, covering the entire treatment procedures from preoperative assessment and preparation, surgical operation process, postoperative management and traditional Chinese medicine treatment to individualized treatment planning. The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain, reduced the use of opioid drugs, and significantly improved the quality of life and enhanced immune function of the patients. Postoperative follow-up suggested good treatment tolerance among the patients without serious complications. CONCLUSIONS The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy. The combined treatment has a high clinical value with a good safety profile for management of cancer pain.
Humans ; Medicine, Chinese Traditional ; Cancer Pain/therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Drug Delivery Systems ; Pain Management/methods* ; China

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors

OBJECTIVE: Poxviruses are zoonotic pathogens that infect humans, mammals, vertebrates, and arthropods. However, the specific role of ticks in transmission and evolution of these viruses remains unclear. METHODS: Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses. Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences. RESULTS: Fifty-eight poxvirus species, representing two subfamilies and 20 genera, were identified, with 212 poxviral sequences assembled. A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes. These genomic sequences contained fragments originating from rodents, archaea, and arthropods. CONCLUSION Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses. These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer, gene recombination, and gene mutations, thereby promoting co-existence and co-evolution with their hosts. This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
Animals ; Poxviridae/physiology* ; Ticks/virology* ; Phylogeny ; Transcriptome ; Evolution, Molecular ; Poxviridae Infections/virology* ; Genome, Viral