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1.
The fascinating theory of fetal programming of adult diseases: A review of the fundamentals of the Barker hypothesis.
Faa, G, Fanos, V, Manchia, M, Van Eyken, P, Suri, JS, Saba, L
Journal of public health research. 2024;(1):22799036241226817
Abstract
The theory of fetal programming of adult diseases was first proposed by David J.P. Barker in the eighties of the previous century, to explain the higher susceptibility of some people toward the development of ischemic heart disease. According to his hypothesis, poor maternal living conditions during gestation represent an important risk factor for the onset of atherosclerotic heart disease later in life. The analysis of the early phases of fetal development is a fundamental tool for the risk stratification of children and adults, allowing the identification of susceptible or resistant subjects to multiple diseases later in life. Here, we provide a narrative summary of the most relevant evidence supporting the Barker hypothesis in multiple fields of medicine, including neuropsychiatric disorders, such as Parkinson disease and Alzheimer disease, kidney failure, atherosclerosis, coronary heart disease, stroke, diabetes, cancer onset and progression, metabolic syndrome, and infectious diseases including COVID-19. Given the consensus on the role of body weight at birth as a practical indicator of the fetal nutritional status during gestation, every subject with a low birth weight should be considered an "at risk" subject for the development of multiple diseases later in life. The hypothesis of the "physiological regenerative medicine," able to improve fetal organs' development in the perinatal period is discussed, in the light of recent experimental data indicating Thymosin Beta-4 as a powerful growth promoter when administered to pregnant mothers before birth.
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2.
Carotid Artery Plaque Calcifications: Lessons From Histopathology to Diagnostic Imaging.
Saba, L, Nardi, V, Cau, R, Gupta, A, Kamel, H, Suri, JS, Balestrieri, A, Congiu, T, Butler, APH, Gieseg, S, et al
Stroke. 2022;(1):290-297
Abstract
The role of calcium in atherosclerosis is controversial and the relationship between vascular calcification and plaque vulnerability is not fully understood. Although calcifications are present in ≈50% to 60% of carotid plaques, their association with cerebrovascular ischemic events remains unclear. In this review, we summarize current understanding of carotid plaque calcification. We outline the role of calcium in atherosclerotic carotid disease by analyzing laboratory studies and histopathologic studies, as well as imaging findings to understand clinical implications of carotid artery calcifications. Differences in mechanism of calcium deposition express themselves into a wide range of calcification phenotypes in carotid plaques. Some patterns, such as rim calcification, are suggestive of plaques with inflammatory activity with leakage of the vasa vasourm and intraplaque hemorrhage. Other patterns such as dense, nodular calcifications may confer greater mechanical stability to the plaque and reduce the risk of embolization for a given degree of plaque size and luminal stenosis. Various distributions and patterns of carotid plaque calcification, often influenced by the underlying systemic pathological condition, have a different role in affecting plaque stability. Modern imaging techniques afford multiple approaches to assess geometry, pattern of distribution, size, and composition of carotid artery calcifications. Future investigations with these novel technologies will further improve our understanding of carotid artery calcification and will play an important role in understanding and minimizing stroke risk in patients with carotid plaques.
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3.
Benefits and drawbacks of statins and non-statin lipid lowering agents in carotid artery disease.
Paraskevas, KI, Gloviczki, P, Antignani, PL, Comerota, AJ, Dardik, A, Davies, AH, Eckstein, HH, Faggioli, G, Fernandes E Fernandes, J, Fraedrich, G, et al
Progress in cardiovascular diseases. 2022;:41-47
Abstract
International guidelines strongly recommend statins alone or in combination with other lipid-lowering agents to lower low-density lipoprotein cholesterol (LDL-C) levels for patients with asymptomatic/symptomatic carotid stenosis (AsxCS/SCS). Lowering LDL-C levels is associated with significant reductions in transient ischemic attack, stroke, cardiovascular (CV) event and death rates. The aim of this multi-disciplinary overview is to summarize the benefits and risks associated with lowering LDL-C with statins or non-statin medications for Asx/SCS patients. The cerebrovascular and CV beneficial effects associated with statins, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and other non-statin lipid-lowering agents (e.g. fibrates, ezetimibe) are reviewed. The use of statins and PCSK9 inhibitors is associated with several beneficial effects for Asx/SCS patients, including carotid plaque stabilization and reduction of stroke rates. Ezetimibe and fibrates are associated with smaller reductions in stroke rates. The side-effects resulting from statin and PCSK9 inhibitor use are also highlighted. The benefits associated with lowering LDL-C with statins or non-statin lipid lowering agents (e.g. PCSK9 inhibitors) outweigh the risks and potential side-effects. Irrespective of their LDL-C levels, all Asx/SCS patients should receive high-dose statin treatment±ezetimibe or PCSK9 inhibitors for reduction not only of LDL-C levels, but also of stroke, cardiovascular mortality and coronary event rates.
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4.
Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.
Munjral, S, Maindarkar, M, Ahluwalia, P, Puvvula, A, Jamthikar, A, Jujaray, T, Suri, N, Paul, S, Pathak, R, Saba, L, et al
Diagnostics (Basel, Switzerland). 2022;(5)
Abstract
Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.
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5.
Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.
Munjral, S, Ahluwalia, P, Jamthikar, AD, Puvvula, A, Saba, L, Faa, G, Singh, IM, Chadha, PS, Turk, M, Johri, AM, et al
Frontiers in bioscience (Landmark edition). 2021;(11):1312-1339
Abstract
Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.
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6.
Bidirectional link between diabetes mellitus and coronavirus disease 2019 leading to cardiovascular disease: A narrative review.
Viswanathan, V, Puvvula, A, Jamthikar, AD, Saba, L, Johri, AM, Kotsis, V, Khanna, NN, Dhanjil, SK, Majhail, M, Misra, DP, et al
World journal of diabetes. 2021;(3):215-237
Abstract
Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality rate than non-DM patients if they get COVID-19. Recent studies have indicated that patients with a history of diabetes can increase the risk of severe acute respiratory syndrome coronavirus 2 infection. Additionally, patients without any history of diabetes can acquire new-onset DM when infected with COVID-19. Thus, there is a need to explore the bidirectional link between these two conditions, confirming the vicious loop between "DM/COVID-19". This narrative review presents (1) the bidirectional association between the DM and COVID-19, (2) the manifestations of the DM/COVID-19 loop leading to cardiovascular disease, (3) an understanding of primary and secondary factors that influence mortality due to the DM/COVID-19 loop, (4) the role of vitamin-D in DM patients during COVID-19, and finally, (5) the monitoring tools for tracking atherosclerosis burden in DM patients during COVID-19 and "COVID-triggered DM" patients. We conclude that the bidirectional nature of DM/COVID-19 causes acceleration towards cardiovascular events. Due to this alarming condition, early monitoring of atherosclerotic burden is required in "Diabetes patients during COVID-19" or "new-onset Diabetes triggered by COVID-19 in Non-Diabetes patients".
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7.
Wilson's disease: A new perspective review on its genetics, diagnosis and treatment.
Saba, L, Tiwari, A, Biswas, M, Gupta, SK, Godia-Cuadrado, E, Chaturvedi, A, Turk, M, Suri, HS, Orru, S, Sanches, JM, et al
Frontiers in bioscience (Elite edition). 2019;(1):166-185
Abstract
Wilson's disease (WD) is an autosomal recessive disorder which is caused by poor excretion of copper in mammalian cells. In this review, various issues such as effective characterization of ATP7B genes, scope of gene network topology in genetic analysis, pattern recognition using different computing approaches and fusion possibilities in imaging and genetic dataset are discussed vividly. We categorized this study into three major sections: (A) WD genetics, (B) diagnosis guidelines and (3) treatment possibilities. We addressed the scope of advanced mathematical modelling paradigms for understanding common genetic sequences and dominating WD imaging biomarkers. We have also discussed current state-of-the-art software models for genetic sequencing. Further, we hypothesized that involvement of machine and deep learning techniques in the context of WD genetics and image processing for precise classification of WD. These computing procedures signify changing roles of various data transformation techniques with respect to supervised and unsupervised learning models.
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8.
Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.
Banchhor, SK, Londhe, ND, Araki, T, Saba, L, Radeva, P, Khanna, NN, Suri, JS
Computers in biology and medicine. 2018;:184-198
Abstract
PURPOSE OF REVIEW Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and quantify the calcium. This is due to the presence of multiple components of plaque buildup in the arterial walls. The American College of Cardiology/American Heart Association guidelines point to the importance of calcium in the coronary and carotid arteries and further recommend its quantification for the prevention of heart disease. It is therefore essential to stratify the CVD risk of the patient into low- and high-risk bins. RECENT FINDING Calcium formation in the artery walls is multifocal in nature with sizes at the micrometer level. Thus, its detection requires high-resolution imaging. Clinical experience has shown that even though optical coherence tomography offers better resolution, intravascular ultrasound still remains an important imaging modality for coronary wall imaging. For a computer-based analysis system to be complete, it must be scientifically and clinically validated. This study presents a state-of-the-art review (condensation of 152 publications after examining 200 articles) covering the methods for calcium detection and its quantification for coronary and carotid arteries, the pros and cons of these methods, and the risk stratification strategies. The review also presents different kinds of statistical models and gold standard solutions for the evaluation of software systems useful for calcium detection and quantification. Finally, the review concludes with a possible vision for designing the next-generation system for better clinical outcomes.
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9.
Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review.
Faust, O, Acharya U, R, Ng, EY, Ng, KH, Suri, JS
Journal of medical systems. 2012;(1):145-57
Abstract
Diabetes is a chronic end organ disease that occurs when the pancreas does not secrete enough insulin or the body is unable to process it properly. Over time, diabetes affects the circulatory system, including that of the retina. Diabetic retinopathy is a medical condition where the retina is damaged because fluid leaks from blood vessels into the retina. Ophthalmologists recognize diabetic retinopathy based on features, such as blood vessel area, exudes, hemorrhages, microaneurysms and texture. In this paper we review algorithms used for the extraction of these features from digital fundus images. Furthermore, we discuss systems that use these features to classify individual fundus images. The classifications efficiency of different DR systems is discussed. Most of the reported systems are highly optimized with respect to the analyzed fundus images, therefore a generalization of individual results is difficult. However, this review shows that the classification results improved has improved recently, and it is getting closer to the classification capabilities of human ophthalmologists.