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.

ObjectiveThis paper aims to use the digital muscle function assessment system Myoton PRO to assess the correlation between muscle tension，clinical characteristics， and traditional Chinese medicine（TCM） syndromes in patients with hepatolenticular degeneration ［also known as Wilson disease（WD）］. MethodsA total of 104 patients with WD accompanied by abnormal muscle tension（increased or decreased，hereinafter the same） who were hospitalized in the Brain Disease Centre of the First Affiliated Hospital of Anhui University of Chinese Medicine from April 2021 to November 2023 were selected，all of whom were subjected to TCM syndrome diagnosis and Myoton PRO for the measurement of F value of muscle tension，Goldstein， and UWDRS-N scales. The age of onset of the disease and disease duration were analyzed，and the differences and correlations of the above indexes in different TCM syndromes of WD were analyzed ResultsAmong the 104 patients with WD ，the phlegm and stasis syndrome was the most common（60 patients），followed by the damp-heat syndrome（33 patients），and the least common was the liver-kidney Yin deficiency syndrome（11 patients）. The F value of the phlegm and stasis syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group（P<0.01）. The F value of the damp-heat syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group（P<0.05），and the F value of the lower limbs of each group was higher than that of the upper limbs（P<0.01）. Goldstein and UWDRS-N scores of the patients in the phlegm and stasis syndrome group were higher than those in the damp-heat syndrome group and the liver-kidney Yin deficiency syndrome group（P<0.05）. There was no significant difference between the Goldstein and UWDRS-N scores of patients in the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group. Correlation analysis revealed that the age of onset and duration of the disease were positively correlated with the F values of the lower limbs（r=0.20，P<0.05，r=0.38，P<0.01）and had no significant correlation with those of the upper limbs. The F value levels of muscle tension of all limbs in the three groups of patients were positively correlated with the Goldstein and UWDRS-N scores（muscle tension of the upper limbs in the phlegm and stasis syndrome group，r=0.36，P<0.01，r=0.42，P<0.01. muscle tension of the lower limbs in the phlegm and stasis syndrome group，r=0.70，P<0.01，r=0.60，P<0.01. muscle tension of the upper limbs in the damp-heat syndrome group，r=0.64，P<0.01，r=0.53，P<0.01. muscle tension of the lower limbs in the damp-heat syndrome group，r=0.59，P<0.01，r=0.70，P<0.01. muscle tension of the upper limbs in the liver-kidney Yin deficiency syndrome group，r=0.70，P<0.01，r=0.74，P<0.01. muscle tension of the lower limbs in the liver-kidney Yin deficiency syndrome group，r=0.85，P<0.01，r=0.62，P<0.01）. Conlusion： The digital muscle function assessment system Myoton PRO can objectively evaluate the muscle tension level of patients with WD accompanied by abnormal muscle tension. This level has significant differences among different TCM syndromes and can evaluate the patient's condition to some extent.

Objective: To understand the dynamic temporal evolution pathways of Internet addiction among university students and to identify the core driving nodes, so as to provide theoretical evidences for the precise implementation of targeted interventions. Methods: Using a convenient cluster sampling method, a total of 1 066 full time freshmen and sophomores were recruited from three universities in Guizhou, Jiangxi, and Guangdong Provinces for a follow up survey (T1:January-March 2024; T2:January-March 2025). The Revised Chen Internet Addiction Scale (CIAS-R) was employed to assess the status of Internet addiction among university students, and cross sectional as well as cross lagged panel network models were constructed to analyze Internet addiction and its multidimensional influencing factors. Results: The T1 network comprised 19 nodes and 114 non zero edges, while the T2 network comprised 19 nodes and 126 non zero edges. Cross sectional network analysis revealed the strongest association between "insufficient sleep" and "daytime fatigue"; the core nodes were "first thought upon waking for going online" and "feeling low after disconnection" (characteristics of psychological dependence) at T1, while the core nodes shifted to "impaired health" and "excitement when online" (characteristics of functional impairment and addictive psychodynamic features) at T2. Cross lagged network analysis further indicated that "reduced leisure" directly predicted "sleep compression", and a bidirectional relationship was observed between "needing more time to achieve satisfaction" and "academic decline". Conclusions Internet addiction among university students exhibits dynamic evolutionary characteristics. Stage specific targeted interventions focusing on core driving nodes are needed, integrating behavioral regulation and academic support to break the vicious cycle and enhancing the ability to cope with real life demands.

ObjectiveTo investigate the therapeutic effects of direct-acting antiviral agents (DAAs) combined regimens for hepatitis C virus (HCV) patients in Dehong Prefecture, Yunnan Province from 2022 to 2024, to analyze the characteristics of treatment failure patients, so as to provide a basis for discovering more effective treatment regimens in the future. MethodsData on HCV prevention and treatment in Dehong Prefecture was extracted from the China Disease Control and Prevention Information System. A total of 617 patients with HCV antiviral therapy were included, and the differences in variable characteristics among patients with different genotypes were analyzed using comparative statistical tests, including basic socio-demographic characteristics, biochemical testing indicators, and information on previous treatment and current treatment. In addition, the cure rate of HCV patients with diverse characteristics was compared, and the potential causes of treatment failure were explored simultaneously. ResultsThe cure rate of HCV was 96.8%, and statistically significant differences were observed in aspartate transaminase (AST) and alanine transaminase (ALT) levels, previous antiviral therapy history and initial treatment regimens among patients with different HCV genotypes (all P<0.05). Among the multi-type combination regimens, the cure rate of sofosbuvir (SOF)-containing regimens was 97.00%, that of velpatasvir (VEL)-containing regimens was 95.45%, and the cure rate of other treatment regimens, including the regimens with ribavirin (RIB) intervention, was 93.10%. Among the patients with treatment failure, 45.00% had genotype 3, 40.00% had abnormal abdominal ultrasound results, and all presented with elevated baseline AST test levels. ConclusionThe clinical treatment of HCV patients should consider the differences in genotype and biochemical test results. DAAs combined regimens for HCV have achieved a high cure rate in Dehong Prefecture and are applicable to HCV patients with diverse clinical characteristics, providing research evidence for wider application.

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.

Humans ; Artificial Intelligence ; Algorithms ; Brain ; Head

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

Objective To observe the incidence of pericardial tamponade(PT)after left atrial appendage closure(LAAC)in patients with non-valvular atrial fibrillation(NVAF),and to explore its related factors and outcomes.Methods NVAF patients who were hospitalized and treated with LAAC in Department of Cardiology of our hospital from August 2014 to March 2023 were selected for the study.The general clinical data,preoperative transthoracic echocardiography and transesophageal echocardiography data,results of routine preoperative laboratory tests,intraoperative data and follow-up data of the patients were collected through the hospital medical record management system.The enrolled patients were classified into the non-PT group(n=8)and the PT group(n =1184)according to whether PT occurred after LAAC or not.The incidence of PT,related risk factors and outcomes were statistically analyzed.Results This study included 639 males(53.6%)and 553 females(46.4%),with an average age of 68.1±9.65 years.The CHA2 DS2-VASc score was 4.51±1.72,and the HAS-BLED score was 3.36±1.09.PT occurred in 8 cases(0.67%),among them,6 cases occurred 1 to 33 h after LAAC,and 2 cases occurred on day 19 and day 27 after LAAC.As for the results of transesophageal echocardiography(TEE)and LAA angiography,compared with the non-PT group,the PT group had the significantly larger maximum caliber of the LAA(P=0.025,P=0.015),smaller maximum depth of the LAA(P=0.028,P=0.031),and lower success rate of one-time placement of the occluder(P=0.031);The occluder compression rate of the PT group was significantly greater than that of the non-PT group(P=0.046).Multivariate analysis showed that larger maximum diameter of LAA,smaller average effective depth of LAA and larger compression rate of occluder were the main risk factors for PT.All the 8 PT patients were cured by stopping antithrombotic drugs,pericardiocentesis or surgical drainage.During a mean follow-up of 39±27 months,there were no device-related thrombosis(DRT),ischemic stroke,systemic embolism and other complications in the PT group.Conclusion The incidence of PT after LAAC is low,which is related to the large diameter of LAA,the relatively insufficient depth of the LAA and the large compression rate of the occlude.PT can be cured by stopping antithrombotic drugs and pericardiocentesis/surgical drainage.

Objective To evaluate the performance of two molecular point-of-care testing(POCT)prod-ucts in the diagnosis of influenza A virus(Flu A)and influenza B virus(Flu B)of clinical samples,and pre-liminarily evaluate the clinical diagnostic value of the changes of infection-related indicators in peripheral blood.Methods A total of 491 oropharyngeal swabs from patients with influenza-like symptoms who were treated in the hospital were recruited into this study from November 1,2019 to June 30,2023.These swabs were collected using reverse transcription real-time quantitative fluorescent polymerase chain reaction(RT-qPCR),and two POCT molecular products,XpertTM Xpress Flu/RSV and EasyNAT? Flu Assay,respectively.The diagnostic performance of two POCT molecular products was analyzed using RT-qPCR reaction as a standard.According to the results of RT-qPCR method,the subjects were divided into Flu A positive group,Flu B positive group and negative group(both Flu A and Flu B were negative).The levels of indicators in pe-ripheral blood of the three groups were compared to evaluate the value of these indicators in the clinical diag-nosis of Flu A and Flu B.Results Among the 491 patient specimens,the XpertTM Xpress Flu/RSV assay showed the sensitivity for Flu A was 96.88%,and the specificity was 99.75%,and the sensitivity for Flu B was 100.00%,and the specificity was 100.00%.EasyNAT? Flu Assay assay showed the sensitivity for Flu A was 94.79%,and the specificity was 96.81%,and the sensitivity for Flu B was 100.00%,and the specificity was 100.00%.And two POCT molecular methods performed well consistency(Kappa value was 0.974).There was no significant difference in the levels of C-reactive protein and serum amyloid A among the negative group,Flu A positive group,and Flu B positive group(P>0.05).But the levels of white blood cell count in the negative group were higher than those in the Flu A positive group and Flu B positive group(P<0.01).Conclusion In this paper,two typical molecular POCT products are studied.Their sensitivity and specificity are highly consistent with the results of RT-qPCR.Molecular POCT products have the advantages of flexibil-ity and rapidity,which are of great value for the improvement of clinical diagnosis and treatment.Molecular detection combined with peripheral blood infection related indicators is helpful for the early diagnosis of influ-enza virus infectious diseases.

The preparation edge of the tooth in oral restoration has always been the hot concern for dentists,and the improper preparation edge may lead to such diseases as caries and periodontitis,and ultimately lead to the restoration failure.The application of biologically oriented preparation technique has been proven to restore good periodontal soft and hard tissue morphology,which is expected to replace the traditional dental preparation methods.This article aims to comprehensively discuss the application of biologically oriented preparation technique in veneers,full crown and implantation.