Changes in cardiac gene expression due to myocardial injury are usually assessed in whole heart tissue. However, as the heart is a heterogeneous system, spatial and temporal heterogeneity is expected in gene expression. In an ischemia/reperfusion (I/R) rat model we evaluated gene expression of mitochondrial and cytoplasmatic superoxide dismutase (MnSod, Cu-ZnSod) and thioredoxin reductase (trxr1) upon short (4 h) and long (72 h) reperfusion times in the right ventricle (RV), and in the ischemic/reperfused (IRR) and the remote region (RR) of the left ventricle. Gene expression was assessed by Real-time reverse-transcription quantitative PCR (RT-qPCR). In order to select most stable reference genes suitable for normalization purposes, in each myocardial region we tested nine putative reference genes by geNorm analysis. The genes investigated were: Actin beta (actb), Glyceraldehyde-3-P-dehydrogenase (gapdh), Ribosomal protein L13A (rpl13a), Tyrosine 3-monooxygenase (ywhaz), Beta-glucuronidase (gusb), Hypoxanthine guanine Phosphoribosyltransferase 1 (hprt), TATA binding box protein (tbp), Hydroxymethylbilane synthase (hmbs), Polyadenylate-binding protein 1 (papbn1). According to our findings, most stable reference genes in the RV and RR were hmbs/hprt and hmbs/tbp/hprt respectively. In the IRR, six reference genes were recommended for normalization purposes; however, in view of experimental feasibility limitations, target gene expression could be normalized against the three most stable reference genes (ywhaz/pabp/hmbs) without loss of sensitivity. In all cases MnSod and Cu-ZnSod expression decreased upon long reperfusion, the former in all myocardial regions and the latter in IRR alone. trxr1 expression did not vary. This study provides a validation of reference genes in the RV and in the anterior and posterior wall of the LV of cardiac ischemia/reperfusion model and shows that gene expression should be assessed separately in each region.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual’s self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual’s compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications.

Cardiovascular magnetic resonance (CMR) T2* mapping is the gold standard technique for the assessment of iron overload in the heart. The quantitative analysis of T2* values requires the manual segmentation of T2* images, which is a time-consuming and operator-dependent procedure. This study describes a fully-automated method for the regional analysis of myocardial T2* distribution using a deep convolutional neural network (CNN). A CNN with U-Net architecture was trained to segment multi-echo T2*-weighted images in 16 sectors in accordance with the American Heart Association (AHA) model. We used images from 210 patients (three slices, 10 multi-echo images) with iron overload diseases to train and test the CNN. The performance of the proposed method was quantitatively evaluated on an independent holdout test set by comparing the segmentation accuracy of the CNN and the T2* values obtained by the automated method against ground-truth labels provided by two experts. Segmentation metrics and global and regional T2* values assessed by the proposed DL method closely matched those obtained by experts with excellent intraclass correlation in all myocardial sectors of the AHA model (ICC range [0.944, 0.996]). This method could be effectively adopted in the clinical setting for fast and accurate analysis of myocardial T2*.

Genomic and clinical evidence suggest a major role of microRNAs (miRNAs) in the regulatory mechanisms of gene expression, with a clear impact on development and physiology; miRNAs are a class of endogenous 22-25 nt single-stranded RNA molecules, that negatively regulate gene expression post-transcriptionally, by imperfect base pairing with the 3 UTR of the corresponding mRNA target. Because of this imperfection, each miRNA can bind multiple targets, and multiple miRNAs can bind the same mRNA target; although digital, the miRNAs control mechanism is characterized by an imprecise action, naturally understandable in the theoretical framework of fuzzy logic. A major practical application of fuzzy logic is represented by the design and the realization of efficient and robust control systems, even when the processes to be controlled show chaotic, deterministic as well unpredictable, behaviours. The vagueness of miRNA action, when considered together with the controlled and chaotic gene expression, is a hint of a cellular fuzzy control system. As a demonstration of the possibility and the effectiveness of miRNA based fuzzy mechanism, a fuzzy cognitive map -a mathematical formalism combining neural network and fuzzy logic- has been developed to study the apoptosis/ proliferation control performed by the miRNA-17-92 cluster/E2F1/cMYC circuitry. When experimentally demonstrated, the concept of fuzzy control could modify the way we analyse and model gene expression, with a possible impact on the way we imagine and design therapeutic intervention based on miRNA silencing.

(1) Background: Infections are among the most frequent and life-threatening complications of cardiovascular implantable electronic device (CIED) implantation. The aim of this study is to compare the outcome and safety of a single-procedure device extraction and contralateral implantation versus the standard-of-care (SoC) two-stage replacement for infected CIEDs. (2) Methods: We retrospectively included 66 patients with CIED infections who were treated at two Italian hospitals. Of the 66 patients enrolled in the study, 27 underwent a single procedure, whereas 39 received SoC treatment. All patients were followed up for 12 months after the procedure. (3) Results: Considering those lost to follow-up, there were no differences in the mortality rates between the two cohorts, with survival rates of 81.5% in the single-procedure group and 84.6% in the SoC group (p = 0.075). (4) Conclusions: Single-procedure reimplantation associated with an active antibiofilm therapy may be a feasible and effective therapeutic option in CIED-dependent and frail patients. Further studies are warranted to define the best treatment regimen and strategies to select patients suitable for the single-procedure reimplantation.