Biomarkers For Acute Myocardial Infarction Research Articles

Circulating cell-free micro-RNA as biomarkers: from myocardial infarction to hypertension.

MicroRNA (miRNA) are small, single strand non-coding RNA molecules involved in the post-transcriptional regulation of target genes. Since their discovery in 1993, over 2000 miRNAs have been identified in humans and there is growing interest in both the diagnostic and therapeutic potential of miRNA. The identification of biomarkers for human disease progression remains an active area of research, and there is a growing number of miRNA and miRNA combinations that have been linked to the development and progression of numerous cardiovascular diseases, including hypertension. In 2010, Chen et al. reported in Clinical Science that cell-free circulating miRNA could serve as novel biomarkers for acute myocardial infarction [1]. In this commentary, we expand on this topic to discuss the potential of using miRNA as biomarkers for hypertension and hypertension-related end-organ damage.

Higher serum phosphorus and calcium levels provide prognostic value in patients with acute myocardial infarction.

BackgroundAlthough traditional cardiovascular risk factors are closely related to the poor prognosis of acute myocardial infarction (AMI) patients, there are few studies on the relationship of serum phosphorus and calcium with prognosis in AMI patients. The relationship of serum phosphorus and calcium with prognostic biomarkers in AMI remains unclear.Methods and resultsA total of 3,891 AMI patients were enrolled from a prospective cohort study. We investigated the association of serum phosphorus and calcium with prognostic biomarkers. The risk of in-hospital heart failure (HF), post-discharge HF, all-cause mortality and cardiac mortality was estimated across quartiles of serum phosphorus and calcium levels. Serum phosphorus and calcium levels were associated with biomarkers of prognosis. Overall, 969 patients developed in-hospital HF during hospitalization, 549 patients developed post-discharge HF during a median follow-up of 12 months, and 252 patients died, with 170 cardiac deaths since admission. In the fully adjusted model, compared with patients in quartile 2 (Q2), patients with serum phosphorus levels in Q4 were at greater risk of post-discharge HF [sub-distributional hazard ratios (SHR) 1.55; 95% confidence interval (CI), 1.21–1.99], in-hospital HF [odds ratio (OR) 1.84; 95% CI, 1.47–2.31], all-cause mortality (HR 1.59; 95% CI, 1.08–2.32), and cardiac mortality (SHR 1.68; 95% CI, 1.03–2.75). Compared with patients in Q2, patients with corrected calcium levels in Q4 had a higher risk of in-hospital HF (OR 1.62; 95% CI, 1.29–2.04), all-cause mortality (HR 1.99; 95% CI, 1.37–2.88), and cardiac mortality (SHR 1.87; 95% CI, 1.19–2.96; all p-trend < 0.05).ConclusionSerum phosphorus and calcium levels were associated with AMI prognostic biomarkers in AMI. Higher serum phosphorus was independently related to the increased risk of in-hospital HF, postdischarge HF, all-cause mortality and cardiac mortality, and higher serum calcium was independently related to the increased risk of in-hospital HF, all-cause mortality and cardiac mortality after AMI.

Inflammation and Oxidative Stress Role of S100A12 as a Potential Diagnostic and Therapeutic Biomarker in Acute Myocardial Infarction.

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases with high morbidity and mortality. Numerous studies have indicated that S100A12 may has an essential role in the occurrence and development of AMI, and in-depth studies are currently lacking. The purpose of this study is to investigate the effect of S100A12 on inflammation and oxidative stress and to determine its clinical applicability in AMI. Here, AMI datasets used to explore the expression pattern of S100A12 in AMI were derived from the Gene Expression Omnibus (GEO) database. The pooled standard average deviation (SMD) was calculated to further determine S100A12 expression. The overlapping differentially expressed genes (DEGs) contained in all included datasets were recognized by the GEO2R tool. Then, functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were carried out to determine the molecular function of overlapping DEGs. Gene set enrichment analysis (GSEA) was conducted to determine unrevealed mechanisms of S100A12. Summary receiver operating characteristic (SROC) curve analysis and receiver operating characteristic (ROC) curve analysis were carried out to identify the diagnostic capabilities of S100A12. Moreover, we screened miRNAs targeting S100A12 using three online databases (miRWalk, TargetScan, and miRDB). In addition, by comprehensively using enzyme-linked immunosorbent assay (ELISA), real-time quantitative PCR (RT-qPCR), Western blotting (WB) methods, etc., we used the AC16 cells to validate the expression and underlying mechanism of S100A12. In our study, five datasets related to AMI, GSE24519, GSE60993, GSE66360, GSE97320, and GSE48060 were included; 412 overlapping DEGs were identified. Protein-protein interaction (PPI) network and functional analyses showed that S100A12 was a pivotal gene related to inflammation and oxidative stress. Then, S100A12 overexpression was identified based on the included datasets. The pooled standard average deviation (SMD) also showed that S100A12 was upregulated in AMI (SMD = 1.36, 95% CI: 0.70-2.03, p = 0.024). The SROC curve analysis result suggested that S100A12 had remarkable diagnostic ability in AMI (AUC = 0.90, 95% CI: 0.87-0.92). And nine miRNAs targeting S100A12 were also identified. Additionally, the overexpression of S100A12 was further confirmed that it maybe promote inflammation and oxidative stress in AMI through comprehensive in vitro experiments. In summary, our study suggests that overexpressed S100A12 may be a latent diagnostic biomarker and therapeutic target of AMI that induces excessive inflammation and oxidative stress. Nine miRNAs targeting S100A12 may play a crucial role in AMI, but further studies are still needed. Our work provides a positive inspiration for the in-depth study of S100A12 in AMI.

Heart-Type Fatty Acid Binding Protein as Potential Biomarker for Acute Myocardial Infarction

Acute myocardial infarction (AMI) is the most recurrent heart emergency which can lead to morbidity and death. During infarction, the heart releases cytoplasmic protein in the blood. These proteins such as creatine kinase, troponin and Heart type fatty acid binding protein (H-FABP) are used as indicators to spot cardiovascular arrest. This research paper aims to evaluate the efficiency, specificity and sensitivity of biomarkers in determining the AMI. This paper shows the use of direct sandwich ELISA technique to determine the level of H-FABP released in early stage of AMI. 50 suspected AMI subjects were used to observe the specificity, sensitivity and diagnostic efficacy. The study also discusses the correlation of the concentration of H-FABP in confirmed AMI, non AMI and normal subjects.

A novel Apt-SERS platform for the determination of cardiac troponin I based on coral-like silver-modified magnetic substrate and BCA method

As a kind of acute cardiovascular disease, acute myocardial infarction (AMI) endangers human's life and fitness seriously. The detection of cardiac troponin I (cTnI), a biomarker of AMI, is the key to early medical prognosis and treatment. Surface-enhanced Raman spectroscopy is viewed to be an effective approach for detection of low-concentration substances, and aptamers are regarded to be effective fragments to recognize proteins specifically. In this work, a magnetic nanoparticle substrate coated with coral-like nano-silver was prepared, and the aptamer-modified substrate Fe3O4@PEI/Ag NC-Apt was used as magnetic capture probe. Combined with BCA method and SERS detection technology, an Apt-SERS platform was successfully constructed and used for high sensitivity quantitative detection of protein. Taking cTnI as the target, the detection range of the proposed Apt-SERS platform was 0.001–100 ng mL−1, and the estimated detection of limit (LOD) was 0.23 pg mL−1. The recovery and relative standard deviations (RSD) of spiked experiment in human serum samples were 92–106% and 3.8–10.1%, respectively. The platform combining BCA method and SERS provides a high sensitivity and good reproducibility method for cTnI detection, which offers a new method for the specific detection and analysis of proteins.

Zero-Biased Photoelectrochemical Detection of Cardiac Biomarker Myoglobin Based on CdSeS/ZnS Quantum Dots and Barium Titanate Perovskite

Cardiovascular diseases are considered one of the leading causes of premature mortality of patients worldwide. Therefore, rapid diagnosis of these diseases is crucial to ensure the patient’s survival. During a heart attack or severe muscle damage, myoglobin is rapidly released in the body to constitute itself as a precise biomarker of acute myocardial infarction. Thus, we described the photoelectrochemical immunosensor development to detect myoglobin. It was based on fluorine-doped tin oxide modified with CdSeS/ZnSe quantum dots and barium titanate (BTO), designated as CdSeS/ZnSQDS/BTO. It was characterized by scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDX), transmission electron microscopy (TEM), X-ray diffraction (XRD), electrochemical impedance spectroscopy (EIS), and amperometry. The anodic photocurrent at the potential of 0 V (vs. Ag/AgCl) and pH 7.4 was found linearly related to the myoglobin (Mb) concentration from 0.01 to 1000 ng mL−1. Furthermore, the immunosensor showed an average recovery rate of 95.7–110.7% for the determination of myoglobin.

Fluorescence immunoassay based on alkaline phosphatase-induced in situ generation of fluorescent non-conjugated polymer dots

Alkaline phosphatase (ALP) activity assay is not only significant to the clinical diagnosis of some related disease, but also momentous to the construction of ALP-based enzyme-linked immunosorbent assay (ELISA). Herein, for the first time, we have discovered that ascorbic acid (AA) can specially react with N-methylethylenediamine (N-MEDA) to generate fluorescent non-conjugated polymer dots (NCPDs) under mild conditions. On the basis of the AA-responsive emission and ALP-catalyzed hydrolysis of ascorbic acid 2-phosphate (AA2P) to AA, we have exploited a fluorometric ALP activity assay with high sensitivity and selectivity. Furthermore, by means of conventional ALP-based ELISA platform, a conceptual fluorescent ELISA has been constructed and applied in the potential clinical diagnosis, during which cardiac troponin I (cTnI), a well-established biomarker of acute myocardial infarction, has been chosen as the model target. We envision that such original fluorescent NCPDs generation-enabled ELISA could become a versatile tool in biochemical sensing and medical diagnosis in the future.

Label-free detection of cardiac troponin-I with packaged thin-walled microbubble resonators.

The measurement of cardiac troponin-I (cTnI) is widely used for diagnosing acute myocardial infarction (AMI) diseases because of its myocardial specificity. Packaged microbubble resonators with thin wall are utilized for label-free and specific detection of cTnI based on whispering gallery mode (WGM). This packaged structure can provide a good protection for the biosensor, improve the anti-interference ability of the sensor and reduce the system noise. The theoretical detection limit of the biosensors for cTnI in phosphate buffer saline (PBS) is 0.4ag mL-1 (0.02 aM ). Furthermore, we demonstrated that the biosensors can be used to detect cTnI molecules in simulated serum and the theoretical detection limit is also 0.4ag mL-1 (0.02 aM ). These results are much far below the clinical cut-off value and show a huge application potential for the detection of cardiac biomarkers of AMI.

Comprehensive Analysis of circRNA-miRNA-mRNA Regulatory Network and Novel Potential Biomarkers in Acute Myocardial Infarction.

BackgroundCircular RNA (circRNA) plays an important role in the regulation of gene expression and the occurrence of human diseases. However, studies on the role of circRNA in acute myocardial infarction (AMI) are limited. This study was performed to explore novel circRNA-related regulatory networks in AMI, aiming to better understand the molecular mechanism of circRNAs involvement in AMI and provide basis for further scientific research and clinical decision-making.MethodsThe AMI-related microarray datasets GSE160717 (circRNA), GSE31568 (miRNA), GSE61741 (miRNA), and GSE24519 (mRNA) were obtained from the Gene Expression Omnibus (GEO) database. After differential expression analysis, the regulatory relationships between these DERNAs were identified by online databases circBank, circInteractome, miRDB, miRWalk, Targetscan, and then two circRNA-miRNA-mRNA regulatory networks were constructed. Differentially expressed genes (DEGs) in this network were selected followed by enrichment analysis and protein–protein interaction (PPI) analysis. Hub genes were identified using Cytohubba plug-in of Cytoscape software. Hub genes and hub gene-related miRNAs were used for receiver operating characteristic curve (ROC) analysis to identify potential biomarkers. The relative expression levels of these biomarkers were further assessed by GSE31568 (miRNA) and GSE66360 (mRNA). Finally, on the basis of the above analysis, myocardial hypoxia model was constructed to verify the expression of Hub genes and related circRNAs.ResultsA total of 83 DEcircRNAs, 109 CoDEmiRNAs and 1204 DEGs were significantly differentially expressed in these datasets. The up-regulated circRNAs and down-regulated circRNAs were used to construct a circRNA-miRNA-mRNA regulatory network respectively. These circRNA-related DEGs were mainly enriched in the terms of “FOXO signaling pathway,” “T cell receptor signaling pathway,” “MAPK signaling pathway,” “Insulin resistance,” “cAMP signaling pathway,” and “mTOR signaling pathway.” The top 10 hub genes ATP2B2, KCNA1, GRIN2A, SCN2B, GPM6A, CACNA1E, HDAC2, SRSF1, ANK2, and HNRNPA2B1 were identified from the PPI network. Hub genes GPM6A, SRSF1, ANK2 and hub gene-related circRNAs hsa_circ_0023461, hsa_circ_0004561, hsa_circ_0001147, hsa_circ_0004771, hsa_circ_0061276, and hsa_circ_0045519 were identified as potential biomarkers in AMI.ConclusionIn this study, the potential circRNAs associated with AMI were identified and two circRNA-miRNA-mRNA regulatory networks were constructed. This study explored the mechanism of circRNA involvement in AMI and provided new clues for the selection of new diagnostic markers and therapeutic targets for AMI.

FENDRR: A Long Non-coding RNA as a novel Biomarker for Acute Myocardial Infarction

FENDRR: A Long Non-coding RNA as a novel Biomarker for Acute Myocardial Infarction

Prefab Hollow Glass Microsphere-Based Immunosensor with Liquid Crystal Sensitization for Acute Myocardial Infarction Biomarker Detection.

Quantitative detection of cardiac troponin biomarkers in blood is an important method for clinical diagnosis of acute myocardial infarction (AMI). In this work, a whispering gallery mode (WGM) microcavity immunosensor based on a prefab hollow glass microsphere (HGMS) with liquid crystal (LC) sensitization was proposed and experimentally demonstrated for label-free cardiac troponin I-C (cTnI-C) complex detection. The proposed fiber-optic immunosensor has a simple structure; the tiny modified HGMS serves as the key sensing element and the microsample reservoir simultaneously. A sensitive LC layer with cTnI-C recognition ability was deposited on the inner wall of the HGMS microcavity. The arrangement of LC molecules is affected by the cTnI-C antigen—antibody binding in the HGMS, and the small change of the surface refractive index caused by the binding can be amplified owing to the birefringence property of LC. Using the annular waveguide of the HGMS, the WGMs were easily excited by the coupling scanning laser with a microfiber, and an all-fiber cTnI-C immunosensor can be achieved by measuring the resonant wavelength shift of the WGM spectrum. Moreover, the dynamic processes of the cTnI-C antigen—antibody binding and unbinding was revealed by monitoring the wavelength shift continuously. The proposed immunosensor with a spherical microcavity can be a cost-effective tool for AMI diagnosis.

Procalcitonin and Troponin-I as Predictor of Mortality in Acute Myocardial Infarction Patients

Acute Myocardial Infarction (AMI) is known as one of the leading causes of death in the world as well as in Indonesia. Procalcitonin is a marker of inflammation that has been recognized as a predictor of mortality in sepsis patients. The role of procalcitonin as a predictor of mortality in AMI patients has not been widely studied. Troponin-I has been recognized as a biomarker of AMI. It is unclear whether Troponin-I can also act as a biomarker to predict the death of AMI patients. This study aim is to determine the role of procalcitonin and troponin-I as predictors of mortality in AMI patients. A 5-month analytical observational study was performed on AMI patients who were admitted to Dr. Saiful Anwar, Malang. Patients with sepsis or infection were excluded. There were 51 study subjects, of whom median procalcitonin and troponin-I levels of patients who died were significantly different from survivors (p&lt;0.05). Procalcitonin level with a cut-off of 2.16 ng/mL had a sensitivity of 77% and specificity of 87%. Troponin-I level with a cut-off of 3.1 ng/mL had a sensitivity of 61% and specificity of 84%. Odds ratio of procalcitonin to mortality was 17.78 (p=0.001), while troponin-I was not significant. Procalcitonin correlated with mortality (r= 0.519, p= 0.005). The conclusion of this research is procalcitonin acts as a predictor of in AMI patients.

A novel lncRNA-miRNA-mRNA triple network identifies lncRNA XIST as a biomarker for acute myocardial infarction.

Despite the well-established role of long non-coding RNAs (lncRNAs) across various biological processes, their mechanisms in acute myocardial infarction (AMI) are not fully elucidated. The GSE34198 dataset from the Gene Expression Omnibus (GEO) database, which comprised 49 specimens from individuals with AMI and 47 specimens from controls, was extracted and analysed using the weighted gene co-expression network analysis (WGCNA) package. Twenty-seven key genes were identified through a combination of the degree and gene significance (GS) values, and the CDC42 (degree = 64), JAK2 (degree = 41), and CHUK (degree = 30) genes were identified as having the top three-degree values among the 27 genes. Potential interactions between lncRNA, miRNAs and mRNAs were predicted using the starBase V3.0 database, and a lncRNA-miRNA-mRNA triple network containing the lncRNA XIST, twenty-one miRNAs and three hub genes (CDC42, JAK2 and CHUK) was identified. RT–qPCR validation showed that the expression of the JAK2 and CDC42 genes and the lncRNA XIST was noticeably increased in samples from patients with AMI compared to normal samples. Pearson’s correlation analysis also proved that JAK2 and CDC42 expression levels correlated positively with lncRNA XIST expression levels. The area under ROC curve (AUC) of lncRNA XIST was 0.886, and the diagnostic efficacy of the lncRNA XIST was significantly better than that of JAK2 and CDC42. The results suggested that the lncRNA XIST appears to be a risk factor for AMI likely through its ability to regulate JAK2 and CDC42 gene expressions, and it is expected to be a novel and reliable biomarker for the diagnosis of AMI.

Ultra-sensitive and rapid screening of acute myocardial infarction using 3D-affinity graphene biosensor

Acute myocardial infarction (AMI) is one of the highest mortality diseases in the world. It is critical to treat AMI patients within a few hours, which can explain the high mortality. However, timely diagnosis of AMI out of hospital is still challenging because of low accuracy, sophisticated testing procedures, and requirement of experienced professionals. Here, we propose ultra-sensitive, facile, and rapid detection of the AMI biomarker by using a three-dimensional affinity biosensor (3DA-biosensor), which uses a graphene field-effect transistor constructed with a superwetting hydrogel-aptamer hybrid layer. The 3DA-biosensor exhibits the high sensitivity, adjustable sensitive range, and self-filtration ability, evidenced by a limit of detection down to 1.08 × 10 −9 nM in whole blood. Through preliminary application tests, the 3DA-biosensor enables the identification of positive or negative for patient samples within 5 min, with the accuracy rate over 94%, paving a way for convenient self-screening of AMI for the patients with suspected symptoms. • Ultra-sensitive detection of biomarkers in whole blood and patient samples • Graphene field-effect transistor constructed with 3D hydrogel-aptamer structure • Adjustable sensitive range and self-filtration ability of biosensor • Rapid identification of positive or negative AMI samples with accuracy over 94% Wang et al. demonstrate a graphene field-effect transistor constructed with 3D hydrogel-aptamer structure, which exhibits ultra-sensitive and rapid screening of acute myocardial infarction. The biosensor achieves the adjustable sensitive range and self-filtration ability. Moreover, rapid identification of the positive or negative status of patient clinical samples is realized with the accuracy over 94%.

Plasma Quantitative Lipid Profiles: Identification of CarnitineC18:1-OH, CarnitineC18:2-OH and FFA (20:1) as Novel Biomarkers for Pre-warning and Prognosis in Acute Myocardial Infarction

This study was aimed to determine the association between potential plasma lipid biomarkers and early screening and prognosis of Acute myocardial infarction (AMI). In the present study, a total of 795 differentially expressed lipid metabolites were detected based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Out of these metabolites, 25 lipid metabolites were identified which showed specifical expression in the AMI group compared with the healthy control (HC) group and unstable angina (UA) group. Then, we applied the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) methods to obtain three lipid molecules, including CarnitineC18:1-OH, CarnitineC18:2-OH and FFA (20:1). The three lipid metabolites and the diagnostic model exhibited well predictive ability in discriminating between AMI patients and UA patients in both the discovery and validation sets with an area under the curve (AUC) of 0.9. Univariate and multivariate logistic regression analyses indicated that the three lipid metabolites may serve as potential biomarkers for diagnosing AMI. A subsequent 1-year follow-up analysis indicated that the three lipid biomarkers also had prominent performance in predicting re-admission of patients with AMI due to cardiovascular events. In summary, we used quantitative lipid technology to delineate the characteristics of lipid metabolism in patients with AMI, and identified potential early diagnosis biomarkers of AMI via machine learning approach.

S100A9 and SOCS3 as diagnostic biomarkers of acute myocardial infarction and their association with immune infiltration.

Acute myocardial infarction (AMI) is one of the leading causes of death globally, with a mortality rate of over 20%. However, the diagnostic biomarkers frequently used in current clinical practice have limitations in both sensitivity and specificity, likely resulting in delayed diagnosis. This study aimed to identify potential diagnostic biomarkers for AMI and explored the possible mechanisms involved. Datasets were retrieved from the Gene Expression Omnibus. First, we identified differentially expressed genes (DEGs) and preserved modules, from which we identified candidate genes by LASSO (least absolute shrinkage and selection operator) regression and the SVM-RFE (support vector machine-recursive feature elimination) algorithm. Subsequently, we used ROC (receiver operating characteristic) analysis to evaluate the diagnostic accuracy of the candidate genes. Thereafter, functional enrichment analysis and an analysis of immune infiltration were implemented. Finally, we assessed the association between biomarkers and biological processes, infiltrated cells, clinical traits, tissues and time points. We identified nine preserved modules containing 1,016 DEGs and managed to construct a diagnostic model with high accuracy (GSE48060: AUC = 0.923; GSE66360: AUC = 0.973) incorporating two genes named S100A9 and SOCS3. Functional analysis revealed the pivotal role of inflammation; immune infiltration analysis indicated that eight cell types (monocytes, epithelial cells, neutrophils, CD8+ T cells, Th2 cells, NK cells, NKT cells and platelets) were likely involved in AMI. Furthermore, we observed that S100A9 and SOCS3 were correlated with inflammation, variably infiltrated cells, clinical traits of patients, sampling tissues and sampling time points. In conclusion, we suggested S100A9 and SOCS3 as diagnostic biomarkers of AMI and discovered their association with inflammation, infiltrated immune cells and other factors.

Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm.

AimsThe 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations.Methods and resultsIndividuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2–12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547–0.664] in BACS/BAMI to 0.772 (95% CI 0.659–0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options.ConclusionThe SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.

Predicting Diagnostic Gene Biomarkers Associated With Immune Checkpoints, N6-Methyladenosine, and Ferroptosis in Patients With Acute Myocardial Infarction.

This study aimed to determine early diagnosis genes of acute myocardial infarction (AMI) and then validate their association with ferroptosis, immune checkpoints, and N6-methyladenosine (m6A), which may provide a potential method for the early diagnosis of AMI. Firstly, we downloaded microarray data from NCBI (GSE61144, GSE60993, and GSE42148) and identified differentially expressed genes (DEGs) in samples from healthy subjects and patients with AMI. Also, we performed systematic gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used STRING to predict protein interactions. Moreover, MCC and MCODE algorithms in the cytoHubba plug-in were used to screen nine key genes in the network. We then determined the diagnostic significance of the nine obtained DEGs by plotting receiver operating characteristic curves using a multiscale curvature classification algorithm. Meanwhile, we investigated the relationship between AMI and immune checkpoints, ferroptosis, and m6A. In addition, we further validated the key genes through the GSE66360 dataset and consequently obtained nine specific genes that can be used as early diagnosis biomarkers for AMI. Through screening, we identified 210 DEGs, including 53 downregulated and 157 upregulated genes. According to GO, KEGG, and key gene screening results, FPR1, CXCR1, ELANE, TLR2, S100A12, TLR4, CXCL8, FPR2 and CAMP could be used for early prediction of AMI. Finally, we found that AMI was associated with ferroptosis, immune checkpoints, and m6A and FPR1, CXCR1, ELANE, TLR2, S100A12, TLR4, CXCL8, FPR2 and CAMP are effective markers for the diagnosis of AMI, which can provide new prospects for future studies on the pathogenesis of AMI.

Single-Electrode Electrochemical System for the Visual and High-Throughput Electrochemiluminescence Immunoassay.

The electrochemiluminescence (ECL) immunoassay with its visual and high-throughput detection has received considerable attention in the past decade. However, the development of a facile and cost-effective ECL device is still a great challenge. Herein, a single-electrode electrochemical system (SEES) for the visual and high-throughput ECL immunoassay was developed. The SEES was designed by attaching a plastic sticker with multiple holes onto a single carbon ink screen-printed electrode based on a resistance-induced potential difference. Due to its excellent properties of adsorption and bioaffinity, the carbon ink screen-printed electrode is applied to immobilize antibodies. When cardiac troponin I (cTnI), a specific biomarker of acute myocardial infarction, is present, it will be captured by the immobilized cTnI antibodies on the electrode surface, inhibiting electron transfer, resulting in a decrease of the ECL intensity of the luminol-H2O2 system. Using a smartphone as the detector, cTnI could be determined, ranging from 1 to 1000 ng mL-1, with a detection limit of 0.94 ng mL-1. The SEES based on the carbon ink screen-printed electrode is characterized by its high simplicity, cost effectiveness, and user-friendliness compared with conventional three-electrode systems and bipolar electrochemical systems using electrode arrays and shows superior advantages over other immunoassay strategies, with the elimination of multistep assembling and labeling processes. What is more, the fabricated SEES holds great potential in the point-of-care testing due to its tiny size and the combination of a smartphone detector.

Considerations on triangular‐shaped electrodes for deoxyribonuclease detection

AbstractIn this paper, complex impedance locus of the triangular‐shaped electrodes with immobilized λDNAs were calculated by numerical simulations. Compare with the impedance of the electrodes with immobilized λDNAs, its impedance after deoxyribonuclease (DNase) treatment were increased by about three times or more. The DNA molecules can be applied to electrical detection of DNase, which is a candidate biomarker for acute myocardial infarction.