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.

ObjectiveBased on ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， the chemical constituents of Qili Qiangxin capsules was identified， and their distribution in vivo was analyzed. MethodsUPLC-Q-Orbitrap-MS was used to detect the sample solution of Qili Qiangxin capsules， as well as the serum， brain， heart， lung， spleen， liver and kidney tissues of mice after oral administration. Using the Thermo Xcalibur 2.2 software， the compound information database was constructed， and the molecular formulas of compounds corresponding to the quasi-molecular ions were fitted. Based on the information of retention time， accurate relative molecular mass and fragments， the compounds and their distribution in vivo were analyzed by comparing with the data of reference substances and literature. ResultsA total of 233 compounds， including 70 terpenoids， 60 flavonoids， 23 organic acids， 17 alkaloids， 20 steroids， 7 coumarins and 36 others， were identified or predicted from Qili Qiangxin capsules， 73 of which were identified matching with standard substances. Tissue distribution results showed that 71， 17， 38， 33， 32， 58 and 43 migrating components were detected in blood， brain， heart， lung， spleen， liver and kidney， respectively. Thirty-seven components were absorbed into the blood and heart， including quinic acid， benzoylaconitine benzoylmesaconine and so on. Fourteen components were absorbed into the blood and six tissues， including calycosin， methylnissolin， formononetin， alisol B， alisol A and so on. ConclusionThis study comprehensively analyzes the chemical components of Qili Qiangxin capsules and their distribution in vivo. Among them， astragaloside Ⅳ， salvianolic acid B， ginsenoside Rb₁， ginsenoside Rb₃， ginsenoside Rd， ginsenoside Rg₃， calycosin-7-glucoside， and sinapine may be the important components for the treatment of heart failure， which can provide useful reference for its quality control and research on pharmacodynamic material basis.

Objective: To analyze the relationship between parental psychological control and Internet Gaming Disorder (IGD) among junior high school students, so as to provide evidence for preventing IGD development in adolescents. Methods: From August 2019 to February 2020, a survey was conducted among 1 169 junior high school students from three middle schools in Xian using stratified cluster sampling. The Parental Psychological Control Scale and IGD Scale were administered to assess parental psychological control and IGD prevalence. Univariate and binary Logistic regression analyses were used to explore IGD risk factors and their correlation with parental psychological control. Results: The detection rate of IGD in middle school students was 19.9%(184/1 169). Multivariate Logistic regression revealed that compared to those with lower parental psychological control scores(≤21 points), students with higher parental psychological control scores (>21 points) had a higher risk of IGD (OR=1.82, 95%CI=1.21-2.74), a 1.58fold higher risk of selfperceived gaming addiction (95%CI=1.07-2.30), as well as reduced likelihood of seeking external help to reduce gaming time (OR=0.66, 95%CI=0.47-0.94) (P<0.05). Conclusions Parental psychological control may elevate the risks of IGD and selfperceived addiction while diminishing proactive helpseeking behaviors to reduce gaming time. Parents should enhance communication with adolescents and provide positive guidance to mitigate potential gamingrelated harms.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

ObjectiveTo study the correlations between traditional Chinese medicine （TCM） syndromes and lipid metabolism in children with Wilson disease （WD）. MethodsClinical data and lipid metabolism indicators ［total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， apolipoprotein A1 （ApoA1）， apolipoprotein B （ApoB）， and lipoprotein a （Lpa）］ were retrospectively collected from 341 children with WD. The clinical data were compared among WD children with different syndromes， and the correlations between TCM syndromes and lipid metabolism in children with WD were analyzed. Least absolute shrinkage and selection operator （LASSO） regression was used for variable screening， and unordered multinomial Logistic regression was employed to analyze the effects of lipid metabolism indicators on TCM syndromes. ResultsThe 341 children with WD included 121 （35.5%） children with the dampness-heat accumulation syndrome， 103 （30.2%） children with the liver-kidney Yin deficiency syndrome， 68 children with the combined phlegm and stasis syndrome， 29 children with the spleen-kidney Yang deficiency syndrome， and 20 children with the liver qi stagnation syndrome. The liver-kidney Yin deficiency syndrome， combined phlegm and stasis syndrome， and spleen-kidney Yang deficiency syndrome had correlations with the levels of lipid metabolism indicators （P<0.05）. Lipid metabolism abnormalities occurred in 232 （68.0%） children， including hypertriglyceridemia （108）， hypercholesterolemia （23）， mixed hyperlipidemia （67）， lipoprotein a-hyperlipoproteinemia （12）， and hypo-HDL-cholesterolemia （22）. The percentages of hypertriglyceridemia and hypo-HDL-cholesterolemia varied among children with different TCM syndromes （P<0.05）. Correlations existed for the liver-kidney Yin deficiency syndrome with TG， TC， and HDL-C， the combined phlegm and stasis syndrome with TG， the spleen-kidney Yang deficiency syndrome with TG， TC， and LDL-C， and the liver Qi stagnation syndrome with TC and LDL-C （P<0.05， P<0.01）. ConclusionThe TCM syndromes of children with WD are dominated by the dampness-heat accumulation syndrome and the liver-kidney Yin deficiency syndrome， and dyslipidemia in the children with WD is dominated by hypertriglyceridemia and mixed hyperlipidemia. There are different correlations between TCM syndromes and lipid metabolism indicators， among which TG， TC， LDL-C， and HDL-C could assist in identifying TCM syndromes in children with WD.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE: To observe the efficacy of "Biaoben acupoint compatibility" moxibustion for abdominal obesity and its effect on blood lipid, lipid accumulation product (LAP) and cardiometabolic index (CMI). METHODS: A total of 150 patients with abdominal obesity were randomly divided into an observation group (75 cases, 5 cases dropped out) and a control group (75 cases, 6 cases dropped out). The control group received lifestyle guidance. The observation group received "Biaoben acupoint compatibility" moxibustion at Zhongwan (CV12), Guanyuan (CV4) and bilateral Tianshu (ST25), Zusanli (ST36) on the basis of the control group, 20 min each time, once every other day, 3 times a week for 8 weeks. Before and after treatment, the waist circumference, hip circumference, weight, body mass index (BMI) were observed, the levels of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were measured, and the LAP and CMI were calculated in the two groups. RESULTS: After treatment, the waist circumference, weight and BMI were decreased compared with those before treatment in both groups (P<0.05), the changes of the above indexes in the observation group were larger than those in the control group (P<0.05). After treatment, the hip circumference, TC level, TG level, LAP and CMI in the observation group were decreased compared with those before treatment (P<0.05), the HDL-C level was increased compared with that before treatment (P<0.05)；the changes of the TC level, TG level, LAP, CMI and HDL-C level in the observation group were larger than those in the control group (P<0.05). CONCLUSION "Biaoben acupoint compatibility" moxibustion can reduce the degree of obesity in patients with abdominal obesity, and improve blood lipid and reduce lipid accumulation.
Humans ; Acupuncture Points ; Moxibustion ; Male ; Female ; Middle Aged ; Obesity, Abdominal/blood* ; Adult ; Lipids/blood* ; Lipid Metabolism ; Triglycerides/blood* ; Young Adult ; Treatment Outcome ; Aged

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

BACKGROUND: Pancreatic cancer is a lethal malignancy prone to gemcitabine resistance. The single-strand selective monofunctional uracil DNA glycosylase (SMUG1), which is responsible for initiating base excision repair, has been reported to predict the outcomes of different cancer types. However, the function of SMUG1 in pancreatic cancer is still unclear. METHODS: Gene and protein expression of SMUG1 as well as survival outcomes were assessed by bioinformatic analysis and verified in a cohort from Fudan University Shanghai Cancer Center. Subsequently, the effect of SMUG1 on proliferation, cell cycle, and migration abilities of SMUG1 cells were detected in vitro . DNA damage repair, apoptosis, and gemcitabine resistance were also tested. RNA sequencing was performed to determine the differentially expressed genes and signaling pathways, followed by quantitative real-time polymerase chain reaction and Western blotting verification. The cancer-promoting effect of forkhead box Q1 (FOXQ1) and SMUG1 on the ubiquitylation of myelocytomatosis oncogene (c-Myc) was also evaluated. Finally, a xenograft model was established to verify the results. RESULTS: SMUG1 was highly expressed in pancreatic tumor tissues and cells, which also predicted a poor prognosis. Downregulation of SMUG1 inhibited the proliferation, G1 to S transition, migration, and DNA damage repair ability against gemcitabine in pancreatic cancer cells. SMUG1 exerted its function by binding with FOXQ1 to activate the Protein Kinase B (AKT)/p21 and p27 pathway. Moreover, SMUG1 also stabilized the c-Myc protein via AKT signaling in pancreatic cancer cells. CONCLUSIONS SMUG1 promotes proliferation, migration, gemcitabine resistance, and c-Myc protein stability in pancreatic cancer via protein kinase B signaling through binding with FOXQ1. Furthermore, SMUG1 may be a new potential prognostic and gemcitabine resistance predictor in pancreatic ductal adenocarcinoma.
Humans ; Pancreatic Neoplasms/pathology* ; Forkhead Transcription Factors/genetics* ; Signal Transduction/genetics* ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation/physiology* ; Mice ; Uracil-DNA Glycosidase/genetics* ; Female ; Male ; Gemcitabine ; Mice, Nude ; Apoptosis/physiology* ; Deoxycytidine/analogs & derivatives* ; Cell Movement/genetics*