During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

ObjectiveTo evaluate the efficacy of Shexiang Baoxinwan in treating stable angina pectoris with Qi stagnation and blood stasis syndrome in patients with coronary artery disease （CAD） complicated with anxiety and depression and explore its underlying mechanisms. MethodsThis study employed a randomized， double-blind， and placebo-controlled clinical trial design. Patients admitted to the hospital were randomly assigned to the observation group and the control group， with 52 patients in each group. Patients in the observation and control groups received Shexiang Baoxinwan and placebo， respectively， both in combination with conventional Western medication. The dose was 45.0 mg， three times daily， for a total duration of eight weeks. The primary outcome was the Seattle Angina Questionnaire （SAQ） scores before and after treatment. Secondary outcomes included changes in traditional Chinese medicine （TCM） syndrome score， the patient health questionnaire-9 （PHQ-9）， generalized anxiety disorder-7 （GAD-7）， inflammatory markers ［interleukin-18 （IL-18）， interleukin-10 （IL-10）， tumor necrosis factor-alpha （TNF-α）， CD40， etc.］， monoamine neurotransmitters ［e.g.， dopamine （DA）］， vascular endothelial function markers ［e.g.， endothelin-1（ET-1）］， adipokines， and ischemia-modified albumin （IMA）. Adverse reactions were also recorded. ResultsA total of 92 patients completed the study， with 44 in the observation group and 48 in the control group. Compared with baseline， both groups showed significant decreases in PHQ-9， GAD-7， and TCM syndrome scores following treatment （P<0.05）， along with a significant increase in SAQ scores （P<0.05）. In the observation group， DA levels were significantly increased （P<0.05）， while levels of IL-18， TNF-α， CD40， ET-1， and IMA were decreased （P<0.05）. In contrast， the control group exhibited significantly increased CD40 levels （P<0.05）. Compared with the control group after treatment， the observation group showed significant improvements in the SAQ dimensions of physical limitation， angina stability， treatment satisfaction， and disease perception， as well as in TCM syndrome score， PHQ-9 score， IL-18， CD40， ET-1， and IMA （P<0.05）. No adverse reactions were observed in either group during treatment. ConclusionShexiang Baoxinwan can improve anxiety and depression， alleviate angina symptoms， and reduce TCM symptoms of Qi stagnation and blood stasis in CAD patients. The mechanism may involve anti-inflammation， improvement of vascular endothelial function， reduction of IMA， and increase of monoamine neurotransmitter levels.

ObjectiveTo evaluate the efficacy of Shexiang Baoxinwan in treating stable angina pectoris with Qi stagnation and blood stasis syndrome in patients with coronary artery disease （CAD） complicated with anxiety and depression and explore its underlying mechanisms. MethodsThis study employed a randomized， double-blind， and placebo-controlled clinical trial design. Patients admitted to the hospital were randomly assigned to the observation group and the control group， with 52 patients in each group. Patients in the observation and control groups received Shexiang Baoxinwan and placebo， respectively， both in combination with conventional Western medication. The dose was 45.0 mg， three times daily， for a total duration of eight weeks. The primary outcome was the Seattle Angina Questionnaire （SAQ） scores before and after treatment. Secondary outcomes included changes in traditional Chinese medicine （TCM） syndrome score， the patient health questionnaire-9 （PHQ-9）， generalized anxiety disorder-7 （GAD-7）， inflammatory markers ［interleukin-18 （IL-18）， interleukin-10 （IL-10）， tumor necrosis factor-alpha （TNF-α）， CD40， etc.］， monoamine neurotransmitters ［e.g.， dopamine （DA）］， vascular endothelial function markers ［e.g.， endothelin-1（ET-1）］， adipokines， and ischemia-modified albumin （IMA）. Adverse reactions were also recorded. ResultsA total of 92 patients completed the study， with 44 in the observation group and 48 in the control group. Compared with baseline， both groups showed significant decreases in PHQ-9， GAD-7， and TCM syndrome scores following treatment （P<0.05）， along with a significant increase in SAQ scores （P<0.05）. In the observation group， DA levels were significantly increased （P<0.05）， while levels of IL-18， TNF-α， CD40， ET-1， and IMA were decreased （P<0.05）. In contrast， the control group exhibited significantly increased CD40 levels （P<0.05）. Compared with the control group after treatment， the observation group showed significant improvements in the SAQ dimensions of physical limitation， angina stability， treatment satisfaction， and disease perception， as well as in TCM syndrome score， PHQ-9 score， IL-18， CD40， ET-1， and IMA （P<0.05）. No adverse reactions were observed in either group during treatment. ConclusionShexiang Baoxinwan can improve anxiety and depression， alleviate angina symptoms， and reduce TCM symptoms of Qi stagnation and blood stasis in CAD patients. The mechanism may involve anti-inflammation， improvement of vascular endothelial function， reduction of IMA， and increase of monoamine neurotransmitter levels.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Twelve compounds were isolated from the ethyl acetate fraction of the 80% aqueous ethanol extract of the roots and stems of Dalbergia rimosa Roxb. by silica gel, MCI, Sephadex LH-20 column chromatography, and semi-preparative HPLC. Their structures were identified by spectral analysis such as UV, IR, MS, 1D/2D NMR and by comparison with literature information as dalbergiquinol A (1), dalbergiquinol B (2), R-(-)-3′-hydroxy-2,4,5-trimethoxydalbergiquinol (3), neokhriol A (4), mucronulatol (5), (3R)-7,2′,3′-trihydroxy-4′-methoxy-isoflavane (6), isomucronulatol (7), (3S)-violanone (8), 3′-O-methylviolanone (9), eryvarin M (10), (±)-α,3,4,2′,4′-pentahydroxydihydrochalcone (11) and (-)-butin (12). Compound 1 and 2 are new compounds, and compounds 3-12 were isolated from this plant for the first time. Compounds 1, 2, 4, 6, 8, 11, 12 showed good scavenging effect on DPPH free radical.

Tumor cells use glycolysis to provide material and energy under hypoxic conditions to meet the energy requirements for rapid growth and proliferation， namely the Warburg effect. Even under aerobic conditions， tumor cells mainly rely on glycolysis to provide energy. Therefore， glucose transporter protein 1（GLUT1）， which is involved in the process of glucose metabolism， plays an important role in tumorigenesis， development and drug resistance， and is considered to be one of the important targets in the treatment of malignant tumors. In recent years， research on tumor glucose metabolism has gradually become a hot spot. It has been shown that various factors are involved in the regulation of tumor energy metabolism， among which the role of GLUT1 is the most critical. In this paper， the authors reviewed the latest research progress of GLUT1-targeted traditional Chinese medicine（TCM） active ingredient nano-delivery system in tumor therapy， aiming to reveal the feasibility and effectiveness of this system in the delivery of chemotherapeutic drugs. The GLUT1-targeted TCM active ingredient nano-delivery system can overcome the bottleneck of the traditional targeting strategy as well as the high-permeability long retention（EPR） effect. In summary， the authors believe that the GLUT1-targeted TCM active ingredient nano-delivery system provides a new strategy for targeted treatment of tumors and has a broad application prospect in tumor prevention and treatment.