Activation-induced cell death (AICD) of immune cells is widely believed to be crucial for the regulation of immune responses. Although macrophage apoptosis has been observed under a variety of pathological conditions, questions as to whether there is AICD of macrophages and how macrophage life span is regulated have not been well addressed. AICD in macrophages requires two signals. One is cell activation triggered by LPS or other bacterial components. The other is an event that exists in AICD-susceptible (primed) but not unsusceptible (resting) macrophages. Here we show that RAW264.7 cell is susceptible to LPS stimulation when it is primed with Salmonella typhimurium, type 5 adenovirus (Ad5) or IFN-g. We found that the stability of the transcription factor MEF2C is increased in primed RAW264.7 cell. Transfection of a dominant negative form of MEF2C protects primed macrophage from cell death triggered by LPS. Our data demonstrate that the increase of MEF2C protein stability is a key factor in the AICD of macrophage.

Background:Females with ST-segment elevation myocardial infarction (STEMI) have higher in-hospital and short-term mortality rates compared with males in China, suggesting that a sex disparity exists. The age of onset of STEMI is ahead of time and tends to be younger. However, there are relatively little data on the significance of sex on prognosis for long-term outcomes for adult patients with STEMI after percutaneous coronary intervention (PCI) in China. This study sought to analyze the sex differences in 30-day, 1-year, and long-term net adverse clinical events (NACEs) in Chinese adult patients with STEMI after PCI.Methods:This study retrospectively analyzed 1920 consecutive STEMI patients (age ≤60 years) treated with PCI from January 01, 2006, to December 31, 2012. A propensity score analysis between males and females was performed to adjust for differences in baseline characteristics and comorbidities. The primary endpoint was the incidence of 3-year NACE. Survival curves were constructed with Kaplan-Meier estimates and compared by log-rank tests between the two groups. Multivariate analysis was performed using a Cox proportional hazards model for 3-year NACE.Results:Compared with males, females had higher risk profiles associated with old age, longer prehospital delay at the onset of STEMI, hypertension, diabetes mellitus, and chronic kidney disease, and a higher Killip class (≥3), with more multivessel diseases (P < 0.05). The female group had a higher levels of low-density lipoprotein (2.72 [2.27, 3.29] vs. 2.53 [2.12, 3.00], P < 0.001), high-density lipoprotein (1.43 [1.23, 1.71] vs. 1.36 [1.11, 1.63], P = 0.003), total cholesterol (4.98 ± 1.10 vs. 4.70 ± 1.15, t = −3.508, P < 0.001), and estimated glomerular filtration rate (103.12 ± 22.22 vs. 87.55 ± 18.03, t = −11.834, P < 0.001) than the male group. In the propensity-matched analysis, being female was associated with a higher risk for 3-year NACE and major adverse cardiac or cerebral events compared with males. In the multivariate model, female gender (hazard ratio [HR]: 2.557, 95% confidence interval [CI]: 1.415–4.620, P = 0.002), hypertension (HR: 2.017, 95% CI: 1.138–3.576, P = 0.016), and family history of coronary heart disease (HR: 2.256, 95% CI: 1.115–4.566, P = 0.024) were independent risk factors for NACE. The number of stents (HR: 0.625, 95% CI: 0.437–0.894, P = 0.010) was independent protective factors of NACE.Conclusions:Females with STEMI undergoing PCI have a significantly higher risk for 3-year NACE compared with males in this population. Sex differences appear to be a risk factor and present diagnostic challenges for clinicians.

Background Atrial fibrillation (AF) is the most prevalent cardiac dysrhythmia with high morbidity and mortality rate. Evidence shows that in every three patients with AF, one is asymptomatic. The asymptomatic and paroxysmal nature of AF is the reason for unsatisfactory and delayed detection using traditional instruments. Research indicates that wearing a dynamic electrocardiogram (ECG) recorder can guide accurate and safe analysis, interpretation, and distinction of AF from normal sinus rhythm. This is also achievable in an upright position and after exercises, assisted by an artificial intelligence (AI) algorithm. Methods This study enrolled 114 participants from the outpatient registry of our institution from June 24, 2020 to July 24, 2020. Participants were tested with a wearable dynamic ECG recorder and 12-lead ECG in a supine, an upright position and after exercises for 60 s. Results Of the 114 subjects enrolled in the study, 61 had normal sinus rhythm and 53 had AF. The number of cases that could not be determined by the wristband of dynamic ECG recorder was two, one and one respectively. Case results that were not clinically objective were defined as false-negative or false-positive. Results for diagnostic accuracy, sensitivity, and specificity tested by wearable dynamic ECG recorders in a supine position were 94.74% (95% CI% 88.76–97.80%), 88.68% (95% CI 77.06–95.07%), and 100% (95% CI 92.91–100%), respectively. Meanwhile, the diagnostic accuracy, sensitivity and specificity in an upright position were 97.37% (95% CI 92.21–99.44%), 94.34% (95% CI 84.03–98.65%), and 100% (95% CI 92.91–100%), respectively. Similar results as those of the upright position were obtained after exercise. Conclusion The widely accessible wearable dynamic ECG recorder integrated with an AI algorithm can efficiently detect AF in different postures and after exercises. As such, this tool holds great promise as a useful and user-friendly screening method for timely AF diagnosis in at-risk individuals.

Background: Atherosclerotic renal artery stenosis (ARAS) is frequently related to ischemic nephropathy, secondary hypertension, and end-stage renal failure. Thus, this study aimed to explore whether certain circulating long noncoding RNAs (lncRNAs) may be used as potential specific ARAS biomarkers. Methods: In the present study, a microarray analysis was performed to screen for lncRNAs in renal artery tissue from four ARAS patients and four non-ARAS individuals. To identify specific lncRNAs as candidate potential biomarkers of ARAS, we used the following criteria: the fold change was set to >3.0 (compared with non-ARAS tissues), and p value cutoff was set at .05. According to these criteria, six lncRNAs were identified from 1150 lncRNAs. After validation by quantitative PCR (qPCR), these lncRNAs were independently validated in blood from groups of 18 ARAS patients, 18 non-ARAS individuals, and 18 healthy volunteers, furthermore, the predictive value of lncRNA PR11-387H17.6 was further assessed using blood from groups of 99 ARAS patients, 49 non-ARAS individuals, and 50 healthy volunteers. A receiver operating characteristic (ROC) curve analysis was performed to assess the performance of these lncRNAs as biomarkers. Results: In the ROC analysis, the area under the curve (AUC) of PR11-387H17.6 was 0.733, with 52.5% sensitivity and 84.8% specificity in predicting the occurrence of ARAS. After considering the risk factors, the AUC of PR11-387H17.6 was 0.844, and the optimal sensitivity increased from 52.5% to 74.5%, although the specificity decreased from 84.8% to 81.9%. In the multivariable logistic analysis, PR11-387H17.6 was an independent predictor of major adverse events (OR: 3.039; 95% CI: 1.388-6.654; p¼ .006). Conclusions: PR11-387H17.6 is a potential diagnostic biomarker of ARAS. The lncRNA levels in blood cells are regulated in ARAS. Thus, further investigations of the role of lncRNAs in ARAS are warranted.