OBJECTIVE To investigate the application and influencing factors of sodium-dependent glucose transporters 2 inhibitors（SGLT-2i） in patients with heart failure with preserved ejection fraction（HFpEF） in the real world. METHODS Data from 358 patients with HFpEF who were hospitalized at the First Affiliated Hospital of Chongqing Medical University from May 2023 to May 2024 were retrospectively collected. The patients were divided into the SGLT-2i group and the non-SGLT-2i group based on whether they were prescribed SGLT-2i upon discharge. Baseline characteristics， comorbidities， and differences in drug treatment were compared between the two groups. Based on univariate analysis， multivariate Logistic regression analysis was performed to identify independent influencing factors of SGLT-2i use in patients with HFpEF， followed by further stratified analysis. RESULTS Among 358 HFpEF patients， the overall utilization rate of SGLT-2i was 33.5%. Combined with type 2 diabetes [OR＝9.063，95%CI（4.924-16.679） ] ， atrial fibrillation [OR＝3.135，95%CI（1.590-6.178） ] ， coronary artery heart disease [OR＝1.888，95%CI（1.072-3.327） ] and the use of loop diuretics [OR＝3.822， 95%CI （1.588-9.200） ] were all independent influencing factors for the use of SGLT-2i in patients with HFpEF （ P ＜0.05）. The results of the stratified descriptive analysis were consistent with those of the multivariate analysis， showing a higher utilization rate of SGLT-2i among patients with concomitant T2DM，atrial fibrillation， coronary artery heart disease， and those receiving loop diuretics （ P ＜0.05）； whereas the utilization rate of SGLT-2i was comparable across patients with different levels of renal function （ P ＞0.05）. CONCLUSIONS In the real-world clinical practice， the utilization of SGLT-2i in patients with HFpEF remains suboptimal， and treatment coverage still needs to be improved. Their use of SGLT-2i is primarily influenced by the presence of type 2 diabetes， atrial fibrillation， coronary artery heart disease， and the use of loop diuretics.

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.

Quality control (QC) of biospecimens from oral and maxillofacial tumors patients constitutes a critical foundation for the prevention, diagnosis, treatment, and precision medicine research of these diseases. Biospecimen quality directly governs the discovery and validation of disease biomarkers, the elucidation of pathogenesis, and the efficacy of clinical translation. QC spans the entire biospecimen lifecycle—encompassing collection, processing, storage, transportation, and utilization. Its primary objectives are to ensure sample integrity, reliability, traceability, and consistency, thereby guaranteeing the robustness of research data; the accuracy of molecular subtyping, biomarker identification, and treatment response prediction; and the precision of clinical decision-making. However, current QC frameworks for these biospecimens remain underdeveloped. Drawing on domestic and international technical standards, regulatory guidelines, and recent research advances, this paper elaborates on the importance of implementing a QC management system throughout the biospecimen lifecycle. It focuses on QC methodologies tailored to diverse biospecimen types, examining how standardized sampling procedures, regulated preprocessing workflows, and optimized long-term storage conditions influence sample quality. We aim to provide concrete guidance and a transferable paradigm for establishing standardized QC protocols and an informatics-enabled traceability system specific to oral and maxillofacial tumors. Such efforts are intended to enhance the research value and clinical utility of these biospecimens, furnishing reliable sample resources and technical support for the development of precision diagnostics and therapeutics. Furthermore, we advocate for a dual-track “QC plus Ethics” management framework within biobanks. This approach would reinforce ethical and legal safeguards, establishing a robust barrier to support safe scientific innovation and clinical translation.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

Objective To explore the causal relationship between breast cancer and free fatty acid receptor 4(FFAR4)by using two-sample Mendelian randomization.Methods By using Genome-wide Association Studies and expression quantitative trait locus(eQTL)data,single nucleotide polymorphism sites closely related to breast cancer and FFAR4 were extracted.Causal effect values were calculated by using five methods:inverse variance weighting(IVW),MR-Egger,weighted median,simple mode and weighted mode.Cochran Q tests were used to detect heterogeneity,MR-Egger intercept tests and MR-PRESSO tests were used to assess level multiplicity,and the hold-out method was employed for sensitivity analysis to ensure robustness of the results.Additionally,Bayesian co-location analysis was used to evaluate whether FFAR4 expression shares the same causal genetic variant with breast cancer in given genomic region.Results A total of 12 eQTLs closely related to FFAR4 expression levels were included in this study.The results of IVW analysis showed that increased FFAR4 expression levels increased the risk of overall breast cancer,Luminal A,Luminal B/HER2-negative,and HER2-enhanced subtypes of breast cancer.The co-location analysis showed that the posterior probability of FFAR4 expression level and total breast cancer shared causal variation was 0.889.Conclusion There may be a causal relationship between FFAR4 expression and breast cancer.

Objective Through visual analysis of literatures related to the treatment of chronic glomerulonephritis(CGN),the research hotspots and trends in this field were discussed.Methods Relevant literatures from CNKI,Wanfang Data Knowledge Service Platform,VIP,SinoMed,PubMed from 2010 to 2024 were retrieved,and analyzed using CiteSpace 6.2.R4 software.Results A total of 8887 articles in Chinese and 117 articles in English were included.The countries,institutions and authors who published most were China,the Affiliated Hospital for Liaoning University of Traditional Chinese Medicine and Wang Yiping.The research hotspots mainly focued on therapeutic drugs and clinical efficacy,and the research trend tended to be the treatment mechanism.Conclusion To further strengthen collaboration among different countries,institutions and authors,and to delve deeper into the mechanistic studies of CGN,will effectively promote the research progress in this field.

Objective:To characterize COVID-19-associated skin diseases and explore their influencing factors.Methods:A cross-sectional survey was conducted via the online platform Wenjuanxing in Changsha area from February 16, 2023, to March 16, 2023. The convenience sampling method was employed to conduct a survey of outpatients with a history of COVID-19 infection from the Second Affiliated Hospital of Hunan University of Chinese Medicine, as well as individuals in certain areas of Changsha who met the inclusion criteria for past COVID-19 infections. Demographic characteristics, COVID-19 infection details, and the occurrence of skin conditions after COVID-19 infection were collected. The chi-square test was used for inter-group comparisons of categorical data, and multivariate logistic regression analysis was performed to investigate factors associated with skin diseases following COVID-19 infection.Results:A total of 357 valid questionnaires were collected, and 357 patients with a history of COVID-19 infection were involved, including 246 females (68.9%) and 111 males (31.1%). Among these patients, 260 (72.8%) were aged ≤ 35 years. After COVID-19 infection, skin diseases occurred in 96 patients (26.9%), with urticaria (27 cases, 31.0%), rosacea (27 cases, 31.0%), hair loss (18 cases, 20.7%), and Henoch-Sch?nlein purpura (15 cases, 17.2%) being the most common diseases. Additionally, 96 patients (26.9%) had a history of pre-existing skin diseases, among whom 36 experienced exacerbation of their pre-existing skin diseases due to COVID-19 infection. Univariate analysis showed that gender, history of chronic diseases, history of allergic diseases, COVID-19 vaccination, duration of COVID-19 infection, and exacerbation of pre-existing skin diseases were significantly associated with the development of new skin diseases following COVID-19 infection (all P < 0.05). Multivariate logistic regression analysis revealed that gender (compared with females, males: OR = 0.235, 95% CI: 0.113, 0.490), history of allergic diseases (compared with patients without a history of allergic diseases, those with the history: OR = 2.159, 95% CI: 1.239, 3.761), and duration of COVID-19 infection (compared with the duration of < 5 days, duration of 6 - 7 days: OR = 3.043, 95% CI: 1.495, 6.193; duration of 8 - 14 days: OR = 2.364, 95% CI: 1.105, 5.506; duration of ≥ 15 days: OR = 4.406, 95% CI: 1.972, 9.849) were influencing factors for skin diseases after COVID-19 infection (all P < 0.05) . Conclusions:COVID-19 infection may lead to skin diseases such as urticaria, rosacea, hair loss, and Henoch-Sch?nlein purpura. Females, individuals with a history of allergic diseases, and those with a relatively long duration of COVID-19 infection were more prone to develop skin diseases after COVID-19 infection.

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.
Animals ; Mice ; RNA, Untranslated/metabolism* ; Aging/genetics* ; Mice, Transgenic ; Telomerase/metabolism* ; RNA/genetics* ; Hippocampus/metabolism* ; Humans ; Mice, Inbred C57BL