Brain age prediction, as a significant approach for assessing brain health and early diagnosing neurodegenerative diseases, has garnered widespread attention in recent years. Electroencephalogram (EEG), an non-invasive, convenient, and cost-effective neurophysiological signal, offers unique advantages for brain age prediction due to its high temporal resolution and strong correlation with brain functional states. Despite substantial progress in enhancing prediction accuracy and generalizability, challenges remain in data quality and model interpretability. This review comprehensively examined the advancements in EEG-based brain age prediction, detailing key aspects of data preprocessing, feature extraction, model construction, and result evaluation. It also summarized the current applications of machine learning and deep learning methods in this field, analyzed existing issues, and explored future directions to promote the widespread application of EEG-based brain age prediction in both clinical and research settings.
Humans ; Electroencephalography/methods* ; Brain/physiology* ; Machine Learning ; Aging/physiology* ; Deep Learning ; Signal Processing, Computer-Assisted

The coupling analysis of continuous physiological signals is a crucial tool for revealing the dynamic activities and interactions within physiological systems. To gain a deeper understanding of the coupling relationships between physiological systems, this paper provides a comprehensive review of recent research on coupling analysis methods for continuous physiological signals, both domestically and internationally. It focuses on various coupling analysis techniques, including time-domain, frequency-domain, time-frequency-domain and nonlinear methods, and explores their applications in the coupling assessment of different physiological systems. Finally, the paper discusses the limitations of these methods and their future development trends. By systematically reviewing the current methods of continuous physiological signal coupling analysis, this paper aims to provide valuable references for further research on coupling evaluation methods for physiological systems.
Signal Processing, Computer-Assisted ; Humans

To explore the status and characteristics of clinical trials of therapeutic cancer vaccines, and provide the overall trend of clinical translational research of therapeutic cancer vaccines.

Objective In this study,we analyzed the transcriptome sequences of Kupffer cells exposed to simulated microgravity for 3 d and conducted biological experiments to determine how microgravity initiates apoptosis in Kupffer cells. Methods Rotary cell culture system was used to construct a simulated microgravity model.GO and KEGG analyses were conducted using the DAVID database.GSEA was performed using the R language.The STRING database was used to conduct PPI analysis.qPCR was used to measure the IL1B,TNFA,CASP3,CASP9,and BCL2L11 mRNA expressions.Western Blotting was performed to detect the level of proteins CASP3 and CASP 9.Flow cytometry was used to detect apoptosis and mitochondrial membrane cells.Transmission electron microscopy was used to detect changes in the ultrastructure of Kupffer cells. Results Transcriptome Sequencing indicated that simulated microgravity affected apoptosis and the inflammatory state of Kupffer cells.Simulated microgravity improved the CASP3,CASP9,and BCL2L11 expressions in Kupffer cells.Annexin-V/PI and JC-1 assays showed that simulated microgravity promoted apoptosis in Kupffer cells.Simulated microgravity causes M1 polarization in Kupffer cells. Conclusion Our study found that simulated microgravity facilitated the apoptosis of Kupffer cells through the mitochondrial pathway and activated Kupffer cells into M1 polarization,which can secrete TNFA to promote apoptosis.

In recent years, the research focus on health-related behavior and chronic non-communicable diseases has shifted from the analysis on independent effects of multiple causes on a single outcome to the evaluation the complex relationships between multiple causes and multiple effects. Complex network theory, an important branch of system science, considers the relationships among factors in a network and can reveal how health-related behaviors interact with chronic diseases through a series of complex network models and indicators. This paper summarizes the definition and development of complex network theory and its commonly used models, indicators, and case studies in the field of health-related behavior and chronic disease to promote the application of complex network theory in the field of health and provide reference and tools for future research of the relationship between health-related behavior and chronic disease.

Objective:To analyze the effect of long-term care insurance on the incidence of falls in old people with disability, and the modification effect of different living arrangements.Methods:Based on the discharge diagnosis records of the hospitalization in urban residents who applied for long-term care insurance in Chengdu from July 2014 to June 2021, those who received long-term care insurance were selected as the intervention group and those who received no long-term care insurance were selected as the control group, the changes in the incidence of falls before and after the long-term care were analyzed using difference-in-differences method, and the modification effects of different living arrangements were explored using stratified analysis.Results:Long-term care insurance significantly reduced the risk for monthly incidence of falls in older adults [average treatment effects on treated (ATT) = -1.21% (95% CI: -1.82%--0.60%)], and the effect increased over time (ATT=-1.26%, 95% CI: -1.93%--0.59%). Long-term care insurance had a significant effect on reducing the incidence of falls in old people living with spouses/family members (ATT=-0.92%, 95% CI: -1.47%--0.37%) and in nursing facilities/hospitals (ATT=-2.10%, 95% CI: -3.81%--0.40%), but it had no significant effect in those living alone. Conclusions:Long-term care insurance can effectively reduce the incidence of falls in old people with disability, showing a positive effect. Living with family members or in nursing facilities/hospitals has a modification effect of the implementation of long-term care insurance policy. It is necessary to pay attention to key populations in the future and expand the coverage of long-term care insurance.

BACKGROUND:Currently,there have been a variety of conservative and surgical treatment plans for spontaneous osteonecrosis of the knee,achieving excellent results.However,a broad consensus on indication and guide of surgical treatment has not been announced.In clinical practice,there is still a misunderstanding that unicondylar replacement or total knee arthroplasty should be performed upon the discovery of spontaneous osteonecrosis of the knee,while an urgent need for universal access to the concept of stepwise therapy. OBJECTIVE:To summarize and find the factors leading to the poor effect of conservative treatment in spontaneous osteonecrosis of the knee,which occurred on the medial femoral condyle,from the literature and clinical cases,at the same time,combined with the Koshino stage,to propose the strategy of stepwise spontaneous osteonecrosis of the knee treatment on the medial femoral condyle. METHODS:A systematic search of the literature database was conducted to summarize the factors leading to poor outcomes of conservative treatment in spontaneous osteonecrosis of the medial femoral condyle.Meanwhile,according to the Clinical&Health Records for analytics&Sharing system,the cases receiving conservative and surgical treatment in spontaneous osteonecrosis of the medial femoral condyle in the Department of Orthopedics of Guangdong Provincial Hospital of Chinese Medicine from January 2017 to January 2023 were analyzed retrospectively,then the causes of success and failure in typical cases were summarized and analyzed. RESULTS AND CONCLUSION:(1)Early diagnosis and treatment of spontaneous osteonecrosis of the knee were very important for prognosis.For sudden knee pain in some patients,if no obvious abnormality was found in the X-ray examination,and the symptoms persisted and could not be relieved for more than 1 week,an MRI examination was recommended to detect early spontaneous osteonecrosis of the knee.(2)The X-ray images of Koshino stage 1 and stage 2 of spontaneous osteonecrosis of the medial femoral condyle were difficult to be distinguished,which needed to be probed by MRI.MRI images of Koshino stage 1 were mainly characterized by bone marrow edema,and an osteonecrosis area with a clear boundary was not formed,while MR images of Koshino stage 2 showed a necrotic area with a clear boundary.(3)Five factors leading to the poor effect of conservative treatment on spontaneous osteonecrosis of the medial femoral condyle were summarized:a.The necrotic area was＞5 cm2;b.The necrotic area accounted for more than 40%of the condyle;c.relative compression percentage of medial meniscus≥33%(with or without medial meniscus injury and subchondral bone marrow edema);d.MRI depth of necrotic area(anterior-posterior diameter of sagittal necrotic area)＞20 mm;e.varus deformity of lower limb＞6°.(4)Conservative treatment of spontaneous osteonecrosis of the knee in Koshino stage 1 was good.For spontaneous osteonecrosis of the knee in Koshino stage 2,conservative treatment was preferred or combined with drilling decompression.If there was no relief or improvement of symptoms or in MRI after 3 months,while the patient had any of the previous five factors,then knee preservation surgery should be considered.For spontaneous osteonecrosis of the knee in Koshino stage 3 and stage 4,knee preservation surgery should be selected based on the previous five factors,including age,gender and activity level of the patient.Total knee arthroplasty was used for spontaneous osteonecrosis in Koshino stage 4,which was associated with symptomatic patellofemoral arthritis,valgus alignment,or necrotic area,which greatly affected the stability of unicondyle prosthesis.

Objective:To investigate the clinical value of abdominal adipose volume in predicting early tumor recurrence after resection of hepatocellular carcinoma (HCC).Methods:The retrospective case-control study was conducted. The clinicopathological data of 132 HCC patients with tumor diameter ≤5 cm who were admitted to The First Affiliated Hospital of Army Medical University from December 2017 to October 2019 were collected. There were 110 males and 22 females, aged (51±4)years. All patients underwent resection of HCC. Preoperative computer tomography scanning was performed and the visceral and subcutaneous fats of patients were quantified using the Mimics Research 21.0 software. Based on time to postoperative tumor recurrence patients were divided to two categories: early recurrence and non-early recurrence. Observation indicators: (1) consistency analy-sis; (2) analysis of factors influencing early tumor recurrence after resection of HCC and construction of prediction model. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribu-tion were represented as M( Q1,Q3) or M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were expressed as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Consistency analysis was conducted using the intragroup correlation coefficient (ICC) test. Multivariate analysis was performed using the binary Logistic regression model forward method. Independent risk factors influencing early tumor recurrence after resection of HCC were screened. The area under curve (AUC) of receiver operating characteristic (ROC) curve was applied to select the optimal cut-off value to classify high and low risks of recurrence. The Kaplan-Meier method was used to draw survival curve and calculate survival time. The Log-Rank test was used for survival analysis. Results:(1) Consistency analysis. The consistency ICC of abdominal fat parameters of visceral fat volume (VFV), subcutaneous fat volume, visceral fat area, and subcutaneous fat area measured by 2 radiologists were 0.84, 1.00, 0.86, and 0.94, respectively. (2) Analysis of factors influencing early tumor recurr-ence after resection of HCC and construction of prediction model. All 132 patients were followed up after surgery for 662(range, 292-1 111)days. During the follow-up, there were 52 patients with non-early recurrence and 80 patients with early recurrence. Results of multivariate analysis showed that VFV was an independent factor influencing early tumor recurrence after resection of HCC ( odds ratio=4.07, 95% confidence interval as 2.27-7.27, P<0.05). The AUC of ROC curve based on VFV was 0.78 (95% confidence interval as 0.70-0.85), and the sensitivity and specificity were 72.2 % and 77.4 %, respectively. The optimal cut-off value of VFV was 1.255 dm 3, and all 132 patients were divided into the high-risk early postoperative recurrence group of 69 cases with VFV >1.255 dm 3, and the low-risk early postoperative recurrence group of 63 cases with VFV ≤1.255 dm 3. The disease-free survival time of the high-risk early postoperative recurrence group and the low-risk early post-operative recurrence group were 414(193,702)days and 1 047(620,1 219)days, showing a significant difference between them ( χ2=31.17, P<0.05). Conclusions:VFV is an independent factor influen-cing early tumor recurrence of HCC after resection. As a quantitative indicator of abdominal fat, it can predict the prognosis of HCC patients.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

With the changing disease spectrum, the incidence of tumors is increasing and tends to occur among the youth. The long-term survival rate of patients with cancer has increased significantly, and attention to their reproductive rights is growing. Surgery, chemotherapy, radiotherapy, immunotherapy, and molecular targeted therapy are the conventional treatment methods for cancer, with each exerting different effects on the fertility of patients. Common fertility preservation techniques currently include sperm cryopreservation, embryo and oocyte cryopreservation, ovarian tissue cryopreservation, uterine transplantation, and assisted reproductive technology. This article systematically summarizes the influence of different antitumor treatments on fertility, as well as the current status and prospects of fertility preservation in patients with cancer. This study aims to improve cooperation between clinical oncologists and reproductive medicine doctors to enhance fertility preservation for patients with cancer.