Cuproptosis, a recently discovered form of regulated cell death involving copper ion metabolism, has emerged as a promising approach for tumor therapy. This pathway not only directly eliminates tumor cells but also promotes immunogenic cell death (ICD), reshaping the tumor microenvironment (TME) and initiating robust anti-tumor immune responses. However, translating cuproptosis-based therapies into clinical applications is hindered by challenges, including complex metabolic regulation, TME heterogeneity, and the precision required for effective drug delivery. To address these limitations, nanoparticles offer transformative solutions by providing precise delivery of cuproptosis-inducing agents, controlled drug release, and enhanced therapeutic efficacy through simultaneous modulation of metabolic pathways and immune responses. This review systematically discusses recent advancements in nanoparticle-based cuproptosis delivery systems, highlighting nanoparticle design principles and their synergistic effects when integrated with other therapeutic modalities such as ICB, PTT, and CDT. Furthermore, we explore the potential of cuproptosis-based nanomedicine for personalized cancer treatment by emphasizing strategies for TME stratification and therapeutic optimization tailored to patient profiles. By integrating current insights from metabolic reprogramming, tumor immunotherapy, and nanotechnology, this review aims to facilitate the clinical translation of cuproptosis nanomedicine and significantly contribute to the advancement of precision oncology.

OBJECTIVE: To observe change in serum growth differentiation factor 11 (GDF11) and killer cell lectin-like receptor B1 (KLRB1), to construct a nomogram model for 28-day death in patients with septic shock, and to explore its predictive value. METHODS: A prospective observational study was conducted. The patients with septic shock admitted to the emergency intensive care unit (ICU) of Cangzhou Central Hospital from September 2023 to March 2025 were selected as the septic shock group, the patients with sepsis admitted to the emergency general ward during the same period were selected as the sepsis group, and healthy individuals undergoing physical examination during the same period were selected as the control group. On the day of hospital admission or physical examination for the research subjects, the levels of serum GDF11 and KLRB1 were detected by enzyme-linked immunosorbent assay (ELISA). The patients with septic shock were divided into survival and death groups based on their 28-day survival status. The patients' gender, age, past medical history, infection site, severity of illness, mechanical ventilation, blood purification, infection indicators, biochemical indicators, coagulation function indicators, and blood lactic acid (Lac) were collected. The clinical data of the patients with septic shock between the two groups with different prognoses were compared. Multivariate Logistic regression analysis was used to screen the risk factors for 28-day death in patients with septic shock, and bivariate Pearson correlation analysis was conducted. A nomogram model was constructed based on the risk factors for 28-day death in patients with septic shock. The discrimination and calibration of the nomogram model were evaluated using the receiver operator characteristic curve (ROC curve), Hosmer-Lemeshow goodness-of-fit test, and calibration curve. The clinical utility of the model was evaluated using clinical decision curve analysis (DCA). RESULTS: A total of 168 patients in the emergency ICU were enrolled in the septic shock group, 40 patients in the emergency general ward were enrolled in the sepsis group, and 40 healthy individuals were enrolled in the control group. Compared with the healthy control group, the serum GDF11 levels in the sepsis and septic shock groups were significantly increased (μg/L: 13.09±3.51, 19.28±5.36 vs. 4.17±0.92, both P < 0.05), and the serum KLRB1 levels were significantly decreased (ng/L: 57.36±11.28, 45.52±9.07 vs. 84.19±17.16, both P < 0.05), with more significant changes in the septic shock group (both P < 0.05). Among the 168 patients with septic shock, 96 survived and 72 died within 28 days. Compared with the survival group, the serum GDF11 level in the death group was significantly increased (μg/L: 24.24±4.81 vs. 15.56±4.62, P < 0.05), and the serum KLRB1 level was significantly decreased (ng/L: 28.53±8.69 vs. 58.26±9.45, P < 0.05). There were also statistically significant differences in sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHEII) score, procalcitonin (PCT), activated partial thromboplastin time (APTT), D-dimer, and Lac between the two groups. Multivariate Logistic regression analysis showed that SOFA score [odds ratio (OR) = 1.96, 95% confidence interval (95%CI) was 1.38-3.65), Lac (OR = 1.38, 95%CI was 1.09-2.01), GDF11 (OR = 1.54, 95%CI was 1.21-2.33) and KLRB1 (OR = 0.64, 95%CI was 0.41-0.78) were independent risk factors for 28-day death in patients with septic shock (all P < 0.05). Bivariate Pearson correlation analysis showed that SOFA score was significantly positively correlated with Lac and GDF11 (r value was 0.37 and 0.58, respectively, both P < 0.05), and significantly negatively correlated with KLRB1 (r = -0.72, P < 0.05). A nomogram model was constructed based on the risk factors for 28-day death in patients with septic shock. ROC curve analysis showed that the area under the ROC curve (AUC) of the nomogram model for predicting 28-day death in patients with septic shock was 0.963 (95%CI was 0.929-0.990), indicating that the model had good discrimination and predictive ability. The Hosmer-Lemeshow goodness-of-fit test (χ ² = 9.578, P = 0.295) and calibration curve indicated that the predicted values of the model were in good agreement with the actual values. DCA indicated that the model provided a high net benefit for clinical decision-making. CONCLUSIONS The serum GDF11 level was significantly increased and the KLRB1 level was significantly decreased in patients with septic shock. The nomogram model based on GDF11 and KLRB1 could more accurately evaluate the 28-day death of patients with septic shock.
Humans ; Shock, Septic/blood* ; Nomograms ; Prospective Studies ; Prognosis ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units

Traditional Chinese medicine,ancient Greek medicine,Ayurvedic medicine,and Arab medicine are recognized as the four major traditional medicines in the world.It reviews the education and training systems of the four major traditional medicines and finds that traditional Chinese medicine focuses on the teacher-student relation-ship and the combination of theory and practice;Ancient Greek medicine was mainly characterized by strong theoreti-cal research and experimental observation;Ayurveda highly values cultural identity as its main characteristic;Arab medicine attaches great importance to cultural exchange and practical promotion.It suggests promoting innovative de-velopment,strengthening practical teaching,improving teaching quality,strengthening international exchanges and cooperation,and increasing public acceptance abroad.

Non-alcoholic fatty liver disease(NAFLD)is a series of diseases characterized by hepatic steatosis and is also a metabolism-associated disease and an important factor for liver fibrosis,liver cirrhosis,and hepatocellular carcinoma.Endoplasmic reticulum is a core organelle for the regulation of lipid metabolism,and unfolded protein response is an important process of endoplasmic reticulum stress(ERS).Based on the important stress role of endoplasmic reticulum in metabolism-associated diseases,this article explores the influencing mechanism between ERS and NAFLD and reviews the research advances in lipid metabolism,inflammatory response,hepatocyte death,fibrosis,and ERS-targeted therapies in the pathological development of NAFLD.

Objective:To describe demographic,clinical and physiological characteristics,treatment between first-episode major depressive disorder(MDD)and relapse MDD,and to explore characteristics of relapse MDD.Methods:Totally 858 patients who met the diagnostic criteria for depression of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),were included by using the Mini International Neuropsychiatric Interview(MINI),Clinician-Rated Dimensions of Psychosis Symptom Severity,and Hamilton Depression Scale etc.Among them,529(58.6％)were first-episode depression and 329(36.0％)were relapsed.The differences of demographic characteristics,clinical and physiological characteristics,treatment were compared byx2test and Kruskal-Wallis rank sum test.Multivariate logistic regression was used to explore the characteristics of MDD recur-rence.Results:Compared to first-episode MDD,relapse MDD had more comorbidity(OR=2.11,95％CI:1.00-4.44),more days out of role(OR=1.26,95％CI:1.01-1.56),more history of using psychiatric drug more than one month(OR=1.41,95％CI:1.02-1.97)and electroconvulsive therapy(OR=3.23,95％CI:1.42-7.36),and higher waist-hip ratio(OR=33.88,95％CI:2.88-399.32).Conclusion:Relapse MDD has positive as-sociation with comorbidity of mental disorders,out of role,and higher waist-hip ratio.

Objective To explore the application low of stimulation parameters of transcutaneous electrical acupoint stimulation(TEAS)and transcranial direct current stimulation(tDCS)for post-stroke movement disorders based on data mining.Methods The relevant clinical research literature was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed and Web of Science from January 2000 to May 2023.A database was set up after quality assessment.Frequency analysis,association rules and complex network analysis were used to explore the application law of core acupoints and electrical stimulation parameters.Results A total of 79 articles were included and 128 groups of data were contained.For TEAS,the core acupoints included Waiguan(TE5),Shousanli(LI10),Zusanli(ST36),Hegu(LI4),Neiguan(PC6),Yanglingquan(GB34),etc.,while the most commonly used acupoint combinations of upper limb and lower limb were Shousanli(LI10)-Waiguan(TE5)and Yanglingquan(GB34)-Zusanli(ST36).Among the electrical stimulation parameters of TEAS,the frequencies used vary widely,and 100 Hz was most commonly used,while 2 Hz TEAS was also mainly used for stimulating acupoints located on upper limbs in the treatment of flaccid paralysis.The application of other electrical stimulation parameters was relatively consistent.The bidirectional symmetrical square-wave with 200-250 μs pulse-width was used in majority of studies.The stimulus intensity was mostly determined by patient tolerance.For tDCS,stimulation electrodes were often positioned on the projection of the primary M1,and the safe stimulus intensity was mostly set as 1 to 2 mA.Conclusion In the treatment of post-stroke movement disorders,appropriate acupoints and electrical stimulation parameters of TEAS should be determined on the muscle strength and muscle tension of stroke patients at different stages after stroke,particularly the selection of electric stimulating frequency.

Objective:To explore any effect of combining robot-assisted virtual scenario training of the upper limbs with scalp acupuncture on post-stroke cognitive impairment.Methods:Ninety patients with post-stroke cognitive impairment (PSCI) were divided at random into a control group, a scalp acupuncture group and a comprehensive group, each of 30. In addition to routine health education and rehabilitation training, the scalp acupuncture group was given scalp acupuncture, while the comprehensive group was treated with scalp acupuncture and virtual scenario training with an upper limb robot. Before and after 4 weeks of the treatment, the subjects′ cognitive functioning was assessed using the Mini-mental State Examination (MMSE) and the Montreal Cognitive Assessment scale (MoCA). Ability in the activities of daily living (ADL) was quantified using the Modified Barthel Index (MBI).Results:After the intervention, significant improvement was observed in the average MMSE, MoCA and MBI scores of all three groups. The average MMSE and MBI scores of the scalp acupuncture group were then significantly higher than the control group′s averages, while the average MMSE, MoCA and MBI scores of the comprehensive group were all significantly better than those of the other two groups.Conclusion:Robot-assisted virtual scenario upper limb training combined with scalp acupuncture can significantly improve the cognition and ADL ability of PSCI patients.

Objective To explore the correlation between neutrophil-to-lymphocyte ratio(NLR)and Behcet's disease(BD)activity.Methods A total of 103 BD patients were divided into the low activity group(0-4,61 cases)and the high activity group(5-11,42 cases)according to electronic medical record-based disease activity index(EMRAI)score.The white blood cell(WBC),neutrophil(NEU),lymphocyte(LY),platelet(PLT),red blood cell(RBC),hemoglobin(Hb),erythrocyte sedimentation rate(ESR),C-reactive protein(CRP),IgG,IgA,IgM,complement C3 and C4 were detected.NLR and platelet-to-lymphocyte ratio(PLR)were calculated.The correlation between NLR,PLR and ESR,CRP,EMRAI were analyzed.Logistic regression was used to analyze the influencing factors of BD disease activity.Receiver operating characteristic(ROC)curve was drawn to evaluate the effectiveness of NLR in judging BD disease activity.Results WBC,NEU,PLT,ESR,CRP,NLR,PLR,complement C3 and C4 in patients were higher in the high activity group than those in the low activity group(P＜0.05),and there were no significant differences in other indexes(P＞0.05).NLR was positively correlated with ESR,CRP and EMRAI in the whole group,while PLR was positively correlated with ESR,CRP and EMRAI in the whole group(P＜0.05).Logistic regression analysis showed that high NLR was a risk factor for BD disease activity(OR=1.511,95%CI:1.080-2.113,P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of NLR in evaluating BD disease activity was 0.706(95%CI:0.603-0.809).Conclusion NLR is effective in judging the disease activity of BD patients,and can be used as a biological index to evaluate the disease activity of BD.

Objective To explore a method to improve the accuracy and generalization ability of medical diagnostic neural network models under conditions of small data volumes,and to address the issue of poor neural network model performance in computer-aided diagnosis of nail diseases due to limited training data.Methods A dual-model strategy integrating instance segmentation with fine-grained feature classification was proposed.The neural network model based on dual-model strategy was trained using the dataset of Image-Based Intelligent Diagnosis of Nail Disease Model task of the first National Digital Health Innovation Application Competition & Health and Medical Big Data Theme Competition.This dataset covered 8 types of nail diseases,including nail matrix nevi,paronychia,nail psoriasis,onychomycosis,subungual hemorrhage,melanonychia,periungual warts,and nail melanoma,with class imbalance present.The diagnostic performance of the dual-model strategy was evaluated and compared with single-model strategies(image classification models[ResNet50 and Swin Transformer]and target detection model based on faster region-based convolutional neural network[Faster R-CNN])under the same hardware and software training conditions.Results The dataset included 1 048 samples,including 210 cases of nail matrix nevi,186 cases of paronychia,69 cases of nail psoriasis,203 cases of onychomycosis,149 cases of subungual hemorrhage,71 cases of melanonychia,93 cases of periungual warts,and 67 cases of nail melanoma,with 90％used for training various models and 10％for evaluation.The micro F1 score was 0.324 in the image classification model based on ResNet50,0.381 in the image classification model based on Swin Transformer,0.572 in the target detection model based on Faster R-CNN,and 0.714 in the dual-model strategy model Mask R-CNN+Swin Transformer.The accuracy rates for diagnosing different nail diseases in the dual-model strategy were:nail matrix nevi 80.95％(17/21),paronychia 89.47％(17/19),nail psoriasis 100.00％(7/7),onychomycosis 70.00％(14/20),subungual hemorrhage 73.33％(11/15),melanonychia 14.29％(1/7),periungual warts 55.56％(5/9),and nail melanoma 42.86％(3/7).The micro F1 score for evaluating the dual-model strategy on a test set of 1 000 cases was 0.844.Conclusion The dual-model strategy can effectively combine models with different functions to well accomplish the task of intelligent diagnosis of nail diseases under small data volume training conditions.

The syndrome/pattern of defensive qi deficiency is a common basic syndrome of traditional Chinese medicine in clinical practice. However,there is a lack of standardized and operable diagnostic specifications in practical applications. Based on the previous literature,this study proposed the idea of starting from the elements of the syndrome,qualitative diagnostic criteria for the syndrome/pattern of defensive qi deficiency oriented to the entire region of the disease were constructed based on the two dimensions of " deficient defensive qi failing to consolidate the exterior" and " qi deficiency" and constructing a set of quantitative evaluation criteria as the supporting content for the diagnostic items. The core members of the research group attempted to formulate the draft standard,then reached a consensus through the Delphi method expert questionnaire consultation and the Nominal group technique,and finally evaluated the reliability and validity of the standard through clinical verification to provide ideas for the standardization and normalization of research on syndromes.