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 investigate the optimal ratio of goat horn replacing antelope horn in Fufang Lingjiao Jiangya pills and the blood pressure-lowering mechanism of this medicine. MethodsThe blood pressure-lowering efficacy of Fufang Lingjiao Jiangya pills with varying proportions of goat horn replacing antelope horn was evaluated on spontaneous hypertensive rats （SHR）. In this experiment， 50 SHR rats were randomly grouped as follows： model （n=8）， captopril （0.01 g·kg^-1） （n=6）， low-dose blank Fufang Lingjiao Jiangya pills （0.342 g·kg^-1） （n=6）， high-dose blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1） （n=6）， low-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， high-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）， low-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， and high-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）. Additionally， 8 WKY rats were used as the normal group. Drugs were administered by gavage for 4 weeks while an equal volume of distilled water was administered for the normal and model groups. Blood pressure was measured before administration， 3 h post administration， and biweekly thereafter. In the experiment for Fufang Lingjiao Jiangya pills with goat horn replacing antelope horn in different proportions， 48 SHR rats were randomly grouped as follows： model， blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1）， antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1）， 2× goat horn-containing Fufang Lingjiao Jiangya pills （0.824 g·kg^-1）， 4× goat horn Fufang Lingjiao Jiangya pills （0.969 g·kg^-1）， and 6× goat horn Fufang Lingjiao Jiangya pills （1.112 g·kg^-1）. The normal group included 8 WKY rats， and the normal group and model group received an equal volume of distilled water. The treatment lasted for 2 weeks， and blood pressure was recorded at various time points （pre-administration， 3 h post administration， and on days 4， 7， 10， and 14 of administration）. Serum levels of angiotensin-converting enzyme （ACE）， angiotensin Ⅱ（Ang Ⅱ）， renin， and interleukin-6 （IL-6） were measured by enzyme-linked immunosorbent assay. Histopathological changes in the heart， kidney， and thoracic aorta were observed by hematoxylin-eosin staining. The protein levels of ACE2， angiotensin Ⅱ type 1 receptor （AT1R）， and angiotensinogen （AGT） in the kidney tissue were determined by Western blot， while the expression of nuclear factor （NF）-κB p65 and Toll-like receptor 4 （TLR4） in the thoracic aorta tissue was assessed by immunohistochemistry. ResultsCompared with the model group， all treatment groups showed lowered blood pressure （P<0.05， P<0.01）， and the 6× goat horn-containing Fufang Lingjiao Jiangya pills group showed consistent blood pressure-lowering effect with the antelope horn-containing Fufang Lingjiao Jiangya pills group. Compared with the normal group， the model group showed elevated serum levels of ACE， Ang Ⅱ， renin， and IL-6， while the elevations were declined in the Fufang Lingjiao Jiangya pills groups （P<0.05， P<0.01）. Pathological changes in the heart， kidney， and thoracic aorta were alleviated in all the treatment groups， with the 6× goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups exhibited the best effect. Western blot and immunohistochemistry results showed that all the treatment groups exhibited down-regulated protein levels of AT1R， AGT， NF-κB p65， and TLR4 and up-regulated protein levels of ACE2 （P<0.05， P<0.01） compared with model group， with the 6×goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups showcasing the best effect. ConclusionReplacing antelope horn with 6×goat horn in Fufang Lingjiao Jiangya pills can achieve consistent blood pressure-lowering effect with the original prescription. The prescription may exert the effect by inhibiting the renin-angiotensin-aldosterone system （RAAS） and TLR4/NF-κB signaling pathways.

OBJECTIVE To screen the primary processing methods of Ligusticum sinense slice based on differential metabolites， and provide theoretical basis for the scientific processing of L. sinense. METHODS Using 13 groups of L. sinense slice processed by fresh-cutting or traditional methods as samples， UHPLC-QE-MS was employed for metabolite identification. Multivariate statistical analysis was applied to screen differential metabolites among the 13 sample groups， analyzing the effects of washing， soaking， drying methods， and drying cycles on both the relative expressions of differential metabolites and the contents of carboxylic acids and their derivatives in the samples （to reflect the total amino acid content）. RESULTS Principal component analysis and partial least squares-discriminant analysis both showed significant intergroup differences among the 13 sample groups. A total of 688 differential metabolites were screened from the 13 sample groups， with carboxylic acids and their derivatives showing the highest proportion. The relative expression levels of phosphatidylcholine significantly increased after washing treatment， while tryptophan expression significantly decreased after soaking treatment. Samples dried at 50-60 ℃ showed significantly increased expression of psoralen， whereas those dried at 40 ℃ showed significantly decreased expression of methyl -p- methoxycinnamate. Both washing and soaking treatments significantly reduced the total amino acid content in samples， while secondary drying significantly increased it. The three controlled-temperature drying methods maintained relatively stable total content of amino acids in samples. CONCLUSIONS The optimal processing protocol for L. sinense slice is as follows: fresh L. sinense slice should be freshly cut at the production site， undergo quick washing after soil removal， and be dried twice at 40 ℃ （before and after slicing）.

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.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

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　Exploring the risk factors and degree of influence on treatment regression of patients with etiologically positive pulmonary tuberculosis in Bijie city, so as to provide reference for the precise prevention and treatment of pulmonary tuberculosis epidemic. Methods　The medical records of registration, treatment and management of pulmonary tuberculosis patients in Bijie City with positive etiology from 2017 to 2022 were derived from the Tuberculosis Monitoring Report Information Management System. Statistically significant variables were screened using binary logistic regression. Revealing interdependencies between factors and conditional probabilities by constructing Bayesian network models. 　Results　A total of 21 662 cases of etiologically positive pulmonary tuberculosis were registered in Bijie City from 2017 to 2022, with etiologically positive rate of 48.60% and a successful treatment rate of 89.52%, both of which were on the rise overall (χ2trend=2 618.15, P<0.001; χ2trend=102.84, P<0.001). A multifactorial analysis showed that gender, age, ethnicity, occupation, patient origin, HIV test results, migrating population, and treatment classification were influencing factor for the successful treatment rate (P<0.05). The Bayesian network model showed that age and treatment classification were the direct factors affecting the treatment outcome, while gender, occupation and patient origin were the indirect factors. Conditional probability showed that patients<20 years of age and initial treatment had the highest rate of successful treatment (96.75%), with a 3.25% probability of having an adverse outcome; Patients≥80 years of age who were retreated had the lowest rate of successful treatment (58.70%), with a 41.30% probability of having an adverse outcome. Conducting causal effect speculation, when preventing tuberculosis in older persons aged 60 years and over, and the other patients are newly treated patients, the successful treatment rate increased from 89.50% to 93.10%, with an increase of 3.60%; Nearly 50.00% fewer farmers are without tuberculosis, and the source of the other patients is active detection (health check-ups and proactive screening), with an increase in the successful treatment rate from 89.50% to 91.70%, with a change in the conditional probability value of 2.20%. Conclusions　Consultation and management of male, elderly, re-treatment, farmer, HIV-positive pulmonary tuberculosis patients in Bijie should be strengthened. Meanwhile, causal correlation effect inference using Bayesian networks is important for precise prevention, control and treatment of diseases.

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.

Platycodonis Radix is the dry root of Platycodon grandiflorum of Campanulaceae, which has a variety of pharmacological effects and is a commonly used bulk Chinese medicine. In this study, the chloroplast genome sequences of six P. grandiflorum from different producing areas has been sequenced with Illumina HiSeq X Ten platform. The specific DNA barcodes were screened, and the germplasm resources and genetic diversity were analyzed according to the specific barcodes. The total length of the chloroplast genome of 6 P. grandiflorum samples was 172 260-172 275 bp, and all chloroplast genomes showed a typical circular tetrad structure and encoded 141 genes. The comparative genomics analysis and results of amplification efficiency demonstrated that trnG-UCC and ndhG_ndhF were the potential specific DNA barcodes for identification the germplasm resources of P. grandiflorum. A total of 305 P. grandiflorum samples were collected from 15 production areas in 9 provinces, for which the fragments of trnG-UCC and ndhG_ndhF were amplificated and the sequences were analyzed. The results showed that trnG-UCC and ndhG_ndhF have 5 and 11 mutation sites, respectively, and 5 and 7 haplotypes were identified, respectively. The combined analysis of the two sequences formed 13 haplotypes (named Hap1-Hap13), and Hap4 is the main genotype, followed by Hap1. The unique haplotypes possessed by the three producing areas can be used as DNA molecular tags in this area to distinguish from the germplasm resources of P. grandiflorum from other areas. The haplotype diversity, nucleotide diversity and genetic distance were 0.94, 4.79×10^-3 and 0.000 0-0.020 3, respectively, suggesting that the genetic diversity was abundant and intraspecific kinship was relatively close. This study laid a foundation for the identification of P. grandiflorum, the protection and utilization of germplasm resources, and molecular breeding.