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.

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 explore the predictive value of soluble fms-like tyrosine kinase-1(sFlt-1)and leukotriene B4(LTB4)in patients with intracranial aneurysms for cerebral vasospasm(CVS)after interventional embolization.Methods A total of 98 patients with intracranial aneurysms admitted to our hospital from January 2019 to September 2023 were regarded as the observation group,and were divided into the CVS group(32 cases)and the non CVS group(66 cases)according to whether CVS occurred or not within 3 to 5 days after surgery;102 healthy examinees in our hospital were selected as the control group.Enzyme-linked immunosorbent assay was used to detect serum levels of sFlt-1 and LTB4;the influencing factors for CVS after interventional embolization of intracranial aneurysms were analyzed by Logistic regression analysis;the predictive value of serum sFlt-1 and LTB4 levels for the occurrence of CVS after interventional embolization of intracranial aneurysms was analyzed by receiver operating characteristic(ROC)curve.Results The serum levels of sFlt-1 and LTB4 of patients in the observation group were obviously higher than those in the control group,and the differences were statistically significant(P<0.05).The serum levels of sFlt-1 and LTB4,and the proportions of patients with postoperative blood pressure fluctuation range≥30 mmHg and Hunt-Hess grade Ⅲ in the CVS group were obviously higher than those in the non CVS group,and the differences were statistically significant(P<0.05).SFlt-1(OR:2.985;95%CI:1.684 to 5.291)and LTB4(OR:2.868;95%CI:1.581 to 5.204)were the independent risk factors for CVS after interventional embolization of intracranial aneurysms(P<0.05).The area under the curve(AUC)of sFlt-1 and LTB4 alone and in combination for predicting the occurrence of CVS after interventional embolization of intracranial aneurysms were 0.839,0.825,and 0.915,respectively,with sensitivity of 84.44%,87.59%,and 81.36%,and specificity of 74.26%,75.87%,and 90.98%,respectively.The AUC of the combination of the two was higher than those of sFlt-1 and LTB4 alone,and the differences were statistically significant(Z=2.150,2.546,P<0.05).Conclusion The serum levels of sFlt-1 and LTB4 in patients with CVS after interventional embolization of intracranial aneurysms are increased,and the combination of the two can serve as the important indicators for predicting CVS.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective: To understand the antimicrobial resistance and genome characteristics of Campylobacter isolates recovered from retailed poultry meat samples in 20 provinces in China in 2020. Methods: In 2020, 265 Campylobacter strains including 244 Campylobacter jejuni and 21 Campylobacter coli collected from retailed poultry meat samples in China were tested for antimicrobial resistance to 9 antimicrobial compounds by using the agar dilution method. Forty-two selected isolates were sent for whole genome sequencing and 38 high-quality genomes were analyzed for their antimicrobial resistance genes, virulence genes, sequence types and genetic diversity. Results: The resistance rates of Campylobacter isolates from poultry meats to tetracycline, nalidixic acid and ciprofloxacin were the highest (84%-100%), with 53.2% of the isolates showing multidrug resistance in this study. The resistance rates of C. coli to erythromycin, azithromycin, telithromycin, gentamicin and clindamycin were significantly higher than those of C. jejuni (P<0.05). The resistance genes conferring resistance to β-lactams (100%, 38/38), quinolones (94.7%, 36/38), tetracycline (81.6%, 31/38) and aminoglycosides (50%, 19/38) were the most frequently detected among 38 Campylobacter genomes. C. jejuni carried more virulence genes than C. coli. In total, 19 and 17 sequence types (ST) were obtained from 20 sequenced C. jejuni and 18 C. coli isolates, respectively, including 5 novel STs. The isolates showed a high genetic diversity based on their sequence types. Conclusion: The phenomenon of antimicrobial resistance in Campylobacter from poultry meat sources in China is relatively serious, and resistance and virulence genes are widely distributed in Campylobacter. There is genetic diversity in Campylobacter.
Humans ; Animals ; Anti-Bacterial Agents/pharmacology* ; Campylobacter/genetics* ; Poultry ; Drug Resistance, Bacterial/genetics* ; Genomics ; China ; Tetracycline

OBJECTIVE: To compare and analyze the feasibility of autologous facet joint bone block as an alternative to polyetheretherketone (PEEK) cage in lumbar intervertebral fusion surgery for patients with osteoporosis. METHODS: From December 2018 to June 2021, the case data of patients with osteoporosis (T value ≤ -2.5 on dual energy X-ray bone density) who underwent posterior lumbar interbody fusion in the Fourth Medical Center, Chinese PLA General Hospital were retrospectively reviewed. All the cases were followed up for no less than 12 months and were divided into two groups according to the differences of interbody fusion materials: the autologous facet joint bone block group (autogenous bone group) and the PEEK cage group (PEEK group). The general data [such as age, gender, body mass index (BMI), primary diagnosis, distribution of fusion segments, bone mineral density of lumbar (BMD), incidence of preoperative complications], the perioperative data (such as duration of operation, intraoperative blood loss, postoperative drainage, perioperative allogeneic blood transfusion rate), and the incidence of postoperative complications were compared between the two groups. Imaging parameters (disc height, lumbar lordosis angle, segment lordosis angle, segmental lordosis angle, disc height improvement rate, and fusion rate) and lumbar functional scores [visual analogue scale (VAS), Oswestry disability index (ODI), Japanese Orthopedics Association (JOA) score for lower back pain] were compared to evaluate the clinical efficacy between the kinds of intervertebral fusion materials 1 week, 3 months and 6 months postoperative and at the last follow-up. RESULTS: A total of 118 patients were enrolled, including 68 cases in the autogenous bone group and 50 cases in the PEEK group, there were no statistical differences in age, gender, BMI, primary diagnosis, distribution of fusion segments, BMD, incidence of preoperative complications, duration of operation, intraoperative blood loss, postoperative drainage, perioperative allogeneic blood transfusion rate, incidence of postoperative complications, all the preoperative imaging parameters and all the lumbar function scores between the two groups (P>0.05). Postoperative superficial surgical site infections occurred in 3 patients in the autogenous bone group and 2 patients in the PEEK group. At the last follow-up, 3 cases of intervertebral graft collapse occurred in the autogenous bone group and 5 cases in the PEEK group, 1 case of graft subsidence in the autogenous bone group and 1 case in the PEEK group. All the imaging parameters showed significant differences between postoperation and preoperation (P < 0.05), and all the imaging parameters showed significant differences between 1 week and 3 months postoperative in both groups (P < 0.05). The height, angle of fusion gap in the autogenous bone group were lower than those in the PEEK group 1 week postoperatively (P < 0.05), and the fusion gap height improvement rate in the autogenous bone group was lower than that in the PEEK group (P < 0.05). The cases in both groups started to show final fusion 3 months after surgery, and the fusion rate in the autogenous bone group was 75% 6 months postoperatively, which was significantly higher than the rate of 56% in the PEEK group (P < 0.05), and there was no statistically significant difference in the final fusion rate between the two groups (P>0.05). The ODI, the postoperative VAS score was significantly lower than that in preoperation, while the postoperative JOA score was significantly higher than that in preoperation (P < 0.05). The ODI was lower while the JOA score was higher of the autogenous bone group than that of the PEEK group 6 months postoperatively (P < 0.05). CONCLUSION In osteoporosis patients, good interbody fusion rate and improvement of lumbar vertebral function can be obtained by using autologous facet joint bone block or PEEK cage, while the fusion rate and the improvement of lumbar function with autologous facet joint bone block are better than those with PEEK cage 6 months post-operatively. PEEK cage is superior to autologous facet joint bone block in intervertebral distraction and improvement of lumbar lordosis. Significant disc space subsidence occurred in osteoporotic patients within 3 months after lumbar interbody fusion, and the subsidence of PEEK cage was more obvious than that of autologous facet joint bone block.
Humans ; Retrospective Studies ; Lordosis ; Zygapophyseal Joint ; Spinal Fusion/methods* ; Polyethylene Glycols/therapeutic use* ; Treatment Outcome ; Ketones ; Lumbar Vertebrae/surgery* ; Osteoporosis ; Blood Loss, Surgical ; Postoperative Complications ; Postoperative Hemorrhage

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

Three new anthraquinones were isolated from the 80% ethanol extract of Prismatomeris tetrandra by silica gel, MCI, ODS column chromatography and high performance preparative liquid chromatography (HPLC). The structures of the new compounds were identified by mass spectrometry, nuclear magnetic resonance and other spectroscopic methods as 6-hydroxy-1,2,3-trimethoxy-7-methylanthracene-9,10-dione (1), 6-(hydroxymethyl)-1,2,3-trimethoxyanthracene-9,10-dione (2) and 7-hydroxy-6-(hydroxymethyl)-1,2-dimethoxyanthracene-9,10-dione (3). Compounds 1, 2 and 3 showed protective effects against monosodium glutamate-induced damage in SH-SY5Y neuroblastoma cells, with the cell survival rates elevated 18.45%, 4.31%, and 7.65%, respectively.