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.

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.

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.

Ischemic stroke (IS) ranks as a leading cause of death and disability globally. The blood-brain barrier (BBB) poses significant challenges for effective drug delivery to brain tissues. Recent decades have seen the development of targeted nanomedicine and biomimetic technologies, sparking substantial interest in biomimetic drug delivery systems for treating IS. These systems are devised by utilizing or replicating natural cells and their derivatives, offering promising new pathways for detection and transport across the BBB. Their multifunctionality and high biocompatibility make them effective treatment options for IS. In addition, the incorporation of engineering techniques has provided these biomimetic drug delivery systems with active targeting capabilities, enhancing the accumulation of therapeutic agents in ischemic tissues and specific cell types. This improvement boosts drug transport and therapeutic efficacy. However, it is crucial to thoroughly understand the advantages and limitations of various engineering strategies employed in constructing biomimetic delivery systems. Selecting appropriate construction methods based on the characteristics of the disease is vital to achieving optimal treatment outcomes. This review summarizes recent advancements in three types of engineered biomimetic drug delivery systems, developed from natural cells and their derivatives, for treating IS. It also discusses their effectiveness in application and potential challenges in future clinical translation.
Humans ; Drug Delivery Systems/methods* ; Ischemic Stroke/drug therapy* ; Animals ; Blood-Brain Barrier/metabolism* ; Stroke/drug therapy*

A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity. However, regulatory mechanisms at the translational level under cardiac stress remain poorly understood. Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction (TAC) and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy (DCM). The results showed that the heart weight to body weight ratio was significantly elevated, and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC. Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle. RNA-seq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling, metabolic processes, and signaling cascades associated with pathological cardiomyocyte growth. When combined with ribosome profiling analysis, we revealed that translation efficiency (TE) of 1,495 genes was enhanced, while the TE of 933 genes was inhibited following TAC. In DCM patients, 1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level. Although the majority of the genes were not shared between mouse and human, we identified 93 genes, including Nos3, Kcnj8, Adcy4, Itpr1, Fasn, Scd1, etc., with highly conserved translational regulations. These genes were remarkably associated with myocardial function, signal transduction, and energy metabolism, particularly related to cGMP-PKG signaling and fatty acid metabolism. Motif analysis revealed enriched regulatory elements in the 5' untranslated regions (5'UTRs) of transcripts with differential TE, which exhibited strong cross-species sequence conservation. Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.
Animals ; Humans ; Cardiomegaly/physiopathology* ; Ribosomes/physiology* ; Protein Biosynthesis/physiology* ; Mice ; Cardiomyopathy, Dilated/genetics* ; Ribosome Profiling

This study aims to investigate the ameliorating effect of Corni Fructus(CF) on the myocardial ischemic injury and the pharmacokinetic properties of characteristic components of CF. The mouse model of isoproterenol-induced myocardial ischemia was established and administrated with the aqueous extract of CF. The general efficacy of CF in ameliorating the myocardial ischemic injury was evaluated based on the cardiac histopathology and the levels of myocardial injury markers: creatine kinase isoenzyme(CK-MB) and cardiac troponin I(cTn-I). The metabolomics analysis was carried out for the heart and serum samples of mice to screen the biomarkers of CF in ameliorating the myocardial ischemic injury and then the predicted biomarkers were submitted to metabolic pathway enrichment. The pharmacokinetic analysis was performed for morroniside, loganin, and cornuside Ⅰ in mouse heart and serum samples to obtain the pharmacokinetic parameters of these components. The pharmacokinetic parameters were then integrated on the basis of self-defined weighting coefficients to simulate an integrated pharmacokinetic profile of CF iridoid glycosides in the heart and serum of the mouse model of myocardial ischemia. The results indicated that CF reduced the pathological damage to cardiac cells and tissue(hematoxylin-eosin staining) and lowered the levels of CK-MB and cTn-I in the serum of the mouse model of myocardial ischemia(P<0.01). Metabolomics analysis screed out 31 endogenous metabolites in the heart and 35 in the serum as biomarkers of CF in ameliorating the myocardial ischemic injury. These biomarkers were altered by modeling and restored by CF. Six metabolic pathways in the heart and 5 in the serum were enriched based on these metabolic markers. The main integrated pharmacokinetic parameters of CF iridoid glycosides were T_(max)=1 h, t_(1/2)=(1.52±0.05) h in the heart and T_(max)=1 h, t_(1/2)=(1.56±0.50) h in the serum. Both concentration-time curves showed a double-peak phenomenon. In conclusion, CF demonstrated the cardioprotective effect by regulating metabolic pathways such as taurine and hypotaurine metabolism, and pantothenic acid and coenzyme A biosynthesis. The integrated pharmacokinetics reflect the general pharmacokinetic properties of characteristic components in CF.
Animals ; Cornus/chemistry* ; Mice ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Myocardial Ischemia/metabolism* ; Humans ; Troponin I/metabolism* ; Myocardium/pathology* ; Disease Models, Animal ; Biomarkers/metabolism* ; Creatine Kinase, MB Form/metabolism*

This study investigated the mechanism of Croci Stigma in treating immune checkpoint inhibitor(ICI)-associated myocarditis based on network pharmacology and molecular docking. Network pharmacology was employed to screen the active ingredients and molecular targets of Croci Stigma in treating ICI-associated myocarditis. The "drug-ingredient-target-disease" network and protein-protein interaction network were constructed to screen the key ingredients and core targets. Gene Ontology functional enrichment analysis showed that the mechanism was related to the regulation of inflammation and apoptosis. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the treatment was related to the advanced glycation end product-receptor for advanced glycation end products(AGE-RAGE) signaling pathway. Molecular docking result showed that crocins had close associations with RAC-alpha serine/threonine-protein kinase 1(AKT1), signal transducer and activator of transcription 3, and matrix metalloproteinase 9. Crocins were then selected as the therapeutic drug. The mouse model of ICI-associated myocarditis was established by subcutaneous injection of porcine cardiac myosin combined with intraperitoneal injection of pembrolizumab. The results suggested that Croci Stigma reduced the spleen index but had no effect on the heart index. The electrocardiogram showed that Croci Stigma increased the heart rate and shortened PR and QRS intervals. Echocardiographic data indicated that Croci Stigma increased the left ventricular stroke volume, cardiac output, ejection fraction, and fractional shortening. Hematoxylin-eosin and Masson staining results showed that Croci Stigma decreased the number of inflammatory cells infiltrating in the myocardium and alleviated myocardial fibrosis. Enzyme-linked immunosorbent assay results showed that Croci Stigma decreased the serum levels of inflammatory cytokines including tumor necrosis factor-alpha, interleukin-6, interleukin-12, and regulated on activation, normal T-cell expressed and secreted and lowered the levels of creatine kinase and creatine kinase isoenzyme MB. Biochemical data suggested that Croci Stigma inhibited the activities of superoxide dismutase and lactate dehydrogenase. Western blot result showed that Croci Stigma regulated the expression of myocardial AKT. The findings demonstrate that Croci Stigma may regulate AKT expression to effectively protect the cardiac tissue from ICI-associated myocarditis through antagonizing immune responses and inflammation, inhibiting oxidative stress, alleviating cardiac fibrosis, relieving cardiac block, and improving the cardiac function.
Animals ; Molecular Docking Simulation ; Myocarditis/metabolism* ; Immune Checkpoint Inhibitors/adverse effects* ; Mice ; Network Pharmacology ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Humans ; Protein Interaction Maps/drug effects*