OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

Metabolic diseases have seen a steady increase in incidence in recent years, becoming one of the main causes of sub-health status globally. Neutrophil extracellular traps(NETs) are reticular complexes containing DNA, which trap foreign microorganisms or induce an immune response. Current research indicates that NETs are widely active in various metabolic diseases and can cause severe damage to the body through multiple mechanisms, including promoting blood glucose elevation, damaging vascular endothelial cells, forming vascular embolisms, triggering intense inflammation, and promoting lipid accumulation. Therefore, intervening in NETs is an important approach to treating metabolic diseases. Research has shown a close relationship between the theory of spleen heat-turbid toxin theory and metabolic diseases-NETs mechanism. The basic pathogenesis include the internal accumulation of phlegm-dampness, qi stagnation and blood stasis, internal accumulation of dampness-heat, phlegm and blood stasis, and flourishing toxic heat. Various Chinese herbal medicines with the functions of dispelling dampness, resolving phlegm, promoting blood circulation to remove blood stasis, and clearing heat and toxins, along with their extracts and compound prescriptions, can treat metabolic diseases by regulating NETs and delaying disease progression. This paper systematically outlined the formation mechanisms of NETs, their connection to metabolic diseases, the theoretical basis in TCM, their roles in numerous metabolic diseases, and the current research status of TCM in regulating NETs to prevent and control metabolic diseases, aiming to provide effective reference ideas for developing therapeutic strategies for metabolic diseases.
Humans ; Extracellular Traps/metabolism* ; Metabolic Diseases/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Animals ; Neutrophils/metabolism* ; Medicine, Chinese Traditional

This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

Acori Tatarinowii Rhizoma is the dried rhizome of Acorus tatarinowii in the family of Tennantiaceae, which has the efficacy of opening up the orifices and expelling phlegm, awakening the mind and wisdom, and resolving dampness and opening up the stomach. Modern studies have shown that volatile oil is the main active ingredient of Acori Tatarinowii Rhizoma, and α-asarone and β-asarone have been proved to be the active ingredients in the volatile oil of Acori Tatarinowii Rhizoma, with pharmacological effects such as anti-Alzheimer's disease, antiepileptic, anti-Parkinson's disease, antidepressant, anticerebral ischemia/reperfusion injury, anti-thrombosis, lipid-lowering, and antitumor. By summarising and outlining the pharmacological effects of α-asarone and β-asarone and elucidating the possible mechanisms of their pharmacological effects, we can provide theoretical basis for the further research and clinical application of Acori Tatarinowii Rhizoma.
Allylbenzene Derivatives ; Acorus/chemistry* ; Anisoles/chemistry* ; Rhizome/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Animals

From the perspective of competitive endogenous RNA(ceRNA) constructed by metastasy-associated lung adenocarcinoma transcript 1(Malat1) and microRNA 16-5p(miR-16-5p), the improvement mechanism of Tonggu Xiaotong Capsules(TGXTC) on the imbalance and disorder of "cholesterol-iron" metabolism in chondrocytes of osteoarthritis(OA) was explored. In vivo experiments, 60 8-week-old C57BL/6 mice were acclimatized and fed for 1 week and then randomly divided into two groups: blank group(12 mice) and modeling group(48 mice). The animals in modeling group were anesthetized by 5% isoflurane inhalation, which was followed by the construction of OA model. They were then randomly divided into model group, TGXTC group, Malat1 overexpression group, and TGXTC+Malat1 overexpression(TGXTC+Malat1-OE) group, with 12 mice in each group. The structural changes of mouse cartilage tissues were observed by Masson staining after the intervention in each group. RT-PCR was employed to detect the mRNA levels of Malat1 and miR-16-5p in cartilage tissues. Western blot was used to analyze the protein expression of ATP-binding cassette transporter A1(ABCA1), sterol regulatory element-binding protein(SREBP), cytochrome P450 family 7 subfamily B member 1(CYP7B1), CCAAT/enhancer-binding protein homologous protein(CHOP), acyl-CoA synthetase long-chain family member 4(ACSL4), and glutathione peroxidase 4(GPX4) in cartilage tissues. In vitro experiments, mouse chondrocytes were induced by thapsigargin(TG), and the combination of Malat1 and miR-16-5p was detected by double luciferase assay. The fluorescence intensity of Malat1 in chondrocytes was determined by fluorescence in situ hybridization. The miR-16-5p inhibitory chondrocyte model was constructed. RT-PCR was used to analyze the levels of Malat1 and miR-16-5p in chondrocytes under the inhibition of miR-16-5p. Western blot was adopted to analyze the regulation of TG-induced chondrocyte proteins ABCA1, SREBP, CYP7B1, CHOP, ACSL4, and GPX4 by TGXTC under the inhibition of miR-16-5p. The results of in vivo experiments showed that,(1) compared with model group, TGXTC group exhibited a relatively complete cartilage layer structure. Compared with Malat1-OE group, TGXTC+Malat1-OE group showed alleviated cartilage surface damage.(2) Compared with model group, TGXTC group had a significantly decreased Malat1 mRNA level and an increased miR-16-5p mRNA level in mouse cartilage tissues(P<0.01).(3) Compared with the model group, the protein levels of ABCA1 and GPX4 in the cartilage tissue of mice in the TGXTC group increased, while the protein levels of SREBP, CYP7B1, CHOP and ACSL4 decreased(P<0.01). The results of in vitro experiments show that,(1) dual-luciferase was used to evaluate that miR-16-5p has a targeting effect on the Malat1 gene.(2)Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group had an increased mRNA level of miR-16-5p and an decreased mRNA level of Malat1(P<0.01).(3) Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group exhibited increased expression of ABCA1 and GPX4 proteins and decreased expression of SREBP, CYP7B1, CHOP, and ACSL4 proteins(P<0.01). The reasults showed that TGXTC can regulate the ceRNA of Malat1 and miR-16-5p to alleviate the "cholesterol-iron" metabolism disorder of osteoarthritis chondrocytes.
Animals ; MicroRNAs/metabolism* ; RNA, Long Noncoding/metabolism* ; Chondrocytes/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice, Inbred C57BL ; Mice ; Osteoarthritis/drug therapy* ; Iron/metabolism* ; Male ; Cholesterol/metabolism* ; Humans ; Capsules ; RNA, Competitive Endogenous

Hepatic fibrosis is a key pathological process in the development of chronic liver disease to cirrhosis, and its core mechanism involves the activation of hepatic stellate cells(HSC) and abnormal deposition of extracellular matrix(ECM). Although existing treatments, such as antiviral drugs, can delay disease progression, they have the problem of single therapeutic targets and cannot reverse fibrosis. Accordingly, multidimensional intervention strategies are urgently needed. Recent studies have shown that circadian rhythm disorders aggravate hepatic fibrosis by regulating metabolism, immunity, and inflammation. Traditional Chinese medicine(TCM) plays a unique role in restoring the circadian clock via multi-target and holistic regulation. This paper establishes a three-dimensional network by systematically integrating biological clock, metabolism, and immunity for the first time to elucidate the scientific connotation of the theory of time-concerned treatment of TCM, and proposes a new strategy for the development of time-targeted compound prescriptions, providing innovative ideas for the treatment of hepatic fibrosis.
Humans ; Liver Cirrhosis/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Circadian Rhythm/drug effects* ; Animals ; Medicine, Chinese Traditional ; Hepatic Stellate Cells/drug effects*

The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine and intelligent care. However, the artificial intelligent medical device sector still faces significant challenges, such as data privacy protection and algorithm reliability. This study, based on invention patent analysis, revealed the technological innovation trends in the field of artificial intelligent medical devices from aspects such as patent application time trends, hot topics, regional distribution, and innovation players. The results showed that global invention patent applications had remained active, with technological innovations primarily focused on medical image processing, physiological signal processing, surgical robots, brain-computer interfaces, and intelligent physiological parameter monitoring technologies. The United States and China led the world in the number of invention patent applications. Major international medical device giants, such as Philips, Siemens, General Electric, and Medtronic, were at the forefront of global technological innovation, with significant advantages in patent application volumes and international market presence. Chinese universities and research institutes, such as Zhejiang University, Tianjin University, and the Shenzhen Institute of Advanced Technology, had demonstrated notable technological innovation, with a relatively high number of patent applications. However, their overseas market expansion remained limited. This study provides a comprehensive overview of the technological innovation trends in the artificial intelligent medical device field and offers valuable information support for industry development from an informatics perspective.
Artificial Intelligence ; Patents as Topic ; Humans ; Inventions ; China ; Brain-Computer Interfaces ; Telemedicine ; Equipment and Supplies ; Robotics ; Algorithms

The rapid development of artificial intelligence technology is driving profound changes in medical practice, particularly in the field of medical device application. Based on data from the U.S. clinical trials registry, this study analyzes the global registration landscape of clinical trials involving artificial intelligence-based medical devices, aiming to provide a reference for their clinical research and application. A total of 2 494 clinical trials related to artificial intelligence medical devices have been registered worldwide, with participation from 66 countries or regions. The United States leads with 908 trials, while for other countries or regions, including China, each has fewer than 300 trials. Germany, the United States, and Belgium serve as central hubs for international collaboration. Among the sponsors, 63.96% are universities or hospitals, 22.36% are enterprises, and the remainder includes individuals, government agencies and others. Of all trials, 79.99% are interventional studies, 94.67% place no restrictions on participant gender, and 69.69% exclude children. The targeted diseases are primarily neurological and mental disorders. This study systematically reveals the global distribution characteristics and research trends of artificial intelligence medical device clinical trials, offering valuable data support and practical insights for advancing international collaboration, resource allocation, and policy development in this field.
Artificial Intelligence ; Humans ; Clinical Trials as Topic/statistics & numerical data* ; Equipment and Supplies ; Registries ; United States

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures