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.

Macroautophagy (referred to as autophagy hereafter) is a major intracellular lysosomal degradation pathway that is responsible for the degradation of misfolded/damaged proteins and organelles. Previous studies showed that autophagy protects against acetaminophen (APAP)-induced injury (AILI) via selective removal of damaged mitochondria and APAP protein adducts. The lysosome is a critical organelle sitting at the end stage of autophagy for autophagic degradation via fusion with autophagosomes. In the present study, we showed that transcription factor EB (TFEB), a master transcription factor for lysosomal biogenesis, was impaired by APAP resulting in decreased lysosomal biogenesis in mouse livers. Genetic loss-of and gain-of function of hepatic TFEB exacerbated or protected against AILI, respectively. Mechanistically, overexpression of TFEB increased clearance of APAP protein adducts and mitochondria biogenesis as well as SQSTM1/p62-dependent non-canonical nuclear factor erythroid 2-related factor 2 (NRF2) activation to protect against AILI. We also performed an unbiased cell-based imaging high-throughput chemical screening on TFEB and identified a group of TFEB agonists. Among these agonists, salinomycin, an anticoccidial and antibacterial agent, activated TFEB and protected against AILI in mice. In conclusion, genetic and pharmacological activating TFEB may be a promising approach for protecting against AILI.

To explore the mechanism of spleen- were obtained for the treatment of acute-on-chronic livstrengthening and moisture-nourishing liver prescription er failure, and 244 intersecting target genes and 7 core (JPLSYGF) in the treatment of acute-on-chronic liver target genes were screened. Molecular docking showed failure using network pharmacology and the molecular that the core target genes AKT1, SRC, VEGFA, docking. Methods Relying on TCMSP and Gene- STAT3 , EGFR, MAPK3 , HRAS had good affinity with Cards and other databases, the relevant targets of JPL- quercetin, the main active component in the JPLSYGF in the treatment of acute-on-chronic liver failure SYGF, and had strong binding activity. In addition, in were obtained. String and Cytoscape were used to con- vivo tests verified that the JPLSYGF could reduce the struct PPI networks of targets, core targets were expression of HRAS, EGFR, STAT3 , SRC, and VEGscreened out, and DAVID was used for GO function FA, to delay the progression of acute-on-chronic liver annotation and KEGG pathway enrichment analysis. failure. Conclusions JPLSYGF may act on core tar- The main active ingredients of the traditional Chinese gets such as HRAS, EGFR, STAT3, SRC, VEGFA medicine compound formula for JPLSYGF were select- and so on, to achieve the effect of treating acute-oned with a bioavailability OB value of =Э 30% and a chronic liver failure. drug-like DL^O. 18 as the screening conditions, and.

Objective:To investigate the correlation between the expression of GLI1 and im-mune invasion and clinical prognosis in gastric cancer.To study the effect of GLI1 expression on drug resistance in gastric cancer.Methods:The expression difference of GLI1 in gastric cancer and normal tissues was analyzed by using TCGA database,and the effect of clinical features and GLI1 gene ex-pression level on prognosis of patients with gastric cancer was analyzed.The correlation between GLI1 gene expression and tumor immune cell infiltration in gastric cancer tissues was analyzed to explore its influence on drug resistance of chemotherapy drugs and targeted drugs.Clinical samples were collect-ed to analyze the difference of GLI1 expression in gastric cancer and paracancer tissues.Results:The expression of GLI1 in gastric cancer tissues was 1.7 times that in normal tissues,and the overall sur-vival and disease-free survival of patients with high expression are shorter than those with low ex-pression(P＜0.05).The interstitial score,immune score and abundance of immunoinfiltrating cells were higher in the high expression of GLI1 in gastric cancer tissues.High expression of GLI1 reduces drug sensitivity and is positively correlated with the expression of immune checkpoint markers PDCD1(P＜0.05).GLI1 expression was significantly increased in patients with subdifferentiated gastric cancer.Conclusions:GLI1 expression is associated with the prognosis and immune infiltration of patients with gastric cancer,and it may lead to poor prognosis of patients by regulating chemotherapy resis-tance,which may be a potential therapeutic target and molecular marker for gastric cancer.

Objective:To investigate the effect of sleep on physical performance and the correlation between sleep quality and physical performance in the elderly.Methods:In this prospective multicenter case-control study, 472 elderly people aged 60-80 years were recruited from three regions in China, Beijing, Tianjin, and Hainan Province.Basic information of study participants was collected through face-to-face interviews, and physical performance of study participants was assessed by the time up and go(TUG)test on site, with 106 cases(22.5%)in the normal physical performance group and 366 cases(77.5%)in the abnormal group.The Pittsburgh Sleep Quality Index(PSQI)and the Epworth Sleepiness Scale(ESS)were applied to assess sleep quality of study subjects.Correlation analysis was performed to examine factors affecting subjects' physical performance.Results:Age, history of alcohol consumption, BMI, past medical history, the ESS score, daytime sleepiness, and some components of PSQI, such as sleep quality, sleep efficiency, sleep disturbances, use of sleeping drugs and daytime dysfunction, were influencing factors of the TUG score.Two components of PSQI, sleep duration and habitual sleep efficiency, and the ESS score were positively correlated with physical performance.Logistic regression analysis showed that risk factors for decreased physical performance in the elderly included increased age( OR=1.125, 95% CI: 1.083-1.168, P<0.01), history of alcohol consumption( OR=0.482, 95% CI: 0.384-0.605, P<0.001), abnormally high body mass index( OR=1.663, 95% CI: 1.340-2.063, P<0.01), hyperlipemia( OR=0.156, 95% CI: 0.077-0.318, P<0.01), digestive system diseases( OR=0.154, 95% CI: 0.044-0.532, P<0.01), use of sleeping drugs( OR=0.415, 95% CI: 0.202-0.854, P<0.05), daytime sleepiness( OR=4.234, 95% CI: 2.800-6.403, P<0.01), a high habitual sleep efficiency score of PSQI( OR=1.425, 95% CI: 1.214-1.672, P<0.01)and a high sleep disturbances score in PSQI( OR=3.356, 95% CI: 2.337-4.819, P<0.01). Conclusions:The incidence of physical performance decline is high in the elderly.There is a correlation between physical performance and sleep quality.

The breakthrough progress of implantable brain-computer interfaces (iBCIs) technology in the field of clinical trials has attracted widespread attention from both academia and industry. The development and advancement of this technology have provided new solutions for the rehabilitation of patients with movement disorders. However, challenges from many aspects make it difficult for iBCIs to further implement and transform technologies. This paper illustrates the key challenges restricting the large-scale development of iBCIs from the perspective of system implementation, then discusses the latest clinical application progress in depth, aiming to provide new ideas for researchers. For the system implementation part, we have elaborated the front-end signal collector, signal processing and decoder, then the effector. The most important part of the front-end module is the neural electrode, which can be divided into two types: piercing and attached. These two types of electrodes are newly classified and described. In the signal processing and decoder section, we have discussed the experimental paradigm together with signal processing and decoder for the first time and believed that the experimental paradigm acts as a learning benchmark for decoders that play a pivotal role in iBCIs systems. In addition, the characteristics and roles of the effectors commonly used in iBCIs systems, including cursors and robotic arms, are analyzed in detail. In the clinical progress section, we have divided the latest clinical progress into two categories: functional rehabilitation and functional replacement from the perspective of the application scenarios of iBCIs. Functional rehabilitation and functional replacement are two different types of application, though the boundary between the two is not absolute. To this end, we have first introduced the corresponding clinical trial progress from the three levels: application field, research team, and clinical timeline, and then conducted an in-depth discussion and analysis of their functional boundaries, in order to provide guidance for future research. Finally, this paper mentions that the key technical challenges in the development of iBCIs technology come from multiple aspects. First of all, from the signal acquisition level, high-throughput and highly bio-compatible neural interface designing is essential to ensure long-term stable signal acquisition. The electrode surface modification method and electrode packaging were discussed. Secondly, in terms of decoding performance, real-time, accurate, and robust algorithms have a decisive impact on improving the reliability of iBCIs systems. The third key technology is from the perspective of practicality, we believe that the signal transmission mode of wireless communication is the trend of the future, but it still needs to overcome challenges such as data transmission rate and battery life. Finally, we believe that issues such as ethics, privacy, and security need to be addressed through legal, policy, and technological innovation. In summary, the development of iBCIs technology requires not only the unremitting efforts of scientific researchers, but also the participation and support of policymakers, medical professionals, technology developers, and all sectors of society. Through interdisciplinary collaboration and innovation, iBCIs technology will achieve wider clinical applications in the future and make important contributions to improving the quality of life of patients.

Objective To investigate the spatiotemporal distribution characteristics and potential influencing factors of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, so as to provide insights into the formulation of the echinococcosis control strategy in Qinghai Province. Methods The number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases, number of registered dogs and number of stray dogs were captured from the annual reports of echinococcosis control program in Qinghai Province from 2016 to 2022, and the detection of newly diagnosed echinococcosis cases was calculated. The number of populations, precipitation, temperature, wind speed, sunshine hours, average altitude, number of year-end cattle stock, number of year-end sheep stock, gross domestic product (GDP) per capita, and number of village health centers in each county (district) of Qinghai Province were captured from the Qinghai Provincial Statistical Yearbook, and county-level electronic maps in Qinghai Province were downloaded from the National Platform for Common Geospatial Information Services. The software ArcGIS 10.8 was used to map the distribution of newly diagnosed echinococcosis cases in Qinghai Province, and the spatial autocorrelation analysis of newly diagnosed echinococcosis cases was performed. In addition, the spacetime scan analyses of number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases and geographical coordinates in Qinghai Province were performed with the software SaTScan 10.1.2, and the spatial stratified heterogeneity of the detection of newly diagnosed echinococcosis cases was investigated with the software GeoDetector. Results A total of 6 569 426 residents were screened for echinococcosis in Qinghai Province from 2016 to 2022, and 5 924 newly diagnosed echinococcosis cases were found. The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline over years from 2016 to 2022 (χ² = 11.107, P < 0.01), with the highest detection in Guoluo Tibetan Autonomous Prefecture in 2017 (82.12/10⁵). There were spatial clusters in the detection of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2018 (Moran’s I = 0.34 to 0.65, all Z values > 1.96, all P values < 0.05), and the distribution of newly diagnosed echinococcosis cases appeared random distribution from 2019 to 2022 (Moran’s I = −0.09 to 0.04, all Z values < 1.96, all P values > 0.05). Local spatial autocorrelation analysis showed high-high clusters and low-low clusters in the detection of new diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, and space-time scan analysis showed that the first most likely cluster areas of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022 were mainly distributed in Yushu Tibetan Autonomous Prefecture and Guoluo Tibetan Autonomous Prefecture. GeoDetector-based analysis of the driving factors for the spatial stratified heterogeneity of detection of newly diagnosed echinococcosis cases in Qinghai Province showed that average altitude, number of village health centers, number of cattle and sheep stock, GDP per capita, annual average sunshine hours, and annual average temperature had a strong explanatory power for the spatial distribution of newly diagnosed echinococcosis cases, with q values of 0.630, 0.610, 0.600, 0.590, 0.588, 0.537 and 0.526, respectively. Conclusions The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline in Qinghai Province over years from 2016 to 2022, showing spatial clustering. Targeted control measures are required in cluster areas of newly diagnosed echinococcosis cases for further control of the disease.

Schimke immuno-osseous dysplasia (SIOD)caused by SMARCAL1 gene mutations is a rare genetic disorder characterized by multi-system involvement, including T-cell dysfunction, skeletal dysplasia, disproportionate short stature, nephrotic syndrome, and kidney failure. This multidisciplinary consultation involved a 9-year-old boy with intrauterine growth retardation, presenting with short stature, T-cell lymphopenia, proteinuria, and degenerative bone and joint disease. Treatment primarily focused on symptomatic and supportive care. Through the multidisciplinary rare disease consultation, holistic support was provided to the patient, offering comprehensive care from various specialtiesx.We also aim to use this case report to enhance clinicians′ under-standing of SIOD and improve the management and treatment of rare diseases.

Objective To investigate the therapeutic effect and mechanism of paeoniflorin(PAE)on thrombosis angiitis obliterans(TAO)in rats.Methods TAO rat model was established by sodium laurate injection.Rats were randomly divided into sham operation group(intraperitoneal injection of 0.9％NaCl),model group(intraperitoneal injection of 0.9％NaCl),experimental-L,-H groups(intraperitoneal injection of PAE 5,20 mg·kg-1·d-1),experimental-H+agonist group(intraperitoneal injection of 20 mg·kg-1·d-1 PAE+caudal vein injection of 10 ng·mL-1·kg 1·d-1 740 Y-P).Thrombin time(TT)was measured by magnetic bead coagulation;the levels of interleukin(IL)-1 β and endothelin 1(ET-1)were detected by enzyme-linked immunosorbent assay kit;the expression levels of phosphatidylinositol 3-kinase(PI3K),phosphorylated-PI3K(p-PI3 K),protein kinase B(AKT),p-AKT,nuclear factor(NF)-κB p65,p-NF-κB p65 were detected by Western blotting.Results The TT of sham operation group,model group,experimental-L,-H groups and experimental-H+agonist group were(14.88±1.32),(10.02±0.95),(12.65±1.22),(14.70±1.36)and(10.64±1.21)s;IL-1β were(154.23±13.45),(356.69±31.17),(268.62±23.58),(199.64±20.87)and(337.48±31.46)pg·mL-1;ET-1 were(6.78±0.68),(14.43±1.14),(11.23±1.07),(8.20±0.81)and(13.33±1.27)pg·mL-1;p-PI3K/PI3K were 0.36±0.04,0.76±0.07,0.59±0.05,0.44±0.04 and 0.69±0.07;p-AKT/AKT were 0.52±0.05,0.90±0.09,0.74±0.08,0.61±0.06 and 0.86±0.08;p-NF-κB p65/NF-κB p65 were 0.28±0.03,0.95±0.04,0.69±0.07,0.35±0.05 and 0.87±0.08,respectively.There were statistically significant differences between model group and sham operation group(all P＜0.05);the above indexes in experimental-L group and experimental-H group were significantly different from those in medel group(all P＜0.05);the above indexes in experimental-H+agonist group were significantly different from those in experimental-H group(all P＜0.05).Conclusion PAE may improve disease progression in TAO rats by inhibiting the PI3K/AKT/NF-κB signaling pathway.

Objective To evaluate tolerability,safety and pharmacokinetics of JS026 and JS026-JS016 single dose intravenous infusion in healthy adults.Methods This phase 1,randomized,double-blind,placebo-controlled,dose-escalation study totally included 48 participants:32 healthy subjects were enrolled in JS026 single intravenous infusion groups and 16 healthy subjects were enrolled in JS026-JS016 groups.JS026 was sequentially administered from low dose to high dose(30-1 000 mg),with intravenous infusion of JS026 or placebo in JS026 single-dose groups,and intravenous infusion of JS026-JS016 or placebo in the combination drug groups.Blood was collected according to the time point designed for trial.Serum concentrations of JS026 and JS016 were determined by enzyme linked immunosorbnent assay(ELISA),and pharmacokinetics parameters were calculated by WinNonlin 8.2.The power model method was used to evaluate the linear analysis of dose and drug exposure.Results 47 subjects completed trial and 1 subject lost to follow-up.After a single intravenous injection of JS026 of 30 mg,100 mg,300 mg,600 mg,and 1 000 mg,mean Cmax were(9.47±1.53),(33.20±4.95),(96.10±13.70),(177.00±22.20)and(353.00±56.70)μg·mL-1,respectively;mean AUC0-∞ were(4 225.00±607.00),(1.78 × 104±3 268.00),(5.83 × 104±1 038.00),(1.07 × 105±152.00),(1.66 × 105±327.00)μg·h·mL-1,respectively;mean t1/2 of JS026 were 563-709 h.The Cmax and AUC0-∞ of JS026 were basically similar alone or in combination with JS016.The results of Power model showed that Cmax and AUC0-∞ increased approximately linearly with the increasing dose of JS026.Treatment emergent adverse event was not increasing when dose increased and most of adverse event associated with drugs were abnormal on laboratory tests and haematuria,thus JS026 and JS016 was well tolerated in all groups.Conclusion The single intravenous infusion of JS026 can almost be thought to be a linear relationship between the doses and drug serum exposure.JS016 had no significant effect on serum concentration of JS026 and JS026 was well tolerated and safe in healthy subjects within 30-1 000 mg.