From Atherosclerosis to Myocardial Infarction: A Process-Oriented Model Investigating the Role of Risk Factors

Nanozyme-based visual diagnosis and therapeutics for myocardial infarction: The application and strategy

BACKGROUND

Myocardial infarction (MI) is a heart injury caused by ischemia and low oxygen conditions. The occurrence of MI lead to the activation of a large number of neutrophils and macrophages, inducing severe inflammatory injury. Meanwhile, the inflammatory response produces much more free radicals, further exacerbating the inflammatory response and tissue damage. Efforts are being dedicated to developing antioxidants and enzymes, as well as small molecule drugs, for treating myocardial ischemia. However, poor pharmacokinetics and potential side effects limit the clinical application of these drugs. Recent advances in nanotechnology have paved new pathways in biomedical and healthcare environments. Nanozymes exhibit the advantages of biological enzymes and nanomaterials, including with higher catalytic activity and stability than natural enzymes. Thus, nanozymes provide new possibilities for the diagnosis and treatment of oxidative stress and inflammation-related diseases.

AIM OF REVIEW

We describe the application of nanozymes in the diagnosis and therapy of MI, aiming to bridge the gap between the diagnostic and therapeutic needs of MI.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We describe the application of nanozymes in the diagnosis and therapy of MI, and discuss the new strategies for improving the diagnosis and treatment of MI. We review in detail the applications of nanozymes to achieve highly sensitive detection of biomarkers of MI. Due to their unique enzyme catalytic capabilities, nanozymes have the ability to sensitively detect biomolecules through colorimetric, fluorescent, and electrochemical assays. In addition, nanozymes exhibit excellent antioxidase-mimicking activity to treat MI by modulating reduction/oxidation (REDOX) homeostasis. Nanozymes can also passively or actively target MI tissue sites, thereby protecting ischemic myocardial tissue and reducing the infarct area. These innovative applications of nanozymes in the field of biomedicine have shown promising results in the diagnosis and treatment of MI, offering a novel therapeutic strategy.

Natural compounds from botanical drugs targeting mTOR signaling pathway as promising therapeutics for atherosclerosis: A review

Atherosclerosis (AS) is a chronic inflammatory disease that is a major cause of cardiovascular diseases (CVDs), including coronary artery disease, hypertension, myocardial infarction, and heart failure. Hence, the mechanisms of AS are still being explored. A growing compendium of evidence supports that the activity of the mechanistic/mammalian target of rapamycin (mTOR) is highly correlated with the risk of AS. The mTOR signaling pathway contributes to AS progression by regulating autophagy, cell senescence, immune response, and lipid metabolism. Various botanical drugs and their functional compounds have been found to exert anti- AS effects by modulating the activity of the mTOR signaling pathway. In this review, we summarize the pathogenesis of AS based on the mTOR signaling pathway from the aspects of immune response, autophagy, cell senescence, and lipid metabolism, and comb the recent advances in natural compounds from botanical drugs to inhibit the mTOR signaling pathway and delay AS development. This review will provide a new perspective on the mechanisms and precision treatments of AS.

A new approach to calculating fiber fields in 2D vessel cross sections using conformal maps

An arterial vessel has three layers, namely, the intima, the media and the adventitia. Each of these layers is modeled to have two families of strain-stiffening collagen fibers that are transversely helical. In an unloaded configuration, these fibers are coiled up. In the case of a pressurized lumen, these fibers stretch and start to resist further outward expansion. As the fibers elongate, they stiffen, affecting the mechanical response. Having a mathematical model of vessel expansion is crucial in cardiovascular applications such as predicting stenosis and simulating hemodynamics. Thus, to study the mechanics of the vessel wall under loading, it is important to calculate the fiber configurations in the unloaded configuration. The aim of this paper is to introduce a new technique of using conformal maps to numerically calculate the fiber field in a general arterial cross-section. The technique relies on finding a rational approximation of the conformal map. First, points on the physical cross section are mapped to points on a reference annulus using a rational approximation of the forward conformal map. Next, we find the angular unit vectors at the mapped points, and finally a rational approximation of the inverse conformal map is used to map the angular unit vectors back to vectors on the physical cross section. We have used MATLAB software packages to achieve these goals.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less is known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD.

RESULTS

The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

Breast cancer radiotherapy and the risk of acute coronary events - insights from a process oriented model

BACKGROUND AND PURPOSE

Acute coronary events (ACEs) are considered the most important side effect of radiotherapy (RT) for breast cancer but underlying mechanisms still have to be identified. Process oriented models mathematically describe the development of disease and provide a link between mechanisms and subsequent risk. Here, this link is exploited to learn about the underlying mechanisms from the observed age-time patterns of ACE risk.

MATERIALS AND METHODS

A process oriented model of atherosclerosis and subsequent ACEs was applied to a contemporary breast cancer cohort of 810 patients with measurements of coronary artery calcification. Patients with prior ischemic heart disease were excluded. The process oriented model describes disease development as a series of different stages. Different variants of the model were fitted to the data. In each variant, one stage was assumed to be accelerated in relation to mean heart dose.

RESULTS

During a mean follow up of 9.1 years, 25 ACEs occurred. The model reproduced the prevalence and associated risk of coronary calcifications. Mean heart dose significantly improved the fit only when implemented as affecting a late stage of atherosclerosis on already existing, complicated lesions (achieving p = 0.007). This can be understood by atherosclerosis being a slowly progressing disease. Therefore, an increase of ACEs few years after RT requires advanced atherosclerosis at the time of RT.

CONCLUSION

Risk of ACE increases within few years in patients with advanced atherosclerosis at RT. Therefore, patients should be assessed for cardiovascular risk, and also elderly patients need to be considered for heart sparing techniques.

Validation of the 30-Year Framingham Risk Score in a German Population-Based Cohort

The Framingham Risk Score to predict 30-year risk (FRS30y) of cardiovascular disease (CVD) constitutes an important tool for long-term risk prediction. However, due to its complex statistical properties and the paucity of large population-based cohorts with appropriate data, validation of the FRS30y is lacking. A population-based cohort from Southern Germany (N = 3110, 1516 (48.7%) women) was followed up for a median time of 29.5 [18.7, 31.2] years. Discrimination and calibration were assessed for the original, recalibrated and refitted FRS30y version. During follow up, 620 incident CVD events (214 in women) occurred. The FRS30y showed adequate discrimination (original and recalibrated version: Area under the curve (AUC): 78.4 for women and 74.9 for men) but overestimated actual CVD risk (original version: discordance 45.4% for women and 37.3% for men, recalibrated version: 37.6% and 28.6%, respectively). Refitting showed substantial improvement in neither discrimination nor calibration. The performance of FRS30y is adequate for long-term CVD risk prediction and could serve as an important tool in risk communication, especially for younger audiences.