Diabetic retinopathy(DR)is one of the most common and serious microvascular complications of diabetes, posing a significant threat to patients' visual health. In recent years, epigenetic mechanisms have garnered increasing attention in the scientific community for their pivotal role in the onset and progression of DR. This paper systematically examines the regulatory roles of epigenetic mechanisms in DR, covering key pathways such as DNA methylation, histone modifications, chromatin remodeling, and non-coding RNAs. Under hyperglycemic conditions in diabetes, these epigenetic mechanisms modulate gene expression, thereby influencing critical pathological processes such as oxidative stress, inflammatory responses, mitochondrial dysfunction, and metabolic memory. This article reviews recent advances in epigenetic regulation in DR, providing an in-depth analysis of its underlying molecular mechanisms and complex regulatory networks, and explores the potential of epigenetic markers as diagnostic biomarkers and therapeutic targets. Additionally, this article highlights emerging therapeutic strategies targeting epigenetic modifications, aiming to provide a theoretical foundation and research direction for the early diagnosis and precision treatment of this disease.

In the period of digital transformation of the medical service model， maintaining algorithm justice for medical artificial intelligence possesses multiple value implications. However， practical dilemmas exist at different stages of achieving this value goal. At the initial stage of diagnosis and treatment decision-making， there is a risk of imbalance in patients’ rights and interests， such as weakened effectiveness of patients’ right to informed consent， as well as low synergy between rights and interests protection and technological innovation. In the process of diagnosis and treatment decision-making， the algorithmic model is constrained by the technological bottleneck in the underlying application， deviating from the legal track of technological neutrality. After the diagnosis and treatment decision-making is generated， it triggers a crisis in the remedy of patients’ rights and interests and breeds the phenomenon of an ambiguous definition of subject qualification and attribution principle. In this regard， it is essential to establish a preemptive safeguard system focusing on the protection of patients’ rights and interests， set technological fairness standards， and shape review norms of technological neutrality. The aim is to ensure the equalization of remedy channels for patients’ rights and interests， promote the fairness in the proportion of responsibilities among multiple subjects， and thereby safeguard the digital justice in the field of intelligent diagnosis and treatments.

Objective: To verify the inhibitory effect of a carbon monoxide hemoglobin-based oxygen carrier (CO-HBOC) on the fibrotic process in mice with idiopathic pulmonary fibrosis (IPF), clarify its efficacy difference compared with hemoglobin-based oxygen carriers (HBOCs), and elucidate its mechanism of action via proteomic analysis. Methods: CO-HBOC was prepared using gas loading technology. An IPF mouse model was established and the mice were randomly divided into a normal saline control group, an HBOC treatment group, and a CO-HBOC treatment group. The fibrotic area percentage was analyzed using Micro-CT; the degree of inflammatory infiltration and fibrosis in lung tissue was assessed by pathological section staining (e.g., HE and Masson staining); and differentially expressed proteins in lung tissue of IPF mice after CO-HBOC treatment were screened using proteomic technology. Results: Micro-CT results showed that the mean fibrotic area percentage in the CO-HBOC treatment group on day 21 was (8.89±0.98)%, which was better than that of the HBOC group (16.5±1.732)% and the normal saline group (30.75±6.45)% (P<0.05). HE and Masson staining results showed that the CO-HBOC group had reduced inflammatory cell infiltration and significantly decreased collagen fiber deposition in lung tissue, with a mean pathological score of 3.33±0.58, which was lower than that of the normal saline control group (8.33±1.53)(P<0.05); the mean collagen-positive area percentage was (3.33±1.53)%, significantly lower than that of the normal saline control group (14.00±3.61)% (P<0.05). Proteomic analysis identified 330 differentially expressed proteins, which were mainly enriched in inflammatory response regulatory pathways (such as the complement and coagulation cascades), and the expression changes of complement proteins may be the core target of CO-HBOC's anti-fibrotic effects. Conclusion: CO-HBOC can inhibit inflammatory responses and regulate fibrosis-related signaling pathways, there-by effectively inhibiting the fibrotic process in IPF mice, with superior efficacy to HBOC. Its mechanism of action involves the regulation of complement cascade-related signaling pathways and complement protein expression, providing an experimental and theoretical basis for targeted therapy of IPF.

Background Air pollution remains a critical public health issue, with persistent exposure to air pollutants continuing to pose significant health risks. Currently, research investigating the association between air pollution and myocardial infarction mortality in Shenzhen remains inadequate. Objective To quantitatively assess the association between air pollutants and myocardial infarction mortality in residents. Methods Based on the mortality surveillance system of Shenzhen Center for Disease Control and Prevention, we conducted a time-stratified case-crossover study of 10089 permanent residents who died from myocardial infarction in Shenzhen between 2013 and 2022. Using residential address information, we obtained individual-level exposure data for air pollutants from the China High Air Pollutants dataset and meteorological factors from the China Meteorological Administration Land Data Assimilation System. A time-stratified case-crossover study design was employed to construct a conditional logistic regression model to assess the association between short-term exposure to air pollutants and myocardial infarction mortality. The exposure-response relationship was visualized, and a comprehensive health risk assessment was performed. Results This study included a total of 10 089 cases of myocardial infarction deaths in Shenzhen. The median [interquartile range (IQR)] concentrations of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) in Shenzhen from 2013 to 2022 were 24.59 (20.19) μg·m⁻³, 42.85 (28.42) μg·m⁻³, 8.53 (3.39) μg·m⁻³, 29.47 (13.56) μg·m⁻³, 0.77 (0.27) mg·m⁻³, and 86.53 (51.39) μg·m⁻³, respectively. The moving average concentrations of PM_2.5 and PM₁₀ over the current day and the previous 2 days (lag02) showed the highest risk of myocardial infarction mortality, with an odds ratio (OR) and 95% confidence interval (95%CI) of 1.004 (1.001, 1.007) and 1.004 (1.002, 1.006), respectively. At lag05, SO₂ demonstrated the strongest association with the risk of myocardial infarction mortality, with an OR (95%CI) of 1.042 (1.019, 1.065). The exposure-response relationships of PM_2.5, PM₁₀, and SO₂ with myocardial infarction mortality were approximately linear, whereas NO₂ exhibited a nonlinear relationship. At lag05, the highest risk of myocardial infarction mortality associated with NO₂ exposure was observed when the NO₂ concentration was ≤21.92 μg·m⁻³, with an OR (95% CI) of 1.024 (1.003, 1.046). The health risk assessment indicated that, using the WHO Air Quality Guidelines as the reference, the local PM_2.5 and NO₂ exposure led to an excess mortality of 398 and 298 cases, respectively. The sensitivity analysis revealed that after adjusting for O₃ and restricting the study period to 2013—2019, the effect estimates for PM_2.5, PM₁₀, NO₂, and SO₂ on myocardial infarction mortality slightly increased. Conclusion Short-term exposure to air pollutants, including PM_2.5, PM₁₀, NO₂, and SO₂, could increase the risk of myocardial infarction mortality. This study provides important scientific evidence for environmental health risk assessment and environmental management in Shenzhen.

Knowledge graphs have been more popular in the medical industry in recent years due to the development of big data analysis technologies.Information reflecting a range of physiological markers of patients is gathered in laboratory medicine,which forms an essential basis for clinical decision-making.Knowledge graphs could uncover the hidden value in inspection and consequently furnish accurate inspection data.Knowledge graphs are currently used in laboratory medicine to forecast possible adverse drug responses,help with diagnosis,integrate historical trends of patient laboratory inspections,and identify correlations across detection projects.The interaction between inspection items,auxiliary diagnosis,and medication guidance are three angles from which the use of knowledge graphs in laboratory medicine is analyzed and evaluated.Further support the intelligent construction of clinical laboratory diagnosis,it is also suggested that the development of test medical knowledge graphs extend in the direction of semantic search,decision support,and intelligent question answer.

At present, liver transplantation is the most effective method for the treatment of various end-stage liver diseases, and electronic health technology is a new medical service model, which can be used as an efficient and cost-effective alternative to the health management of liver transplant recipients. This paper summarizes the application of electronic health technology in postoperative health management of liver transplant recipients, including applications, robots, video conferencing, tablet computers, text messages, telephones and wearable devices, etc., summarizes the implementation effect of electronic health technology in health management of liver transplant recipients, and analyzes the limitations of research and application at the present stage. In order to provide basis and reference for Chinese medical staff to carry out electronic health technology in the health management of liver transplant recipients.

Thyroid nodules are a common endocrine disorder with complex pathogenesis that remains incompletely understood. In recent years, studies have revealed that the gut microbiota may play a critical role in the occurrence and progression of thyroid nodules. This review systematically summarizes the current research progress on the association between gut microbiota and thyroid nodules, with a particular focus on potential mechanisms through which gut dysbiosis influences nodule formation via immune regulation, metabolic pathways, and gut barrier function. Evidence suggests that reduced gut microbial diversity, decreased abundance of specific beneficial bacteria, and an increased proportion of pro-inflammatory bacteria may contribute to a pro-inflammatory environment and metabolic disturbances associated with thyroid nodules. Furthermore, this review explores the potential of interventions such as probiotics, prebiotics, dietary modifications, and fecal microbiota transplantation in modulating gut microbiota and improving thyroid nodule outcomes. Although direct clinical evidence is currently lacking, the regulation of gut microbiota has emerged as a promising direction for the diagnosis and treatment of thyroid nodules, demonstrating significant clinical potential. Future efforts should focus on advancing basic and clinical research strategies to facilitate the translational application of findings in this field.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

BACKGROUND:Metformin is currently considered the first-line medication for the treatment of type 2 diabetes.Metformin may delay the progression of osteoarthritis,but its specific mechanism of action remains unclear.OBJECTIVE:To evaluate the therapeutic effects and the related action mechanisms of metformin on osteoarthritis in rats.METHODS:(1)Network pharmacology:Potential common targets for metformin,osteoarthritis,and ferroptosis were screened using the CTD,SwissTargetPrediction,GeneCards,and OMIM databases.After importing the targets into the STRING database,protein-protein interaction analysis was conducted to identify the key targets for metformin,osteoarthritis,and ferroptosis.(2)Molecular docking:P53 and its downstream factor SLC7A11 protein structures in PDB format were downloaded from the PDB database.The 2D structure of metformin was converted to a 3D structure,and molecular docking of metformin with the proteins was performed using Discovery Studio 2019 Client.(3)In vivo experiments:Thirty male SD rats were randomly divided into three groups(n=10).The blank group did not receive surgery.The osteoarthritis model was established using the modified Hulth method for the model and metformin groups.One day after the surgery,rats in the metformin group were gavaged with metformin 200 mg/kg per day,while the blank and model groups were gavaged with physiological saline.Treatment continued for 4 weeks.Hematoxylin-eosin staining and Safranin O-fast green staining were used to observe the pathological morphology and structure of the knee cartilage,and Mankin scoring was performed.ELISA was used to measure the levels of tumor necrosis factor-α and interleukin-6 in the serum.The microplate method was used to measure serum ferroptosis-related indicators,including glutathione,malondialdehyde,and Fe2+.Immunofluorescence staining,western blot assay,and real-time qPCR were used to detect the protein and mRNA expression of P53,SLC7A11,glutathione peroxidase 4,proteoglycans,and matrix metalloproteinase 13 in the cartilage tissue of the rats.RESULTS AND CONCLUSION:(1)A total of 96 intersecting targets among metformin,osteoarthritis,and ferroptosis were identified.After protein-protein interaction analysis,77 potential targets were found.Further screening identified the core targets as TP53,AKT1,JUN,interleukin-6,MYC,interleukin-1β,and tumor necrosis factor-α,among others.(2)Docking analysis results showed that metformin bound strongly and stably with P53 and its downstream factor SLC7A11.(3)In the model group,the knee cartilage surface was irregular,with cartilage tissue defects and reduced chondrocyte numbers.Compared to the model group,the knee cartilage structure damage in the metformin group was significantly improved,with a smoother cartilage surface and increased chondrocyte numbers.The Mankin score in the model group was significantly higher than that in the blank group,while the Mankin score in the intervention group was significantly lower than that in the model group.(4)Compared with the model group,the metformin group had significantly lower levels of tumor necrosis factor-α,interleukin-6,malondialdehyde,and Fe2+,and significantly higher glutathione levels.(5)Compared to the model group,the metformin group had significantly increased protein and mRNA expression of SLC7A11,glutathione peroxidase 4,and proteoglycans,and significantly decreased protein and mRNA expression of P53 and matrix metalloproteinase 13 in their cartilage tissue.(6)The results indicate that metformin can effectively improve cartilage damage in osteoarthritis rats and alleviate chondrocyte ferroptosis by inhibiting the aberrantly activated P53/SLC7A11/glutathione peroxidase 4 signaling pathway.This improvement in chondrocyte iron metabolism and lipid peroxidation response further reduces cartilage matrix degradation and prevents further cartilage damage and inflammatory response.

Prostate cancer is one of the most common male urological malignancies,in which bone metastasis of desmo-plasia-resistant prostate cancer is an important stage in the progression of the disease,which seriously affects the quality of life and survival of patients.With the development of nuclide therapy technology in recent years,223-Ra,as a new type of alpha-targeted therapy,has shown good efficacy in the treatment of desmoplasia-resistant prostate cancer bone metastasis.The purpose of this pa-per is to review the characteristics,mechanism of action,treatment,and the main research results of its treatment of desmoplasia-resistant prostate cancer bone metastasis,and provide a comprehensive review of the clinical application of 223-Ra in the treatment of desmoplasia-resistant prostate cancer bone metastasis for the clinical application of 223-Ra in prostate cancer bone metastasis.