Objective To investigate the role and regulatory mechanism of LINC00657 in the progression of cervical cancer. Methods Bioinformatics analysis predicted potential binding sites between LINC00657 and miR-30a-5p and between miR-30a-5p and Skp2. These sites were verified by using RNA immunoprecipitation and dual-luciferase reporter experiments. LINC00657, miR-30a-5p, and Skp2 mRNA expression levels in cervical cancer tissues and cell lines were assessed by utilizing RT-qPCR. Western blot analysis was employed to examine the protein levels of Skp2 in cells and subcutaneous xenograft tumor models in nude mice. Immunohistochemistry was applied to analyze Skp2 expression in animal tissues. The cellular processes of cervical cancer cell lines were evaluated through CCK-8, scratch, and Transwell assays. Results LINC00657 and Skp2 presented binding sites for miR-30a-5p. In cervical cancer, LINC00657 and Skp2 showed high expression levels (P<0.05), whereas miR-30a-5p displayed low expression (P<0.05). Functional experiments demonstrated that linc00657 upregulates Skp2 expression, a process that is dependent on its sequestration of miR-30a-5p. Conclusion LINC00657 promoted the malignant progression of cervical cancer by upregulating Skp2 expression through specifically sequestering miR-30a-5p, thereby relieving its inhibitory effect on the target gene Skp2.

Diabetic retinopathy(DR)remains the leading cause of vision loss in patients with diabetes. Current anti-vascular endothelial growth factor(VEGF)therapies are limited by inadequate response in some patients and the necessity for repeated intravitreal injections, underscoring the urgent need for novel therapeutic targets. Angiopoietin-like protein 4(ANGPTL4), a multifunctional secreted protein, has emerged as a critical regulator in the pathogenesis and progression of DR, positioning it as a promising interventional target. This review systematically elaborates the biological characteristics of ANGPTL4, with a focus on its expression dynamics, molecular mechanisms, and regulatory networks rolesin the development of DR. Furthermore, the prospects of ANGPTL4-targeted therapeutic strategies are discussed, aiming to offer new insights and directions for understanding DR pathogenesis, advancing multi-target drug development, and improving clinical management.

Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease mediated by T lymphocytes， and it can progress to liver cirrhosis or even liver failure without timely intervention. As a natural flavonoid compound， naringenin （NAR） shows a potential value in the prevention and treatment of AIH through multiple mechanisms such as remodeling immune homeostasis， targeted inhibition of inflammatory pathways， antioxidation， regulating hepatocyte metabolism and apoptosis， improving mitochondrial function， and regulating intestinal flora. However， the clinical translation and application of NAR is limited by issues such as low bioavailability and insufficient efficiency of liver-targeted delivery. This article systematically reviews the mechanism of action of NAR in the prevention and treatment of AIH， explores the potential signaling pathways involved in this process， and analyzes existing challenges in its translation and application and future research directions， so as to provide a reference for further research on NAR and its application in the prevention and treatment of AIH.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Objective To analyze the chest computed tomography (CT) imaging features of occupational pneumoconiosis induced by dust of iron and iron compounds (OPTIDIC), and to explore imaging evidence for its diagnosis and differential diagnosis. Methods Abnormal coronal multiplanar reconstruction CT images of 19 patients with OPTIDIC were analyzed retrospectively, and imaging findings were compared with those from chest digital radiography (DR). Results Chest CT imaging of 19 patients with OPTIDIC showed multiple small, round opacities in both lungs, with predominantly low-density nodules in 14 cases, and high-density nodules in five cases. Nodules were mainly distributed in the upper and middle lung zones in 15 cases and diffusely distributed in four cases. Hilar/mediastinal lymphadenopathy and lymph node calcification were observed in 11 and 6 cases, respectively. Interlobular septal thickening was observed in six cases, while reticular opacities, increased lung markings, patchy ground-glass opacities, pleural thickening, and emphysema were observed in 6, 4, 7, 5, and 4 cases, respectively. On chest DR, small opacities were classified as p/s and p/t types in 16 and 3 cases, respectively. No large opacities or honeycombing were observed on either coronal chest CT or chest DR among 19 patients with OPTIDIC. Conclusion Chest CT findings of OPTIDIC patients are characterized by small, low-density round opacities, with a predominance in the upper and middle lung zones and frequent hilar and mediastinal lymphadenopathy. CT provides valuable evidence for the diagnosis and differential diagnosis of OPTIDIC.

OBJECTIVE To construct a risk prediction model for nonattainment plasma concentration of zonisamide in children with epilepsy， and to provide evidence for individualized dosing.METHODS Children with epilepsy who received standardized zonisamide treatment orally in Kunming Children’s Hospital were retrospectively selected as research subjects. Those treated from May 2022 to May 2024 were included in the modeling cohort， and those treated from June 2024 to January 2025 were included in the external validation cohort. According to plasma concentration， children were divided into therapeutic group and nonattainment group. Independent influencing factors for nonattainment plasma concentration of zonisamide were screened by collinearity diagnosis， univariate analysis， Lasso regression and random forest， based on which a nomogram risk prediction model was constructed and validated. Finally， the Shapley additive explanations （SHAP） method was used to interpret the features of the nomogram risk prediction model.RESULTS A total of 945 children with epilepsy were included in this study. There was no statistically significant difference in baseline data between the modeling cohort （531 cases） and the external validation cohort （414 cases） （ P ＞0.05）， indicating comparability. Through multi-stage feature screening， seven influencing factors were finally included to construct the prediction model， namely gender， age， dosage， aspartate transferase， total bilirubin， uric acid and vitamin D. The corrected area under the curve of the model was 0.799 in the modeling cohort and 0.762 in the external validation cohort， showing good calibration and clinical applicability. SHAP analysis showed that gender， dosage， total bilirubin， age and aspartate transferase were the top five important variables affecting model prediction.CONCLUSIONS The nomogram risk prediction model for nonattainment plasma concentration of zonisamide constructed in this study has stable predictive performance. Clinically， the risk of nonattainment plasma concentration can be quickly assessed by combining the child’s gender， age， dosage， liver and kidney function， and vitamin D， and the dosing regimen can be adjusted in time.

Objective To investigate the causes and management strategies for lower limb ischemic necrosis following xenogeneic heterotopic heart transplantation from a multigene-edited pig to a rhesus monkey. Methods A xenogeneic heterotopic heart transplantation was performed on December 16, 2023, at the Institute of Experimental Animals of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, using a quintuple-gene-edited pig as the donor and a rhesus monkey as the recipient. On postoperative day (POD) 9, the recipient monkey underwent left lower limb amputation due to ischemic necrosis. Blood samples were collected at various time points after transplantation for analysis of hematologic parameters, liver and renal function, myocardial enzymes, and coagulation profiles. Ultrasound and computed tomography (CT) were used to evaluate anastomotic patency and cardiac structure. Immunological assays, including complement-dependent cytotoxicity (CDC) and IgG/IgM antibody detection, combined with clinical observations, were employed to assess rejection type and therapeutic response. Results The recipient monkey survived for 46 days after transplantation. Echocardiography demonstrated preserved biventricular systolic function in the recipient’s native heart, with left ventricular ejection fraction (LVEF) consistently exceeding 50%. In the donor pig heart, left ventricular endocardial thickening was noted on POD 9, followed by right ventricular endocardial thickening on POD 24, while LVEF remained around 35%. No hyperacute or acute rejection was detected immunologically. CDC positivity ranged between 3.4% and 5.1%, with IgG/IgM antibody binding trends consistent with CDC results. Following amputation, the recipient exhibited elevated inflammatory markers, coagulopathy, and reactive thrombocytosis, which later normalized. Immunohistochemical staining of the necrotic limb revealed arterial and venous thrombosis; however, no T-cell or B-cell infiltration was observed in vascular structures, thrombi, nerves, muscles, fascia, or skin tissues, with CD3 and CD20 staining both negative. Conclusion Limb ischemia after xenogeneic heart transplantation may be associated with lower extremity vascular thrombosis triggered by local trauma in the context of transplantation-induced inflammatory activation and coagulation dysfunction. While no clear lymphocyte-mediated rejection was observed, further studies are needed to explore the potential role of non-lymphocyte-mediated immune mechanisms.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become the most common chronic liver disease worldwide. Its pathological process is centered on the “two-hit” theory， with gut-liver axis dysregulation running through the entire disease course from steatosis to liver cirrhosis and even hepatocellular carcinoma， and it forms an extensive cross-system regulatory mechanism with the metabolic， cardiovascular， renal， and psychological and nervous systems through multi-dimensional pathways such as the “gut-liver-brain axis”， the “liver-kidney axis”， and the “liver-heart axis”. Disease progression is not limited to the liver itself， and it also involves functional imbalance of multiple organ systems throughout the body. This article systematically elaborates on the association mechanism of “liver pathological progression-multi-axis regulation-comorbidity occurrence” in MAFLD， proposes synergistic management strategies integrating early screening based on risk stratification， targeted intervention， and multidisciplinary diagnosis and treatment， and analyzes the limitations of current research and future development directions， in order to provide a theoretical basis and practical guidance for precise diagnosis and treatment and individualized management of MAFLD.

Background: Visual impairment is increasingly prevalent, underscoring the need for effective prevention strategies. This study investigated the association between cardiovascular health and visual impairment using three progressively developed metrics: Life’s Simple 7 (LS7), a cardiovascular health score developed by the American Heart Association based on 7 components, including physical activity, smoking status, body mass index (BMI), diet, blood glucose, blood pressure, and total cholesterol; Life’s Essential 8(LE8), which adds sleep health as an additional component; and Life’s Crucial 9 (LC9), which further incorporates mental health. We aimed to evaluate whether these expanded metrics provide additional explanatory value and to inform future public health strategies. Objective: To investigate the associations among LS7, LE8, and LC9 cardiovascular health scores and visual impairment in National Health and Nutrition Examination Survey 2013 to 2018, assess the added value of sleep and mental health components, and identify key contributing subcomponents using regression and machine learning methods. Methods: We analyzed data from 9891 participants in the 2013 to 2018 National Health and Nutrition Examination Survey. Multivariable logistic regression, restricted cubic spline modeling, and subgroup analyses were conducted to evaluate the association between cardiovascular health and visual impairment. Machine learning methods, including Random Forest and SHapley Additive exPlanations, a model interpretation approach used to assess feature importance, were applied. The Boruta algorithm, a feature selection method, was used to identify key subcomponents of cardiovascular health. Results: Participants with visual impairment were older, had lower poverty-to-income ratios, and exhibited lower cardiovascular health scores (LS7, LE8, and LC9). Higher cardiovascular health scores were negatively associated with visual impairment. Each one standard deviation increase in LS7, LE8, and LC9 was associated with approximately 8%, 2%, and 3% lower odds of visual impairment, respectively. LS7 showed the strongest negative association, whereas LE8 and LC9 emerged as the most important predictors in the machine learning models. Key subcomponents such as blood glucose, blood pressure, and BMI, as well as mental health status, were strongly associated with visual impairment. Conclusion: Higher cardiovascular health scores were negatively associated with visual impairment. LS7 demonstrated the strongest statistical association, whereas LE8 and LC9 were the most influential features in the machine learning models. Blood glucose, blood pressure, BMI, and mental health status were important correlates of visual impairment. From the perspective of the “prevention and treatment of diseases” in traditional Chinese medicine and the holistic concept, the aforementioned research findings confirm that severe visual impairment is indeed an external manifestation of overall health imbalance (such as organ dysfunction and Qi deficiency and blood stasis). The prevention strategy lies in comprehensively adjusting lifestyle, emotional factors, and metabolic indicators (corresponding to the key factors in the study) to restore the body’s internal balance and achieve prevention before disease arises.