OBJECTIVE To study the protective effect and potential mechanism of chikusetsu saponin Ⅳ a （chsⅣ） on renal function in diabetic nephropathy （DN） model rats. METHODS DN rat model was established by high-fat diet combined with streptozotocin injection. Thirty-six model rats were randomly divided into model group （i.g. administration of normal saline， high-fat diet）， chsⅣ low-dose and high-dose groups （i.g. administration of 90， 180 mg/kg chsⅣ， high-fat diet）， with 12 rats in each group. Additionally， 10 normal rats were set as the control group （i.g. administration of normal saline， regular diet）. From the 5th to the 12th week after streptozotocin injection， they were given intragastric administration of relevant drug or normal saline， once a day. After the last medication， the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine and urine protein as well as the levels of reduced glutathione （GSH）， superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were measured. Additionally， the insulin resistance index was calculated. Hematoxylin-eosin， periodic acid-Schiff， and Masson staining techniques were employed to examine the histopathological alterations in the renal tissue. The expressions of Notch signaling pathway-related proteins in renal tissue were detected by immunohistochemical staining and Western blot methods. RESULTS Compared with model group， the histomorphological of renal tissues in the chsⅣ low- and high-dose groups were significantly improved， with significant decreases in renal histological scores， mesangial expansion index， and glomerulosclerosis scores （ P ＜0.05）； the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine， urine protein and homeostasis model assessment for insulin resistance， as well as MDA content， the expression levels of Notch1， Notch intracellular domain， hairy and enhancer of Split 1 and Delta-like protein 1 in renal tissue were all significantly decreased （ P ＜0.05）. The levels of GSH and SOD in renal tissue were significantly elevated （ P ＜0.05）. Moreover， the improvement in these indicators was significantly more pronounced in the chsⅣ high-dose group compared to the chsⅣ low-dose group （ P ＜0.05）. CONCLUSIONS ChsⅣ can ameliorate renal pathological damage and functional impairment in DN rats. Its underlying mechanisms include restoration of glucose homeostasis and insulin sensitivity， attenuation of renal oxidative stress， and suppression of aberrant Notch signaling pathway activation.

Abstract Adolescents are a high risk group for non suicidal self injury (NSSI), and the severity of the issue has been increasing. However, stigma originating from self perceptions, the public, and healthcare professionals poses significant barriers to help seeking and recovery among adolescents with NSSI. The paper systematically reviews the main intervention strategies targeting NSSI related stigma in adolescents, along with their effectiveness, from three perspectives: educational approaches, contact based interventions, and public advocacy against stigma, aiming to inform the development of a scientific, effective, and multi stakeholder collaborative integrated intervention framework to provide a basis for reducing and ultimately eliminating stigma associated with adolescent NSSI.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

Objective To evaluate the changes in cerebral perfusion after moyamoya disease revascularization using two-phase arterial spin labeling(ASL)combined with territorial arterial spin labeling(t-ASL).Methods A retrospective selection was conducted on 34 moy-amoya disease patients with 37 cerebral hemispheres who underwent revascularization surgery.ASL[post labeling delay(PLD)of 1.5 s and 2.5 s],t-ASL,and digital subtraction angiography(DSA)were performed before and after surgery.The cerebral blood flow(CBF)and relative cerebral blood flow(rCBF)values in the middle cerebral artery(MCA)supply area from ASL were com-pared before and after surgery.t-ASL and DSA were used to score the area of revascularization on a 3-point scale,and weighted Kappa was used to compare the consistency of the revascularization area assessments.A DSA score greater than 1 point was classified as good revascularization.The diagnostic efficacy of ASL(PLD 1.5 s,2.5 s)and t-ASL for revascularization were compared.Results In ASL PLD 1.5 s,the preoperative and postoperative CBF values were(32.65±12.71)mL·100 g-1·min-1 and(43.09±18.05)mL·100 g-1·min-1,respectively,and the rCBF values were 0.76±0.23 and 1.02±0.31;In ASL PLD 2.5 s,the preoperative and postoperative CBF val-ues were(47.07±13.28)mL·100 g-1·min-1and(52.85±14.98)mL·100 g-1·min-1,respectively,and the rCBF values were 1.21±0.31 and 1.33±0.29.There were statistically significant differences between preoperative values and postoperative values above(P<0.05).The revascularization area score showed strong consistency(weighted Kappa coefficient=0.729).Receiver operating charac-teristic(ROC)curve analysis revealed that t-ASL reflected the revascularization area with area under the curve(AUC)of 0.982,while ASL PLD 1.5 s and 2.5 s CBF reflected the revascularization area with AUC of 0.813 and 0.794,espectively.Conclusion The com-bination of two-phase ASL and t-ASL more effectively evaluates cerebral blood after moyamoya disease revascularization.Furthermore,t-ASL demonstrates higher efficacy in evaluating postoperative revascularization.

Objective:To analyze the relationship between neck pain severity and duration and cervical sagittal parameters in non-specific neck pain (NNP) patients from a real world data, and to initially explore the relationship between NNP and cervical sagittal position sequence.Methods:The clinical data of 126 patients with main complaint of neck pain in the outpatient department of Beijing Friendship Hospital, Capital Medical University from January to September 2023 were retrospectively analyzed. This cohort included 84 female and 42 male patients with a mean age of (42.21±14.88) years (aged from 15 to 76 years). According to the duration of neck pain was more than 3 month or not, patients were divided into acute neck pain group ( n=57) and chronic neck pain group ( n=69). Patients were divided into mild neck pain group ( n=72) and moderate and severe neck pain group ( n=54) according to the severity of neck pain. The duration and visual analogue scale (VAS) of neck pain for each patient was recorded. Cervical sagittal related parameters, including cervical lordosis (C 2-C 7 Cobb′ angle, CL), C 2-C 7 sagittal vertical axis (cSVA), T 1 slope (TS) were measured by cervical lateral X-ray, and the value of T 1 slope minus cervical lordosis (TS-CL) was calculated. At the same time, cervical lateral X-ray was used to record whether the patient had cervical kyphosis and whether the patient was associated with ossification of the nuchal ligament (ONL). The VAS score of neck pain was expressed as the median (interquartile) [ M( Q1, Q3)]. Measurement data with normal distribution were represented as mean±standard deviation( ± s), and the comparison between groups was conducted using the t-test; the comparison of count data were represented as cases and percentage, and was conducted by Chi-square test. Spearman correlation analysis was used to investigate the correlation of VAS score and duration of neck pain with age, gender, imaging parameters (CL, cSVA, TS, TS-CL), cervical kyphosis and ONL. Results:The median VAS score of all patients with neck pain was 4(3, 5). For all patients, VAS score of neck pain was significantly correlated with cSVA ( P=0.029) and TS-CL ( P=0.028). There was no correlation between VAS score and CL ( P=0.235), TS ( P=0.355), with cervical kyphosis or not ( P=0.988), or with ONL or not ( P=0.181). The TS-CL values of acute neck pain group and chronic neck pain group were (11.80±8.38)° and (8.77±7.61)°, respectively, with a significant difference ( P=0.035). There was no significant difference in the incidence of cSVA, CL, TS, ONL and cervical kyphosis between the two groups ( P>0.05). The cSVA of mild neck pain group and moderate and severe neck pain group were (1.16±0.94) cm and (1.80±1.04) cm, respectively. CL was (12.25±10.76)° and (8.27±9.08)°, respectively. The TS-CL values were (8.11±7.54)° and (12.84±8.04)°, respectively, and the differences between the two groups were statistically significant ( P<0.05). The incidence of ONL in moderate and severe neck pain group was significantly higher (35.2% vs 19.4%), and the difference was statistically significant ( P<0.05). Conclusions:The severity of NNP was significantly correlated with cSVA, the more severe the neck pain, the more the mismatch between TS and CL was presented. Compared with chronic neck pain, patients with acute neck pain tended to appear TS and CL mismatch. There was a large value of cSVA and TS-CL in moderate and severe neck pain patients. The incidence of ONL was significantly increased in patients with moderate and severe neck pain.

Objective:To evaluate the perioperative application effect of enhanced recovery after surgery (ERAS) clinical pathway in percutaneous vertebro plasty (PVP).Methods:The clinical data of 274 patients who underwent PVP treatment for osteoporotic vertebral compression fracture (OVCF) in Beijing Friendship Hospital, Capital Medical University from May 2023 to August 2024 were retrospectively analyzed. The patients were divided into two groups according to the different numbers of surgical segments: the single-segment group ( n=211) and the multisegment group ( n=63). Patients in the single-segment group underwent single-segment surgery, while patients in the multisegment group underwent surgery on ≥2 segments. The core points of the ERAS clinical pathway adopted in this study include perioperative education, pain management, early mobilization, application of "outfast", and joint guidance from the departments of nutrition and rehabilitation. Comparison was made between the two groups of patients in terms of visual analog scale (VAS) scores for low back pain at preoperative, 2 h, 6 h, 24 h postoperatively, and on the day of discharge; Oswestry disability index (ODI) scores preoperatively and on the day of discharge; time to first ambulation postoperatively, total length of hospital stay, postoperative length of stay, perioperative complications, and perioperative application of Opioid consumption. Measurement data were expressed as mean±standard deviation ( ± s), and the independent sample t-test was used for comparison between groups; count data were expressed as cases and percentage, and the Chi-square test was used for comparison between groups. The VAS pain scores at each stage of the perioperative period were evaluated using repeated measures analysis of variance or generalized estimating equations. Results:Compared with that before the operation [(6.17±0.93) points, (6.29±0.83) points], the VAS scores of low back pain of patients in the single-segment group and the multisegment group at 2 hours after surgery [(3.09±0.82) points, (3.27±0.65) points], 6 hours after surgery [(2.60±0.79) points, (2.62±0.55) points], and 24 hours after surgery [(1.89±0.77) points, (1.97±0.72) points] and on the day of discharge [(1.72±0.71) points, (1.81±0.64) points] were significantly decreased, and the differences were statistically significant ( P<0.05). At the same stage, the VAS scores of low back pain in both groups were not statistically significant ( P>0.05). The ODI scores of patients in the single-segment group and the multisegment group on the day of discharge [(24.21±2.35) points, (24.63±3.31) points] were significantly lower than those before the operation [(64.50±4.81) points, (65.52±4.08) points], and the differences were statistically significant ( P<0.05). There were no statistically significant differences in perioperative complications and the proportion of Opioid drug application between the two groups of patients ( P>0.05). Conclusion:For patients with single-segment or multisegment OVCF, PVP surgical treatment under ERAS clinical pathway management can achieve immediate pain relief, early ambulation exercise, and satisfactory perioperative efficacy.

Objective:To evaluate preoperative malnutrition risk in patients with osteoporotic vertebral compression fracture (OVCF) based on mini nutritional assessment short form (MNA-SF) and analyze the related clinical risk factors.Methods:A cross-sectional study was conducted using clinical data from 129 OVCF patients who underwent percutaneous vertebroplasty at Beijing Friendship Hospital, Capital Medical University, between May 2023 and December 2023. The cohort included 26 males and 103 females, aged (74.71±9.13) years(ranging from 48-98 years). According to MNA-SF scoring method, they were divided into three groups, the malnutrition group ( n=6), the nutritional risk group ( n=40), and the good nutrition group ( n=83). Nutritional risk and malnutrition rates were evaluated using the MNA-SF score. Measurement data with normal distribution were expressed as mean±standard deviation ( ± s) and compared using one-way ANOVA. The comparison between groups of count data was conducted using chi-square test. Univariate analysis and multivariate logistic regression were performed to identify independent risk factors for malnutrition and nutritional risk. Results:According to the MNA-SF score, among 129 patients, the malnutrition rate was 4.7%, the nutritional risk rate was 31.0%, and 64.3% exhibited adequate nutrition based on MNA-SF scores. The results of one-way ANOVA showed that gender ( P=0.023) and BMI ( P<0.001) were significantly correlated with malnutrition and nutritional risk; Logistic regression analysis suggested that the influencing factors of nutritional risk included gender ( P=0.002) and BMI ( P<0.001), while the only dangerous factor of malnutrition was BMI ( P<0.001). Conclusions:Bsed on MNA-SF, OVCF patients undergoing percutaneous vertebroplasty have a higher incidence of malnutrition and nutritional risk. The risk factors for nutritional risk in patients are gender and BMI, while the risk factor for malnutrition is only BMI.