ObjectiveTo explore the effect of blood flow restriction training (BFRT) under different intensities combined with low-intensity resistance training (LIRT) on motor function in stroke patients with frailty. MethodsFrom August, 2024 to August, 2025, 200 elderly ischemic stroke patients with frailty from Affiliated Hospital, North China University of Science and Technology were randomized into control group and observation groups 1, 2 and 3, with 50 cases in each group. All the groups received 30% 1RM resistance training. In addition, the observation groups received BFRT of 40%, 50% and 60% arterial occlusion pressure (AOP), respectively. Before training, and four and eight weeks after training, their motor function was evaluated with Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and Fugl-Meyer Assessment-Lower Extremities (FMA-LE), grip strength, 10-Metre Walk Test (10MWT) and Berg Balance Scale (BBS); Fried Frailty Phenotype (FFP) was used to assess frailty status; and the score of modified Ashworth Scale (MAS), blood pressure and resting heart rate were recorded. ResultsOne case dropped out in each group. For the scores of FMA-UE and FMA-LE, the grip strength of both hands, the time of 10MWT and the score of BBS, the main effects of group and time, and interaction effect were all significant (F > 2.745, P < 0.05); four weeks after training, the above indexes were better in the observation groups than in the control group (P < 0.05); eight weeks after training, the scores of FMA-UE and FMA-LE, the grip strength of both hand and the score of BBS were better in the observation group 3 than in the observation groups 1 and 2 (P < 0.05), and the time of 10MWT was better in the observation group 3 than in the observation group 1 (P < 0.05). For the score of FFP, the main effect of group was significant (F = 688.360, P < 0.001), however, the effects of time and interaction were not significant (P > 0.05). For the score of MAS, the main effect of group was significant (F = 7.171, P = 0.008), however, the effects of time and interaction were not significant (P > 0.05). For the blood pressure and resting heart rate, the main effects of group and time, and interaction effect were not significant (P > 0.05). ConclusionBFRT under different intensities combined with LIRT can safely improve the motor function, grip strength, walking ability in elderly stroke patients, and 60% AOP may be more effective.

BACKGROUND:The role of microRNA-214 in osteoporosis has been reported both at home and abroad,whereas the interrelationship between microRNA-214 and osteoarthritic articular cartilage and subchondral bone degeneration is unclear. OBJECTIVE:To investigate the relationship between microRNA-214 and cartilage and subchondral bone degeneration in mice with knee osteoarthritis. METHODS:Thirty C57BL/6J mice were randomly grouped:Experiment 1:sham operation group and medial meniscus destabilization group (n=3 per group) underwent hematoxylin-eosin staining and qPCR to detect changes in microRNA-214 gene expression;Experiment 2:sham operation group,medial meniscus destabilization group,medial meniscus destabilization+null-loaded adenovirus group (null-loaded group),and medial meniscus destabilization+microRNA-214 antagonist overexpression adenovirus group (antagonist group;n=6 per group). Cartilage tissues were taken from each group 4 weeks after surgery,and stained with hematoxylin-eosin,safranin O-fast green,and toluidine blue. qPCR and western blot were used to detect the expression of related factors in articular cartilage. RESULTS AND CONCLUSION:(1) In Experiment 1,hematoxylin-eosin staining results showed that cartilage degeneration was visible in the medial meniscus destabilization group compared with the sham operation group. qPCR assay results showed that microRNA-214 was expressed in all the samples,and the expression level of microRNA-214 in cartilage samples of the medial meniscus destabilization group was significantly higher than that of the sham operation group (P<0.05). (2) In Experiment 2,the results of hematoxylin-eosin staining,safranin O-fast green staining,and toluidine blue staining showed that the degree of cartilage degeneration in the antagonist group was significantly reduced compared with the medial meniscus destabilization group. Adenovirus-validated PCR assay showed that the microRNA-214 expression level in cartilage tissue was higher in the null-loaded group than in the antagonist group (P<0.05). (3) In Experiment 2,X-ray results showed typical osteoarthritis imaging changes in the medial meniscus destabilization group and null-loaded group,while the degree of degenerative joint lesions was relatively mild in the antagonist group. The results of microcomputed tomography showed that after injection of microRNA-214 antagonist,trabecular structure model index became smaller in the antagonist group,and the data were better than those of the medial meniscus destabilization group and null-loaded group. (4) In Experiment 2,western blot results showed that The relative expression levels of cartilage-associated factor type Ⅱ collagen α1,sex-determining region Y-box 9,Runt-associated transcription factor 2,and osteopontin in cartilage specimens of the medial meniscus destabilization group and the null-loaded group were lower than that in the sham operation group and the antagonist group (P<0.05),whereas the relative expression level of matrix metalloproteinase 13 was higher in the medial meniscus destabilization group and the null-loaded group than the sham operation group and the antagonist group (P<0.05). (5) In Experiment 2,PCR results indicated that the relative mRNA expression of tumor necrosis factor-α and interleukin-6 was relatively higher in the medial meniscus destabilization group and null-loaded group,but relatively lower in the antagonist group,as compared with the sham operation group (P<0.05). The relative mRNA expression of tumor necrosis factor-α and interleukin-6 was also higher in the medial meniscus destabilization group and the null-loaded group compared with the antagonist group (P<0.05). To conclude,the expression level of microRNA-214 in articular cartilage was elevated in the mouse osteoarthritis model,suggesting that the elevated expression level of microRNA-214 is closely related to osteoarthritis;and injection of microRNA-214 antagonist into the knee joint cavity of the mouse osteoarthritis model could delay articular cartilage degradation,promote subchondral bone remodeling,and ameliorate the progression of osteoarthritis.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Objective:To investigate the effect of applying the analog of miR-145(agomiR-145)to target a disintegrin and metallopro-tease 17(ADAM17)on the growth of triple-negative breast cancer(TNBC)xenograft tumors in nude mice and the underlying mecha-nism.Methods:A subcutaneous xenograft tumor model was established in nude mice with MDA-MB-231 cells(n=30).The 30 nude mice were randomly divided into agomiR group,agomiR-NC group,and control group to receive intratumoral injection of 100 μL of agomiR-145(0.33 g/L),agomiR-NC(0.33 g/L),and normal saline,respectively.We examined tumor tissue morphology with HE stain-ing;measured the expression of miR-145,ADAM17,and epidermal growth factor receptor(EGFR)in tumor tissues by real-time poly-merase chain reaction(RT-PCR);and determined the protein expression of ADAM17,EGFR,and p-EGFR in tumor tissues by immu-nohistochemistry and Western blot.Results:The tumor growth in the agomiR group was slow,with a significantly smaller tumor volume than those in the control group and the agomiR-NC group(P<0.05).The results of HE staining showed more severe necrosis and hem-orrhage within tumor tissues in the control group and the agomiR-NC group than in the agomiR group.RT-PCR results showed that the expression level of miR-145 in the agomiR group was significantly higher than those in the agomiR-NC and control groups(P<0.001);the agomiR group had a significantly lower mRNA expression level of ADAM17 than the other two groups(P<0.05);and there was no significant difference in EGFR mRNA expression between the three groups(P>0.05).Immunohistochemistry and Western blot detected significantly lower protein expression levels of ADAM17 and EGFR in the agomiR group than in the agomiR-NC group and the control group(P<0.05).Conclusion:AgomiR-145 inhibits the growth of TNBC xenografts in nude mice by targeted suppression of ADAM17-EGFR activity.

Primary pulmonary nuclear protein of the testis (NUT) midline carcinoma (NMC) is a rare and highly aggressive thoracic malignancy that poses significant diagnostic and therapeutic challenges in clinical practice. This tumor is characterized by its heterogeneous clinical presentations and poor prognosis, often evading accurate initial diagnosis. In this study, we present two cases of primary pulmonary NMC treated with an integrated therapeutic approach combining anti-angiogenic agents, platinum-based chemotherapy, and radiotherapy. This multimodal strategy achieved survival durations of 32 and 13 months, respectively, surpassing the currently reported median survival of advanced NMC. Through a systematic literature review of reported cases, we have summarized the currently used diagnostic methods and treatment modalities for NMC. Our findings suggest that multimodal therapy incorporating anti-angiogenic treatment may offer superior clinical outcomes compared to conventional monotherapy regimens, particularly for patients who are not eligible for surgery. This comprehensive investigation enhances our understanding of NMC management by elucidating diagnostic pitfalls through histopathological correlation and proposing an effective therapeutic combination that demonstrates improved survival outcomes. By providing valuable insights into the diagnosis and treatment of primary pulmonary NMC, we hope to contribute to the development of more effective strategies for managing this rare and aggressive malignancy.
Humans ; Angiogenesis Inhibitors/therapeutic use* ; Carcinoma/therapy* ; Combined Modality Therapy ; Lung Neoplasms/diagnosis* ; Nuclear Proteins ; Oncogene Proteins ; Neoplasm Proteins

BACKGROUND:The role of microRNA-214 in osteoporosis has been reported both at home and abroad,whereas the interrelationship between microRNA-214 and osteoarthritic articular cartilage and subchondral bone degeneration is unclear. OBJECTIVE:To investigate the relationship between microRNA-214 and cartilage and subchondral bone degeneration in mice with knee osteoarthritis. METHODS:Thirty C57BL/6J mice were randomly grouped:Experiment 1:sham operation group and medial meniscus destabilization group (n=3 per group) underwent hematoxylin-eosin staining and qPCR to detect changes in microRNA-214 gene expression;Experiment 2:sham operation group,medial meniscus destabilization group,medial meniscus destabilization+null-loaded adenovirus group (null-loaded group),and medial meniscus destabilization+microRNA-214 antagonist overexpression adenovirus group (antagonist group;n=6 per group). Cartilage tissues were taken from each group 4 weeks after surgery,and stained with hematoxylin-eosin,safranin O-fast green,and toluidine blue. qPCR and western blot were used to detect the expression of related factors in articular cartilage. RESULTS AND CONCLUSION:(1) In Experiment 1,hematoxylin-eosin staining results showed that cartilage degeneration was visible in the medial meniscus destabilization group compared with the sham operation group. qPCR assay results showed that microRNA-214 was expressed in all the samples,and the expression level of microRNA-214 in cartilage samples of the medial meniscus destabilization group was significantly higher than that of the sham operation group (P<0.05). (2) In Experiment 2,the results of hematoxylin-eosin staining,safranin O-fast green staining,and toluidine blue staining showed that the degree of cartilage degeneration in the antagonist group was significantly reduced compared with the medial meniscus destabilization group. Adenovirus-validated PCR assay showed that the microRNA-214 expression level in cartilage tissue was higher in the null-loaded group than in the antagonist group (P<0.05). (3) In Experiment 2,X-ray results showed typical osteoarthritis imaging changes in the medial meniscus destabilization group and null-loaded group,while the degree of degenerative joint lesions was relatively mild in the antagonist group. The results of microcomputed tomography showed that after injection of microRNA-214 antagonist,trabecular structure model index became smaller in the antagonist group,and the data were better than those of the medial meniscus destabilization group and null-loaded group. (4) In Experiment 2,western blot results showed that The relative expression levels of cartilage-associated factor type Ⅱ collagen α1,sex-determining region Y-box 9,Runt-associated transcription factor 2,and osteopontin in cartilage specimens of the medial meniscus destabilization group and the null-loaded group were lower than that in the sham operation group and the antagonist group (P<0.05),whereas the relative expression level of matrix metalloproteinase 13 was higher in the medial meniscus destabilization group and the null-loaded group than the sham operation group and the antagonist group (P<0.05). (5) In Experiment 2,PCR results indicated that the relative mRNA expression of tumor necrosis factor-α and interleukin-6 was relatively higher in the medial meniscus destabilization group and null-loaded group,but relatively lower in the antagonist group,as compared with the sham operation group (P<0.05). The relative mRNA expression of tumor necrosis factor-α and interleukin-6 was also higher in the medial meniscus destabilization group and the null-loaded group compared with the antagonist group (P<0.05). To conclude,the expression level of microRNA-214 in articular cartilage was elevated in the mouse osteoarthritis model,suggesting that the elevated expression level of microRNA-214 is closely related to osteoarthritis;and injection of microRNA-214 antagonist into the knee joint cavity of the mouse osteoarthritis model could delay articular cartilage degradation,promote subchondral bone remodeling,and ameliorate the progression of osteoarthritis.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To investigate the application status of emergency radiology in China, and to provide data support for the standardized development, scientific management and big data research of emergency radiology.Methods:From August 12th to October 19th, 2022, a questionnaire survey was conducted through WeChat"Questionnaire Star"to send targeted questionnaires to investigate the relevant data of the current status of emergency radiology in China, mainly including digital radiography (DR) and computed tomography (CT). This study was initiated by the Chinese Emergency Radiology Database Collaboration Group, and comprehensively investigated emergency imaging personnel, equipment, workload, critical value reporting process, and artificial intelligence (AI) application status.Results:There were 123 hospitals in the study. The survey showed that emergency DR/CT reports were mainly completed by residents and above (69.1%). There were 21 DR brands, 10 CT brands and 8 MR brands used for emergency imaging examinations. The median number of DR examinations in tertiary hospitals and secondary hospitals investigated from January to June 2022 was 4 642 and 2 015 cases respectively, and the median number of CT examinations was 16 512 and 3 762 cases respectively. The average single-shift workload of DR in the emergency radiology department during the day and night shift in tertiary hospitals was mainly ≤20 copies and 21-50 copies, and the average single-shift workload of CT in the emergency radiology department during the day and night shift was mainly 21-50 copies and 51-100 copies, while the average single-shift workload of DR/CT in the emergency radiology department during the day/night shift in secondary hospitals was mainly ≤20 copies. In terms of critical value reporting process, 74.8% of emergency imaging doctors and 84.6% of emergency imaging technicians took the way of phone/text message to notify the clinical doctor or the patients′ family. The overall deployment rate of AI in emergency imaging was about 60.2%. 75% of the respondents believed that in the future, AI can improve emergency radiology work from aspects such as emergency screening, aided diagnosis and process optimization.Conclusions:The emergency medical imaging mainly based on DR and CT has the current situations such as generally low seniority of doctors, diverse brands of imaging equipments, large volume of examinations and intense workload per doctor, especially in tertiary hospitals, and dependence on traditional means for critical value reporting. At present, AI is emerging in the field of emergency imaging, and there is still a long way to go to play the huge potential of AI in the intelligent whole process of emergency imaging in the future.