Introduction: Mesenchymal stem cells (MSCs) play a central role in mediating endogenous repair of cell and tissue damage. Biologic aging is a universal process that results in changes at the cellular and molecular levels. In the present study, the role of microRNA (miRNA) in age-induced molecular changes in MSCs derived from adipose tissue (ASCs) and bone marrow (BMSCs) from young and old human donors were investigated by using an unbiased genome-wide approach. Methods: Human ASCs and BMSCs from young and old donors were cultured, and total RNA was isolated. The miRNA fraction was enriched and used to determine the expression profile of miRNA in young and old donor MSCs. Based on miRNA expression, differences in donor MSCs were further investigated by using differentiation assays, Western blot, immunocytochemistry, and bioinformatics. Results: Biologic aging demonstrated reduced osteogenic and adipogenic potential in ASCs isolated from older donors, whereas cell size, complexity, and cell-surface markers remained intact with aging. Analysis of miRNA profiles revealed that small subsets of active miRNAs changed secondary to aging. Evaluation of miRNA showed significantly decreased levels of gene expression of inhibitory kappa B kinase (IκB), interleukin-1α, inducible nitric oxide synthase (iNOS), mitogen-activated protein kinase/p38, ERK1/2, c-fos, and c-jun in MSCs from older donors by both bioinformatics and Western blot analysis. Nuclear factor kappa B (NF-κB), myc, and interleukin-4 receptor mRNA levels were significantly elevated in aged cells from both the adipose and bone marrow depots. Immunocytochemistry showed nuclear localization in young donors, but a cytosolic predominance of phosphorylated NF-κB in ASCs from older donors. Western blot demonstrated significantly elevated levels of NF-κB subunits, p65 and p50, and AKT. Conclusions: These findings suggest that differential expression of miRNA is an integral component of biologic aging in MSCs.

In this study, we propose a post-hoc explainability framework for deep learning models applied to quasi-periodic biomedical time-series classification. As a case study, we focus on the problem of atrial fibrillation (AF) detection from electrocardiography signals, which has strong clinical relevance. Starting from a state-of-the-art pretrained model, we tackle the problem from two different perspectives: global and local explanation. With global explanation, we analyze the model behavior by looking at entire classes of data, showing which regions of the input repetitive patterns have the most influence for a specific outcome of the model. Our explanation results align with the expectations of clinical experts, showing that features crucial for AF detection contribute heavily to the final decision. These features include R-R interval regularity, absence of the P-wave or presence of electrical activity in the isoelectric period. On the other hand, with local explanation, we analyze specific input signals and model outcomes. We present a comprehensive analysis of the network facing different conditions, whether the model has correctly classified the input signal or not. This enables a deeper understanding of the network's behavior, showing the most informative regions that trigger the classification decision and highlighting possible causes of misbehavior.

The 12-lead electrocardiogram (ECG) is an integral component to the diagnosis of a multitude of cardiovascular conditions. It is performed using a complex set of skin surface electrodes, limiting its use outside traditional clinical settings. We developed an artificial intelligence algorithm, trained over 600,000 clinically acquired ECGs, to explore whether fewer leads as input are sufficient to reconstruct a 12-lead ECG. Two limb leads (I and II) and one precordial lead (V3) were required to generate a reconstructed 12-lead ECG highly correlated with the original ECG. An automatic algorithm for detection of ECG features consistent with acute myocardial infarction (MI) performed similarly for original and reconstructed ECGs (AUC = 0.95). When interpreted by cardiologists, reconstructed ECGs achieved an accuracy of 81.4 ± 5.0% in identifying ECG features of ST-segment elevation MI, comparable with the original 12-lead ECGs (accuracy 84.6 ± 4.6%). These results will impact development efforts to innovate ECG acquisition methods with simplified tools in non-specialized settings.

Resulting from a various etiologies, the most notable remains ischemia; heart failure (HF) manifests as the common end pathway of many cardiovascular processes and remains among the top causes for hospitalization and a major cause of morbidity and mortality worldwide. Current pharmacologic treatment for HF utilizes pharmacologic agents to control symptoms and slow further deterioration; however, on a cellular level, in a patient with progressive disease, fibrosis and cardiac remodeling can continue leading to end-stage heart failure. Cellular therapeutics have risen as the new hope for an improvement in the treatment of HF. Mesenchymal stem cells (MSCs) have gained popularity given their propensity of promoting endogenous cellular repair of a myriad of disease processes via paracrine signaling through expression of various cytokines, chemokines, and adhesion molecules resulting in activation of signal transduction pathways. While the exact mechanism remains to be completely elucidated, this remains the primary mechanism identified to date. Recently, MSCs have been incorporated as the central focus in clinical trials investigating the role how MSCs can play in the treatment of HF. In this review, we focus on the characteristics of MSCs that give them a distinct edge as cellular therapeutics and present results of clinical trials investigating MSCs in the setting of ischemic HF.

Single-cell RNA-seq (scRNAseq) struggles to capture the cellular heterogeneity of transcripts within individual cells due to the prevalence of highly abundant and ubiquitous transcripts, which can obscure the detection of biologically distinct transcripts expressed up to several orders of magnitude lower levels. To address this challenge, here we introduce single-cell CRISPRclean (scCLEAN), a molecular method that globally recomposes scRNAseq libraries, providing a benefit that cannot be recapitulated with deeper sequencing. scCLEAN utilizes the programmability of CRISPR/Cas9 to target and remove less than 1% of the transcriptome while redistributing approximately half of reads, shifting the focus toward less abundant transcripts. We experimentally apply scCLEAN to both heterogeneous immune cells and homogenous vascular smooth muscle cells to demonstrate its ability to uncover biological signatures in different biological contexts. We further emphasize scCLEAN’s versatility by applying it to a third-generation sequencing method, single-cell MAS-Seq, to increase transcript-level detection and discovery. Here we show the possible utility of scCLEAN across a wide array of human tissues and cell types, indicating which contexts this technology proves beneficial and those in which its application is not advisable.

Background: Widespread use of angiotensin receptor blocker and neprilysin inhibitor (ARNI) remains low, and many patients are unable to tolerate the medication due to hypotension at the currently recommended starting dose. Hypothesis: The aim of this study is to assess if lower than standard doses of ARNI, sacubitril/valsartan (S/V), significantly reduces NT-proBNP and leads to any change in diuretic dose, serum potassium, or creatinine. Methods: In a retrospective study of 278 patients who were started on a low dose S/V at a single medical center, 45 patients were selected for the study cohort. Patients were subcategorized to Group 1 (n = 10): very low dose S/V (half a tab of 24/26 mg BID), Group 2 (n = 10): very low dose titrated to low dose S/V, and Group 3 (n = 25): low dose S/V (24/26 mg BID). NT-proBNP, diuretic dose, serum potassium, and creatinine were compared before and after initiation of S/V. Results: Among all groups, there was a significant reduction in NT-proBNP level (Group 1: p < .01, Group 2: p < .01, and Group 3: p < .001). In addition, there was a significant reduction in diuretic dose across all groups combined (furosemide 53 mg/day vs. 73 mg/day; p = .03), with 17.8% (8/45) patients being able to discontinue their diuretic completely. There was no significant change in potassium or creatinine. Conclusions: Lower than standard dose of S/V significantly reduces NT-proBNP and diuretic requirement without change in potassium or creatinine, which provides hope that patients who cannot tolerate standard doses of S/V due to hypotension may be able to receive the benefits of S/V therapy.