Cardiac arrest (CA) is a critical condition in the field of cardiovascular medicine. Despite successful resuscitation, patients continue to have a high mortality rate, largely due to post CA syndrome (PCAS). However, the injury and pathophysiological mechanisms underlying PCAS remain unclear. Experimental animal models are valuable tools for exploring the etiology, pathogenesis, and potential interventions for CA and PCAS. Current CA animal models include electrical induction of ventricular fibrillation (VF), myocardial infarction, high potassium, asphyxia, and hemorrhagic shock. Although these models do not fully replicate the complexity of clinical CA, the mechanistic insights they provide remain highly relevant, including post-CA brain injury (PCABI), post-CA myocardial dysfunction (PAMD), systemic ischaemia/reperfusion injury (IRI), and the persistent precipitating pathology. Summarizing the methods of establishing CA models, the challenges encountered in the modeling process, and the mechanisms of PCAS can provide a foundation for developing standardized CA modeling protocols.
Animals ; Disease Models, Animal ; Post-Cardiac Arrest Syndrome/physiopathology* ; Heart Arrest/physiopathology* ; Humans ; Ventricular Fibrillation/complications*

Azvudine and nirmatrelvir/ritonavir (Paxlovid) are recommended for COVID-19 treatment in China, but their safety and efficacy in the elderly population are not fully known. In this multicenter, retrospective, cohort study, we identified 5131 elderly hospitalized COVID-19 patients from 32,864 COVID-19 patients admitted to nine hospitals in Henan Province, China, from December 5, 2022, to January 31, 2023. The primary outcome was all-cause death, and the secondary outcome was composite disease progression. Propensity score matching (PSM) was performed to control for confounding factors, including demographics, vaccination status, comorbidities, and laboratory tests. After 2:1 PSM, 1786 elderly patients receiving azvudine and 893 elderly patients receiving Paxlovid were included. Kaplan-Meier and Cox regression analyses revealed that compared with Paxlovid group, azvudine could significantly reduce the risk of all-cause death (log-rank P = 0.002; HR: 0.71, 95% CI: 0.573-0.883, P = 0.002), but there was no difference in composite disease progression (log-rank P = 0.52; HR: 1.05, 95% CI: 0.877-1.260, P = 0.588). Four sensitivity analyses verified the robustness of above results. Subgroup analysis suggested that a greater benefit of azvudine over Paxlovid was observed in elderly patients with primary malignant tumors (P for interaction = 0.005, HR: 0.32, 95% CI: 0.18-0.57) compared to patients without primary malignant tumors. Safety analysis revealed that azvudine treatment had a lower incidence of adverse events and higher lymphocyte levels than Paxlovid treatment. In conclusion, azvudine treatment is not inferior to Paxlovid treatment in terms of all-cause death, composite disease progression and adverse events in elderly hospitalized COVID-19 patients.

OBJECTIVE: To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment. METHODS: A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria. RESULTS: A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876). CONCLUSIONS A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.
Humans ; Critical Illness ; Retrospective Studies ; Heart Arrest/complications* ; Nomograms ; Brain Injuries/etiology* ; Intensive Care Units ; Algorithms ; Male ; Female ; Middle Aged ; ROC Curve ; Risk Factors ; Risk Assessment ; Logistic Models ; Aged

Objective:To construct an early prediction model for post cardiopulmonary resuscitation-acute kidney injury (PCPR-AKI) by machine learning and provide a basis for early identification of acute kidney injury (AKI) high-risk patients and accurate treatment.Methods:It was a single-center retrospective study. The clinical data of patients admitted to Tianjin Medical University General Hospital after cardiopulmonary resuscitation following cardiac arrest from January 1, 2016 to October 31, 2023 were collected. The end-point event of the study was defined as AKI occurring within 48 hours after cardiopulmonary resuscitation. The patients were divided into AKI group and non-AKI group according to the AKI diagnostic criteria, and the differences of baseline clinical data between the two groups were compared. The patients who met the inclusion criteria were randomly (using the train_test_split function, set the random seeds to 1, 2, and 3) divided into training and validation sets at a ratio of 7∶3. Random forest (RF), support vector machine, decision tree, extreme gradient boosting and light gradient boosting machine algorithm were used to develop the early prediction model of PCPR-AKI. The receiver-operating characteristic curve and decision curve analysis were used to evaluate the performance and clinical practicality of the predictive models, and the importance of variables in the optimal model was screened and ranked.Results:A total of 547 patients were enrolled, with age of 66 (59, 70) years old and 282 males (51.6%). There were 238 patients (43.5%) having incidence of AKI within 48 hours after cardiopulmonary resuscitation. In the AKI group, 182 patients (76.5%) were in stage 1, 47 patients (19.7%) were in stage 2, and 9 patients (3.8%) were in stage 3. There were statistically significant differences in the age, time to reach resuscitation of spontaneous circulation, time from cardiac arrest to starting cardiopulmonary resuscitation, proportion of initial defibrillation rhythm, proportion of electric defibrillation, proportion of mechanical ventilation, adrenaline dosage, sodium bicarbonate dosage, proportion of coronary heart disease, proportion of hypertension, proportion of diabetes, serum creatinine, blood urea nitrogen, blood lactic acid, blood potassium, brain natriuretic peptide, troponin, D-dimer, neuron specific enolase, and 24 hours urine volume after cardiopulmonary resuscitation between AKI group and non-AKI group (all P<0.05). Among the five machine learning algorithms, RF model achieved the best performance and clinical practicality, with area under the curve of 0.875, sensitivity of 0.863, specificity of 0.956, and accuracy rate of 90.7%. In the variable importance ranking of RF model, the top 10 variables were as follows: time to reach resuscitation of spontaneous circulation, time from cardiac arrest to starting cardiopulmonary resuscitation, initial defibrillable rhythm, serum creatinine, mechanical ventilation, blood lactate acid, adrenaline dosage, brain natriuretic peptide, D-dimer and age. Conclusions:An early predictive model for PCPR-AKI is successfully constructed based on machine learning. RF model has the best predictive performance. According to the importance of the variables, it can provide clinical strategies for early identification and precise intervention for PCPR-AKI.

Objective:To understand the incidence of HIV infection, high risk behaviors and pre-exposure prophylaxis/post-exposure prophylaxis (PrEP/PEP) utilization in men who have sex with men (MSM) in Beijing.Methods:Sample size was estimated to be 1 227 persons and 207 person year respectively in the survey and the cohort by using Epi Info 7.0 software. Using convenient sampling method, MSM were recruited by using Wechat app. Questionnaire was completed online to collect the information about demographic characteristics, high risk behavior, and utilization of PrEP/PEP of the MSM. MSM collected dry blood spot (DBS) samples by themselves, and mailed the DBS samples to laboratory for HIV nucleic acid testing. Open cohort was established and those with HIV negative nucleic acid testing results were followed up. Non-conditional binary logistic regression method was used to identify the associated factors for high risk anal sex in the last month and having multiple homosexual partners in the last month.Results:A total of 1 147 MSM were recruited, and follow up for 236 person years was conducted in 956 MSM with negative HIV nucleic acid testing results. The detection rate of new HIV infection was 1.3 per 100 person-years (3/236). During the last month, the proportions of consistent condom use in anal sex and oral sex were 50.7% (238/469) and 4.9% (23/469). In the MSM, 5.9% (43/723) had sex with HIV positive partners in the last month. 9.8% (103/1 049) used PrEP, and 8.7% (91/1 049) used PEP. The proportion of consistent condom use in PrEP and PEP were 34.3% (24/70) and 72.2% (39/54) respectively. Logistic regression analysis revealed that compared with those who used no PrEP/PEP, those who used PrEP/PEP were more likely to have unprotected anal sex in the last month (a OR=3.16, 95% CI:1.45-7.18), and more likely to have multiple homosexual partners in the last month (a OR=2.64, 95% CI:1.19-6.30), and compared with those who used no Rush Popper or drugs in the last month, those who used Rush Popper or drugs in the last month were more likely to have unprotected anal sex in the last month (a OR=2.34, 95% CI:1.67-3.30), and more likely to have multiple homosexual partners (a OR=2.42,95% CI:1.76-3.33). Conclusions:It is necessary to strengthen the health education to promote condom use and introduce the harm of drug use in MSM. In PrEP and PEP services, it is still necessary to suggest consistent condom use for MSM.

Objective:To investigate the predictive value of neuron-specific enolase (NSE), serum 100 calcium-binding protein β (S100β), gray-white-matter-ratio on head CT (GWR) and the combination of the three on the prognosis of neurological function in patients with post-cardiac arrest brain injury (PCABI).Methods:A total of 136 patients admitted to Tianjin Medical University General Hospital after resuscitation from cardiac arrest from September 2021 to May 2023 were selected and included in the good prognosis group (96 patients) and the poor prognosis group (40 patients) based on the Glasgow-Pittsburgh Cerebral Performance (CPC) classification at discharge, respectively, to compare the demographic data, resuscitation data and NSE, S100β and GWR levels within 24 h of admission between the 2 groups, and modified Poisson regression was applied to investigate the factors affecting the neuroprognosis of PCABI patients. The effectiveness of NSE, S100β, GWR and the combination of the three in predicting neurological prognosis was evaluated using receiver operating characteristic (ROC) curve and the area under the curve (AUC), and the statistical differences in AUC were compared by Delong's test.Results:NSE, S100β, GWR, history of coronary artery disease, APACHEⅡ score, time from CA to CPR, duration of resuscitation, and dose of epinephrine use were independent factors influencing the neurological prognosis of PCABI patients ( P<0.05). Compared with the good prognosis group, NSE and S100β levels were significantly higher and GWR levels were significantly lower in the poor prognosis group, with statistically significant differences ( P<0.01). The AUCs for NSE, S100β and GWR to predict poor neurological prognosis were 0.905(0.851, 0.959), 0.876 (0.797, 0.956), 0.842(0.754, 0.930), with cut-off values of 26.75 ng/mL, 1.35 ng/mL and 1.195, respectively, and an AUC of 0.982 (0.961, 1.000) for the combination of the three predicting poor neurological prognosis, significantly higher than any single indicator ( P=0.001 4, 0.001 6, 0.002 8). Conclusions:Early monitoring of NSE, S100β and GWR is effective in predicting the neurological prognosis of PCABI patients at discharge, and the combination of all three significantly improves the predictive power.

Adult ; Humans ; Heart Arrest/therapy* ; Cardiopulmonary Resuscitation ; Emergency Service, Hospital ; Out-of-Hospital Cardiac Arrest/therapy* ; Treatment Outcome

Cystatin, a cysteine protease inhibitor found in many parasites, plays important roles in immune evasion. This study analyzed the molecular characteristics of a cystatin from Fasciola hepatica (FhCystatin) and expressed recombinant FhCystatin (rFhcystatin) to investigate the immune modulatory effects on lipopolysaccharide-induced proliferation, migration, cytokine secretion, nitric oxide (NO) production, and apoptosis in mouse macrophages. The FhCystatin gene encoded 116 amino acids and contained a conserved cystatin-like domain. rFhCystatin significantly inhibited the activity of cathepsin B. rFhCystatin bound to the surface of mouse RAW264.7 cells, significantly inhibited cell proliferation and promoted apoptosis. Moreover, rFhCystatin inhibited the expression of cellular nitric oxide, interleukin-6, and tumor necrosis factor-α, and promoted the expression of transforming growth factor-β and interleukin-10. These results showed that FhCystatin played an important role in regulating the activity of mouse macrophages. Our findings provide new insights into mechanisms underlying the immune evasion and contribute to the exploration of potential targets for the development of new drug to control F. hepatica infection.

Objective:To analyze the influencing factors of HIV-testing awareness of Myanmar people in Dehong, and provide references for early discovery of HIV infection among Myanmar people.Methods:A cross-sectional study was conducted among 400 Myanmar people in Dehong through convenient sampling method in a form of face-to-face questionnaire interview. HIV-testing awareness and influencing factors were described and analyzed with χ2 and logistic regression method . Results:A total of 393 participants were included in the study, in whom 241 (61.3%) were males, 256(65.1%) were Myanmar people, 233(59.3%) received 1-7 years of education in Myanmar, 348 do not speak Chinese (88.5%), 226(57.5%) were married, 378(96.2%) were non-solitary, 257(65.4%) were workers, the main purpose of etering into China in 273(69.5%) was working in China, 273(69.5%) had stayed in China for more than 2 years, 573(95.4%) had a clear plan on whether to stay in China for a long time in the future. In these Myanmar people, the rate of AIDS-related knowledge awareness was 75.6%; 165(42.0%) had sexual behavior in the last 6 months. 221(56.2%) knew that they had been tested for HIV. Ninety (22.9%) were more likely to actively seek HIV-testing after they had unprotected behaviors such as homosexual sex, injecting drug use, and sex without using condom. Multivariate logistic regression analysis showed that the influencing factors of HIV-testing awareness included being women (compared with men, OR=2.155, 95% CI: 1.088-4.270), educational level of 8-10 years or more than 10 years (compared with education level 1-4 years, OR=5.207, 95% CI: 2.094-12.950; OR=19.780, 95% CI: 5.800-67.457), having sexual behavior in the last 6 months (compared with those who had not, OR=2.534, 95% CI: 1.343-4.779), having received AIDS-related education in the last 6 months (compared with those who had not, OR=2.462, 95% CI: 1.303-4.654), AIDS-related knowledge awareness (compared with those who had no awareness, OR=8.126, 95% CI: 2.936-22.491). Conclusions:Myanmar people have low awareness of HIV-testing in Dehong. Those who were women and high literacy levels, having received AIDS-related knowledge education in the past 6 months, and having AIDS-related knowledge have an active HIV-testing awareness, after they have high-risk behaviors. AIDS-related knowledge should be publicized to promote early discovery of high-risk behaviors.

[摘 要] 目的：探究微小RNA-504（miRNA-504）在胃癌（GC）组织中的表达水平及其对GC细胞生物学行为的调控机制。方法：收集2020年6月至2020年12月期间三亚中心医院外科收治的48例胃癌患者的肿瘤组织及癌旁组织标本，qPCR检测组织中miR-504、肿瘤蛋白53诱导型核蛋白1（tumor protein 53-induced nuclear protein 1，TP53INP1）mRNA的水平，WB法检测TP53INP1水平。体外培养人胃癌细胞BGC-823，分为对照组（正常培养的BGC-823细胞）、miR-504 mimic组、mimic-NC组、miR-504 inhibitor组、inhibitor-NC组、miR-504 inhibitor+si-NC组、miR-504 inhibitor+si-TP53INP1组，qPCR检测细胞中miR-504和TP53INP1 mRNA的表达，MTT法、流式细胞术、划痕实验和Transwell侵袭实验分别检测各组细胞的增殖、凋亡、迁移和侵袭能力，WB法检测各组细胞中增殖、迁移和侵袭相关蛋白（Cyclin D1、E-cadherin、MMP-2、MMP-9）以及TP53INP1的表达。双荧光素酶报告基因实验进一步验证miR-504与TP53INP1 mRNA的靶向关系。结果：与癌旁组织相比，胃癌组织中miR-504的表达显著升高（P<0.05），而TP53INP1 mRNA和蛋白表达水平显著降低（P<0.05或P<0.01），miR-504和TP53INP mRNA两者的表达呈负相关（P<0.01）。与对照组相比，miR-504 mimic组BGC-823细胞中miR-504的表达显著升高（P<0.05）、TP53INP1 mRNA和蛋白的表达显著降低（均P<0.05），且细胞增殖率、划痕愈合率、侵袭入Transwell小室下层的细胞数量，Cyclin D1、MMP-2、MMP-9蛋白表达均显著增加，细胞凋亡率和E-cadherin蛋白表达均显著降低（均P<0.05）。转染miR-504 inhibitor能显著下调BGC-823中miR-504的表达、上调TP53INP1 mRNA和蛋白的表达，抑制细胞的增殖、迁移与侵袭能力而促进细胞凋亡（均P<0.05）；而下调TP53INP1的表达可明显减弱miR-504下调对BGC-823细胞增殖、迁移与侵袭的抑制作用（P<0.01）。miR-504高表达能明显抑制野生型TP53INP1质粒的荧光素酶活性（P<0.05）。结论：miR-504在胃癌组织中呈高表达，下调miR-504可抑制胃癌BGC-823细胞的恶性生物学行为而促进其凋亡，其作用机制可能与靶向调控TP53INP1的表达有关。