A numerical study on the siphonic effect of enhanced external counterpulsation at lower extremities with a coupled 0D-1D closed-loop personalized hemodynamics model.

Enhanced external counterpulsation (EECP) is a treatment and rehabilitation approach for ischemic diseases, including coronary artery disease. Its therapeutic benefits are primarily attributed to the improved blood circulation achieved through sequential mechanical compression of the lower extremities. However, despite the crucial role that hemodynamic effects in the lower extremity arteries play in determining the effectiveness of EECP treatment, most studies have focused on the diastole phase and ignored the systolic phase. In the present study, a novel siphon model (SM) was developed to investigate the interdependence of several hemodynamic parameters, including pulse wave velocity, femoral flow rate, the operation pressure of cuffs, and the mean blood flow changes in the femoral artery throughout EECP therapy. To verify the accuracy of the SM, we coupled the predicted afterload in the lower extremity arteries during deflation using SM with the 0D-1D patient-specific model. Finally, the simulation results were compared with clinical measurements obtained during EECP therapy to verify the applicability and accuracy of the SM, as well as the coupling method. The precision and reliability of the previously developed personalized approach were further affirmed in this study. The average waveform similarity coefficient between the simulation results and the clinical measurements during the rest state exceeded 90%. This work has the potential to enhance our understanding of the hemodynamic mechanisms involved in EECP treatment and provide valuable insights for clinical decision-making.

Preparation of hepatocellular carcinoma mRNA vaccines based on potential tumor targets and immunophenotypes.

Background: With the development of messenger RNA (mRNA)-based therapeutics for malignant tumor, mRNA vaccines have shown considerable promise for tumor immunotherapy. Immunophenotypes can reflect the tumor microenvironment, which might have a significant influence on the effect of immunotherapy. This study seeks to discover and validate effective antigens that can be employed to develop mRNA vaccines for hepatocellular carcinoma (HCC) and to construct immunophenotypes and immune landscapes to identify potential beneficiaries. Methods: RNA sequencing (RNASeq) data, mutation information, and clinical information were obtained from HCC patients and control cases from The Cancer Genome Atlas - Liver Hepatocellular Carcinoma (TCGA-LIHC), International Cancer Genome Consortium - Liver Cancer (ICGC-LIRI) and Gene Expression Omnibus (GEO) cohorts. Gene Expression Profiling Interactive Analysis (GEPIA2.0), cBioPortal for Cancer Genomics (cBioPortal), Tumor IMmune Estimation Resource (TIMER2.0), and immunohistochemistry (IHC) were employed to discover tumor antigens. ConsensusClusterPlus was employed to perform consistency matrix building and immunophenotypic clustering. Single sample gene set enrichment analysis (ssGSEA), ESTIMATE and monocle2 were employed to map immune cell distribution. Weighted correlation network analysis (WGCNA) was employed to identify potential gene modules that influence the efficacy of mRNA vaccines. Results: Six antigen targets were discovered in the TCGA cohort, including AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1, which were associated with antigen-presenting cell infiltration and poor prognosis. IHC scores of AURKA, CDC25C and MCM3 were higher in tumor tissues, and high scores of AURKA and CDC25C indicated poor prognosis in the validation cohort. Five immunophenotypes derived from TCGA-LIHC and ICGC-LIRI cohorts were consistent. Furthermore, increased expression of blue and black modules may reduce vaccine responsiveness. Conclusions: AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1 may be potential targets for mRNA vaccine development for HCC, especially AURKA and CDC25C. HCC patients with IS1 and IS5 subtypes perhaps present an autoimmunosuppressed state, then IS2 and IS3 subtypes perhaps the potential beneficiaries.

Identification of Three Cuproptosis-specific Expressed Genes as Diagnostic Biomarkers and Therapeutic Targets for Atherosclerosis.

Atherosclerosis is a chronic, inflammatory disease characterized by a lipid-driven infiltration of inflammatory cells in large and medium arteries and is considered to be a major underlying cause of cardiovascular diseases. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical implication of cuproptosis-related genes (CRGs) in atherosclerosis remains unclear. In this study, genes collected from the GEO database intersected with CRGs were identified in atherosclerosis. GSEA, GO and KEGG pathway enrichment analyses were performed for functional annotation. Through the random forest algorithm and the construction of a protein-protein interaction (PPI) network, eight selected genes (LOXL2, SLC31A1, ATP7A, SLC31A2, COA6, UBE2D1, CP and SOD1) and a vital cuproptosis-related gene FDX1 were then further validated. Two independent datasets (GSE28829 (N = 29), GSE100927 (N = 104)) were collected to construct the signature of CRGs for validation in atherosclerosis. Consistently, the atherosclerosis plaques showed significantly higher expression of SLC31A1, SLC31A2 and lower expression of SOD1 than the normal intimae. The area under the curve (AUC) of SLC31A1, SLC31A2 and SOD1 performed well for the diagnostic validation in the two datasets. In conclusion, the cuproptosis-related gene signature could serve as a potential diagnostic biomarker for atherosclerosis and may offer novel insights into the treatment of cardiovascular diseases. Based on the hub genes, a competing endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA and a transcription factor regulation network were ultimately constructed to explore the possible regulatory mechanism in atherosclerosis.