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.

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.

This article discussed the evolution of the traditional preparation process of Pinelliae Rhizoma Fermentata.The production methods for Pinelliae Rhizoma Fermentata in Song Dynasty include cake-making of Pinelliae Rhizoma together with ginger juice and fermentation after cake-making,and the former method of cake-making was the mainstream.The process technology in Jin and Yuan Dynasties inherited from that in Song Dynasty,and the application of Pinelliae Rhizoma Fermentata had certain limitations.The medical practitioners of Ming Dynasty elucidated the mechanism of processing of Pinelliae Rhizoma Fermentata,and proposed the view of"sliced Pinelliae Rhizoma being potent while fermented Pinelliae Rhizoma being mild".In the Ming Dynasty,LI Shi-Zhen defined the cake-making process and fermentation process for Pinelliae Rhizoma,and HAN Mao's Han Shi Yi Tong(Han's Clear View of Medicine)contained five prescriptions for the processing of Pinelliae Rhizoma Fermentata,which had the epoch-making signficance in the expansion of prescriptions for the processing of Pinelliae Rhizoma Fermentata.In the Qing Dynasty,HAN Fei-Xia's ten methods for making Pinelliae Rhizoma Fermentata were summarized on the basis of the methods recorded in Han Shi Yi Tong,and at that time,the processing of Pinelliae Rhizoma Fermentata and the preparation of Massa Medicata Fermentata interacted with each other.After the founding of the People's Republic of China,the local experience in the preparation of Pinelliae Rhizoma Fermentata was deeply influenced by the methods in the Qing Dynasty,and the local preparation technical standards gradually became the same.Moreover,this article also explored the issues of the importance of"Pinelliae Rhizoma"and"ingredients for fermentation",the pre-treatment of Pinelliae Rhizoma,the distinction between cake-making process and fermentation process for Pinelliae Rhizoma,the amount of flour added as well as the timing of adding,the addition of Massa Medicata Fermentata powder,the role of Alum in Pinelliae Rhizoma Fermentata and so on.

Objective To explore the severity of loneliness among the elderly in communities in Shanghai,and to identify factors associated with social and emotional loneliness respectively.Methods A cross-sectional study was conducted in older adults aged 65 years or above in Pudong New Area,Jing'an District and Huangpu District in Shanghai from Mar to Jun 2021.In Pudong New Area,multi-stage stratified random sampling was conducted based on the age and gender distribution of Shanghai,while in Huangpu District and Jing'an District convenience sampling was conducted.A total of 635 samples were included in the study.Loneliness was assessed using the De Jong Gierveld Loneliness Scale with social and emotional loneliness subscales.Logistic regression analyses were conducted to identify factors associated with social and emotional loneliness.Results Among the 635 participants,only 53 older adults(8.4%)were not lonely.Female(OR=0.46,95%CI:0.31-0.70),higher self-efficacy(OR=0.97,95%CI:0.94-1.00),more objective social support(OR=0.96,95%CI:0.93-0.99)were associated with less severe social loneliness.Meanwhile,higher level of education(secondary education,OR=0.56,95%CI:0.34-0.95;college or above,OR=0.30,95%CI:0.11-0.83)and higher self-efficacy(OR=0.96,95%CI:0.93-0.99)were associated with less severe emotional loneliness,while depression(OR=3.41,95%CI:1.76-6.60)and worse social capital(OR=2.02,95%CI:1.29-3.16)were associated with more severe emotional loneliness.Conclusion Up to 91.6%of the elderly in our study sample were moderately lonely or above.The factors associated with social loneliness include self-efficacy,gender and social support.The factors associated with emotional loneliness are self-efficacy,education level,depression,and social capital.

OBJECTIVE: To investigate whether electroacupuncture (EA) at sensitized acupoints could reduce sympathetic-sensory coupling (SSC) and neurogenic inflammatory response by interfering with 5-hydroxytryptamine (5-HT)ergic neural pathways to relieve colitis and somatic referred pain, and explore the underlying mechanisms. METHODS: Rats were treated with 5% dextran sodium sulfate (DSS) solution for 7 days to establish a colitis model. Twelve rats were randomly divided into the control and model groups according to a random number table (n=6). According to the "Research on Rat Acupoint Atlas", sensitized acupoints and non-sensitized acupoints were determined. Rats were randomly divided into the control, model, Zusanli-EA (ST 36), Dachangshu-EA (BL 25), and Xinshu (BL 15) groups (n=6), as well as the control, model, EA, and EA + GR113808 (a 5-HT inhibitor) groups (n=6). The rats in the control group received no treatment. Acupuncture was administered on 2 days after modeling using the stimulation pavameters: 1 mA, 2 Hz, for 30 min, with sparse and dense waves, for 14 consecutive days. GR113808 was injected into the tail vein at 5 mg/kg before EA for 10 min for 7 consecutive days. Mechanical sensitivity was assessed with von Frey filaments. Body weight and disease activity index (DAI) scores of rats were determined. Hematoxylin and eosin staining was performed to observe colon histopathology. SSC was analyzed by immunofluorescence staining. Immunohistochemical staining was performed to detect 5-HT and substance P (SP) expressions. The calcitonin gene-related peptide (CGRP) in skin tissue and tyrosine hydroxylase (TH) protein levels in DRG were detected by Western blot. The levels of hyaluronic acid (HA), bradykinin (BK), prostaglandin I2 (PGI2) in skin tissue, 5-HT, tryptophan hydroxylase 1 (TPH1), serotonin transporters (SERT), 5-HT 3 receptor (5-HT3R), and 5-HT 4 receptor (5-HT4R) in colon tissue were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: BL 25 and ST 36 acupoints were determined as sensitized acupoints, and BL 15 acupoint was used as a non-sensitized acupoint. EA at sensitized acupoints improved the DAI score, increased mechanical withdrawal thresholds, and alleviated colonic pathological damage of rats. EA at sensitized acupoints reduced SSC structures and decreased TH and CGRP expression levels (P<0.05). Furthermore, EA at sensitized acupoints reduced BK, PGI2, 5-HT, 5-HT3R and TPH1 levels, and increased HA, 5-HT4R and SERT levels in colitis rats (P<0.05). GR113808 treatment diminished the protective effect of EA at sensitized acupoints in colitis rats (P<0.05). CONCLUSION EA at sensitized acupoints alleviated DSS-induced somatic referred pain in colitis rats by interfering with 5-HTergic neural pathway, and reducing SSC inflammatory response.
Rats ; Animals ; Electroacupuncture ; Rats, Sprague-Dawley ; Serotonin ; Acupuncture Points ; Pain, Referred ; Calcitonin Gene-Related Peptide ; Signal Transduction ; Colitis/therapy* ; Indoles ; Sulfonamides

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Objective To establish a population pharmacokinetic(PPK)model of duloxetine in Chinese subjects.Methods Based on the data of intensive sampling of duloxetine hydrochloride enteric coated tablets in 36 healthy subjects after single/multiple administrations,a PPK model of duloxetine was established using NONMEM software.The effects of gender,age,body weight,albumin,serum creatinine,glutamic pyruvic transaminase and dose on pharmacokinetic parameters were investigated by stepwise forward and backward methods.Model validation includes goodness of fit,visual prediction check and bootstrap.Results The PPK model of duloxetine was a one compartment model with first-order elimination and the absorption characteristics were described by the transit model,and the dose was a covariate of clearance.The inter-individual variability of clearance,volume of distribution,mean transit time and number of transit compartments were 54.71％,56.86％,27.30％and 87.71％,respectively.Conclusion The transit model more reasonably describes the absorption characteristics of duloxetine in Chinese subjects.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

AIM To study the extraction process,enzymatic properties and practical application of glucuronic hydrolase in Scutellaria baicalensis stems and leaves(sbsl GUS).METHODS With granularity,water consumption,extraction time and extraction frequency as influencing factors,enzymatic activity as an evaluation index,the extraction process was optimized by orthogonal test on the basis of single factor test.The relationship between substrate(baicalin)concentration and enzymolysis rate,after which Vmax and Km were calculated,the effects of pH value,temperature and metal ion on enzymatic activity were investigated,pH stability and heat stability were evaluated.sbsl GUS was adotped in the enzymolysis of baicalin to prepare baicalein,then the effects of pH value,temperature,reaction time,initial substrate concentration and enzyme addition on transfer rate were investigated.RESULTS The optimal extraction process was determined to be 40 mesh for granularity,10 times for water consumption,15 min for extraction time,and 3 times for extraction frequency.The enzymolysis accorded with the kinetics of enzymatic reaction,Km was 0.006 3 mol/L,Vmax was 70.42 μmol/h,the strongest enzymatic activity was found at the pH value of 6.0,temperature of 45℃and metal ion of 100 mmol/L Cu2+,sbsl GUS demonstrated good stability at the ranges of 4.0-7.0 for pH value and 4-30℃for temperature.The optimal preparation process was determined to be 6.0 for pH value,45℃for temperature,more than 12 h for reaction time,67.2 mmol/L for initial substrate concentration,and 1 mL/0.269 mmol baicalin for enzyme addition,the transfer rate was 97.83%.CONCLUSION sbsl GUS enzymolysis exhibits high efficiency and mild condition,which can provide a simple preparation method for obtaining baicalein,and expand the application path of Scutellaria baicalensis stems and leaves.