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.

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.

Following the core outcome set standards for development(COS-STAD), this study aims to construct core outcome set(COS) for clinical research on traditional Chinese medicine(TCM) treatment of simple obesity. Firstly, a comprehensive review was conducted on the randomized controlled trial(RCT) and systematic review(SR) about TCM treatment of simple obesity that were published in Chinese and English databases to collect reported outcomes. Additional outcomes were obtained through semi-structured interviews with patients and open-ended questionnaire surveys for clinicians. All the collected outcomes were then merged and organized as an initial outcome pool, and then a preliminary list of outcomes was formed after discussion by the working group. Subsequently, two rounds of Delphi surveys were conducted with clinicians, methodology experts, and patients to score the importance of outcomes in the list. Finally, a consensus meeting was held to establish the COS for clinical research on TCM treatment of simple obesity. A total of 221 RCTs and 12 SRs were included, and after integration of supplementary outcomes, an initial outcome pool of 141 outcomes were formed. Following discussions in the steering advisory group meeting, a preliminary list of 33 outcomes was finalized, encompassing 9 domains. Through two rounds of Delphi surveys and a consensus meeting, the final COS for clinical research on TCM treatment of simple obesity was determined to include 8 outcomes: TCM symptom scores, body mass index(BMI), waist-hip ratio, waist circumference, visceral fat index, body fat rate, quality of life, and safety, which were classified into 4 domains: TCM-related outcomes, anthropometric measurements, quality of life, and safety. This study has preliminarily established a COS for clinical research on TCM treatment of simple obesity. It helps reduce the heterogeneity in the selection and reporting of outcomes in similar clinical studies, thereby improving the comparability of research results and the feasibility of meta-analysis and providing higher-level evidence support for clinical practice.
Humans ; Obesity/therapy* ; Medicine, Chinese Traditional ; Randomized Controlled Trials as Topic ; Treatment Outcome ; Drugs, Chinese Herbal/therapeutic use*

Ankle fractures are common traumatic injuries, especially among diabetic patients, and their treatment faces many challenges. Diabetic patients, due to factors such as long-term high blood sugar, osteoporosis, microvascular lesions and neuropathy, are prone to problems such as delayed fracture healing, increased risk of infection, non-union of fractures and postoperative complications, which affect their treatment effect and recovery process. Diabetes significantly affects the treatment of ankle fractures, mainly through factors such as high blood sugar, osteoporosis, microvascular lesions, and hypercoagulable state of the blood. In recent years, advancements in strong fixation techniques, blood glucose control and postoperative rehabilitation have achieved remarkable results in the treatment of ankle fractures for diabetic patients. However, at present, there are many studies on the treatment of ankle fractures in patients with diabetes, but there is still a lack of large-scale data reports. With the continuous advancement of medical technology, through precise admission assessment, perfect perioperative management, advanced fixation techniques and the latest treatment concepts, postoperative complications could be significantly reduced, and the fracture healing and prognosis of patients with ankle fractures combined with diabetes could be improved.
Humans ; Ankle Fractures/complications* ; Diabetes Complications/surgery* ; Diabetes Mellitus ; Fracture Fixation, Internal

Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Integrative Medicine ; Drugs, Chinese Herbal/therapeutic use* ; Practice Guidelines as Topic

Chaihu Longgu Muli Decoction can be used to treat perimenopausal insomnia (PMI). It can be used either alone with modification or in combination with Western medicine or acupuncture and moxibustion and other external TCM treatment methods, which has achieved good efficacy, and can improve the symptoms of patients with difficulty falling asleep and decreased sleep quality, with good safety. The treatment of Chaihu Longgu Muli Decoction for PMI may exert its effects through multiple pathways, such as inhibiting HPA axis hyperactivity, regulating hormone and neurotransmitter levels, inhibiting oxidative stress and inflammatory responses. However, existing clinical studies suffer from issues such as small sample sizes, inconsistent research protocols, and inconsistent efficacy evaluation criteria, which require further improvement and deeper exploration of relevant mechanisms.

Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Purpose::This study evaluated the methods and clinical effects of multidisciplinary collaborative treatment for occlusal reconstruction in patients with old jaw fractures and dentition defects.Methods::Patients with old jaw fractures and dentition defects who underwent occlusal reconstruction at the Third Affiliated Hospital of Air Force Military Medical University from January 2018 to December 2022 were enrolled. Clinical treatment was classified into 3 phases. In phase I, techniques such as orthognathic surgery, microsurgery, and distraction osteogenesis were employed to reconstruct the correct 3-dimensional (3D) jaw position relationship. In phase II, bone augmentation and soft tissue management techniques were utilized to address insufficient alveolar bone mass and poor gingival soft tissue conditions. In phase III, implant-supported overdentures or fixed dentures were used for occlusal reconstruction. A summary of treatment methods, clinical efficacy evaluation, comparative analysis of imageological examinations, and satisfaction questionnaire survey were utilized to evaluate the therapeutic efficacy in patients with traumatic old jaw fractures and dentition defects. All data are summarized using the arithmetic mean ± standard deviation and compared using independent sample t-tests. Results::In 15 patients with old jaw fractures and dentition defects (an average age of 32 years, ranging from 18 to 53 years), there were 7 cases of malocclusion of single maxillary fracture, 6 of malocclusion of single mandible fracture, and 2 of malocclusion of both maxillary and mandible fractures. There were 5 patients with single maxillary dentition defects, 2 with single mandibular dentition defects, and 8 with both maxillary and mandibular dentition defects. To reconstruct the correct 3D jaw positional relationship, 5 patients underwent Le Fort I osteotomy of the maxilla, 3 underwent bilateral sagittal split ramus osteotomy of the mandible, 4 underwent open reduction and internal fixation for old jaw fractures, 3 underwent temporomandibular joint surgery, and 4 underwent distraction osteogenesis. All patients underwent jawbone augmentation, of whom 4 patients underwent a free composite vascularized bone flap (26.66%) and the remaining patients underwent local alveolar bone augmentation. Free gingival graft and connective tissue graft were the main methods for soft tissue augmentation (73.33%). The 15 patients received 81 implants, of whom 11 patients received implant-supported fixed dentures and 4 received implant-supported removable dentures. The survival rate of all implants was 93.82%. The final imageological examination of 15 patients confirmed that the malocclusion was corrected, and the clinical treatment ultimately achieved occlusal function reconstruction. The patient satisfaction questionnaire survey showed that they were satisfied with the efficacy, phonetics, aesthetics, and comfort after treatment.Conclusion::Occlusal reconstruction of old jaw fractures and dentition defects requires a phased sequential comprehensive treatment, consisting of 3D spatial jaw correction, alveolar bone augmentation and soft tissue augmentation, and implant-supported occlusal reconstruction, achieving satisfactory clinical therapeutic efficacy.

Objective:To analyze the disease burden in middle-aged and elderly population aged ≥55 in Shenzhen from 2016 to 2030 and provide evidence for the development of healthy aging strategies.Methods:The years of life lost (YLL), years lost due to disability (YLD), and the disability-adjusted life year (DALY) in this population from 2016 to 2022 were calculated. Joinpoint log-linear regression model was used to analyze the time trend. Bayesian age-period-cohort model and grey system model were used to predict YLL, YLD, and DALY in this population in 2030.Results:From 2016 to 2022, the crude DALY rate showed a transient fluctuation in age group 55-74 years, but a pronounced increase in age group ≥85 years. The proportions of YLL and YLD due to non-communicable diseases in all age groups was considerably higher than those due to communicable and nutritional diseases and injuries. In 2022, in all age groups, the YLL due to neoplasms (55-74 years old) and cardiovascular disease (≥75 years old) ranked first, and the YLD due to musculoskeletal disorder ranked first. By 2030, the causes of YLL and YLD ranking first in each age group would be remained, while the ranks of some causes would increase.Conclusions:The age specific characteristics of current and predicted disease burden differed in individuals aged ≥55 years. Therefore, it is necessary to allocate social and medical resources according to the disease burden pattern.