BACKGROUND: Chronic kidney disease (CKD) is a progressive disorder that leads to significant structural and functional changes in the kidneys, posing a major global health concern and contributing to high mortality rates. METHODS: The urgent need for innovative treatments is evident. Mesenchymal stem cells (MSCs) are well-regarded in regenerative medicine for their ability to repair tissue and modulate immune responses. Emerging research indicates that the therapeutic benefits of MSCs are largely mediated by the secretion of extracellular vesicles (EVs), particularly exosomes (MSC-Exos), which replicate the effects of MSCs by delivering genetic materials and proteins to target cells. RESULTS: MSC-Exos are novel natural carriers for targeted gene or drug delivery, offering biocompatibility, intrinsic targeting capabilities, and bioactive cargo to modulate recipient cells. They represent a groundbreaking platform for precision medicine, enhancing therapeutic efficacy with minimal immunogenicity and off-target effects. Moreover, embedding exosomes within hydrogels has emerged as a promising strategy to maintain their biological activity and enable a controlled release. CONCLUSION This review explores the roles of MSC-Exos in CKD pathophysiology, highlights the renoprotective effects of MSC-Exos for various sources, and provides a comprehensive overview of how hydrogel biomaterials present a promising approach for integrating exosomes to enhance therapeutic outcomes. The use of hydrogels to encapsulate exosomes improves their sustained release and stability in diseased kidney tissues, providing an innovative strategy to enhance precision therapies.

Background: Cerebral hypoxia-ischemia impairs brain development in extremely preterm infants and is associated with poor neurological outcomes. Near-infrared spectroscopy (NIRS) is a noninvasive continuous monitoring method for regional cerebral oxygen saturation (rcSO2).Purpose: This study evaluated the clinical feasibility and neurological impact of a neurocritical care bundle that incorporates prolonged multidisciplinary hemodynamic monitoring and a stepwise management algorithm. Methods: Preterm infants with a gestational age (GA) ≤28 weeks or birth weight (BW) ≤1,000 g were prospectively enrolled in a bundle group subjected to NIRS for rcSO2, electrical cardiometry for cardiac output, and daily brain and cardiac echography during the first 72 hours of life. Monitoring was repeated weekly in the first month and then monthly until discharge or the term-equivalent age (TEA) was reached. We implemented a stepwise management algorithm for treating cerebral hypoxia. The primary outcome was a composite of mortality and adverse neurological events (structural abnormalities or electroencephalogram-confirmed seizures) before discharge. The secondary outcomes were the physiological pattern of rcSO2 within the initial 72 hours and up to discharge or TEA. Results: Thirty preterm infants (GA, 27.1±2.0 weeks; BW, 830±225 g) were enrolled in the bundle group. The mean time-averaged rcSO2 (66.8%±10.3%) was not associated with GA or BW. However, postnatal age appeared to influence physiological rcSO2 changes, given that rcSO2 values were higher during the initial 72 hours than at subsequent intervals. Seven infants (23.3%) had poor outcomes and significantly lower time-averaged rcSO2 (51.1% [50.0%–65.2%] vs. 71.8% [67.1%–73.1%], P=0.002). Multivariate regression indicated that a lower rcSO2 was an independent risk factor, and a 65% threshold showed an optimal predictive value for poor outcomes. Conclusion The neurocritical care bundle helped identify preterm infants at risk of cerebral hypoxia, and lower rcSO2 was an independent risk factor for composite mortality and adverse neurological outcomes.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

In recent years, the worldwide incidence rate of peripheral arterial and aortic diseases has increased year by year, significantly increasing the cardiovascular mortality and incidence rate of the whole population. In the past, peripheral arterial and aortic diseases were often more prone to missed diagnosis and delayed treatment compared to coronary artery disease. The 2024 ESC guidelines for the management of peripheral arterial and aortic diseases for the first time combines peripheral arterial and aortic diseases, integrating and updating the 2017 guidelines for peripheral arterial disease and the 2014 guidelines for aortic disease. The aim is to provide standardized recommendations for the management of systemic arterial diseases, ensuring that patients can receive coherent and comprehensive diagnosis and treatment, thereby improving prognosis. This article interprets the main content of the guideline in order to provide reference and assistance for the clinical diagnosis and treatment of peripheral arterial and aortic diseases in China at the current stage.

Objective To evaluate the advantages of powder-liquid double-chamber bag products compared with traditional powder injection. Methods The systematic review method was used to collect the literature on powder-liquid double-chamber bag, extract common evaluation indicators, evaluate the use value of powder-liquid double-chamber bag products, and conduct a comprehensive comparison with traditional powder injection products. Results A total of 23 articles were included in the literature. The effectiveness indicators used for evaluation were the stability of the liquid medicine, the accuracy of the preparation concentration, and the residual amount of the liquid medicine; the safety indicators were the incidence of insoluble particles and the incidence of punctures and scratches. The economic indicators were preparation cost, occupied volume of preparation supplies, waste weight, hospitalization cost and incidence of blood infection. The applicability indicators were preparation time, average occupation of medical staff, packaging weight and storage and transportation volume, environmental adaptability, and ease of waste disposal. Accessibility indicators are the number of manufacturers, raw material supply capacity, and patient affordability. Through the evaluation of literature evidence, it was found that the stability and concentration accuracy of the powder-liquid double-chamber bag were higher than those of the traditional powder injection, and the domestic supply had been achieved. The double-chamber bag method can reduce the infusion reaction and shorten the preparation time of the liquid medicine. Conclusion Compared with traditional powder injectabler products, powder-liquid double-chamber bags have advantages in the dimensions of effectiveness, safety, economy, suitability and innovation, and the accessibility dimension meets the requirements.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective To analyze the relationship between frailty and acute kidney injury(AKI)after hip fracture surgery in the elderly.Methods A total of 405 elderly patients who underwent hip fracture surgery in Jieyang People's Hospital from August 2021 to January 2023 were retrospectively analysed.According to the modified frailty index(mFI),they were divided into frail group(mFI≥0.27,n=112)and non-frail group(mFI<0.27,n=293).Postoperative AKI was defined according to the Kidney Disease:Improving Global Outcomes(KDIGO)criteria.After 1:1 propensity score matching(PSM),100 cases in each group were successfully matched.Univariable and multivariable logistic regression models,propensity score adjustment,PSM,inverse probability of treatment weighting(IPTW),standardized mortality ratio weighting(SMRW),pairwise algorithm(PA)weighting,and overlap weighting(OW)methods were used to analyze the relationship between frailty and postoperative AKI.Stratified analyses were performed according to age(≥80 or<80 years),gender,whether angiotensin-converting enzyme inhibitors(ACEI)/angiotensin Ⅱreceptor antagonists(ARB)were used,and whether intraoperative hypotension occurred.Results After PSM,there were no significant differences between the two groups in age,sex,surgical type,ACEI/ARB,blood urea nitrogen,serum creatinine,intraoperative blood loss,and intraoperative hypotension[standardized mean difference(SMD)<0.1].In both the original cohort and the matched cohort,the incidence of AKI was higher in frail group than in non-frail group(25.9%vs.8.9%,P<0.001;28.0%vs.11.0%,P=0.002).Analysis of the risk of postoperative AKI in elderly hip fracture patients in frail group found that compared with the non-frail group,in the univariate logistic regression model the odds ratio(OR)and a 95%confidence interval(CI)for the frail group was 3.59(2.00-6.43),P<0.001,and in the multivariable logistic regression model,the OR(95%CI)for frail group was 3.04(1.55-5.95),P=0.001.After adjustment for propensity score,the OR(95%CI)for frail group was 2.85(1.52-5.34),P=0.001,and the OR(95%CI)for frail group after PSM was 3.15(1.47-6.75),P=0.003.After IPTW,SMRW,PA weighting,and OW,the OR(95%CI)for frail group were 2.48(1.37-4.50),2.43(1.41-4.19),2.63(1.25-5.54),and 2.69(1.07-6.78),respectively,with P<0.05.The interaction tests were not statistically significant for age,sex,use of ACEI/ARB,and intraoperative hypotension(P>0.05).Conclusion In elderly patients with hip fractures,preoperative frailty may be a risk factor for postoperative AKI.

AIM To prepare anisamide-modified ursolic acid self-assembled nanoparticles,and to evaluate their anti-drug resistance effect of enzalutamide on prostate cancer.METHODS Nanoparticle precipitation method was adopted in the preparation of anisamide-modified and non-anisamide-modified self-assembled nanoparticles,respectively,after which the particle size,Zeta potential and encapsulation efficiency were determined,and the morphology was observed under transmission electron microscope.The intake of cancer-associated fibroblasts(CAFs)was investigated,after which the model for enzalutamide resistance in prostate cancer was established,CCK8 assay was applied to analyzing the sensitization effect of self-assembled nanoparticles on enzalutamide,and Western blot was used for the detection of NRG1,HER3,AKT expressions.RESULTS The anisamide-modified self-assembled nanoparticles demonstrated the average particle size,Zeta potential and encapsulation efficiency of(195.13±8.06)nm,(-29.07±0.55)mV and(94.58±0.84)％,respectively.CAFs displayed higher intake in the anisamide-modified self-assembled nanoparticles than that in the non-modified preparation and free Cy5(P＜0.05).Meanwhile,anisamide-modified self-assembled nanoparticles were able to inhibit enzalutamide resistance caused by CAFs,reduce NRG1 expression on CAFs,and anisamide-modified self-assembled nanoparticles-treated conditioned medium of CAFs could reduce HER3 and AKT expression on LNCaP cells(P＜0.05,P＜0.01).CONCLUSION Anisamide-modified ursolic acid self-assembled nanoparticles can enhance the targeting of CAFs,alleviate the drug resistance effect of enzalutamide on prostate cancer caused by CAFs,and reduce NRG1 expression in CAFs.

INTRODUCTION: Foreign body (FB) ingestion is a common paediatric emergency. While guidelines exist for urgent intervention, less is known of the natural progress of FBs passing through the gastrointestinal tract (GIT). We reviewed these FB transit times in an outpatient cohort. METHODS: A retrospective review was performed on all children (≤18 years) treated for radiopaque FB ingestion at two major tertiary paediatric centres from 2015 to 2016. Demographic data, FB types, outcomes and hospital visits (emergency department [ED] and outpatient) were recorded. All cases discharged from the ED with outpatient follow-up were included. We excluded those who were not given follow-up appointments and those admitted to inpatient wards. We categorised the outcomes into confirmed passage (ascertained via abdominal X-ray or reported direct stool visualisation by patients/caregivers) and assumed passage (if patients did not attend follow-up appointments). RESULTS: Of the 2,122 ED visits for FB ingestion, 350 patients who were given outpatient follow-up appointments were reviewed (median age 4.35 years [range: 0.5-14.7], 196 [56%] male). The largest proportion (16%) was aged 1-2 years. Coins were the most common ingested FB, followed by toys. High-risk FB (magnets or batteries) formed 9% of cases ( n =33). The 50 th centile for FB retention was 8, 4 and 7 days for coins, batteries and other radiopaque FBs, respectively; all confirmed passages occurred at 37, 7 and 23 days, respectively. Overall, 197 (68%) patients defaulted on their last given follow-up. CONCLUSION This study provides insight into the transit times of FB ingested by children, which helps medical professionals to decide on the optimal time for follow-up visits and provide appropriate counsel to caregivers.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Infant ; Male ; Eating ; Emergency Service, Hospital ; Foreign Bodies/diagnostic imaging* ; Gastrointestinal Tract/diagnostic imaging* ; Gastrointestinal Transit ; Retrospective Studies ; Singapore ; Tertiary Care Centers