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.

Prostate cancer(PCa) is a common malignant tumor among elderly men, with high incidence and mortality rates worldwide, posing a serious threat to human health. Traditional treatments face limitations, highlighting the urgent need for novel therapeutic strategies. Recent studies on the regulatory mechanisms of micro ribonucleic acid(microRNA, miRNA) in tumor development has identified miRNA as new targets for PCa diagnosis and treatment. Traditional Chinese medicine(TCM), with its multi-mechanism, multi-target, and multi-pathway regulatory properties, shows promising potential in miRNA-based PCa therapy. This review summarized recent findings on miRNA' roles in PCa and research progress of TCM intervention and found that a variety of miRNA played important regulatory roles in cell differentiation, proliferation, apoptosis, invasion, metastasis, immune microenvironment, and drug resistance, and their potential as biomarkers for PCa diagnosis, prognosis, and therapy, indicating the potential to be a biomarker for the diagnosis, prognosis evaluation, and treatment of PCa. The review concluded that the active components of TCM(terpenoids, flavonoids, alkaloids, and others) and compounds(Yishen Tonglong Decoction, Shenhu Decoction, Zhoushi Qiling Decoction, Fuzheng Yiliu Decoction, and Qilan Formula) could regulate the expression of their downstream target genes by acting on specific miRNA and affect the above biological behaviors of PCa cells, thus playing a role in the treatment of PCa. This review aims to provide a theoretical basis for miRNA as potential biomarkers and therapeutic targets for PCa and suggest new avenues for further development of targeted therapy strategies against miRNA.
Humans ; MicroRNAs/metabolism* ; Prostatic Neoplasms/metabolism* ; Male ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Animals ; Gene Expression Regulation, Neoplastic/drug effects*

OBJECTIVES: To study the clinical and genetic characteristics of children with congenital adrenal hyperplasia (CAH). METHODS: Clinical data, laboratory findings, and genetic test results of 63 children diagnosed with CAH at Henan Children's Hospital from January 2017 to December 2024 were retrospectively reviewed. RESULTS: Of the 63 patients, the mean age at the first visit was (21 ± 14) days; 29 (46%) were of male sex and 34 (54%) were of female sex. The predominant clinical manifestations were poor weight gain or weight loss (92%, 58/63), poor feeding (84%, 53/63), skin hyperpigmentation (83%, 52/63), and female external genital anomalies (100%, 34/34). Laboratory abnormalities included hyponatremia (87%, 55/63), hyperkalemia (68%, 43/63), metabolic acidosis (68%, 43/63), and markedly elevated 17-hydroxyprogesterone (92%, 58/63), testosterone (89%, 56/63), and adrenocorticotropic hormone (81%, 51/63). Among 49 patients who underwent genetic testing, CYP21A2 variants were identified in 90% (44/49), with c.293-13A/C>G (33%, 30/91) and large deletions/gene conversions (29%, 26/91) being the most frequent; STAR (8%, 4/49) and HSD3B2 (2%, 1/49) variants were also detected. Following hormone replacement therapy, electrolyte disturbances were corrected in 57 cases, with significant reductions in 17-hydroxyprogesterone, adrenocorticotropic hormone, and testosterone levels (P<0.001). CONCLUSIONS CAH presenting in neonates or young infants is characterized by electrolyte imbalance, external genital anomalies, and abnormal hormone levels. Genetic testing enables definitive subtype classification; in CYP21A2-related CAH, c.293-13A/C>G is a hotspot variant. These findings underscore the clinical value of genetic testing for early diagnosis and genetic counseling in CAH. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(11): 1367-1372.
Humans ; Adrenal Hyperplasia, Congenital/diagnosis* ; Male ; Female ; Retrospective Studies ; Infant ; Infant, Newborn

OBJECTIVE: To explore the preventive and therapeutic effects of Dahuang Zhechong Pill (DZP) on pulmonary fibrosis and the underlying mechanisms. METHODS: The first key rate-limiting enzyme hexokinase 2 (HK2) of glycolysis was silenced and over-expressed through small interfering RNA and lentivirus using lung fibroblast MRC-5 cell line, respectively. The cell viability, migration, invasion and proliferation were detected by cell counting kit-8, wound healing assay, transwell assay, and flow cytometry. The mRNA and protein expression levels of HK2 were detected by RT-PCR and Western blotting, respectively. The contents of glucose, adenosine triphosphate (ATP) and lactate in MRC-5 cells were determined by enzyme-linked immunosorbnent assay (ELISA). Then, the relationship between miR-29b-2-5p and HK2 was explored by luciferase reporter gene assay. Pulmonary fibrosis cell model was induced by transforming growth factor-β 1 (TGF-β 1) in MRC-5 cells, and the medicated serum of DZP (DMS) was prepared in rats. MRC-5 cells were divided into control, TGF-β 1, TGF-β 1+10% DMS, TGF-β 1+10% DMS+miR-29b-2-5p inhibitor, TGF-β 1+10% DMS+inhibitor negative control, TGF-β 1+10% DMS+miR-29b-2-5p mimic and TGF-β 1+10% DMS+mimic negative control groups. After miR-29b-2-5p mimics and inhibitors were transfected into MRC-5 cells, all groups except control and model group were treated with DMS. The effect of DMS on MRC-5 cells were detected using aforementioned methods and immunofluorescence. Similarly, the contents of glucose, ATP and lactate in each group were measured by ELISA. RESULTS: The mRNA and protein expressions of HK2 in MRC-5 cells were successfully silenced and overexpressed through si-HK2-3 and lentiviral transfection, respectively. After silencing HK2, the mRNA and protein expressions of HK2 were significantly decreased (P<0.01), and the concentrations of glucose, ATP and lactate were also significantly decreased (P<0.05). The proliferation, migration and invasion of MRC-5 cells were significantly declined (P<0.05 or P<0.01), while the apoptosis of MRC-5 cells was significantly increased (P<0.01). After overexpressing HK2, the mRNA and protein expressions of HK2 were significantly increased (P<0.05), and the concentrations of glucose, ATP and lactate were also significantly increased (P<0.05 or P<0.01). The proliferation, migration and invasion of MRC-5 cells were significantly increased (P<0.05 or P<0.01), while the apoptosis of MRC-5 cells was significantly decreased (P<0.05). The relative luciferase activity of 3'UTR-WT+hsa-miR-29b-2-5p transfected with HK2 was significantly decreased (P<0.01). After miR-29b-2-5p mimic and inhibitor were transfected into the MRC-5 cells, DMS intervention could significantly reduce the concentration of glucose, ATP and lactate, and the mRNA and proteins expressions of HK2, phosphofructokinase and pyruvate kinase isoform M2 (P<0.05 or P<0.01). The proliferation, migration and invasion of MRC-5 cells were alleviated (P<0.05 or P<0.01), and the deposition of fibronectin, α-smooth muscle actin, and collagen I were significantly decreased (P<0.05 or P<0.01). CONCLUSIONS Glycolysis is closely related to pulmonary fibrosis. DZP reduced glycolysis and inhibited fibroblasts' excessive differentiation and abnormal collagen deposition through the miR-29b-2-5p/HK2 pathway, which played a role in delaying the process of pulmonary fibrosis.
MicroRNAs/genetics* ; Glycolysis/genetics* ; Animals ; Pulmonary Fibrosis/metabolism* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Hexokinase/genetics* ; Cell Line ; Cell Proliferation/drug effects* ; Rats, Sprague-Dawley ; Rats ; Cell Movement/drug effects* ; Male ; Cell Survival/drug effects* ; Signal Transduction/drug effects*

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.

Based on WANG Xugao's “thirty methods of treating the liver”， it is believed that the occurrence and development of childhood tic disorders follow the dynamic progression from liver qi disease to liver fire disease and then liver wind disease. The basic pathogenesis of three stages are characterized by binding constraint of liver qi， liver fire hyperactivity， and internal stirring of liver wind. Moreover， liver-blood deficiency and stagnation， and malnutrition of liver yin as the main point in terms of the imbalance of liver qi， blood， yin， and yang should be considered， as well as the imbalance relationship of the five zang organs such as the involvement of other organs and the gradually reach of the other organs. Guided by the principles of “thirty methods of treating the liver”， the treatment of tic disorders in liver qi stage should focus on soothing the liver and rectifying qi， soothing the liver and unblocking the collaterals， using Xiaochaihu Decoction （小柴胡汤） and Sini Powder （四逆散）. The treatment of tic disorders in liver fire stage involves clearing， draining and resolving liver heat， using Longdan Xiegan Decoction （龙胆泻肝汤）， Xieqing Pill （泻青丸）， Danggui Longhui Pill （当归龙荟丸）， and Huagan Decoction （化肝煎）. The treatment of tic disorders in liver wind stage involves extinguishing wind and subduing yang， using Lingjiao Gouteng Decoction （羚角钩藤汤） and Liuwei Dihuang Pill （六味地黄丸）. Throughout the treatment process， attention should be paid to harmonizing the liver's qi， blood， yin， and yang， as well as addressing the pathology of other organs.

Objective To develop a multicolor photoelectroencephalography evoked flash to identify photosensitive epilepsy patients during the selection of naval aircraft pilots.Methods The multicolor photoelectroencephalography evoked flash was composed of a main body,a control box and a bracket.There were four rows of LED lights in the main body,which emitted four colors of light including red,yellow,green and orange,respectively;there were three sockets for signal,light and power and one color changeover switch on the body of the control box,and a control circuit board was fixed at the bottom inside the control box;the bracket had a double-jointed arm folding structure.The flash developed was compared with the coventional photoelectroencephalography evoked flash to verify its effect for inducing photosensitive epilepsy.Results There were no significant differences between the two flashes in the numbers of identified cases with photosensitive epilepsy when the subjects were under awake and closed-eye conditions(P＞0.05).Condusion The flash developed can make up for the deficiency of the coventional photoelectroencephalography evoked flash when selecting naval aircraft pilots.[Chinese Medical Equipment Journal,2024,45(7):112-114]

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]

In view of the problem of slow development of intensive care medicine in Xizang, the research team made full use of the national partner assistance to Xizang, gathered resources across all cities in Xizang, and formed a national academic platform for critical care medicine in plateau areas. Adhering to the academic orientation with hemodynamics as the main topic, critical care ultrasound as the bedside dynamic monitoring and evaluation method, and blood flow-oxygen flow resuscitation as the core connotation, we have achieved the goals of improving the critical care talent echelon throughout Xizang, driving the overall progress of intensive care medicine in Xizang, making a figure in China, and focusing on training of top-notch talents.