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.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Objective To investigate the relationship between brain white matter lesions (WML) and triglyceride glucose (TyG) index in non-diabetic elderly individuals based on magnetic resonance imaging. Methods A total of 523 non-diabetic elderly individuals aged ≥ 60 years were selected from Jinan, Shandong Province, China from June 2018 to December 2019. According to the quartiles of TyG index, there were 133 participants in the first quartile (Q1) group, 127 in the second quartile (Q2) group, 132 in the third quartile (Q3) group, and 131 in the fourth quartile (Q4) group. All participants underwent brain magnetic resonance imaging to evaluate paraventricular, deep, and total WML volumes, as well as Fazekas scores. Results Compared with Q1, Q2, and Q3 groups, Q4 group showed significant increase in periventricular, deep, and total WML volumes (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in the periventricular, deep, and total WML was higher in the Q4 group compared with the Q1 and Q2 groups (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in deep WML was higher in Q4 group than in Q3 group (P < 0.05). TyG index was significantly positively correlated with periventricular, deep, and total WML volumes (r = 0.401, 0.405, and 0.445, P < 0.001). After adjusting for confounding factors, TyG index was still significantly positively correlated with periventricular, deep, and total WML volumes (P < 0.001). Logistic regression analysis showed that compared with Q1 group, the risk of Fazekas score ≥ 2 in periventricular WML was 1.950-fold (95% confidence interval [CI]: 1.154-3.294, P = 0.013) in Q3 group and 3.411-fold (95% CI: 1.984-5.863, P < 0.001) in Q4 group, the risk of Fazekas score ≥ 2 in total WML was 2.529-fold (95%CI: 1.444-4.430, P = 0.001) in Q3 group and 4.486-fold (95%CI: 2.314-8.696, P < 0.001) in Q4 group. The risk of Fazekas score ≥ 2 in deep WML was 2.953-fold (95%CI: 1.708-5.106, P < 0.001) in Q4 group compared with Q1 group. Conclusion Increased TyG index is an independent risk factor for WML in non-diabetic elderly individuals.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Diabetic cardiomyopathy is a distinct form of cardiomyopathy that can lead to heart failure, arrhythmias, cardiogenic shock, and sudden death. It has become a major cause of mortality in diabetic patients. The pathogenesis of diabetic cardiomyopathy is complex, involving increased oxidative stress, activation of inflammatory responses, disturbances in glucose and lipid metabolism, accumulation of advanced glycation end products (AGEs), abnormal autophagy and apoptosis, insulin resistance, and impaired intracellular Ca²⁺ homeostasis. Recent studies have shown that adenosine monophosphate-activated protein kinase (AMPK) plays a crucial protective role by lowering blood glucose levels, promoting lipolysis, inhibiting lipid synthesis, and exerting antioxidant, anti-inflammatory, anti-apoptotic, and anti-ferroptotic effects. It also enhances autophagy, thereby alleviating myocardial injury under hyperglycemic conditions. Consequently, AMPK is considered a key protective factor in diabetic cardiomyopathy. As part of diabetes prevention and treatment strategies, both pharmacological and exercise interventions have been shown to mitigate diabetic cardiomyopathy by modulating the AMPK signaling pathway. However, the precise regulatory mechanisms, optimal intervention strategies, and clinical translation require further investigation. This review summarizes the role of AMPK in the prevention and treatment of diabetic cardiomyopathy through drug and/or exercise interventions, aiming to provide a reference for the development and application of AMPK-targeted therapies. First, several classical AMPK activators (e.g., AICAR, A-769662, O-304, and metformin) have been shown to enhance autophagy and glucose uptake while inhibiting oxidative stress and inflammatory responses by increasing the phosphorylation of AMPK and its downstream target, mammalian target of rapamycin (mTOR), and/or by upregulating the gene expression of glucose transporters GLUT1 and GLUT4. Second, many antidiabetic agents (e.g., teneligliptin, liraglutide, exenatide, semaglutide, canagliflozin, dapagliflozin, and empagliflozin) can promote autophagy, reverse excessive apoptosis and autophagy, and alleviate oxidative stress and inflammation by enhancing AMPK phosphorylation and its downstream targets, such as mTOR, or by increasing the expression of silent information regulator 1 (SIRT1) and peroxisome proliferator-activated receptor‑α (PPAR‑α). Third, certain anti-anginal (e.g., trimetazidine, nicorandil), anti-asthmatic (e.g., farrerol), antibacterial (e.g., sodium houttuyfonate), and antibiotic (e.g., minocycline) agents have been shown to promote autophagy/mitophagy, mitochondrial biogenesis, and inhibit oxidative stress and lipid accumulation via AMPK phosphorylation and its downstream targets such as protein kinase B (PKB/AKT) and/or PPAR‑α. Fourth, natural compounds (e.g., dihydromyricetin, quercetin, resveratrol, berberine, platycodin D, asiaticoside, cinnamaldehyde, and icariin) can upregulate AMPK phosphorylation and downstream targets such as AKT, mTOR, and/or the expression of nuclear factor erythroid 2-related factor 2 (Nrf2), thereby exerting anti-inflammatory, anti-apoptotic, anti-pyroptotic, antioxidant, and pro-autophagic effects. Fifth, moderate exercise (e.g., continuous or intermittent aerobic exercise, aerobic combined with resistance training, or high-intensity interval training) can activate AMPK and its downstream targets (e.g., acetyl-CoA carboxylase (ACC), GLUT4, PPARγ coactivator-1α (PGC-1α), PPAR-α, and forkhead box protein O3 (FOXO3)) to promote fatty acid oxidation and glucose uptake, and to inhibit oxidative stress and excessive mitochondrial fission. Finally, the combination of liraglutide and aerobic interval training has been shown to activate the AMPK/FOXO1 pathway, thereby reducing excessive myocardial fatty acid uptake and oxidation. This combination therapy offers superior improvement in cardiac dysfunction, myocardial hypertrophy, and fibrosis in diabetic conditions compared to liraglutide or exercise alone.

Aim To investigate the effect of quercetin(Que)on podocyte inflammatory injury and the under-lying mechanism.Methods MPC5 cells were divided into normal glucose group(NG),mannitol group(MA),high glucose group(HG)and high glucose+quercetin group(HG+Que).Cell proliferation and apoptosis were detected by CCK-8 and flow cytometry.The expression of SIRT1,STAT3,apoptosis-related proteins(Bax,Bcl-2,caspase-3)and pyroptosis pro-tein GSDME was detected by Western blot.The ex-pression levels of inflammatory factors(IL-6,TNF-α,IL-18,IL-1β)in cell supernatants were detected by ELISA.Then small interfering RNA technology was used to knockdown SIRT1 expression.To further eval-uate the biological significance of SIRT1 in response to high glucose and Que treatment,negative control group(HG+si-NC+Que)and SIRT1 interference group(HG+si-SIRT1+Que)were added in the presence of high glucose and Que.Results Compared with the high glucose group,40 μmol·L-1 Que could alleviate the apoptosis of MPC5 cells induced by high glucose,decrease the expression of apoptosis related protein Bax and caspase-3,as well as increase the expression of anti-apoptotic protein Bcl-2;ELISA results showed that Que could decrease the expression of TNF-α,IL-6,IL-1 β and IL-18 induced by high glucose.Mechanical-ly,Que could alleviate the inhibitory effect of high glu-cose on the expression of SIRT1,and further decrease the activation of STAT3 and N-GSDME,and inhibit pyroptosis.Compared with the si-NC group,si-SIRT1 group could reverse the protective effect of Que on the high glucose induced inflammatory damage of podo-cytes,the expression of apoptotic proteins Bax and caspase-3 increased,while the expression of anti-apop-totic protein Bcl-2 decreased.At the same time,the levels of inflammatory cytokines TNF-α,IL-6,IL-1 βand IL-18 in supernatants increased,and the expres-sion of STAT3 and N-GSDME increased.Conclusion Que could inhibit pyroptosis and relieve the inflam-matory damage of podocytes through SIRT1/STAT3/GSDME pathway.

Aim To study the main active ingredients,key targets and pathways of Cigu Xiaozhi Decoction(CXD)based on network pharmacology,and to ana-lyze and verify the mechanism of CXD on the transfor-mation of"inflammatory cancer"in non-alcoholic steatohepatitis(NASH)by animal experiments.Meth-ods The potential targets and signaling pathways of CXD in the treatment of NASH"inflammatory carcino-ma"were predicted based on network pharmacology.The mouse model of NASH was induced by methionine-choline deficiency diet(MCD),and CXD and epider-mal growth factor receptor(EGFR)inhibitors were given for 28 days.The mice were killed after the inter-vention,and the liver histopathology of each group was observed by hematoxylin-eosin method(HE).The rel-ative expression levels of EGFR,phosphatidylinositol 3-kinase(PI3K)and protein kinase B(AKT)in liver tissue of mice in each group were detected by Western blot.The contents of interleukin-6(IL-6),interleu-kin-1 β(IL-1β)and tumor necrosis factor-α(TNF-α)in serum were detected by enzyme-linked immunosor-bent assay(ELISA).Results A total of 284 poten-tial active components,159 potential therapeutic tar-gets and 20 key targets of CXD were identified by net-work pharmacological screening.CXD could affect multiple biological processes such as cell proliferation and inflammatory response,involving multiple signa-ling pathways such as tumor and PI3K/AKT.Animal experiments showed that CXD could reduce the levels of IL-6,IL-1β and TNF-α in serum of NASH mice.The relative expression of PI3K and AKT protein in liv-er tissue decreased,and the relative expression of EG-FR protein was increased.Conclusion CXD can reg-ulate EGFR/PI3K/AKT signaling pathway by partici-pating in biological processes such as cell proliferation and inflammatory response,and improve liver tissue injury in NASH mice.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.