Brownian movement analyzed from psychophysiological measures associated with ischemic heart disease and Alzheimer’s disease

There are several coronary diseases that human beings can suffer from, which in themselves generate health deterioration and can lead to the development of other diseases that diminish the quality of life. Ischemic diseases are unique in that they are evidenced by blockages generated by the accumulation of fat that impedes circulation, triggering heart and brain-related problems. By means of fractional Brownian motion in relation to Hurst’s parameter, an analysis of a data of 137 patients aged between 30 and 71 years, who present some type of ischemic disease such as mixed, restricted, effort angina and angina pectoris, is performed. The data used was European, which is found in the PhysioNet open-access medical research data repository, managed by the Massachusetts Institute of Technology Computational Physiology Laboratory. This data shows the Hurst coefficient calculations associated with each type of ischemic heart disease.

Fractal analysis of neuroimaging: comparison between control patients and patients with the presence of Alzheimer’s disease

Alzheimer’s disease is a neurodegenerative cognitive, affective, and behavioral disorder aligned to the aging process and other coronary diseases. To contribute to the early diagnosis of the disease, a neuroimaging treatment is implemented through a preprocessing to subsequently calculate the fractal dimension associated with these images in order to propose an alternative to the one proposed in medical physics through positron emission tomography. In this work, a comparative analysis is made of a previous work using the Box Counting methodology versus the calculation of the fractal dimension by means of software developed by the researchers based on the same method. The differences between the fractal dimensions of the neuroimages of control patients and patients with the presence of the disease are maintained showing a lower value of fractal dimension in patients with the disease due to the physical deterioration of the brain.

EMPLOYABILITY OF SELECTED DATAMINING ALGORITHMS IN THE EARLY PREDICTION OF CORONARY DISEASES

The objective of our work is to take apart unique data mining methods and procedures in the healthcare system that can use an assumption for coronary disease structure and their impact investigation. A coronary disease prediction model, which executes the data mining method, can help the therapeutic experts perceive the coronary sickness status subject to the patient's clinical data. Data mining description techniques for the great fundamental initiative in human system are specifically Decision trees, Naive Bayes, Neural Networks and Support Vector Machines. Hybridizing or merging any of these calculations makes decisions snappier and assigned dynamically. Information mining is a notable new improvement for extracting hypermetropic and critical information from enormous data sets to build significant and novel encounters. Using impelled data mining systems to extract essential information has been considered a fanatic method to improve human management organization's quality and precision while trimming down the social protection cost and execution time. Using this technique can expect the early detection of coronary disease. Using more information properties, for instance, could develop controllable and natural danger factors, progressively detailed results. Can also broaden this strategy. It can use an extensive part of data properties. Other data mining strategies use for forecasts, such as clustering, time series plan, and association rules. The unstructured data open in the human system industry information base can mine using content mining.

Research Progress of Imaging Methods for Detection of Microvascular Angina Pectoris in Diabetic Patients

Diabetes is a complex metabolic disease characterized by hyperglycemia. Its complications are various, often involving the heart, brain, kidney, and other essential organs. At present, the number of diabetic patients in the world is growing day by day. The cardiovascular disease caused by diabetes has dramatically affected the quality of life of diabetic patients. It is the leading cause of death of diabetic patients. Diabetic patients often suffer from microvascular angina pectoris without obstructive coronary artery disease. Still, there are typical ECG ischemia and angina pectoris, that is, chest pain and dyspnea under exercise. Unlike obstructive coronary diseases, nitrate does not affect chest pain caused by coronary microvascular angina in most cases. With the increasing emphasis on diabetic microvascular angina, the need for accurate diagnosis of the disease is also increasing. We can use SPECT, PET, CMR, MCE, and other methods to evaluate coronary microvascular function. SPECT is commonly used in clinical practice, and PET is considered the gold standard for non-invasive detection of myocardial blood flow. This article mainly introduces the research progress of these imaging methods in detecting microvascular angina in diabetic patients.

Cardiac Arrhythmia Detection using Dual Tree Wavelet Transform and Convolutional Neural Network

The non-stationary ECG signals are used as a key tools in screening coronary diseases. ECG recording is collected from millions of cardiac cells’ and depolarization and re-polarization conducted in a synchronized manner as: The P-wave occurs first, followed by the QRScomplex and the T-wave, which will repeat in each beat. The signal is altered in a cardiac beat period for different heart conditions. This change can be observed in order to diagnose the patient’s heart status. There are life-threatening (critical) and non-life - threatening (noncritical) arrhythmia (abnormal Heart). Critical arrhythmia gives little time for surgery, whereas non-critical needs additional life-saving care. Simple naked eye diagnosis can mislead the detection. At that point, Computer Assisted Diagnosis (CAD) is therefore required. In this paper Dual Tree Wavelet Transform (DTWT) used as a feature extraction technique along with Convolution Neural Network (CNN) to detect abnormal Heart. The findings of this research and associated studies are without any cumbersome artificial environments. The CAD method proposed has high generalizability; it can help doctors efficiently identify diseases and decrease misdiagnosis.

The Role of Antiplatelet agents in ischemic events

Antiplatelet treatment could be a key in pharmacological treatment for avoidance of coronary heart disease (CHD) and stroke. Depending on sign, term of antiplatelet monotherapy or double treatment is shifted. Antiplatelet treatment is shown to avoid a repeat of cardiovascular occasion, in any case, expanded term of dual antiplatelet treatment (DAPT) related with expanded hazard of bleeding. Unstable angina happens due to partially or totally block of the blood coronary blood vessel driving to coronary ischaemia. Intense coronary infection happens due to drawn out coronary ischaemia which causes coronary diseases. Keywords: dual antiplatelet treatment (DAPT), coronary heart disease (CHD) and stroke.

Tailoring the Structure of Lipids, Oleogels and Fat Replacers by Different Approaches for Solving the Trans-Fat Issue—A Review

The issue of the adverse effects of trans-fatty acids has become more transparent in recent years due to researched evidence of their link with coronary diseases, obesity or type 2 diabetes. Apart from conventional techniques for lipid structuring, novel nonconventional approaches for the same matter, such as enzymatic interesterification, genetic modification, oleogelation or using components from nonlipid origins such as fat replacers have been proposed, leading to a product with a healthier nutritional profile (low in saturated fats, zero trans fats and high in polyunsaturated fats). However, replacing conventional fat with a structured lipid or with a fat mimetic can alternate some of the technological operations or the food quality impeding consumers’ acceptance. In this review, we summarize the research of the different existing methods (including conventional and nonconventional) for tailoring lipids in order to give a concise and critical overview in the field. Specifically, raw materials, methods for their production and the potential of food application, together with the properties of new product formulations, have been discussed. Future perspectives, such as the possibility of bioengineering approaches and the valorization of industrial side streams in the framework of Green Production and Circular Economy in the production of tailored lipids, have been highlighted. Additionally, a schematic diagram classifying conventional and nonconventional techniques is proposed based on the processing steps included in tailored lipid production as a convenient and straightforward tool for research and industry searching for healthy, sustainable and zero trans edible lipid system alternatives.

Cardiac imaging in cardio-oncology

Every patient before, during and after a cancer treatment, may need an imaging evaluation to manage their clinic path. Essentially will be required methods able to evaluate very accurately left ventricular function, structure, and morphology, coronary diseases, valvular heart diseases, pericardial diseases, vascular diseases, amyloidosis, myocarditis, and pulmonary hypertension. Echocardiographic methods are the most diffuse, easy to use, with low costs, and without radiation use, but are subject to difficulties in evaluation for many technic reasons. Where echocardiography is not able to give correct information, cardiac magnetic resonance (CMR) is the most promising imaging tool, also if costs and availability may preclude its diffuse use. On the other hand scintigraphy methods, due to their radiation related risk, are less utilized. The chapter analyses the main pathologic cancer related toxicities and the most useful imaging methods to be used in clinical practice.

miRNA can be a part of both the onset and cure of Coronary heart disease.

Cardiovascular disease causes the worst destruction. The study suggests that miRNAs are involved in the cause, occurrence, and prognosis of CVD. Even though they were discovered in 1993, their functions have not been well understood; more recently, they are known to control gene expression as well as well as fine-tune many biochemical processes. A myriad of miRNAs contribute to the pathogenesis of coronary diseases. Most experiments on miRN have shown that miRNA is either increased or decreased under various pathophysiological conditions, but its function in CVD remains a mystery. often suggested to be involved in the pathophysiology of CVD The discovery of disease biomarkers that are useful in the processing would highlight the relevance of miRNAs for diagnostics and therapy development of CVDs. During the early stages, the use of miRNAs as therapies has the potential to impact therapeutics. More refined technologies are also required to develop miRNA as biomarkers and treatments Indeed, additional regional and/population research is needed to address any possible challenges or issues. The introduction of new gene therapies discoveries is on the way.