Uncovering Potential lncRNAs and mRNAs in the Progression From Acute Myocardial Infarction to Myocardial Fibrosis to Heart Failure

Ischemia does not provoke the full immune training repertoire in human cardiac fibroblasts

Trained immunity of monocytes, endothelial, and smooth muscle cells augments the cytokine response to secondary stimuli. Immune training is characterized by stabilization of hypoxia-inducible factor (HIF)-1α, mTOR activation, and aerobic glycolysis. Cardiac fibroblast (CF)-myofibroblast transition upon myocardial ischemia/reperfusion (I/R) features epigenetic and metabolic adaptations reminiscent of trained immunity. We assessed the impact of I/R on characteristics of immune training in human CF and mouse myocardium. I/R was simulated in vitro with transient metabolic inhibition. CF primed with simulated I/R or control buffer were 5 days later re-stimulated with Pam3CSK for 24 h. Mice underwent transient left anterior descending artery occlusion or sham operation with reperfusion for up to 5 days. HIF-regulated metabolic targets and cytokines were assessed by qPCR, immunoblot, and ELISA and glucose consumption, lactate release, and lactate dehydrogenase (LDH) by chromogenic assay. Simulated I/R increased HIF-1α stabilization, mTOR phosphorylation, glucose consumption, lactate production, and transcription of PFKB3 and F2RL3, a HIF-regulated target gene, in human CF. PGK1 and LDH mRNAs were suppressed. Intracellular LDH transiently increased after simulated I/R, and extracellular LDH showed sustained elevation. I/R priming increased abundance of pro-caspase-1, auto-cleaved active caspase-1, and the expression and secretion of interleukin (IL)-1β, but did not augment Pam3CSK-stimulated cytokine transcription or secretion. Myocardial I/R in vivo increased abundance of HIF-1 and the precursor and cleaved forms of caspase-1, caspase-11, and caspase-8, but not of LDH-A or phospho-mTOR. I/R partially reproduces features of immune training in human CF, specifically HIF-1α stabilization, aerobic glycolysis, mTOR phosphorylation, and PFKB3 transcription. I/R does not augment PGK1 or LDH expression or the cytokine response to Pam3CSK. Regulation of PAR4 and inflammasome caspases likely occurs independently of an immune training repertoire.

Microneedle system for tissue engineering and regenerative medicines: a smart and efficient therapeutic approach

The global demand for an enhanced quality of life and extended lifespan has driven significant advancements in tissue engineering and regenerative medicine. These fields utilize a range of interdisciplinary theories and techniques to repair structurally impaired or damaged tissues and organs, as well as restore their normal functions. Nevertheless, the clinical efficacy of medications, materials, and potent cells used at the laboratory level is always constrained by technological limitations. A novel platform known as adaptable microneedles has been developed to address the abovementioned issues. These microneedles offer a solution for the localized distribution of various cargos while minimizing invasiveness. Microneedles provide favorable patient compliance in clinical settings due to their effective administration and ability to provide a painless and convenient process. In this review article, we summarized the most recent development of microneedles, and we started by classifying various microneedle systems, advantages, and fundamental properties. Subsequently, it provides a comprehensive overview of different types of microneedles, the material used to fabricate microneedles, the fundamental properties of ideal microneedles, and their applications in tissue engineering and regenerative medicine, primarily focusing on preserving and restoring impaired tissues and organs. The limitations and perspectives have been discussed by concluding their future therapeutic applications in tissue engineering and regenerative medicines.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Evaluation of lncRNA Expression Pattern and Potential Role in Heart Failure Pathology

During the last few decades, the morbidity and mortality of heart failure (HF) have remained on an upward trend. Despite the advances in therapeutic and diagnostic measures, there are still many aspects requiring further research. This study is aimed at finding potential long noncoding RNAs (lncRNAs) that could aid with the diagnosis and treatment of HF. We performed RNA sequencing on the peripheral blood of healthy controls as well as HF patients. The expression of lncRNAs was validated by RT-qPCR. Bioinformatic analysis was performed to investigate the possible mechanism of differentially expressed lncRNAs and mRNAs. The diagnostic value of lncRNAs was analysed by ROC analysis. Finally, a total of 207 mRNAs and 422 lncRNAs were identified. GO and KEGG pathway analyses revealed that biological pathways such as immune response, regulation of cell membrane, and transcriptional regulatory process were associated with the pathological progress of HF. The lncRNA-mRNA coexpression network was conducted, and several mRNAs were identified as key potential pathological targets, while lncRNA CHST11, MIR29B2CHG, CR381653.1, and FP236383.2 presented a potential diagnostic value for HF. These findings provide novel insights for the underlying mechanisms and possible therapeutic targets for HF.

Identification of aberrantly expressed lncRNAs and ceRNA networks in multiple myeloma: a combined high-throughput sequencing and microarray analysis

Background

This study aimed to explore the potential effects of long non-coding RNAs (lncRNAs) in multiple myeloma (MM) patients using two detection methods: high-throughput sequencing and microarray.

Methods

In this study, lncRNAs were detected in 20 newly diagnosed MM patients, with 10 patients analyzed by whole transcriptome-specific RNA sequencing and 10 patients analyzed by microarray (Affymetrix Human Clariom D). The expression levels of lncRNAs, microRNAs, and messenger RNAs (mRNAs) were analyzed, and the differentially expressed lncRNAs identified by both methods were selected. The significant differentially expressed lncRNAs were further validated using PCR.

Results

This study established the aberrant expression of certain lncRNAs involved in the occurrence of MM, with AC007278.2 and FAM157C showing the most significant differences. The top 5 common pathways identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were the chemokine signaling pathway, inflammatory mediator regulation, Th17 cell differentiation, apoptosis, and NF-kappa B signaling pathway. Furthermore, three microRNAs (miRNAs) (miR-4772-3p, miR-617, and miR-618) were found to constitute competing endogenous RNA (ceRNA) networks in both sequencing and microarray analyses.

Conclusions

By the combination analysis, our understanding of lncRNAs in MM will be increased significantly. More overlapping differentially expressed lncRNAs were found to predict therapeutic targets precisely.

Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells

BACKGROUND

Acute myocardial infarction (AMI) is a common cardiovascular disease. This study aimed to mine biomarkers associated with AMI to aid in clinical diagnosis and management.

METHODS

All mRNA and miRNA data were downloaded from public database. Differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) were identified using the metaMA and limma packages, respectively. Functional analysis of the DEmRNAs was performed. In order to explore the relationship between miRNA and mRNA, we construct miRNA-mRNA negative regulatory network. Potential biomarkers were identified based on machine learning. Subsequently, ROC and immune correlation analysis were performed on the identified key DEmRNA biomarkers.

RESULTS

According to the false discovery rate < 0.05, 92 DEmRNAs and 272 DEmiRNAs were identified. GSEA analysis found that kegg_peroxisome was up-regulated in AMI and kegg_steroid_hormone_biosynthesis was down-regulated in AMI compared to normal controls. 5 key DEmRNA biomarkers were identified based on machine learning, and classification diagnostic models were constructed. The random forests (RF) model has the highest accuracy. This indicates that RF model has high diagnostic value and may contribute to the early diagnosis of AMI. ROC analysis found that the area under curve of 5 key DEmRNA biomarkers were all greater than 0.7. Pearson correlation analysis showed that 5 key DEmRNA biomarkers were correlated with most of the differential infiltrating immune cells.

CONCLUSION

The identification of new molecular biomarkers provides potential research directions for exploring the molecular mechanism of AMI. Furthermore, it is important to explore new diagnostic genetic biomarkers for the diagnosis and treatment of AMI.

Integration of RNA molecules data with prior-knowledge driven Joint Deep Semi-Negative Matrix Factorization for heart failure study

Heart failure (HF) is the main manifestation of cardiovascular disease. Recent studies have shown that various RNA molecules and their complex connections play an essential role in HF’s pathogenesis and pathological progression. This paper aims to mine key RNA molecules associated with HF. We proposed a Prior-knowledge Driven Joint Deep Semi-Negative Matrix Factorization (PD-JDSNMF) model that uses a hierarchical nonlinear feature extraction method that integrates three types of data: mRNA, lncRNA, and miRNA. The PPI information is added to the model as prior knowledge, and the Laplacian constraint is used to help the model resist the noise in the genetic data. We used the PD-JDSNMF algorithm to identify significant co-expression modules. The elements in the module are then subjected to bioinformatics analysis and algorithm performance analysis. The results show that the PD-JDSNMF algorithm can robustly select biomarkers associated with HF. Finally, we built a heart failure diagnostic model based on multiple classifiers and using the Top 13 genes in the significant module, the AUC of the internal test set was up to 0.8714, and the AUC of the external validation set was up to 0.8329, which further confirmed the effectiveness of the PD-JDSNMF algorithm.

Transcriptome sequencing and lncRNA-miRNA-mRNA network construction in cardiac fibrosis and heart failure

Cardiac fibrosis (CF) and heart failure (HF) are common heart diseases, and severe CF can lead to HF. In this study, we tried to find their common potential molecular markers, which may help the diagnosis and treatment of CF and HF. RNA library construction and high-throughput sequencing were performed. The DESeq2 package in R was used to screen differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNA (DElncRNAs) and differentially expressed miRNA (DEmiRNAs) between different samples. The common DEmRNAs, DElncRNAs and DEmiRNAs for the two diseases were obtained. The ConsensusPathDB (CPDB) was used to perform biological function enrichment for common DEmRNAs. Gene interaction network was constructed to screen out key genes. Subsequently, real-time polymerase chain reaction (RT-PCR) verification was performed. Lastly, GSE104150 and GSE21125 data sets were utilized for expression validation and diagnostic analysis. There were 1477 DEmRNAs, 502 DElncRNAs and 36 DEmiRNAs between CF and healthy control group. There were 607 DEmRNAs, 379DElncRNAs,s and 42 DEmiRNAs between HF and healthy control group. CH and FH shared 146 DEmRNAs, 80 DElncRNAs, and 6 DEmiRNAs. Hsa-miR-144-3p, CCNE2, C9orf72, MAP3K20-AS1, LEF1-AS1, AC243772.2, FLJ46284, and AC239798.2 were key molecules in lncRNA-miRNA-mRNA network. In addition, hsa-miR-144-3p and CCNE2 may be considered as potential diagnostic gene biomarkers in HF. In this study, the identification of common biomarkers of CF and HF may help prevent CF to HF transition as early as possible.

Research Progress on Leucine-Rich Alpha-2 Glycoprotein 1: A Review

Leucine-rich alpha⁃2 glycoprotein 1 (LRG1) is an important member of the leucine-rich repetitive sequence protein family. LRG1 was mainly involved in normal physiological activities of the nervous system, such as synapse formation, synapse growth, the development of nerve processes, neurotransmitter transfer and release, and cell adhesion molecules or ligand-binding proteins. Also, LRG1 affected the development of respiratory diseases, hematological diseases, endocrine diseases, tumor diseases, eye diseases, cardiovascular diseases, rheumatic immune diseases, infectious diseases, etc. LRG1 was a newly discovered important upstream signaling molecule of transforming growth factor⁃β (TGF⁃β) that affected various pathological processes through the TGF⁃β signaling pathway. However, research on LRG1 and its involvement in the occurrence and development of diseases was still in its infancy and the current studies were mainly focused on proteomic detection and basic animal experimental reports. We could reasonably predict that LRG1 might act as a new direction and strategy for the treatment of many diseases.

Inflammatory Burden and Immunomodulative Therapeutics of Cardiovascular Diseases

Phenotyping cardiovascular illness and recognising heterogeneities within are pivotal in the contemporary era. Besides traditional risk factors, accumulated evidence suggested that a high inflammatory burden has emerged as a key characteristic modulating both the pathogenesis and progression of cardiovascular diseases, inclusive of atherosclerosis and myocardial infarction. To mechanistically elucidate the correlation, signalling pathways downstream to Toll-like receptors, nucleotide oligomerisation domain-like receptors, interleukins, tumour necrosis factor, and corresponding cytokines were raised as central mechanisms exerting the effect of inflammation. Other remarkable adjuvant factors include oxidative stress and secondary ferroptosis. These molecular discoveries have propelled pharmaceutical advancements. Statin was suggested to confer cardiovascular benefits not only by lowering cholesterol levels but also by attenuating inflammation. Colchicine was repurposed as an immunomodulator co-administered with coronary intervention. Novel interleukin-1β and −6 antagonists exhibited promising cardiac benefits in the recent trials as well. Moreover, manipulation of gut microbiota and associated metabolites was addressed to antagonise inflammation-related cardiovascular pathophysiology. The gut-cardio-renal axis was therein established to explain the mutual interrelationship. As for future perspectives, artificial intelligence in conjunction with machine learning could better elucidate the sequencing of the microbiome and data mining. Comprehensively understanding the interplay between the gut microbiome and its cardiovascular impact will help identify future therapeutic targets, affording holistic care for patients with cardiovascular diseases.

Fructose plus High-Salt Diet in Early Life Results in Salt-Sensitive Cardiovascular Changes in Mature Male Sprague Dawley Rats

Fructose and salt intake remain high, particularly in adolescents and young adults. The present studies were designed to evaluate the impact of high fructose and/or salt during pre- and early adolescence on salt sensitivity, blood pressure, arterial compliance, and left ventricular (LV) function in maturity. Male 5-week-old Sprague Dawley rats were studied over three 3-week phases (Phases I, II, and III). Two reference groups received either 20% glucose + 0.4% NaCl (GCS-GCS) or 20% fructose + 4% NaCl (FHS-FHS) throughout this study. The two test groups ingested fructose + 0.4% NaCl (FCS) or FHS during Phase I, then GCS in Phase II, and were then challenged with 20% glucose + 4% NaCl (GHS) in Phase III: FCS-GHS and FHS-GHS, respectively. Compared with GCS-GCS, systolic and mean pressures were significantly higher at the end of Phase III in all groups fed fructose during Phase I. Aortic pulse wave velocity (PWV) was elevated at the end of Phase I in FHS-GHS and FHS-FHS (vs. GCS-GCS). At the end of Phase III, PWV and renal resistive index were higher in FHS-GHS and FHS-FHS vs. GCS-GCS. Diastolic, but not systolic, LV function was impaired in the FHS-GHS and FHS-FHS but not FCS-FHS rats. Consumption of 20% fructose by male rats during adolescence results in salt-sensitive hypertension in maturity. When ingested with a high-salt diet during this early plastic phase, dietary fructose also predisposes to vascular stiffening and LV diastolic dysfunction in later life.