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.

This study aimed to investigate the therapeutic effects of Morinda officinalis iridoid glycosides (MOIG) on bone loss of rheumatoid arthritis (RA) rats, and the mechanism of osteoclast function and activity induced by lipopolysaccharide (LPS). RA rats were established by injecting bovin type II collagen. The Bio-ethic Committee of Zhejiang Chinese Medical University approved all experimental protocols associated with this study (IACUC-20180410-03). The collagen-induced arthritis (CIA) rats were administered drug by gavage for 8 weeks; the femoral trabecular micro-structure changes were observed in CIA rats by micro-CT; the LPS-induced osteoclasts model further observed the effect and mechanism of anti-inflammatory osteoporosis in vitro. The results indicated that MOIG could markedly increase bone mineral density (BMD) in CIA rats, improve trabecular micro-structure. In vitro studies demonstrated that MOIG could significantly inhibit osteoclastogensis and differentiation, suppress tartrate resistant acid phosphatase (TRAP) activity, F-actin ring formation, TNF receptor associated factor 6 (TRAF6) recruitment, and inhibitor of nuclear factor kappa-Bα (IκBα) degradation as well as p65 phosphorylation, thereby repressing nuclear factor kappa-B (NF-κB) signaling pathway activation. Subsequently, MOIG effectively inhibited osteoclast nuclear factor of activated T-cells c1 (NFATc1) and cellular oncogene Fos (c-Fos) expression, as well as bone resorption related protein activity including matrix metalloprotein 9 (MMP-9) and cathepsin K (CtsK). Meanwhile, MOIG also repressed the phosphorylation expression of Janus activating kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3), thereby inhibiting JAK2/STAT3 signaling pathway activation. Moreover, further studies found that MOIG could suppress glycogen synthase kinase-3β (GSK-3β) activity, and GSK-3β gene silencing could markedly inhibit oetsoclast F-actin ring formation as well as the phosphorylation expression of p65 and STAT3. Of note, compared with GSK-3β gene silencing group, there was no significant difference in the group treated with both MOIG with GSK-3β gene silencing simultaneously. Thus, the results suggested that MOIG may inhibit NF-κB signaling pathway and JAK2/STAT3 signaling pathway activation via regulating GSK-3β, thereby alleviating bone destruction in RA.

The gene GeDRP1E encoding dynamin-related protein 1E in Gastrodia elata was cloned by specific primers which were designed based on the transcriptome data of G. elata. Bioinformatics analysis on GeDRP1E gene was carried out by using ExPASy, ClustalW, MEGA, etc. Positive transgenic Arabidopsis plant and potato minituber were obtained with the genetic transformation system of Arabidopsis and potato. The plant height and seed setting rate of transgenic Arabidopsis, and agronomic characters, such as size, weight and starch content of potato minituber of transgenic potato were tested and analyzed. And GeDRP1E gene function was preliminarily investigated. The results showed that the open reading frame of GeDRP1E gene was 1 899 bp in length and 632 amino acids residues were encoded, with a relative molecular weight of 69.90 kDa and a molecular formula of C₃₀₇₉H₄₉₇₃N₈₈₃O₉₃₃S₁₉. It was predicted that the theoretical isoelectric point was 7.27, the instability coefficient was 43.34, and the average hydrophilicity index was -0.259, which was indicative of an unstable hydrophilic protein. GeDRP1E has no transmembrane structure and signal peptide, and was localized in the cytoplasm. The phylogenetic tree showed that GeDRP1E was highly homologous with DRP1E proteins of other plant species, among which GeDRP1E had the highest homology with DcDRP1E (XP_020689662.1) in Dendrobium candidum, reaching 90.05%. GeDRP1E plant expression vector pCambia1300-35Spro-GeDRP1E was constructed by double digests, and Arabidopsis complementary mutant and potato overexpression strain of GeDRP1E gene were obtained by Agrobacterium-mediated gene transformation. Compared with the Arabidopsis AtDRP1E mutant, the height and seed setting rate of the GeDRP1E complementation mutant were rescued. The minituber of GeDRP1E overexpression potato had larger size, heavier weight and higher starch content, comparing to wild-type potato. It was preliminarily induced that GeDRP1E was involved in mitochondrial morphology regulation, which related to the growth and development of Arabidopsis plants and potato miniature. The research results laid a foundation for further elucidating the molecular mechanisms underlying the growth and development of G. elata tuber development.

This study aims to investigate the effect of salvianolic acid B (Sal B), the active ingredient of Salvia miltiorrhiza, on H9C2 cardiomyocytes injured by oxygen and glucose deprivation/reperfusion (OGD/R) through regulating mitochondrial fission and fusion. The process of myocardial ischemia-reperfusion injury was simulated by establishing OGD/R model. The cell proliferation and cytotoxicity detection kit (cell counting kit-8, CCK-8) was used to detect cell viability; the kit method was used to detect intracellular reactive oxygen species (ROS), total glutathione (t-GSH), nitric oxide (NO) content, protein expression levels of mitochondrial fission and fusion, apoptosis-related detection by Western blot. Mitochondrial permeability transition pore (MPTP) detection kit and Hoechst 33342 fluorescence was used to observe the opening level of MPTP, and molecular docking technology was used to determine the molecular target of Sal B. The results showed that relative to control group, OGD/R injury reduced cell viability, increased the content of ROS, decreased the content of t-GSH and NO. Furthermore, OGD/R injury increased the protein expression levels of dynamin-related protein 1 (Drp1), mitofusions 2 (Mfn2), Bcl-2 associated X protein (Bax) and cysteinyl aspartate specific proteinase 3 (caspase 3), and decreased the protein expression levels of Mfn1, increased MPTP opening level. Compared with the OGD/R group, it was observed that Sal B had a protective effect at concentrations ranging from 6.25 to 100 μmol·L^-1. Sal B decreased the content of ROS, increased the content of t-GSH and NO, and Western blot showed that Sal B decreased the protein expression levels of Drp1, Mfn2, Bax and caspase 3, increased the protein expression level of Mfn1, and decreased the opening level of MPTP. In summary, Sal B may inhibit the opening of MPTP, reduce cell apoptosis and reduce OGD/R damage in H9C2 cells by regulating the balance of oxidation and anti-oxidation, mitochondrial fission and fusion, thereby providing a scientific basis for the use of Sal B in the treatment of myocardial ischemia reperfusion injury.

Three 2,3-diketoquinoxaline alkaloids were isolated from Heterosmilax yunnanensis Gagnep. Their structures were determined through 1D and 2D NMR, HR-ESI-MS, UV, and IR as 1-[5′-(3″-hydroxy-3″-methyl) glutaryl] ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (1), 1-[2′-(3″-hydroxy-3″-methyl) glutaryl]ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (2), and 1-ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (3). Compounds 1 and 2 are novel compounds, and 3 was isolated from H. yunnanensis for the first time. The hepatoprotective activity of these three compounds was evaluated, with compound 3 showing promising hepatoprotective activity.

Sonogenetics is an emerging synthetic biology technique that uses sound waves to activate mechanosensitive ion channel proteins on the cell surface to regulate cell behavior and function.Due to the widespread presence of mechanically sensitive ion channel systems in cells and the advantages of non-invasion,strong penetrability,high safety and high accuracy of sonogenetics technology,it has great development potential in basic biomedical research and clinical applications,especially in neuronal regulation,tumor mechanism research,sonodynamic therapy and hearing impairment.This review discusses the basic principles of sonogenetics,the development status of sonogenetics and its application in the prevention and treatment of noise-induced hearing loss,summarizes and analyzes the current challenges and future development direction,thus providing a reference for further research and development of sonogenetics in the field of military medicine.

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.

AIM To explore the effects of Zishui Qinggan Decoction on the mouse model of depression induced by chronic restraint stress(CRS)via ERK/GSK3β/CREB/BDNF signaling pathway.METHODS Except for those of the blank group,the mice of other groups were induced into depression models by CRS,and divided into the model group,the fluoxetine hydrochloride group(10 mg/kg)and the low,medium and high dose Zishui Qinggan Decoction groups(8.835,17.670 and 35.340 g/kg)for the corresponding drug intervention and simultanous CRS treatment.The mice had their sugar water preference experiment and behavior experiment on the 7th and 14th day after administration;the observation of the hippocampal morphological changes by HE staining,the detection of the superoxide dismutase(SOD)activity and malondialdehyde(MDA)level in serum by kits,the detection of levels of serum 5-hydroxytryptamine(5-HT),tumor necrosis factor-α(TNF-α)and interleukin-1β(IL-1β)by ELISA,the detection of the hippocampal mRNA expressions of BDNF,TNF-α and IL-1β by RT-qPCR method,and the detection of the hippocampal protein expressions of ERK1/2,p-ERK1/2,GSK3β,p-GSK3β,CREB and BDNF by Western blot method 14 days after administration.RESULTS Compared with the model group,after 14 days of administration,both fluoxetine hydrochloride group and medium-dose Zishui Qinggan Decoction group displayed increased preference rate of sugar water(P<0.01),shortened immobility time of tail suspension and forced swimming(P<0.01),improved hippocampal damage of nerve cells,decreased levels of serum MDA,TNF-α and IL-1β(P<0.05,P<0.01),increased SOD activity and 5-HT level(P<0.05,P<0.01),decreased hippocampal mRNA expressions of TNF-α and IL-1β(P<0.01),and decreased expressions of BDNF mRNA and p-ERK1/2,p-GSK3β,CREB and BDNF proteins(P<0.05,P<0.01).CONCLUSION Zishui Qinggan Decoction can improve the depression-like behaviors in mice exposed to CRS,and its mechanism may be related to the regulation of hippocampal ERK/GSK3β/CREB/BDNF signaling pathway.

Objective To investigate the role of lipopolysaccharide(LPS)in regulating the inflammatory response of neutrophil through the leucine-rich α-2 glycoprotein 1(LRG1)/Rho-associated protein kinase(ROCK1)signaling.Methods HL-60 cells were treated with 1 μmol/L all-trans retinoic acid(ATRA)and 12.5 μL/mL dimethyl sulfoxide(DMSO)for 72 h and 96 h,and the morphological changes were observed by Wright-Giemsa staining.The expression of CD11b was detected by flow cytometry.LPS induced the activation of dHL-60 and human peripheral blood neutrophils.The transcription and secretion levels of LRG1,ROCK1 and inflammatory cytokines were detected by qPCR and ELISA,respectively.The expression levels of LRG1 and ROCK1 after the activation of dHL-60 were detected by Western blotting.Furthermore,dHL-60 was treated with the recombinant protein LRG1 and ROCK1 inhibitor Y-27632;the transcription levels of inflammatory cytokines were detected by qPCR.Results Neutrophils were activated by LPS.The expression levels of LRG1 and ROCK1 were significantly increased,and the transcription levels of inflammatory cytokines were significantly increased.The recombinant protein LRG1 activated dHL-60 in vitro,and the transcription levels of ROCK1 and inflammatory cytokines were significantly increased.Using the ROCK1 inhibitor Y-27632,the production levels of inflammatory cytokines were significantly reduced.Conclusion LPS can regulate the production levels of neutrophil inflammatory cytokines through activating the LRG1/ROCK1 signaling,thus exacerbating the inflammatory response.