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.

Cardiovascular diseases ( CVDs ) are the leading cause of death worldwide and pose a serious threat to human health. Silent information regulator 5 ( SIRT5 ) , which is widely distributed in cardiac myocytes, vascular smooth muscle cells and endothelial cells,as a novel deacylation-modifying enzyme,plays an important role in CVDs through deacetylation, desuccinylation and demalonylation. This review summarizes the pathophysiolog-ical mechanism of SIRT5 from the aspects of energy metabolism, regulation of inflammatory response and oxidative stress, apart from the role of SIRT5 in CVDs such as myocardial infarction, myocardial hypertrophy, arrhythmia, atherosclerosis and heart failure. This review also figures out the current research progress of SIRT5 -related inhibitors and agonists, so as to provide strategies for targeting SIRT5 to prevent and treat CVDs.

italic>Schisandra chinensis is a traditional Chinese medicine with the functions of reinforcing deficiency, strengthening, and inducing astringency, appliable to treat the chronic cough and deficiency in breath, palpitation, and insomnia, etc. A hybrid mass spectrometry scanning strategy (high-definition data-independent/data-dependent acquisition, HDDIDDA), enabling the ion mobility separation and alternating data-independent acquisition/data-dependent acquisition, was established, which, in combination with in-house library-driven automatic peak annotation workflows facilitated by the UNIFI software, was utilized to systematically characterize the multi-classes of chemical components from S. chinensis. The use of an HSS T3 column (100 mm × 2.1 mm, 1.8 μm), 0.1% formic acid in H₂O-acetonitrile as the mobile phase running at the flow rate of 0.3 mL·min^-1, and column temperature at 35 ℃, could enable good separation of the S. chinensis components within 42 min. HDDIDDA scan in both the positive and negative ion modes was employed for data acquisition. Based on the automatic peak annotation, reference standards comparison, MS² data interpretation, and literature analysis, we were able to identify or tentatively characterize 105 compounds in the S. chinensis decoction, involving 56 terpenoids, 42 lignans, five glycosides, one organic acid, and one flavonoid. HDDIDDA scanning can improve the coverage of data acquisition and improve the accuracy of identification, while CCS prediction analysis provides the possibility to distinguish isomers by the ion mobility technology. The results provide reference for the intelligent material basis research of TCM.

Objective To explore the relationship between the types of bicuspid aortic valves(BAV)and the outcome of functional mitral regurgitation(FMR)and the affecting factors of FMR.Methods From Jun 2018 to Sep 2022,patients with severe BAV aortic valve stenosis(AS)complicated with FMR underwent post transcatheter aortic valve replacement(TAVR)in Zhongshan Hospital,Fudan University were retrospectively analyzed.The baseline information and imaging data of different BAV patients were collected.Logistic regression was used to analyze the factors affecting the outcome of FMR(improvement and non-improvement).Result A total of 100 patients with TAVR were included,including 49 patients with type 0 of BAV and 51 patients with type 1 of BAV.Compared with patients of type 1,patients of type 0 had younger age[(72.78±6.09)y vs.(77.00±8.35)y,P=0.050],lower male ratio(47%vs.73%,P= 0.009)higher BMI[(23.19±2.62)kg/m2 vs.(21.99±3.13)kg/m2,P=0.041],and lower incidence of aortic regurgitation(69%vs.92%,P=0.040).Compared with the non-improvement group,the improvement group had a lower incidence of coronary heart disease(5%vs.18%,P=0.042),higher incidence of pulmonary hypertension(20%vs.2%,P=0.007),larger left ventricular diastolic diameter[(51.98±6.74)mm vs.(48.04±7.72)mm,P=0.009]and higher maximum flow velocity[(4.86±0.95)cm/s vs.(4.47±0.75)cm/s,P= 0.023]of the aortic valve.The results of Logistic regression analysis showed that preoperative pulmonary hypertension,left ventricular end-diastolic diameter and maximum valvular flow velocity of BAV patients were the potential affecting factors of FMR improvement after TAVR.Conclusion No significant difference was found in FMR improvement between BAV patients of type 0 and type 1 after TAVR.For BAV patients with AS,preoperative pulmonary hypertension,larger left ventricular end-diastolic diameter,and faster aortic valve flow velocity were associated with higher FMR improvement rate.

Tricuspid regurgitation(TR)cases are widely distributed in China.Poor clinical drug efficacy,high surgical risk,and poor prognosis for right heart failure are found in patients with moderate or severe TR.In recent years,with the innovation of valve instruments and the development of technology,transcatheter tricuspid valve treatment could be a new choice for high-risk TR patients in surgery.Many TR animal models have emerged these years for the research of the mechanism of TR and for the clinical verification of instruments.Therefore,this review focuses on how to develop an animal model of TR and discusses the advantages and disadvantages of these techniques.

Objective To compare the role and importance of fibular fixation in tibiofibular fractures by Meta-analysis.Methods The literature related to the comparison of the efficacy of fixation of the fibula with or without fixation on the treatment of tibiofibular fractures was searched through the databases of China Knowledge Network,Wipu,Wanfang,The Cochrane Li-brary,Web of science and Pubmed,and statistical analysis was performed using RevMan 5.3 software.The rates of malrotation,rotational deformity,internal/external deformity,anterior/posterior deformity,non-union,infection,secondary surgery and op-erative time were compared between the fibula fixation and non-fixation groups.Results A total of 11 publications were includ-ed,six randomised controlled trials and five case-control trials,eight of which were of high quality.A total of 813 cases were in-cluded,of which 383 were treated with fibula fixation and 430 with unfixed fibulae.Meta-analysis results showed that fixation of the fibulae in the treatment of tibiofibular fractures reduced the rates of postoperative rotational deformity[RR=0.22,95％CI(0.10,0.45),P＜0.000 1]and internal/external deformity[RR=0.34,95％CI(0.14,0.84),P=0.02]and promoted fracture heal-ing[RR=0.76,95％CI(0.58,0.99),P=0.04].In contrast,the rates of poor reduction[RR=0.48,95％CI(0.10,2.33),P=0.36],anterior/posterior deformity[RR=1.50,95％CI(0.76,2.96),P=0.24],infection[RR=1.43,95％CI(0.76,2.72),P=0.27],sec-ondary surgery[RR=1.32,95％CI(0.82,2.11),P=0.25],and operative time[MD=10.21,95％CI(-17.79,38.21),P=0.47]were not statistically significant(P＞0.05)for comparison.Conclusion Simultaneous fixation of the tibia and fibula is clinically more effective in the treatment of tibiofibular fractures.

italic>Artemisia argyi is a traditional Chinese medicine in China, which is used as medicine with its leaves. The leaves of A. argyi mainly contain flavonoids, phenolic acids, volatile oils and other compounds, and have a variety of pharmacological activities. AP2/ERF transcription factors are abundant in plants and are mainly involved in plant growth and development, abiotic stress response and secondary metabolite biosynthesis regulation. However, there are few reports on the AP2/ERF gene family and its functions in A. argyi. In this study, we systematically identified the AP2/ERF gene family in A. argyi genome, and analyzed its phylogenetic tree, protein physicochemical properties, subcellular localization, conserved motifs, promoter elements, and expression patterns. The results showed that a total of 204 AP2/ERF transcription factors were identified in A. argyi genome, encoding proteins consisting of 88-483 amino acids with a relative molecular mass of 10-52.94 kDa and a theoretical isoelectric point of 4.62-9.88. Subcellular prediction showed that the majority of AP2/ERFs were located in the nucleus, cytoplasm, and the minority of them is located in the membrane and chloroplasts. According to the Arabidopsis AP2/ERF family classification, A. argyi AP2/ERF proteins were divided into four subfamilies: Soloist, AP2, ERF (B3, B4, B5, B6), and DREB (A1, A2, A4, A5, A6), among which DREB family accounted for the largest proportion, and the same subfamily had similar conserved motifs. cis-Acting element analysis showed that AP2/ERF promoters have a large number of elements responding to light and abiotic stress. Expression pattern analysis showed that most of the genes of the AP2/ERF family were dominantly expressed mainly in roots and stems, of which 19 were dominantly expressed in leaves, 77 would be induced to be expressed by methyl jasmonate, of which 16 genes were both dominantly expressed in leaves and induced to be expressed by methyl jasmonate, and these AP2/ERF genes may be the key regulatory genes for the synthesis of active ingredients in A. argyi leaves.This study lays the foundation for the functional study of AP2/ERF family genes and their regulating roles in the active components biosynthesis in A. argyi leaves.

Objective To develop a GIS-based 3D playback system for the flight human-plane data to realize the fusion of pilots'airborne flight data and physiological data.Methods The 3D playback system was developed with the Browser/Server(B/S)architecture,micro-server model,Java language and Spring Cloud technology framework,which was composed of three functional modules for flight process reproduction,physiological situational awareness and critical event calibration analysis.Results The system developed achieved time synchronization and data fusion of airborne flight data and physiological data with a time synchronization frequency of 1 Hz and a refresh rate of not less than 120 frames/s.Conclusion The system developed with high safety,stability,reliability and accuracy facilitates pilot in-flight physiological monitoring and fusion and simultaneous display of airborne flight data and physiological data,which can be used as an important platform for decision-making support in flight training.[Chinese Medical Equipment Journal,2024,45(10):14-19]

Background::Adamantinomatous craniopharyngioma (ACP) is the commonest pediatric sellar tumor. No effective drug is available and interpatient heterogeneity is prominent. This study aimed to identify distinct molecular subgroups of ACP based on the multi-omics profiles, imaging findings, and histological features, in order to predict the response to anti-inflammatory treatment and immunotherapies.Methods::Totally 142 Chinese cases diagnosed with craniopharyngiomas were profiled, including 119 ACPs and 23 papillary craniopharyngiomas. Whole-exome sequencing (151 tumors, including recurrent ones), RNA sequencing (84 tumors), and DNA methylome profiling (95 tumors) were performed. Consensus clustering and non-negative matrix factorization were used for subgrouping, and Cox regression were utilized for prognostic evaluation, respectively.Results::Three distinct molecular subgroups were identified: WNT, ImA, and ImB. The WNT subgroup showed higher Wnt/β-catenin pathway activity, with a greater number of epithelial cells and more predominantly solid tumors. The ImA and ImB subgroups had activated inflammatory and interferon response pathways, with enhanced immune cell infiltration and more predominantly cystic tumors. Mitogen-activated protein kinases (MEK/MAPK) signaling was activated only in ImA samples, while IL-6 and epithelial-mesenchymal transition biomarkers were highly expressed in the ImB group, mostly consisting of children. The degree of astrogliosis was significantly elevated in the ImA group, with severe finger-like protrusions at the invasive front of the tumor. The molecular subgrouping was an independent prognostic factor, with the WNT group having longer event-free survival than ImB (Cox, P = 0.04). ImA/ImB cases were more likely to respond to immune checkpoint blockade (ICB) therapy than the WNT group ( P <0.01). In the preliminary screening of subtyping markers, CD38 was significantly downregulated in WNT compared with ImA and ImB ( P = 0.01). Conclusions::ACP comprises three molecular subtypes with distinct imaging and histological features. The prognosis of the WNT type is better than that of the ImB group, which is more likely to benefit from the ICB treatment.

Lithium(Li)salts are commonly used as psychotropic medications for the treatment of major depressive disorders.However,long-term use of Li salts poses a high risk of toxicity,necessitating continuous monitoring of Li concentration in patient blood to ensure medication safety,which is crucial for clinical treatment.Laser-induced breakdown spectroscopy(LIBS),as a rapid analytical technique,has been widely applied in the elemental analysis of complex matrices in various practical scenarios.In this study,LIBS technology combined with partial least squares(PLS)was employed for quantitative analysis of Li elements in blood matrix.A total of 45 clinical blood samples were utilized,and the quantitative models for plasma and whole blood matrices were separately investigated.The number of latent variables in the PLS algorithm was optimized using a five-fold cross-validation method.Results revealed that the PLS quantitative model constructed on the basis of plasma matrix achieved a predictive determination coefficient(R2)of 0.992,a predictive root mean square error(RMSEP)of 0.204 μg/mL,and a relative standard error(RSD)of 2.14%.In contrast,for the PLS quantitative model constructed on the basis of whole blood matrix,the R2 was 0.984,the RMSEP was 0.728 μg/mL,and the RSD was 3.45%Consequently,the LIBS model constructed on the basis of plasma calibration values demonstrated superior performance in quantitative analysis of Li element in whole blood,and LIBS technology provided a new possibility for rapid assessment of blood Li levels in clinical practice,with promising prospects for application.