In this experiment, self-assembled nanoparticles(SANs) were prepared by the pH-driven method, and Her-HCP SAN was constructed by using herpetrione(Her) and Herpetospermum caudigerum polysaccharides(HCPs). The average particle size and polydispersity index(PDI) were used as evaluation indexes for process optimization, and the quality of the final formulation was evaluated in terms of particle size, PDI, Zeta potential, and microstructure. The proposed Her-HCP SAN showed a spheroid structure and uniform morphology, with an average particle size of(244.58±16.84) nm, a PDI of 0.147 1±0.014 8, and a Zeta potential of(-38.52±2.11) mV. Her-HCP SAN significantly increased the saturation solubility of Her by 2.69 times, with a cumulative release of 90.18% within eight hours. The results of in vivo unidirectional intestinal perfusion reveal that Her active pharmaceutical ingredient(API) is most effectively absorbed in the jejunum, where both K_a and P_(app) are significantly higher compared to the ileum(P<0.001). However, the addition of HCP leads to a significant reduction in the P_(app) of Her in the jejunum(P<0.05). Furthermore, the formation of the Her-HCP SAN results in a notably lower P_(app) in the jejunum compared to Her API alone(P<0.001), while both K_a and P_(app) in the ileum are significantly increased(P<0.001, P<0.05). The absorption of Her-HCP SAN at different concentrations in the ileum shows no significant differences, and the pH has no significant effect on the absorption of Her-HCP SAN in the ileum. The addition of the transporter protein inhibitors(indomethacin and rifampicin) significantly increases the absorption parameters K_a and P_(app) of Her-HCP SAN in the ileum(P<0.05,P<0.01), whereas the addition of verapamil has no significant effect on the intestinal absorption parameters of Her-HCP SAN, suggesting that Her may be a substrate for multidrug resistance-associated protein 2 and breast cancer resistance proteins but not a substrate of P-glycoprotein.
Nanoparticles/metabolism* ; Polysaccharides/pharmacokinetics* ; Intestinal Absorption/drug effects* ; Animals ; Rats ; Particle Size ; Drugs, Chinese Herbal/pharmacokinetics* ; Male ; Rats, Sprague-Dawley ; Drug Carriers/chemistry* ; Drug Compounding ; Cucurbitaceae/chemistry*

Metal ion-promoted chemodynamic therapy(CDT) combined with photodynamic therapy(PDT) offers broad application prospects for enhancing anti-tumor effects. In this study, glycyrrhizic acid(GA), copper ions(Cu~(2+)), and norcantharidin(NCTD) were co-assembled to successfully prepare a natural small-molecule, carrier-free hydrogel(NCTD Gel) with excellent material properties. Under 808 nm laser irradiation, NCTD Gel responded to the tumor microenvironment(TME) and acted as an efficient Fenton reagent and photosensitizer, catalyzing the conversion of endogenous hydrogen peroxide(H_2O_2) within the tumor into oxygen(O_2), and hydroxyl radicals(·OH, type Ⅰ reactive oxygen species) and singlet oxygen(~1O_2, type Ⅱ reactive oxygen species), while depleting glutathione(GSH) to stabilize reactive oxygen species and alleviate tumor hypoxia. In vitro and in vivo experiments demonstrated that NCTD Gel exhibited significant CDT/PDT synergistic therapeutic effects. Further safety evaluation and metabolic testing confirmed its good biocompatibility and safety. This novel hydrogel is not only simple to prepare, safe, and cost-effective but also holds great potential for clinical transformation, providing insights and references for the research and development of metal ion-mediated hydrogel-based anti-tumor therapies.
Hydrogels/chemistry* ; Animals ; Photochemotherapy ; Humans ; Mice ; Antineoplastic Agents/administration & dosage* ; Photosensitizing Agents/chemistry* ; Neoplasms/metabolism* ; Female ; Copper/chemistry* ; Reactive Oxygen Species/metabolism* ; Tumor Microenvironment/drug effects* ; Cell Line, Tumor ; Male

During the decocting process of traditional Chinese medicine(TCM), molecules spontaneously form self-assembled nanoparticles(SAN) through intermolecular non-covalent interactions. This process effectively addresses the low bioavailability of poorly soluble components, becoming a research hotspot. However, SAN formed in traditional decoctions often exhibit low Zeta potential, poor stability, and easy aggregation, which limit their clinical applications. According to the extensive studies of SAN in TCM decoctions, this paper proposes innovative strategies of utilizing techniques such as micro-precipitation and pH-driven methods to improve SAN. These strategies significantly enhance the uniformity and stability of SAN and effectively increase the transfer rate of poorly soluble components, overcoming the technical bottlenecks of low stability and drug delivery efficiency in TCM decoctions. This article reviews the origins, advantages, and limitations of traditional SAN, discusses the strategies for improving SAN construction and characterization, and delves into the scientific issues that need to be addressed in future research. The aim is to provide new directions for the development of modern TCM preparations.
Nanoparticles/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Medicine, Chinese Traditional ; Drug Delivery Systems ; Animals ; Drug Compounding/methods*

This study aims to investigate the effect of Chaijin Jieyu Anshen Formula on the neuroinflammation of rats with insomnia complicated with depression through the regulation of triggering receptor expressed on myeloid cells 2(TREM2)/complement protein C1q signaling pathway. Rats were randomly divided into a normal group, a model group, a positive drug group, as well as a high, medium, and low-dose groups of Chaijin Jieyu Anshen Formula, with 10 rats in each group. Except for the normal group, the other groups were injected with p-chlorophenylalanine and exposed to chronic unpredictable mild stress to establish the rat model of insomnia complicated with depression. The sucrose preference experiment, open field experiment, and water maze test were performed to evaluate the depression in rats. Enzyme-linked immunosorbent assay was employed to detect serum 5-hydroxytryptamine(5-HT), dopamine(DA), and norepinephrine(NE) levels. Hematoxylin and eosin staining and Nissl staining were used to observe the damage in nucleus accumbens neurons. Western blot and immunofluorescence were performed to detect TREM2, C1q, postsynaptic density 95(PSD-95), and synaptophysin 1(SYN1) expressions in rat nucleus accumbens, respectively. Golgi-Cox staining was utilized to observe the synaptic spine density of nucleus accumbens neurons. The results show that, compared with the model group, Chaijin Jieyu Anshen Formula can significantly increase the sucrose preference as well as the distance and number of voluntary activities, shorten the immobility time in forced swimming test and the successful incubation period of positioning navigation, and prolong the stay time of space exploration in the target quadrant test. The serum 5-HT, DA, and NE contents in the model group are significantly lower than those in the normal group, with the above contents significantly increased after the intervention of Chaijin Jieyu Anshen Formula. In addition, Chaijin Jieyu Anshen Formula can alleviate pathological damages such as swelling and loose arrangement of tissue cells in the nucleus accumbens, while increasing the Nissl body numbers. Chaijin Jieyu Anshen Formula can improve synaptic damage in the nucleus accumbens and increase the synaptic spine density. Compared to the normal group, the expression of C1q protein was significantly higher in the model group, while the expression of TREM2 protein was significantly lower. Compared to the model group, the intervention with Chaijin Jieyu Anshen Formula significantly downregulated the expression of C1q protein and significantly upregulated the expression of TREM2. Compared with the model group, the PSD-95 and SYN1 fluorescence intensity is significantly increased in the groups receiving different doses of Chaijin Jieyu Anshen Formula. In summary, Chaijin Jieyu Anshen Formula can reduce the C1q protein expression, relieve the TREM2 inhibition, and promote the synapse-related proteins PSD-95 and SNY1 expression. Chaijin Jieyu Anshen Formula improves synaptic injury of the nucleus accumbens neurons, thereby treating insomnia complicated with depression.
Animals ; Male ; Rats ; Nucleus Accumbens/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Depression/complications* ; Membrane Glycoproteins/genetics* ; Rats, Sprague-Dawley ; Sleep Initiation and Maintenance Disorders/complications* ; Neurons/metabolism* ; Receptors, Immunologic/genetics* ; Signal Transduction/drug effects* ; Synapses/metabolism*

OBJECTIVE: To construct a prediction model for fracture reduction fixator therapy using the multi-modal multi-label classification (MMC) method. METHODS: Medical record data of 818 orthopedic patients from 2019 to 2023 were collected. Medical image features were extracted using the VGG19 network, text features of TCM four diagnostic methods (Inspection, Auscultation & Olfaction, Inquiry, Palpation) were extracted via the MiniLM model, and clinical case features were extracted through a fully connected neural network. After fusing the multi-modal information, multi-label therapy prediction was achieved using a linear layer. RESULTS: Experimental results on the clinical multi-modal dataset showed that the MMC method performed excellently in terms of subset accuracy(SA), accuracy(Acc), precision, and F₁-score, reaching 0.661, 0.856, 0.897, and 0.899 respectively. When the image modality and text modality were removed, the model performance decreased by an average of 8.1% and 2.4% respectively, while the hamming loss(HL) increased by 21.1% and 5.6% respectively. CONCLUSION The fracture reduction fixator therapy prediction model constructed in this study can effectively fuse multi-modal data, accurately predict personalized treatment plans for patients, and significantly improve the accuracy and reliability of treatment decisions. It provides a new solution for the digitalization and intellectualization of Traditional Chinese Medicine(TCM) in fracture treatment and has important clinical application prospects.
Humans ; Female ; Male ; Middle Aged ; Fracture Fixation/methods* ; Adult ; Fractures, Bone/surgery* ; Neural Networks, Computer ; Medicine, Chinese Traditional ; Aged

Aim To investigate the effect of quercetin on the aging model of bone marrow mesenchymal stem cells established under microgravity. Methods Using 3D gyroscope, a aging model of bone marrow mesenchymal stem cells was constructed, and after receiving quercetin and microgravity treatment, the anti-aging effect of the quercetin was evaluated by detecting related proteins and oxidation indexes. Results Compared to the control group, the expressions of age-related proteins p21, pi6, p53 and RB in the microgravity group significantly increased, while the expressions of cyclin D1 and lamin B1 significantly decreased, with statistical significance (P<0.05). In the microgravity group, mitochondrial membrane potential significantly decreased (P<0.05), ROS accumulation significantly increased (P <0.05), SOD content significantly decreased and MDA content significantly increased (P<0.05). Compared to the microgravity group, the expressions of age-related proteins p21, pi6, p53 and RB in the quercetin group significantly decreased, while the expressions of cyclin D1 and lamin B1 significantly increased, with statistical significance (P<0.05). In the quercetin group, mitochondrial membrane potential significantly increased (P<0.05), ROS accumulation significantly decreased (P<0.05), SOD content significantly increased and MDA content significantly decreased (P<0.05). Conclusions Quercetin can resist oxidation, protect mitochondrial function and normal cell cycle, thus delaying the aging of bone marrow mesenchymal stem cells induced by microgravity.

It has become an industry consensus that self-assembled nanoparticles (SAN) are formed by molecular recognition of chemical components in traditional Chinese medicine during the decoction process. The insoluble components in the decoction are mostly in the form of nanoparticles, which can improve the problem of poor water solubility. However, the transfer rate of these insoluble components in the decoction is still very low, which limits the efficacy of the drug. This study aimed to refine the traditional decoction self-assembly phenomenon. The self-assembled nanoparticles were constructed by micro-precipitation method (MP-SAN), and characterized by particle size, zeta potential, stability index and morphology. The formation of MP-SAN and alterations in related physicochemical properties were evaluated using modern spectroscopic and thermal analysis techniques. The quality value transmitting pattern of lignan components within the MP-SAN was assessed via high performance liquid chromatography (HPLC). The MP-SAN showed sphere-like structure with uniform morphology, particle size of (245.3 ± 3.2) nm, polydispersity index (PDI) of (0.13 ± 0.03), zeta potential of (-48.9 ± 5.9) mV and stability index (SI) of (86.05% ± 2.27%). Comprehensive analyses using ultraviolet visible spectroscopy, Fourier transform infrared spectroscopy, differential scanning calorimetry, and other techniques confirmed molecular recognition between the decoction and ethanol extraction, leading to electron rearrangement under the influence of non-covalent bonding. This resulted in the formation of nanoparticles possessing superior thermal stability. As determined by HPLC, the encapsulation rates of the index components in the MP-SAN were all greater than 75% (dehydrodiconiferyl alcohol: 77.00%; herpetolide A: 78.57%; herpetrione: 94.53%), and the transfer rates were all higher than 65% (dehydrodiconiferyl alcohol: 96.01%; herpetolide A: 67.86%; herpetrione: 65.55%), which were 1.34, 1.38 and 4.81 times compared with those of the traditional decoction. In summary, this study successfully constructed the MP-SAN based on micro-precipitation method to achieve high transfer rate and high encapsulation rate of insoluble components in docoction, which provides a pharmaceutics idea for the efficient utilization of pharmacodynamic substance basis of traditional Chinese medicine.

Osteoporosis is an important cause of internal fixation loosening after spinal surgery.Cement-augmented pedicle screw instru-mentation(CAPSI)technique is the most widely used technique in clinical practice to improve the stability of pedicle screw,mainly applied in osteoporosis and revision surgery,which included conventional solid pedicles crews and fenestrated/cannulated pedicle screws technique.CAPSI technique may cause cement leakage and pulmonary embolism,and there is no consensus on its indications or technical points.Therefore,this article reviews the research progress of CAPSI,in order to provide relevant reference for clinical practice.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.