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.

OBJECTIVE: To investigate the therapeutic effect of the short-penis treatment apparatus and wide-band infrared therapy apparatus on penile dysplasia (PDP) in children and establish objective parameters for assessing the severity of PDP. METHODS: This study included 252 children received in the Department of pediatric urology of the First Affiliated Hospital of Xinjiang Medical University from January to December 2023, 102 with PDP (the PDP group) and the other 150 with normal penile development (the control group), those of the former group treated with the short-penis therapeutic apparatus and wide-band infrared therapy apparatus. Before and after 30 days of treatment, we measured the flaccid penile length (FPL), stretched penile length (SPL) and penile diameters (PD) of the children, and defined the penile dysplasia index as the FPL/SPL and FPL/PD ratios. RESULTS: The penile parameters exhibited statistically significant differences between the PDP and control groups, (FPL:［1.97±0.72］cm vs ［3.25±0.51］ cm, P<0.01; SPL:［3.80±0.81］cm vs ［5.21±0.79］cm,P<0.01).The FPL remarkably increased in the PDP group after treatment(［1.97±0.72］cm vs ［2.90±1.20］ cm, P<0.01). Both FPL and SPL were notably shorter in the PDP cases than in the controls, with the cutoff values of 0.57 and 2.09, sensitivities of 80.7% and 95.3%, and specificities of 69.6% and 82.4% for FPL/SPL and FPL/PD, respectively. CONCLUSION The short-penis therapeutic apparatus and wide-band infrared therapy apparatus can promote the growth and development of the penis in children. The ratio of FPL/PD can serve as an objective indicator to effectively describe the severity of penile developmental abnormalities.
Humans ; Male ; Penis/abnormalities* ; Child ; Penile Diseases/therapy* ; Child, Preschool ; Infant

OBJECTIVE: To investigate the clinical effect of physical intervention combined with medical nutritional weight loss (PI+MNWL) in the treatment of short penis in obese children. METHODS: One hundred and twenty obese children with a short penis were included and equally divided into three groups: PI+MNWL, MNWL, and self-guided diet, who underwent PI+MNWL, MNWL intervention under the supervision of professional nutritionists in the hospital, or self-guided diet intervention at home, respectively, all for 30 days. We measured the penile parameters, including stretched penile length (SPL), flaccid penile length (FPL) and penile diameter (PD), of the children before and after treatment, and compared them among the three groups. RESULTS: After intervention, the body weight of the children was significantly decreased in all the three groups (27.1－94.1［53.59±11.88］ kg vs 23.0－85.1［49.01±11.61］ kg， P < 0.05). The weight of children in 3 groups decreased to different degrees, and the difference was statistically significant (P < 0.05). MNWL was found remarkably more effective than self-guided weight loss in reducing the body weight of the children (P < 0.05). Based on weight loss achieved through medical nutrition combined with physical intervention, the FPL in the PI+MNWL group increased from (1.93 ± 0.76) cm before treatment to (3.41 ± 1.41) cm after one course of comprehensive treatment, with a statistically significant difference (P < 0.05). Similarly, SPL increased from (3.75 ± 0.76) cm before treatment to (4.98 ± 0.64) cm, and PD increased from (1.32 ± 0.21) cm before treatment to (1.61 ± 0.66) cm, both showing statistically significant differences (P < 0.05). In the MNWL group , FPL increased from (2.01 ± 0.81) cm to (2.77 ± 0.84) cm after one course of treatment, with a statistically significant difference (P < 0.05). Additionally, SPL increased from (4.03 ± 0.84) cm before treatment to (4.40 ± 0.76) cm, also demonstrating statistical significance (P < 0.05), while PD increased from (1.37 ± 0.21) cm before treatment to (1.42 ± 0.22) cm, with statistical significance (P < 0.05). FPL and SPL increased significantly in the PI+MNWL group compared to the MNWL group (P < 0.05, P < 0.01). However, there was no significant difference in PD between the two groups following the intervention (P > 0.05). CONCLUSION MNWL is more effective than self-guided diet in controlling the body weight of children, while the combination approach of PI+MNWL is even superior to the management of short penis in obese children, with the advantages of improving the appearance and increasing the exposed length of the penis.
Humans ; Male ; Child ; Weight Loss ; Penis/abnormalities* ; Obesity/complications* ; Adolescent

Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals ; NFATC Transcription Factors/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Ovariectomy ; Osteoclasts/metabolism* ; Female ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; NF-kappa B/genetics* ; Osteoporosis/genetics* ; Signal Transduction/drug effects* ; Bone Resorption/genetics* ; Cell Differentiation/drug effects* ; Humans ; RANK Ligand/metabolism* ; Mitogen-Activated Protein Kinases/genetics* ; Transcription Factors

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 investigate the age-related changes of the mandibular third molar root pulp visibility in individuals in East China,and to explore the feasibility of applying this method to deter-mine whether an individual is 18 years or older.Methods A total of 1 280 oral panoramic images were collected from the 15-30 years old East China population,and the mandibular third molar root pulp visibility in all oral panoramic images was evaluated using OLZE 0-3 four-stage method,and the age distribution of the samples at each stage was analyzed using descriptive statistics.Results Stages 0,1,2 and 3 first appeared in 16.88,19.18,21.91 and 25.44 years for males and in 17.47,20.91,22.01 and 26.01 years for females.In all samples,individuals at stages 1 to 3 were over 18 years old.Conclusion It is feasible to determine whether an individual in East China is 18 years or older based on the mandibular third molar root pulp visibility on oral panoramic images.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective: To analyze the detection rate, clinical significance, and prognosis of Epstein-Barr virus (EBV) in the cerebrospinal fluid (CSF) of patients following allogeneic hematopoietic stem cell transplantation. Methods: A retrospective analysis was performed on 1100 patients who underwent the CSF virus test after allogeneic hematopoietic stem cell transplantation in Peking University People's Hospital between January 2017 and June 2022. Among them, 19 patients were screened positive for EBV in their CSF, and their clinical characteristics, treatment, and prognosis were analyzed. Results: Among 19 patients with EBV-positive cerebrospinal fluid, 12 were male and 7 were female, with 5 patients aged <18 years and 12 aged ≥18 years, with a median age of 27 (5-58) years old. There were 7 cases of acute myeloid leukemia, 8 of acute lymphocytic leukemia, 2 of aplastic anemia, 1 of Hodgkin's lymphoma, and 1 of hemophagocytic syndrome. All 19 patients underwent haploid hematopoietic stem cell transplantation, including 1 secondary transplant. Nineteen patients had neurological symptoms (headache, dizziness, convulsions, or seizures), of which 13 had fever. Ten cases showed no abnormalities in cranial imaging examination. Among the 19 patients, 6 were diagnosed with EB virus-related central nervous system diseases, with a median diagnosis time of 50 (22-363) days after transplantation. In 9 (47.3%) patients, EBV was detected in their peripheral blood, and they were treated with intravenous infusion of rituximab (including two patients who underwent lumbar puncture and intrathecal injection of rituximab). After treatment, EBV was not detected in seven patients. Among the 19 patients, 2 died from EBV infection and 2 from other causes. Conclusion: In patients who exhibited central nervous system symptoms after allogeneic hematopoietic stem cell transplantation, EBV should be screened as a potential pathogen. EBV detected in the CSF may indicate an infection; however, it does not confirm the diagnosis.
Humans ; Male ; Female ; Adolescent ; Adult ; Middle Aged ; Herpesvirus 4, Human ; Epstein-Barr Virus Infections/complications* ; Rituximab/therapeutic use* ; Retrospective Studies ; Clinical Relevance ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Lymphoproliferative Disorders/drug therapy*