Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

PURPOSE: This study aims to identify the prevalence and risk factors of military training-related abdominal injuries and help plan and conduct training properly. METHODS: This questionnaire survey study was conducted from October 2021 to May 2022 among military personnel from 6 military units and 8 military medical centers and participants' medical records were consulted to identify the training-related abdominal injuries. All the military personnel who ever participated in military training were included. Those who refused to participate in this study or provided an incomplete questionnaire were excluded. The questionnaire collected demographic information, type of abdominal injury, frequency, training subjects, triggers, treatment, and training disturbance. Chi-square test and t-test were used to compare baseline information. Univariate and multivariate regression analyses were used to explore the risk factors associated with military training-related abdominal injuries. RESULTS: A total of 3058 participants were involved in this study, among which 1797 (58.8%) had suffered training-related abdominal injuries (the mean age was 24.3 years and the service time was 5.6 years), while 1261 (41.2%) had no training-related abdominal injuries (the mean age was 23.1 years and the service time was 4.3 years). There were 546 injured patients (30.4%) suspended the training and 84 (4.6%) needed to be referred to higher-level hospitals. The most common triggers included inadequate warm-up, fatigue, and intense training. The training subjects with the most abdominal injuries were long-distance running (589, 32.8%). Civil servants had the highest rate of abdominal trauma (17.1%). Age ≥ 25 years, military service ≥ 3 years, poor sleep status, and previous abdominal history were independent risk factors for training-related abdominal injury. CONCLUSION More than half of the military personnel have suffered military training-related abdominal injuries. Inadequate warm-up, fatigue, and high training intensity are the most common inducing factors. Scientific and proper training should be conducted according to the factors causing abdominal injuries.
Humans ; Military Personnel ; Risk Factors ; Prevalence ; Male ; Abdominal Injuries/etiology* ; Female ; Adult ; Surveys and Questionnaires ; Young Adult

OBJECTIVE: To investigate the effects of thymoquinone on the proliferation of acute myeloid leukemia (AML) cells and its molecular mechanism, so as to provide theoretical basis for the basic research on the anti-leukemia of traditional Chinese medicine. METHODS: The HL-60 and THP-1 cells were treated with thymoquinone at different concentration gradients, cell proliferation was detected by CCK-8 method, morphological changes were detected by Wright-Giemsa method, apoptosis was detected by Annexin V/PI double staining flow cytometry, and apoptosis and signal pathway protein expression were detected by Western blot. Real-time quantitative fluorescence PCR and Western blot were used to detect the expression changes of high mobility family members of SRY-related proteins (SOX). RESULTS: Thymoquinone inhibited the malignant proliferation of HL-60 and THP-1 cells, up-regulated the expression of pro-apoptotic protein Bax, down-regulated the expression of anti-apoptotic protein Bcl-2 and Survivin, and hydrolyzed Caspase-3 to induce the apoptosis of HL-60 and THP-1 cells. Thymoquinone could also significantly down-regulate the phosphorylation of PI3K, Akt and mTOR, and inhibit the malignant biological characteristics of HL-60 and THP-1 cells by inhibiting the activation of PI3K/Akt/mTOR pathway. After thymoquinone intervention in HL-60 and THP-1 cells, the expression of SOX2 and SOX4 could be down-regulated significantly. At low concentration ( < 10 μmol/L), the expression of SOX12 was weakly affected by thymoquinone. With increasing concentration, the expression of SOX12 could be down-regulated, however, thymoquinone had no effect on SOX11 expression. CONCLUSION Thymoquinone can inhibit the proliferation of AML cells, and its mechanism may be related to inhibiting the activation of PI3K/Akt/mTOR signaling pathway, regulating the expression of apoptotic proteins and core members of SOX family.
Humans ; Benzoquinones/pharmacology* ; Cell Proliferation/drug effects* ; Leukemia, Myeloid, Acute/metabolism* ; Apoptosis/drug effects* ; HL-60 Cells ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; bcl-2-Associated X Protein/metabolism* ; Cell Line, Tumor ; Phosphatidylinositol 3-Kinases/metabolism* ; THP-1 Cells

Objective:To explore the clinical application value of multimodal Magnetic Resonance Imaging(MRI)in cognitive impairment related to Cerebral Small Vessel Disease(CSVD).Methods:This study was a retrospective analysis of 60 CSVD patients,who were divided into cognitive impairment group(n=32)and normal group(n=28)based on Montreal Cognitive Assessment scale(MoCA).Compare the general information and MRI parameters of two groups of patients,use correlation analysis and logistic regression analysis to investigate the relationship between MRI parameters and cognitive dysfunction,and use receiver operating characteristic curve(ROC)to explore the value of MRI parameters in diagnosing cognitive dysfunction in cerebral small vessel disease.Results:Compared with the cognitively normal group,the cognitive impairment group had older age,higher apparent diffusion coefficient(ADC),lower anisotropy score(FA),and an overall increase in microbleeds(P＜0.05).Age(r=-0.510),ADC value(r=-0.591),and overall number of microbleeds(r=-0.369)were significantly negatively correlated with MoCA score(P＜0.05),while FA value(r=0.262)was significantly positively correlated with MoCA score(P＜0.05).The logistic regression results indicate that age,overall microbleeds,ADC value,and FA value are influencing factors for cognitive impairment in patients with cerebral small vessel disease.ROC curve analysis showed that the combination of age,ADC,FA,and microbleeds significantly improved diagnostic efficacy(AUC=0.990,95％CI=0.974-1.000).Conclusion:The joint analysis of multimodal MRI parameters can provide important imaging evidence for the early identification of cognitive dysfunction in CSVD.

Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.

Objective:To explore the clinical application value of multimodal Magnetic Resonance Imaging(MRI)in cognitive impairment related to Cerebral Small Vessel Disease(CSVD).Methods:This study was a retrospective analysis of 60 CSVD patients,who were divided into cognitive impairment group(n=32)and normal group(n=28)based on Montreal Cognitive Assessment scale(MoCA).Compare the general information and MRI parameters of two groups of patients,use correlation analysis and logistic regression analysis to investigate the relationship between MRI parameters and cognitive dysfunction,and use receiver operating characteristic curve(ROC)to explore the value of MRI parameters in diagnosing cognitive dysfunction in cerebral small vessel disease.Results:Compared with the cognitively normal group,the cognitive impairment group had older age,higher apparent diffusion coefficient(ADC),lower anisotropy score(FA),and an overall increase in microbleeds(P＜0.05).Age(r=-0.510),ADC value(r=-0.591),and overall number of microbleeds(r=-0.369)were significantly negatively correlated with MoCA score(P＜0.05),while FA value(r=0.262)was significantly positively correlated with MoCA score(P＜0.05).The logistic regression results indicate that age,overall microbleeds,ADC value,and FA value are influencing factors for cognitive impairment in patients with cerebral small vessel disease.ROC curve analysis showed that the combination of age,ADC,FA,and microbleeds significantly improved diagnostic efficacy(AUC=0.990,95％CI=0.974-1.000).Conclusion:The joint analysis of multimodal MRI parameters can provide important imaging evidence for the early identification of cognitive dysfunction in CSVD.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the clinical predictive value of SPECT myocardial perfusion imaging (MPI) in the occurrence of cardiac death in patients with chronic kidney disease (CKD).Methods:A retrospective follow-up was performed for 160 patients (109 males, 51 females; age: 68.5(61.0, 74.0) years) who underwent MPI in Beijing Anzhen Hospital, Capital Medical University between June 2017 and March 2024. The 17-segment 5-point method was used for image analysis to obtain the left ventricular myocardial perfusion and functional parameters. The patients were followed up for cardiac death, and divided into death group and survival group. Clinical data of those 2 groups were compare by χ2 test, the independent-sample t test or Mann-Whitney U test. Cox proportional hazards regression analysis was used to analyze the predictors related to cardiac death. The ROC curve was used to analyze the performance of predictors. Survival curves were obtained by the Kaplan-Meier method, and log-rank test was performed to compare the difference between 2 groups. Results:The follow-up time of 160 patients with CKD was 26.0(10.0, 46.5) months. Of 160 patients, 17 died and 143 survived. There were statistically significant differences in body mass index (BMI), previous myocardial infarction, previous revascularization, hypersensitive C-reactive protein (hs-CRP), positive MPI, left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), summed stress score (SSS), summed rest score (SRS) and summed difference score (SDS) between the death group and the survival group ( χ2 values: 4.58-16.13, t values: -2.34, -3.97, Z values: from -2.81 to 5.02, all P<0.05). Multivariate Cox regression analysis showed that SSS (hazard ratio ( HR)=1.153, 95% CI: 1.062-1.252, P=0.001) and hs-CRP ( HR=1.031, 95% CI: 1.004-1.058, P=0.023) were independent risk factors for cardiac death in patients with CKD. The optimal cut-off value of SSS for predicting cardiac death in those patients was determined to be 8 with the AUC of 0.815, and the incidence of cardiac death in the SSS ≥8 group was significantly higher than that in the SSS<8 group (33.3%(12/36) vs 4.0%(5/124); χ2 = 25.44, P<0.001). Conclusion:MPI is an important imaging method for the evaluation of cardiac death in patients with CKD, SSS and hs-CRP are important risk factors in predicting cardiac death in those patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.