The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

AIM: To investigate the correlation of serum interleukin-35(IL-35), immunoglobulin 4/immunoglobulin(IgG4/IgG), thyroid stimulating immunoglobulin(TSI)levels with the activity and severity of thyroid associated ophthalmopathy(TAO).METHODS:Prospective study. A total of 148 TAO patients admitted to our hospital from January 2023 to July 2024 were selected as the observation group. They were assigned into an active group(75 cases)and an inactive group(73 cases)based on their activity level, and were assigned into a severe group(95 cases)and a mild group(53 cases)based on the severity of their condition; another 148 healthy patients who underwent physical examinations were regarded as the control group. The levels of IL-35, IgG4/IgG, and TSI in serum were compared between the two groups. The correlation between serum IL-35, IgG4/IgG, and TSI levels and TAO activity and severity of illness were analyzed. A multivariate Logistic regression was performed to analyze the influencing factors of TAO patients developing severe symptoms. ROC curve was applied to analyze the diagnostic value of serum IL-35, IgG4/IgG, and TSI levels for the development of severe TAO in patients.RESULTS: Compared with the control group, the serum IL-35 level in the observation group was significantly lower, while IgG4/IgG and TSI levels were significantly higher(all P<0.01). Compared with non-active TAO patients, active TAO patients had significantly lower serum IL-35 level and significantly higher IgG4/IgG and TSI levels(all P<0.01). Compared with the mild TAO patients, severe TAO patients had significantly lower serum IL-35 level and significantly higher disease duration, IgG4/IgG, and TSI levels(all P<0.01). The serum IL-35 level was negatively correlated with TAO activity and disease severity(r=-0.529, -0.554, both P<0.01), while serum IgG4/IgG level was positively correlated with TAO activity and disease severity(r=0.625, 0.663, both P<0.01). Serum TSI levels were positively correlated with TAO activity and disease severity(r=0.594, 0.607, both P<0.01). Multivariate Logistic regression analysis showed that serum IL-35, IgG4/IgG, and TSI levels were all factors influencing the progression of TAO patients to severe disease(all P<0.01). The areas under the curve(AUC)for diagnosing the progression of TAO patients to severe disease using serum IL-35, IgG4/IgG, and TSI levels were 0.868, 0.859, and 0.830, respectively. The combined AUC for the three markers was 0.955, significantly higher than that of each individual marker(Zthree factors combination-IL-35=2.893, Zthree factors combination-IL-35=3.510, Zthree factors combination-IL-35=4.157, P=0.004, <0.01, <0.01).CONCLUSION: Serum IL-35 level is significantly downregulated in TAO patients, while IgG4/IgG and TSI levels are significantly upregulated. The levels of IL-35, IgG4/IgG, and TSI are correlated with the activity and severity of TAO, and their combination has high diagnostic value for TAO developing into severe.

ObjectiveTo develop a nomogram-based risk prediction model for chronic obstructive pulmonary disease (COPD) incidence among the community-dwelling population aged 40 years old and above, so as to provide targeted references for the screening and prevention of COPD. MethodsBased on a natural population cohort in suburban Shanghai, a total of 3 381 randomly selected participants aged ≥40 years underwent pulmonary function tests between July and October 2021. Cox stepwise regression analysis was used to develop overall and gender-specific risk prediction models, along with the construction of corresponding risk nomograms. Model predictive performance was evaluated using the C-indice, area under the curve (AUC) values, and Brier score. Stability was assessed through 10-fold cross-validation and sensitivity analysis. ResultsA total of 3 019 participants were included, with a median follow-up duration of 4.6 years. The COPD incidence density was 17.22 per 1 000 person-years, significantly higher in males (32.04/1 000 person-years) than that in females (7.38/1 000 person-years) (P<0.001). The overall risk prediction model included the variables such as gender, age, education level, BMI, smoking, passive smoking, and respiratory comorbidities. The male-specific model incorporated the variables such as age, BMI, respiratory comorbidities, and smoking, while the female-specific model included age, marital status, respiratory comorbidities, and pulmonary tuberculosis history. The C-indices for the overall, male-specific, and female-specific models were 0.829, 0.749, and 0.807, respectively. The 5-year AUC values were 0.785, 0.658, and 0.811, with Brier scores of 0.103, 0.176, and 0.059, respectively. Both 10-fold cross-validated C-indices and sensitivity analysis (excluding participants with a follow-up duration of <6 months) yielded C-indices were above 0.740. ConclusionThis study developed concise and practical overall and gender-specific COPD risk prediction models and corresponding nomograms. The models demonstrated robust performance in predicting COPD incidence, providing a valuable reference for identifying high-risk populations and formulating targeted screening and personalized management strategies.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To explore the safety and effects of alpha-lipoic acid (ALA) in patients with ischemic heart failure (IHF). Methods A randomized, double-blind, placebo-controlled trial was designed (ClinicalTrial.gov registration number NCT03491969). From January 2019 to January 2023, 300 patients with IHF were enrolled in four medical centers in China, and were randomly assigned at a 1∶1 ratio to receive ALA (600 mg daily) or placebo on top of standard care for 24 months. The primary outcome was the composite outcome of hospitalization for heart failure (HF) or all-cause mortality events. The second outcome included non-fatal myocardial infarction (MI), non-fatal stroke, changes of left ventricular ejection fraction (LVEF) and 6-minute walking distance (6MWD) from baseline to 24 months after randomization. Results Finally, 138 patients of the ALA group and 139 patients of the placebo group attained the primary outcome. Hospitalization for HF or all-cause mortality events occurred in 32 patients (23.2%) of the ALA group and in 40 patients (28.8%) of the placebo group (HR＝0.753, 95%CI 0.473-1.198, P＝0.231; Figure 1A-1C). The absolute risk reduction (ARR) was 5.6%, the relative risk reduction (RRR) associated with ALA therapy was approximately 19.4% compared to placebo, corresponding to a number needed to treat (NNT) of 18 patients to prevent one event. In the secondary outcome analysis, the composite outcome of the major adverse cardiovascular events (MACE) including the hospitalization for HF, all-cause mortality events, non-fatal MI or non-fatal stroke occurred in 35 patients (25.4%) in the ALA group and 47 patients (33.8%) in the placebo group (HR＝0.685, 95%CI 0.442-1.062, P＝0.091; Figure 1D). Moreover, greater improvement in LVEF (β＝3.20, 95%CI 1.14-5.23, P＝0.002) and 6MWD (β＝31.7, 95%CI 8.3-54.7, P＝0.008) from baseline to 24 months after randomization were observed in the ALA group as compared to the placebo group. There were no differences in adverse events between the study groups. Conclusions These results show potential long-term beneficial effects of adding ALA to IHF patients. ALA could significantly improve LVEF and 6MWD compared to the placebo group in IHF patients.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

Aim To investigate the dynamic changes of neuronal cells at different time points following acute cerebral ischemia-reperfusion injury by establishing a model of brain ischemia-reperfusion injury.Methods Thirty male Sprague-Dawley(SD)rats were ran-domly divided into six groups:sham group and cere-bral ischemia-reperfusion injury(IR)groups at differ-ent time points.Focal cerebral ischemia-reperfusion injury model was established using the middle cerebral artery occlusion(MCAO)technique.The Longa sco-ring method was used to assess neurobehavioral scores in rats.After successful model preparation,routine paraffin sections were made,and TUNEL staining and immunohistochemistry staining with NeuN antibody were performed to observe cell apoptosis and neuronal cell survival,respectively.Immunohistochemistry stai-ning was also performed to investigate the changes in glial fibrillary acidic protein(GFAP)as a marker for astrocytes,ionized calcium-binding adapter molecule 1(IBA-1)as a marker for microglia,and CD31 as a marker for endothelial cells at different time points.Results No significant changes were observed in neu-ronal cells of the sham group at different time points.In the cerebral ischemia-reperfusion injury groups,cell apoptosis was activated at IR3h and increased in quan-tity with morphological damage as time progressed.Ne-uN+neurons showed signs of ischemic injury after IR3h,with abnormal cell morphology.From 12 h,Ne-uN+neurons decreased in a time-dependent manner and reached their peak severity at 24 h.GFAP+astro-cytes decreased significantly after IR3h,while poorly labeled GFAP+astrocytes increased at IR 6 h and al-most disappeared in the infarcted area at 24 h and 48 h.The number of IBA-1+microglia-positive cells de-creased at IR3h,and their volume increased at IR6h.Microglial cell death was observed in the infarcted area at IR12h.CD31+endothelial cells around the infarc-ted cortex and striatum increased significantly after IR3h and persisted until 48 h.Conclusions After cerebral ischemia-reperfusion injury,the number of ap-optotic cells increases with the prolongation of time,and NeuN+neurons exhibit the most severe damage at 24 h.GFAP+astrocytes and microglial cells gradually die over time.The number of CD31+endothelial cells increases significantly around the infarcted cortex and striatum after 3 h of reperfusion and persists until 48 h.

Aim To explore the effect and mechanism of the artesunate(ART)on hepatocellular carcinoma(HCC).Methods The cell lines MHCC-97H and HCC-LM3 were used to be detected.MTT and clone formation were used to determine the cell proliferation;Wound healing was used to detect the cell migration;Transwell was used to test the cell invasion.Flow-cy-tometry was used to detect cell apoptosis and cell cy-cle.RNA-seq and qRT-PCR was used to detect the genes expression.Results The proliferation,migra-tion and invasion of treated cells were obviously inhibi-ted(P＜0.01).Moreover,the apoptosis rate in-creased significantly,so did the proportion of G2/M cells.Transcriptomic analysis identified GADD45A as a potential target of ART through RNA-sequencing da-ta,and suggested that ART might induce apoptosis and cell cycle arrest through regulating the expression of GADD45A.In addition,the results of mechanism studies and signaling analysis suggested that GADD45A had interaction with its upstream gene NACC1(nucle-us accumbens associated 1).Moreover,after ART treatment,the expressions of GADD45A and NACC1 were changed significantly.Conclusion ART may be a potential drug to resist HCC by affecting the expres-sion of GADD45A and its upstream gene NACC1,which provides a new drug,a new direction and a new method for the clinical treatment of HCC.