Objective To explore the functional impact of A-to-I editing in the seed region of miR-411 during post-myocardial infarction (MI) fibrosis and elucidate its therapeutic potential. Methods Integrating GEO database with myocardial RNA-seq data from MI mouse models, we identified dynamic A-to-I RNA editing in small noncoding RNAs across MI progression (1 day to 8 weeks post-MI). Four miRNAs exhibited differential editing rates between MI and controls, with miR-411 showing progressive editing enhancement at seed region position 4 (P＜0.01). This editing event was validated in both murine MI models and human heart failure specimens. Results The A-to-I editing ratio change of the 4th nucleotide in the seed region of miR-411 mainly occurs in cardiac fibroblasts rather than cardiomyocytes, and the editing at this site depends on ADAR2 rather than ADAR1. Edited miR-411 (ED-miR-411) diverged from wild-type miR-411 (WT-miR-411) in suppressing collagen-related pathways (extracellular matrix [ECM]-receptor interaction, collagen-containing ECM, ECM organization; P＜0.01) in cardiac fibroblasts. Mechanistically, dual-luciferase assays confirmed ED-miR-411 directly targeted the 3′UTR and suppressed expression of type Ⅱ transforming growth factor (TGF)-beta receptor (TGFBR2) and CD44, which were key drivers of TGF-β-mediated fibroblast activation. ED-miR-411 overexpression blunted TGF-β-induced collagen synthesis and myofibroblast proliferation (P＜0.05). In vivo, intramyocardial delivery of ED-miR-411 mimics at 1 week post-MI reduced fibrosis by 40% and improved ejection fraction by 15% (P＜0.01 vs controls), whereas WT-miR-411 showed no therapeutic effect. Conclusions A-to-I editing of miR-411 emerges as an endogenous anti-fibrotic mechanism by repressing TGFBR2 and CD44, thereby disrupting TGF-β signaling and ECM dysregulation. Our findings highlight ED-miR-411 as a novel RNA-based therapeutic candidate to mitigate post-infarction cardiac remodeling.

The repair of bone defects is heavily influenced by the dynamic osteogenic microenvironment. Static scaffolds constructed by traditional 3D printing technology cannot simulate the dynamic nature of the microenvironment during bone defect repair due to the fixed structure, uncontrollable release of active factors, and difficult regeneration of blood vessels, among other factors. Breaking through the limitations of these static scaffolds and realizing the intelligent and dynamic regulation of the osteogenic microenvironment is a key scientific issue in the field of bone tissue engineering. 4D printing technology combines the dynamic responsiveness of bone restoration materials with the concept of intelligent design to regulate the micro and macro structure of scaffolds. This technology provides a new method for bone tissue engineering by responding to endogenous and exogenous stimuli and creating a better osteogenic microenvironment through functionalized design, including drug delivery and antibacterial function. However, this technology currently suffers from challenges related to dynamic response material design, insufficient precision of printing technology, and mismatches between multi-stimulus response systems, metabolic rhythms of bone tissue, and functionalized composite scaffolds. Future research should focus on the development of smart response materials with excellent dynamic responses and bioactivity, the creation of new printing technologies, and the design of personalized and precise bone repair solutions. The aim of this paper is to review the current research status of 4D printing for bone tissue engineering in terms of material types, response mechanisms, and applications to provide a theoretical basis for the development and clinical application of functional bone repair materials in the future.

Histopathological examination is currently the gold standard for the diagnosis of metabolic associated fatty liver disease （MAFLD）； however， due to its invasiveness， high risks， and low feasibility， application of noninvasive indicators in the staging and classification of MAFLD has become a research hotspot. This article systematically reviews the efficacy of dynamic changes in various noninvasive markers in reflecting histological changes and clinical outcome events in MAFLD patients， in order to provide theoretical support for dynamic monitoring and individualized management of the disease.

Gastric ulcer （GU） is a high-incidence digestive system disease characterized pathologically by disruption of gastric mucosal integrity， with clinical features including a prolonged course and periodic recurrence. Modern medicine attributes its pathogenesis to the dynamic imbalance between aggressive and defensive factors，while traditional Chinese medicine （TCM） posits its development as closely linked to spleen deficiency. Current therapies combining acid suppressants and antibiotics face challenges such as high recurrence rates，poor mucosal healing，and adverse drug reactions. Long-term use may induce metabolic disturbances like hypergastrinemia and reduced intestinal microbiota diversity. Therefore，exploring safer and longer-lasting therapeutic strategies has become a critical focus. TCM has extensive clinical experience and unique advantages in GU prevention and treatment. Studies demonstrate that the classic formula Shenling Baizhu San exhibits therapeutic properties of "invigorating spleen and tonifying Qi to restore physiological balance and eliminating dampness and regulating middle energizer to unblock Qi movement"， enabling a holistic approach targeting both symptoms and root causes in GU with spleen deficiency as the core pathology by suppressing aggressive factors and strengthening defensive factors. Experimental research reveals its mechanisms involve enhancing the physicochemical barrier of the mucus layer，repairing epithelial barriers and microcirculation，modulating gastric acid secretion and gastrointestinal motility，and regulating microecological barriers and mucosal immunity. Clinical evidence confirms its synergistic effects in promoting ulcer healing，improving Helicobacter pylori eradication rates，and reducing recurrence risks. This review examined the etiology and pathogenesis of GU and systematically evaluated Shenling Baizhu San from three perspectives-clinical application，pharmacological effects， and experimental research-to provide insights for optimizing integrated traditional Chinese and Western medicine protocols and expanding its clinical applications.

Colorectal cancer is a common malignant tumor of the digestive tract. In recent years, with the advancement of surgical concepts and techniques, and remarkable achievements in basic value research and clinical transformation, the clinical treatment of colorectal cancer has made considerable progress. With the deepening application of the "precision medicine" concept, the transformation of the comprehensive diagnostic and therapeutic system for colorectal cancer is not only manifested in core aspects such as the optimization of preoperative neoadjuvant therapy regimens, precise selection of chemotherapy and targeted drugs, and intelligent upgrades of surgical decision-making systems, but also extends to the construction of prognostic prediction models and innovations in immunotherapy strategies. This marks the official entry of colorectal cancer diagnosis and treatment into the precision medicine era. Although surgery remains the cornerstone of colorectal cancer treatment, its potential limitations cannot be overlooked while pursuing therapeutic efficacy. With the continuous development of precision medicine theory and clinical practice, the concept of precision surgery has been integrated into various stages, including preoperative evaluation and adjuvant therapy. It provides critical support for determining surgical timing, formulating surgical plans, and optimizing intraoperative procedures, thereby reshaping the clinical paradigm of colorectal cancer management. Consequently, clinical surgeons must proactively acquire precision medicine expertise and actively engage in related research and clinical practice. The authors synthesize recent global research progress in precision diagnosis and treatment of colorectal cancer through literature review, combined with their team's clinical experience to forecast future developmental trajectories, aiming to provide valuable insights and practical references for surgical colleagues in this evolving field.

Colorectal cancer is a common malignant tumor of the digestive tract. In recent years, with the advancement of surgical concepts and techniques, and remarkable achievements in basic value research and clinical transformation, the clinical treatment of colorectal cancer has made considerable progress. With the deepening application of the "precision medicine" concept, the transformation of the comprehensive diagnostic and therapeutic system for colorectal cancer is not only manifested in core aspects such as the optimization of preoperative neoadjuvant therapy regimens, precise selection of chemotherapy and targeted drugs, and intelligent upgrades of surgical decision-making systems, but also extends to the construction of prognostic prediction models and innovations in immunotherapy strategies. This marks the official entry of colorectal cancer diagnosis and treatment into the precision medicine era. Although surgery remains the cornerstone of colorectal cancer treatment, its potential limitations cannot be overlooked while pursuing therapeutic efficacy. With the continuous development of precision medicine theory and clinical practice, the concept of precision surgery has been integrated into various stages, including preoperative evaluation and adjuvant therapy. It provides critical support for determining surgical timing, formulating surgical plans, and optimizing intraoperative procedures, thereby reshaping the clinical paradigm of colorectal cancer management. Consequently, clinical surgeons must proactively acquire precision medicine expertise and actively engage in related research and clinical practice. The authors synthesize recent global research progress in precision diagnosis and treatment of colorectal cancer through literature review, combined with their team's clinical experience to forecast future developmental trajectories, aiming to provide valuable insights and practical references for surgical colleagues in this evolving field.

Objective To evaluate the modeling characteristics and predictive performance of models for predicting post-stroke neurological deterioration(ND)published in existing literatures.Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidance for scoping reviews,a comprehensive search was conducted in PubMed,CINAHL,Cochrane Library,Embase,Web of Science,Scopus,CNKI,Wanfang Data,and VIP databases from inception to December 15,2024.The search strategy combined Medical Subject Headings(MeSH)and free-text terms,with key words including"Stroke""Ischemic Stroke""Neurological Deterioration""Nomograms""Risk Prediction""Predictive Models""卒中""脑梗死""脑出血""神经功能恶化"and"预测模型".Base on the data extraction checklist and critical appraisal,data extraction covered three domains:(1)basic characteristics,including author,publication year,country,study design(retrospective,prospective,registry-based),sample source(single-center,multicenter),stroke subtypes(acute ischemic stroke[AIS]-conservative therapy,AIS-intravenous thrombolysis[IVT],AIS-endovascular therapy[EVT],intracerebral hemorrhage[ICH]),ND time windows(acute[≤72 h],subacute[≤ 7 d],long-term[≤90 d]),and outcome types(single/composite endpoints);(2)model evaluation metrics,including missing data handling(complete-case analysis,multiple imputation),model development methodologies(multivariate Logistic regression,least absolute shrinkage and selection operator regression,machine learning),presentation formats(nomograms,web calculators,risk prediction tool),discrimination(area under the curve,C-index),calibration(Hosmer-Lemeshow test,calibration curve and slope),clinical utility(decision curve analysis[DCA],global metrics Brier score,R2,AIC),sample size(training set,internal validation set,external validation set),sample size requirements(events per variable[EPV]≥10 to mitigate overfitting),and validation(internal/external);(3)predictor features,including selection strategies(prior knowledge-driven,univariate analysis),quantity,and attributes(demographics,medical history,physical examination,treatment intervention information,imaging/laboratory indicators).Predictive models that meet exclusion criteria from prior literature were analyzed by their discrimination,calibration,clinical utility and global metrics.Forest plots were utilized to visualize discrimination(evaluated via difference in area under the curve)of the extracted models.The prediction model risk of bias assessment tool(PROBAST)was applied to assess bias risk and clinical applicability.Occurrence frequencies of the post-stroke neurological deterioration predictors were ranked and the top 6 high-frequency predictors were extracted.Results(1)Among 3 728 screened studies,25 were included based on the inclusion and exclusion criteria.(2)Basic characteristics:retrospective(72％[18/25])and single-center(64％[16/25])designs dominated.With most models targeted on AIS(92％[23/25]),and the rest(8％[2/25])on ICH.ND was primarily defined by neurological scale changes(60％[15/25];e.g.,National Institutes of Health stroke scale[NIHSS]score increase or Glasgow coma scale[GCS]score decrease),with time windows categorized as acute(36％[9/25]),subacute(48％[12/25]),or long-term(16％[4/25]).(3)Model evaluation:multivariate Logistic regression(96％[24/25])and nomograms(88％[22/25])were predominant.Only 24％(6/25)explicitly addressed missing data handling methods,and 52％(13/25)with EPV≥10.The median area under the curve was 0.865(range:0.650-0.981).44％(11/25)of the studies reported calibration curves,and 4％(1/25)reported calibration slopes.All studies utilized DCA to validate their clinical applicability,84％(21/25)of the studies conducted internal validation,while only 32％(8/25)conducted external validation.PROBAST evaluation revealed low overall bias risk in 8％(2/25;no error across participant,predictor,outcome,or analysis domains)and low clinical applicability risk in 44％(11/25;alignment with target populations,accessible predictors,and clinically relevant outcomes)of the studies.(4)Predictors:64％(16/25)of the predictor were screened predominantly through the prior knowledge-driven based strategy.The top 6 high-frequency predictors are NIHSS score(64％[16/25]),age(36％[9/25]),blood glucose/diabetes(36％[9/25]),blood pressure/hypertension(32％[8/25]),the Alberta stroke program early CT score(20％[5/25]),and neutrophil-to-lymphocyte ratio(20％[5/25]).AIS-ND predictors emphasized readily available metrics,such as NIHSS(65％[15/23]),age(35％[8/23]),while ICH-ND primarily relied on imaging markers(e.g.,baseline hematoma volume[2/2],location[1/2]).Conclusion Current post-stroke ND predictive models demonstrate satisfactory performance on discrimination and multimodal integration,but their practical application are hindered by insufficient calibration quantification,high bias risk,and limited clinical translatability.

This article reports the diagnosis and treatment process of a case with secondary infective femoral artery pseudoaneurysm after intervention surgery for cerebral infarction,who improved after anti-infection and surgical treatment and was discharged.The patient was a 52-year-old female who underwent percutaneous balloon dilatation of basilar artery due to basilar artery stenosis.After surgery,she developed secondary methicillin-resistant Staphy-lococcus aureus(MRSA)bloodstream infection and infective femoral artery pseudoaneurysm.After treatment with vancomycin and linezolid,femoral artery pseudoaneurysm resection,and autovascular replacement,the patient re-covered well after the surgery and discharged from hospital.CT angiography(CTA)re-examination showed artifi-cial blood vessel patency.This study is expected to provide experience for the diagnosis and treatment of such pa-tients in clinical work.

Pulmonary siderosis caused by iron and its compound dust is prone to misdiagnosis and underdiagnosis due to its insidious exposure pathways and non-specific imaging manifestations. This study analyzes the occupational histories and clinical data of six patients with occupational pulmonary siderosis diagnosed at Qingdao Central Hospital between January 2017 and December 2023, summarizes its characteristics, and evaluates the value of AI-assisted diagnosis. All six patients were male, with five being welders. The median dust exposure duration was 9.4 years, and the median latency period was 8.4 years. The main symptoms were chest tightness, cough, and shortness of breath. High-kilovolt chest radiographs were negative in four cases and showed thickened bronchovascular markings in two cases. High-resolution computed tomography (HRCT) revealed centrilobular nodules and tree-in-bud opacities in all cases. Pulmonary siderosis caused by iron and its compound dust is characterized by mild symptoms and a favorable prognosis. Comprehensive assessment and HRCT are crucial for early diagnosis. The development of AI models could enhance diagnostic recognition efficiency and promote precision diagnosis in the future.

Objective:To investigate the efficacy of a decellularized extracellular matrix (dECM)-quaternized chitosan (QCS)-gelatin (Gel) composite scaffold loaded with growth factors in repairing diabetic foot wounds in a rat model.Methods:A dECM-QCS-Gel composite scaffold (referred to as GDQ scaffold) was fabricated using a 3D bioprinter. Forty 8-week-old male Sprague-Dawley (SD) rats were selected to establish a diabetic foot wound model with a diameter of approximately 1 cm. Based on the treatment methods for diabetic foot wounds, the rats were divided into five groups: Control group (no treatment), Exosome group (wound covered with exosome suspension), Exosome+GDQ group (wound covered with GDQ scaffold loaded with exosome suspension), GDQ group (wound covered with GDQ scaffold alone), and Growth factor+GDQ group (wound covered with GDQ scaffold loaded with recombinant human basic fibroblast growth factor suspension). The wound healing rate was measured. Histological analysis was performed by HE staining and Masson staining. ELISA kits were used to determine the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6, and IL-10 in wound tissues from each group. Protein expression levels of MIP-1 and MIP-2 genes were also assessed.Results:The wound healing rate of the growth factor+GDQ group on the 21st d was 94.89%±1.21%, which was higher than that of the exosome+GDQ group ( P<0.05). With increasing repair time, the expression levels of TNF-α, IL-1β and IL-6 in each group all decreased, while IL-10 increased in all groups ( P<0.05). Among them, the exosome+GDQ group (TNF-α: 46.54±1.26 pg/ml, IL-1β: 225.79±7.29 pg/ml, IL-6: 142.81±4.02 pg/ml and IL-10: 117.36±0.95 pg/ml, P<0.001) and the growth factor+GDQ group (TNF-α : 40.01±1.64 pg/ml, IL-1β: 209.15±2.98 pg/ml, IL-6: 138.50±2.61 pg/ml and IL-10: 127.66±1.23 pg/ml, P<0.05); The levels of TNF-α and IL-1β in the exosome+GDQ group were both lower than those in the exosome+GDQ group ( P<0.05), and IL-10 was higher than that in the exosome+GDQ group ( P<0.05). On the 7th d the control group showed the highest expression levels of MIP-1α and MIP-2. All other groups had lower levels, with the growth factor+GDQ group showing the lowest among them. On the 21st d, the inflammatory protein expression in the growth factor+GDQ group had further decreased and remained lower than in all other experimental groups. Conclusions:The GDQ composite scaffold, when combined with bioactive factors, can synergistically reduce inflammation in diabetic foot wounds and promote wound healing. The scaffold loaded with basic fibroblast growth factor demonstrated superior therapeutic efficacy compared to the scaffold loaded with exosomes.