Objective: To explore the characteristics of the diversity and composition of oral microbial flora with age, and to provide a reference for understanding the succession of oral microecology at different ages. Methods: Oral rinse 16S rRNA (V4 region) sequencing data from 9 021 participants 14-69 years of age in the 2009-2012 National Health and Nutrition Examination Survey (NHANES) were analyzed. Alpha diversity (Observed OTUs, Faith’s PD, Shannon Index), beta diversity (Bray-Curtis and UniFrac), and genus-level composition were examined using weighted generalized linear models (GLMs), including quadratic terms for age and adjusting for key covariates (gender, race/ethnicity, BMI, smoking status, and periodontitis severity). Results: Alpha diversity demonstrated a clear inverted U-shaped trajectory across age, peaking at 25-30 years old and declining thereafter. This trend remained consistent across sex, race, smoking, and periodontal health strata. Beta diversity analyses revealed a modest but steady age-related shift in community structure. Genus-level analyses revealed that Rothia, Prevotella_6, and Lactobacillus increased steadily with age, while Haemophilus, Porphyromonas, and Corynebacterium declined significantly. Notably, potential periodontopathogens, such as Fusobacterium and Treponema_2, peaked in early adulthood before declining with age. Conclusion Age is an important driver of oral microbial succession, and the oral microbiome exhibits dynamic changes across different life stages. Future longitudinal and multi-omic studies are warranted to elucidate the mechanisms underlying these age-related trajectories.

Objective: To investigate the protective effects of Gouqizi (Lycii Fructus, GQZ)-Danshen (Salviae Miltiorrhizae Radix et Rhizoma, DS) against hydrogen peroxide (H2O2)-induced oxidative injury in 661W retinal photoreceptor cells and to explore whether these effects involve angiopoietin-like 4 (ANGPTL4). Methods: Liquid chromatography-mass spectrometry (LC-MS) was used to identify the major components of GQZ-DS aqueous extract. An H2O2-induced oxidative injury model was established in 661W cells. Working concentrations of H2O2 and GQZ-DS were determined using the cell counting kit-8 (CCK-8) assay. Cells were subjected to GQZ-DS, ANGPTL4 knockdown, or ANGPTL4 overexpression as indicated. Flow cytometry was used to analyze cell cycle distribution, apoptotic rate, and intracellular reactive oxygen species (ROS). Colorimetric determination of malondialdehyde (MDA) content and superoxide dismutase (SOD) activity using the thiobarbituric acid (TBA) method was performed. The protein expression level of ANGPTL4 was assessed by immunofluorescence. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to quantify the mRNA level of ANGPTL4. Western blot was used to detect the protein levels of ANGPTL4 and cleaved caspase-3. Results: LC-MS identified five major constituents in the GQZ-DS aqueous extract: 2-O-β-D-glucopyranosyl-L-ascorbic acid, rutin, D-galactose, salvianolic acid A, and tanshinone IIA. The CCK-8 method selected 300 μmol/L H2O2 as the oxidative stress condition for experiments, and 0.05 and 0.1 g/mL were selected as the low and high doses of GQZ-DS, respectively, for subsequent experiments. The intervention with H2O2 resulted in reduced cell viability, elevated ROS and MDA levels, decreased SOD activity, increased apoptotic rate, upregulated cleaved caspase-3 expression, and G0/G1 phase cell cycle arrest of 661W cells. Both low and high doses of GQZ-DS alleviated these alterations, with high dose exhibiting stronger protective effects (P < 0.05 or P < 0.01). GQZ-DS also downregulated ANGPTL4 expression at both the mRNA and protein levels. Following plasmid transfection of cells, the study further revealed that ANGPTL4 knockdown mitigated oxidative stress and apoptosis-related injury, whereas ANGPTL4 overexpression exacerbated these pathological changes. Moreover, GQZ-DS partially reversed the degree of cellular oxidative damage induced by ANGPTL4 overexpression. Conclusion GQZ-DS can alleviate the H2O2-induced oxidative injury of 661W retinal photoreceptor cells, and the effects are related to the down-regulation of ANGPTL4 expression.

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 study was aimed at investigating the immunoregulatory function of Mycobacterium tuberculosis Rv3641c gene in modulating host type Ⅰ interferon responses.The shuttle plasmid pMV261 was used to construct Rv3641c overexpression recombinant Mycobacterium smegmatis,and the biological characteristics of the recombinant bacteria were analyzed to explore the effect of Rv3641c on the growth curve,colony morphology and stress resistance of Mycobacterium.Subsequently,RAW264.7 cells were infected with Rv3641c overexpressing Mycobacterium smegmatis,and the transcriptional expression of genes related to the inhibition of type I inter-feron pathway was determined by RT-PCR.The expression level of IFN-βprotein was determined by ELISA,and the intracellular sur-vival level was determined.As a result,the recombinant rMS::pMV261-Rv3641c was successfully constructed.The results of biologi-cal characteristics analysis showed that Rv3641c did not affect the growth of mycobacteria,but significantly changed the colony mor-phology of mycobacteria and improved its resistance to H2O2.The results of recombinant bacteria infection experiments showed that Rv3641c significantly down-regulated the transcription levels of IFN-α,IFN-βand downstream ISGs genes CXCL10,IFIT2 and IL-1β in host cells,and Rv3641c significantly down-regulated the transcription levels of IFN-α,IFN-βand downstream ISGs genes CXCL10,IFIT2 and IL-1βin host cells.The results of intracellular colonization experiments showed that the intracellular mycobacte-ria in the overexpression recombinant bacteria infection group were significantly higher than those in the empty vector group,indicat-ing that Rv3641c could promote the intracellular surviv al of mycobacteria.In summary,the Rv3641c gene of M.tuberculosis can inhibit the host type I interferon response and promote the intracellular survival of M.tuberculosis,which provides a new idea for further explor-ing the immune escape function of M.tuberculosis and the discovery of new targets for anti-tuberculosis drugs.

To provide in-service medical technicians and nurses with convenient access to continuing education resources in transfusion medicine, reduce transfusion-related adverse events, and ensure the safety, rationalization, and effectiveness of clinical transfusion, we designed and developed an online transfusion continuing education platform. The platform was based on the new managed code programming model.NET Core and the powerful functions of hypertext preprocessor PHP 7.4, addressing current issues in transfusion online continuing education. Through in-depth analysis of student attributes, learning behaviors, and teaching behaviors, a comprehensive online continuous teaching quality evaluation index system was established. This system not only facilitates the quantitative assessment of teaching quality but also successfully integrates the two core functions of teaching and management, thereby achieving unified online teaching.

Aim To investigate the effect of total fla-vones of Coreopsis tinctoria Nutt(CF)on cognitive im-pairment in vascular dementia(VD).Methods The VD rat models were established by modified bilateral common carotid arteries ligation method.SD rats were divided into the sham operation group,model group,positive control group(nicergoline),and low,medium,and high dose CF groups.After eight weeks of admin-istration,the short term memory and spatial learning and memory abilities were evaluated by the platform jumping test,dark avoidance test and Morris water maze test.The pathological changes of the hippocam-pal tissues were inspected by HE and Nissl staining.The contents of TNF-α and IL-1β in the hippocampal were examined by ELISA.The protein expression lev-els of TLR4,MyD88,NF-κB p65,and p-NF-κB p65 in the hippocampal were detected by Western blot.The mRNA expression levels of miR-93,TLR4,MyD88,and NF-κB p65 in the hippocampal were determined by qRT-PCR.Results CF obviously improved the short term memory and spatial learning and memory abilities of VD rats,and alleviated the pathological damage of the hippocampus.CF also obviously decreased the lev-els of TNF-α and IL-1β,declined the protein expres-sion levels of TLR4,MyD88,and p-NF-κB p65,and re-duced the miR-93,TLR4,and MyD88 mRNA expres-sion in the hippocampus.Conclusion CF has a nota-ble protective effect on the neuroinflammation and cog-nitive impairments in VD rats by inhibiting the miR-93-mediated TLR4 signaling pathway.

Objective:To compare the accuracy of a Chinese large language model (LLM) and radiologists in Chinese middle level professional qualification examination of radiology, and evaluate the quality of answer reasoning provided by the Chinese LLM.Methods:In this study, 100 high-quality questions were selected using stratified random sampling to form a test set. We asked the ERNIE Bot by dialogues on the website to provide the correct answers and answer reasoning for these questions. These questions were also answered by 15 radiologists with different levels of experience. The accuracy of Chinese LLM and that of radiologists were compared. Two radiologists evaluated the quality of answer reasoning using a 5-point semi-quantitative scale.Results:The accuracy of ERNIE Bot was 60.00%, which was lower than the median (interquartile) accuracy of 67.00% (64.00%, 73.00%) for radiologists, and the difference was statistically significant ( W=2.47, P=0.013). The word count of the reasoning provided by Ernie Bot was (196.44±99.25) words, with no significant difference in word count between correct and incorrect answer reasoning, which were (211.03±107.53) words and (174.55±81.84) words, respectively ( t=1.82, P=0.072). Among the correct answers, the quality of reasoning was scored as follows: 1 point for 3 questions, 2 points for 9 questions, 3 points for 12 questions, and 4 points for 36 questions. No reasoning received a score of 5. Conclusions:Chinese LLM demonstrates a certain level of medical knowledge and clinical reasoning ability, which can assist clinical teachers in educational activities. However, it is not yet able to independently tutor residents and lacks the ability of invitational and heuristic teaching.

Objective:By using cognitive interviews,the interviewees' cognition and understanding of the inflammatory bowel disease(IBD) self-efficacy scale for adolescents and young adults (IBDSES-A) were evaluated,and the semantic content of IBDSES-A,which was initially translated into Chinese,was tested and revised.Methods:Using purposive sampling,15 IBD patients aged 12-18 were selected from Beijing Children's Hospital,Capital Medical University,between January and February 2025,stratified by age group and disease type.Two rounds of cognitive interviews were conducted.Feedback and suggestions from interviewees were analyzed using a question appraisal system for coding and integration.Based on expert panel discussions,ambiguous items were revised to finalize the Chinese version of the IBDSES-A.Results:In the first round,10 interviewees were interviewed,followed by 5 interviewees in the second round.There were no statistically significant differences ( P>0.05) between the interviewees of two rounds in terms of age,gender,and education level.During the first round of interview,interviewees expressed comprehension difficulties with 76.9% (10/13) of the items.Coding analysis revealed that the primary issue was "clarification",as unclear wording made it difficult for interviewees to fully grasp the intended meaning of certain items.Based on these findings,the expert panel revised 10 of the 13 items in the IBDSES-A.The second round of cognitive interview showed that the interviewees generally understood the revised items，achieving linguistic and semantic consistency with the original scale. Conclusion:The application of cognitive interviews in the translation process of the IBDSES-A helps reduce comprehension biases caused by inappropriate wording，ensuring that the localized version of the scale is more accessible and understandable to the target population.