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Atrial fibrillation (AF) is the most common arrhythmia, and atrial fibrosis is a pathological hallmark of structural remodeling in AF. Prostaglandin I2 (PGI2) can prevent the process of fibrosis in various tissues via cell surface Prostaglandin I2 receptor (IP). However, the role of PGI2 in AF and atrial fibrosis remains unclear. The present study aimed to clarify the role of PGI2 in angiotensin II (Ang II)-induced AF and the underlying molecular mechanism. PGI2 content was decreased in both plasma and atrial tissue from patients with AF and mice treated with Ang II. Treatment with the PGI2 analog, iloprost, reduced Ang II-induced AF and atrial fibrosis. Iloprost prevented Ang II-induced atrial fibroblast collagen synthesis and differentiation. RNA-sequencing analysis revealed that iloprost significantly attenuated transcriptome changes in Ang II-treated atrial fibroblasts, especially mitogen-activated protein kinase (MAPK)-regulated genes. We demonstrated that iloprost elevated cAMP levels and then activated protein kinase A, resulting in a suppression of extracellular signal-regulated kinase1/2 and P38 activation, and ultimately inhibiting MAPK-dependent interleukin-6 transcription. In contrast, cardiac fibroblast-specific IP-knockdown mice had increased Ang II-induced AF inducibility and aggravated atrial fibrosis. Together, our study suggests that PGI2/IP system protects against atrial fibrosis and that PGI2 is a therapeutic target for treating AF. The prospectively registered trial was approved by the Chinese Clinical Trial Registry. The trial registration number is ChiCTR2200056733. Data of registration was 2022/02/12. [ABSTRACT FROM AUTHOR]

Background: Over the past decade, immune checkpoint inhibitors (ICIs) have significantly transformed cancer treatment. However, ICIs inevitably may cause a spectrum of immune‐related adverse events, among which cardiovascular toxicity, particularly myocarditis, while infrequent, has garnered increasing attention due to its high fatality rate. Methods: We conducted a multicenter retrospective study to characterize ICI‐associated cardiovascular adverse events. Logistic regression was performed to explore the risk factors for the development of myocarditis and severe myocarditis. Receiver operating characteristic curves were conducted to assess the diagnostic abilities of cardiac biomarkers to distinguish different cardiovascular toxicities, and the performance and calibration were evaluated using Hosmer–Lemeshow test. Results: Forty‐four patients were identified, including thirty‐five myocarditis, five heart failure, three arrhythmias, and one myocardial infarction. Compared with other patients, myocarditis patients had higher cardiac troponin‐I (cTnI) levels (p < 0.001), higher creatine kinase levels (p = 0.003), higher creatine kinase isoenzyme‐MB (CK‐MB) levels (p = 0.013), and shorter time to the incidence of adverse cardiovascular events (p = 0.022) after ICI treatment. Twenty‐one patients (60%) were classified as severe myocarditis, and they presented higher cardiac troponin I (cTnI) levels (p = 0.013), higher N‐terminal pro‐B‐type natriuretic peptide levels (p = 0.031), higher creatine kinase levels (p = 0.018), higher CK‐MB levels (p = 0.026), and higher neutrophil to lymphocyte ratio (NLR) levels (p = 0.016) compared to non‐severe myocarditis patients after ICI treatment. Multivariate logistic regression showed that CK‐MB (adjusted odds ratio [OR]: 1.775, 95% confidence interval [CI]: 1.055–2.984, p = 0.031) was the independent risk factor of the development of ICI‐associated myocarditis, and cTnI (adjusted OR: 1.021, 95% CI: 1.002–1.039, p = 0.03) and NLR (adjusted OR: 1.890, 95% CI: 1.026–3.483, p = 0.041) were the independent risk factors of ICI‐associated severe myocarditis. The receiver operating characteristic curve showed an area under curve of 0.785 (95% CI: 0.642 to 0.928, p = 0.013) for CK‐MB, 0.765 (95% CI: 0.601 to 0.929, p = 0.013) for cTnI, and 0.773 for NLR (95% CI: 0.597 to 0.948, p = 0.016). Conclusions: Elevated CK‐MB after ICI treatment is the independent risk factor for the incidence of ICI‐associated myocarditis, and elevated cTnI and NLR after ICI treatment are the independent risk factors for the development of ICI‐associated severe myocarditis. CK‐MB, cTnI, and NLR demonstrated a promising predictive utility for the identification of ICI‐associated myocarditis and severe myocarditis. [ABSTRACT FROM AUTHOR]

Background: This meta‐analysis evaluated long‐term efficacy and safety of cryoballoon ablation (CB) of atrial fibrillation (AF). Methods: PubMed, Cochrane Library, and Web of Science were searched until July 31, 2023, for published works investigating efficacy and safety of CB of AF in which mean/median follow‐up time was not less than 36 months. Safety was assessed by adverse events. Efficacy was assessed by AF recurrence, defined as any atrial arrhythmias lasting more than 30 s. Results: A total of 19 clinical studies were included. After an average of 58.1 months of follow‐up, the overall AF recurrence rate was about 37%. The predictors of recurrence were duration of AF (HR 1.00; 95% CI [1.00 ∼ 1.01]), early recurrence of atrial fibrillation (HR 3.96; 95%CI [1.12 ∼ 14.02]), left atrial diameter (HR 1.04; 95%CI [1.02 ∼ 1.06]), and persistent AF (HR1.47; 95% CI [1.19 ∼ 1.82]). In terms of safety, the incidence of transient phrenic paralysis (PNP) was the highest, about 3%; followed by vascular complications (about 2%); pseudoaneurysm, permanent PNP, and all‐cause death was (about 1%); and pericardial effusion and stroke / TIA was very low. Conclusion: CB is associated with low rates of severe complications and reasonable success rates. [ABSTRACT FROM AUTHOR]

As an important physical field feature, the magnetic anomaly is widely used in the detection of marine ferromagnetic targets. Influenced by the complex ocean measurement environment, the collected magnetic data are usually contaminated with noise, and traditional magnetic anomaly detection methods are less versatile due to the specific conditions required. Faced with the challenging situations in the ocean, the use of deep learning methods can not only automatically extract discriminative features from the magnetic data but also reduce manual interference in the detection model design. Deep learning requires a large amount of data to train the model, but the real target magnetic anomaly data is expensive to acquire and small in number. In this letter, we propose a multitask deep transfer learning model for simultaneous denoising and detection of marine target magnetic anomaly data under limited labeled samples. Specifically, a convolutional denoising auto-encoder (CDAE) network is designed for adaptive background noise modeling and discriminative feature learning. Meanwhile, a fully connected classification (FCC) network is cascaded and jointly trained with it for simultaneous noise filtering and anomaly detection. To guarantee sufficient learning effect, both real measured data from sea trials and simulated data from the magnetic dipole model are used for training the network in a two-stage manner. During the experiments, the learned multitask deep model is, respectively, used to denoise the marine magnetic data and detect target anomaly signals. It achieves both superior noise-removal and anomaly discovery performance than the traditional methods, and meanwhile, is much more efficient. [ABSTRACT FROM AUTHOR]