Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Objective: To investigate the regional differences in the incidence of urothelial carcinoma among kidney transplant recipients between northern and southern China，so as to provide reference for early diagnosis of this disease. Methods: A comprehensive search was conducted across multiple databases，including CNKI，Wanfang，CBM，and PubMed，using the keywords “kidney transplantation” and “tumor” to collect clinical data from qualified kidney transplant centers.The latest and most complete literature data published by 17 transplant centers in northern China and 14 in southern China were included.Statistical analyses were performed to compare the incidence of post-transplant urothelial carcinoma and non-urothelial malignancies. Results: A total of 37 475 kidney transplant recipients were included，among whom 837 (2.23%) developed post-transplant malignancies，including urothelial carcinoma (366/837，43.73%)，non-urothelial carcinoma (444/837，53.05%)，and malignancies with unspecified pathology (27/837，3.23%).The incidence of malignancies was significantly higher in northern China than in southern China [(2.82±1.39)% vs. (1.67±0.83)%，P=0.011]，with a particularly pronounced difference in the incidence of urothelial carcinoma [(1.68±1.12)% vs. (0.32±0.32)%，P<0.001].No significant difference was observed in the incidence of non-urothelial carcinoma between the two regions [(1.11±0.56)% vs. (1.35±0.65)%，P=0.279].Additionally，female transplant recipients exhibited a higher incidence of malignancies than males in both regions (southern China：2.38% vs. 1.80%; northern China：8.93% vs. 2.52%). Conclusion: The incidence of urothelial carcinoma following kidney transplantation is significantly higher in northern China than in southern China，underscoring the importance of implementing regular tumor screening for kidney transplant recipients，particularly for female patients in northern China，to facilitate early diagnosis and timely intervention.

Tumor has become a major disease that seriously threatens human health and life. The incidence rate is increasing year by year， yet the underlying mechanisms remain incompletely understood. Traditional Chinese medicine （TCM）， a treasure of the Chinese nation and a wealth for people worldwide， plays an important role in the treatment of tumors and has been receiving increasing attention both in China and abroad. In earlier work， based on the symptoms and metastatic characteristics of tumors， and drawing on the TCM theory of Yin and Yang in combination with modern medical research on tumors， the ''Yin deficiency-cancer correlation'' hypothesis was proposed. This hypothesis holds that ''Yin deficiency'' of the body is a major cause of malignant tumors， and that nourishing Yin to eliminate the pathogenic factor of Yin deficiency can treat cancer. By using Yin-nourishing drugs to tonify Yin deficiency， the occurrence and development of malignant tumors can be effectively prevented. Common anti-tumor Yin-nourishing drugs include Glehniae Radix， Lilii Bulbus， Ophiopogonis Radix， Liriopes Radix， Asparagi Radix， Dendrobii Caulis， Dendrobii Officinalis Caulis， Polygonati Odorati Rhizoma， Polygonati Rhizoma， Lycii Fructus， Mori Fructus， Ligustri Lucidi Fructus， Ecliptae Herba， Rehmanniae Radix， and Anemarrhenae Rhizoma. These drugs are generally sweet in flavor， cold and cool in nature， and moist in texture. They have the functions of nourishing Yin fluids， generating body fluids， and moistening dryness， and can also clear heat， being primarily indicated for Yin deficiency with depletion of body fluids. In view of the potential advantages and value of treating malignant tumors by tonifying Yin deficiency with Chinese medicine， this paper reviews recent studies on the anti-tumor effects of active components of Yin-nourishing drugs. It further summarizes their mechanisms of action in inducing apoptosis of tumor cells， arresting tumor cell proliferation， inhibiting tumor invasion， metastasis， and angiogenesis， enhancing and regulating immune function， augmenting the efficacy of chemotherapeutic drugs， and reversing tumor drug resistance. This study provides an objective overview of research progress on Yin-nourishing drugs in tumor treatment and offers new ideas for cancer therapy.

Aim To observe the effect of Astragalus membranaceus and Angelica sinensis on the apoptosis of chondrocytes,and to investigate the effect of Astrag-alus membranaceus and Angelica sinensis on the sur-vival of fresh ostecartilage allograft.Methods Forty-eight 4-month-old New Zealand white rabbits,half male and half female,were randomly divided into sham operation group,model group,positive group and As-tragalus and Angelica 5∶1 group.In addition to the sham operation group,the other groups were both male and female donors and recipients for knee joint osteo-cartilage cross transplantation modeling.After 8 weeks of drug intervention,samples were taken for general observation,HE staining,saffrane-O staining,immu-nohistochemical staining,qPCR and Western blot de-tection.Results Compared with model group,As-tragalus and Angelica 5∶1 group and positive group,the repair site healed better,the morphology of osteo-chondrocytes tended to be normal,and the division and proliferation were obvious.Proteoglycan deposition in-creased and type Ⅱ collagen content was higher,the differences were statistically significant(P＜0.05).qPCR and Western blot results showed that compared with model group,the mRNA and protein expressions of Bax,caspase-3 and caspase-9 in other groups were significantly decreased(P＜0.05).Conclusion As-tragalus and Angelica can promote the survival of fresh osteochondral allograft,and its mechanism may be re-lated to promoting collagen production,promoting chondrocyte proliferation and inhibiting chondrocyte apoptosis.

Objective To investigate the mid-term effect and complications of arthroscopic popliteal tendon suture in the treatment of lateral meniscus injury.Methods From January 2016 to December 2020,the data of 57 patients with lateral meniscus popliteal tendon injury treated by arthroscopic popliteal tendon suture fixation were retrospectively analyzed,includ-ing 35 males and 22 females,aged from 18 to 47 years old with an average of(32.9±7.9)years old.Knee function was evaluat-ed using the International Knee Documentation Committee(IKDC)and Lysholm scores both before the operation and at the fi-nal follow-up.Meniscus healing was evaluated according to the postoperative Barrett standard.Wound healing complications,such as vascular injury,nerve injury,and lower extremity venous thrombosis,were recorded.Results All 57 patients were fol-lowed up for 12 to 58 months with an average of(38.1±14.9)months.The incisions of the patients after the operation were all Grade A healing without infection,popliteal tendon injury,blood vessel injury,nerve injury and lower extremity venous throm-bosis.The IKDC score increased from(49.7±3.6)points preoperatively to(88.5±4.4)points in the final follow-up(P＜0.05).The Lysholm score increased from(48.8±4.9)points preoperatively to(91.9±3.9)points at the final follow-up(P＜0.05).At 3,6 months and 1 year after operation,according to Barrett's criteria,54 cases were clinically healed,the healing rate was 94.7％(54/57).Conclusion This study preliminarily confirmed that arthroscopic suture technique can result in clinical sta-bility through suture and fixation of the meniscus in the injured lateral popliteal tendon area.No adverse effects on knee joint function were found in the mid-term follow-up after the operation.

Objective To preliminarily evaluate the safety and effectiveness of a novel non-implantable atrial shunt device based on radiofrequency ablation for the treatment of chronic heart failure(CHF).Methods This was a prospective single-arm study.From January 2023 to December 2023,five eligible CHF patients were consecutively enrolled at Beijing Anzhen Hospital,Capital Medical University,and underwent inter-atrial shunt using Shenzhen Betterway atrial shunt device.Pulmonary capillary wedge pressure(PCWP),right atrial pressure(RAP),pulmonary artery pressure(PAP),total pulmonary resistance(TPR),pulmonary vascular resistance(PVR),and pulmonary/systemic blood flow ratio(Qp/Qs)were measured using right heart catheterization before and immediately after procedure.Patients were followed up for 90 days,and echocardiography,right heart catheterization,and cardiac functional indicators were evaluated.The primary endpoint was procedural success.Secondary endpoints included clinical success,echocardiographic changes,6-minute walk distance(6MWD)changes,New York Heart Association(NYHA)class changes,Kansas city cardiomyopathy questionnaire(KCCQ)score changes,and amino-terminal probrain natriuretic peptide(NT-proBNP)level changes at 90 days.The safety endpoint was major cardiovascular and cerebrovascular adverse events and device-related adverse events.Results All five patients successfully achieved left-to-right atrial shunt.Compared with baseline,PCWP decreased significantly immediately after procedure in all five patients,with a procedural success rate of 100％.There were no significant changes in RAP,PAP,TPR,and PVR before and immediately after procedure.After 90 days follow-up,four patients had persistent left-to-right atrial shunt,and PCWP was significantly lower than baseline,with a clinical success rate of 80％.Compared with baseline,LVEF increased,left ventricular end-diastolic diameter decreased,and tricuspid annular plane systolic excursion and right ventricular fractional area change were not impaired in all five patients at 90 days.KCCQ scores and 6MWT improved,NT-proBNP decreased,and NYHA class did not change significantly.There were no deaths,rehospitalizations for heart failure,stroke-related adverse events,or device-related adverse events during the follow-up.Conclusions The novel non-implantable atrial shunt catheter can safely and effectively improve hemodynamic,echocardiographic,and cardiac functional indicators in patients with heart failure.However,larger-scale clinical studies are still needed to validate its long-term clinical effectiveness.

Despite significant advancements in treatments for heart failure,the overall prognosis for patients remains poor.Hemodynamic abnormalities in heart failure manifest as elevated left atrial pressure and pulmonary congestion.Previous studies have shown that reducing left atrial pressure can improve symptoms and prognosis for heart failure patients,suggesting that left-sided heart overload may be a potential target for heart failure treatment.Atrial shunting procedures aim to create a stable and controlled left-to-right intracardiac shunt,restoring the decompensated left heart volume and pressure load in heart failure patients to a compensatory state,thereby improving heart failure symptoms and prognosis.Currently,this treatment is still in the clinical research stage globally.Existing data indicate that atrial shunting procedures can lower left atrial pressure at rest or during exercise in heart failure patients,improve pulmonary congestion,enhance patients'exercise tolerance,and clinical cardiac function.However,no studies have yet confirmed that it can improve clinical endpoints such as rehospitalization and mortality due to heart failure.Future research will focus on identifying heart failure patients who may benefit from atrial shunting,with assessments of heart failure etiology,right heart function,and reversibility of pulmonary vascular resistance,as well as heart failure classification based on ejection fraction,serving as potential key factors for patient selection.

Objective:To understand the current situation of nursing undergraduate students ' mastery of core skills and analyze the impact paths of learning environment and self-efficacy on the level of nursing core ability mastery. Methods:Using the convenient sampling method, a total of 431 nursing undergraduates from 6 universities in Macao and Guangdong Province were selected as the research objects from November to December 2022. The self-made general data questionnaire, Nursing Core Skills Mastery Questionnaire and General Self-Efficacy Scale were used to investigate the patients.Results:The total score of core nursing skills for 431 undergraduate nursing students was (3.55±0.59). The learning environment had a positive direct effect on the mastery of core skills ( P<0.05), which could indirectly affect the mastery of core skills through the mediating effects of self-efficacy, personal foundation and planning ( P<0.05) . Conclusions:Application-oriented colleges, progressive practice plans and increasing the proportion of electives are conducive to the improvement of self-efficacy and the mastery of core nursing skills. It is recommended that nursing colleges clarify the direction of talent cultivation based on their own situation, increase the proportion of elective courses and add clinical practice content in the course process, in order to promote the mastery of core nursing skills for nursing undergraduate students.

Objective:To explore the characteristics of the immunophenotypic expression of bone marrow monocytes (M ) and its clinical significance in patients with multiple myeloma (MM ). Methods:The monocyte immunophenotypes expression of 67 MM and 30 anemic patients (control group)were detected by flow cytometry.The immunophenotypes that exhibited statistical differences from the control group were screened out.Further univariate and multivariate regression was used analyze the risk factors affecting the prognosis. The effect of monocyte immunophenotype on the prognosis of MM was analyzed.The correlation of CD38+monocytes with clinical features was explored.Results:The percentages of CD138+monocytes (CD138+M％),CD27+monocytes (CD27+M％),and CD56+monocytes (CD56+M％)in the MM group were significantly higher than that in the control group(P<0.05),but the percentages of CD38+monocytes (CD38+M％)and HLA-DR+monocytes (HLA-DR+M％)were significantly lower than that in the control group (P<0.01 ).The median progression-free survival (PFS)was shorter in the low CD38+monocyte proportion (LCD38+M％)group compared to the high CD38+monocyte proportion (HCD38+M％) group.Additionally,the median overall survival (OS)was significantly shorter in the low CD138+monocyte proportion (LCD138+M％),low CD27+monocyte proportion (LCD27+M％),low CD38+monocyte proportion (LCD38+M％),and low HLA-DR+monocyte proportion (LHLA-DR+M％)groups.Cox regression analysis showed that the low CD38+M％ was an independent risk factor for OS.The LCD38+M％group had significantly higher proportions of involved/uninvolved free light chain ratios ≥100 and 1q21+compared to the HCD38+M％ group (P<0.05 ). Moreover,the proportion of CD38-myeloma cells was significantly higher in the LCD38+M％ group than that in the HCD38+M％ group (P<0.05).Conclusion:The expression of CD38+monocytes in bone marrow of MM patients is closely related to the prognosis and clinical characteristics.CD38+monocytes maybe used to predict prognosis and guide treatment decisions.

Objective:To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.Methods:The patients with septic shock meeting the Sepsis-3 criteria were selected from Medical Information Mart for Intensive Care-Ⅳ v2.0 (MIMIC-Ⅳ v2.0). According to the principle of random allocation, 70% of these patients were used as the training set, and 30% as the validation set. Relevant predictive variables were extracted from three aspects: demographic characteristics and basic vital signs, serum indicators within 24 hours of intensive care unit (ICU) admission and complications possibly affecting indicators, functional scoring and advanced life support. The predictive efficacy of models constructed using five mainstream machine learning algorithms including decision tree classification and regression tree (CART), random forest (RF), support vector machine (SVM), linear regression (LR), and super learner [SL; combined CART, RF and extreme gradient boosting (XGBoost)] for 28-day death in patients with septic shock was compared, and the best algorithm model was selected. The optimal predictive variables were determined by intersecting the results from LASSO regression, RF, and XGBoost algorithms, and a predictive model was constructed. The predictive efficacy of the model was validated by drawing receiver operator characteristic curve (ROC curve), the accuracy of the model was assessed using calibration curves, and the practicality of the model was verified through decision curve analysis (DCA).Results:A total of 3?295 patients with septic shock were included, with 2?164 surviving and 1?131 dying within 28 days, resulting in a mortality of 34.32%. Of these, 2?307 were in the training set (with 792 deaths within 28 days, a mortality of 34.33%), and 988 in the validation set (with 339 deaths within 28 days, a mortality of 34.31%). Five machine learning models were established based on the training set data. After including variables at three aspects, the area under the ROC curve (AUC) of RF, SVM, and LR machine learning algorithm models for predicting 28-day death in septic shock patients in the validation set was 0.823 [95% confidence interval (95% CI) was 0.795-0.849], 0.823 (95% CI was 0.796-0.849), and 0.810 (95% CI was 0.782-0.838), respectively, which were higher than that of the CART algorithm model (AUC = 0.750, 95% CI was 0.717-0.782) and SL algorithm model (AUC = 0.756, 95% CI was 0.724-0.789). Thus above three algorithm models were determined to be the best algorithm models. After integrating variables from three aspects, 16 optimal predictive variables were identified through intersection by LASSO regression, RF, and XGBoost algorithms, including the highest pH value, the highest albumin (Alb), the highest body temperature, the lowest lactic acid (Lac), the highest Lac, the highest serum creatinine (SCr), the highest Ca 2+, the lowest hemoglobin (Hb), the lowest white blood cell count (WBC), age, simplified acute physiology score Ⅲ (SAPSⅢ), the highest WBC, acute physiology score Ⅲ (APSⅢ), the lowest Na +, body mass index (BMI), and the shortest activated partial thromboplastin time (APTT) within 24 hours of ICU admission. ROC curve analysis showed that the Logistic regression model constructed with above 16 optimal predictive variables was the best predictive model, with an AUC of 0.806 (95% CI was 0.778-0.835) in the validation set. The calibration curve and DCA curve showed that this model had high accuracy and the highest net benefit could reach 0.3, which was significantly outperforming traditional models based on single functional score [APSⅢ score, SAPSⅢ score, and sequential organ failure assessment (SOFA) score] with AUC (95% CI) of 0.746 (0.715-0.778), 0.765 (0.734-0.796), and 0.625 (0.589-0.661), respectively. Conclusions:The Logistic regression model, constructed using 16 optimal predictive variables including pH value, Alb, body temperature, Lac, SCr, Ca 2+, Hb, WBC, SAPSⅢ score, APSⅢ score, Na +, BMI, and APTT, is identified as the best predictive model for the 28-day death risk in patients with septic shock. Its performance is stable, with high discriminative ability and accuracy.