Markers for various cardiac diseases

2016 ◽  
Author(s):  
S. Kansal ◽  
P.P. Bansod ◽  
A. Kumar
Keyword(s):  
Cardiac Diseases

Breakthrough Regenerative Cardiopoietic Stem Cells and Related Technologies in the Field of Cardiovascular Medicine – From Bench to Bedside

2012 ◽  
Vol 7 (1) ◽  
pp. 14
Author(s):  
Christian Homsy ◽  
Keyword(s):  
Stem Cells ◽  
Cell Therapy ◽  
Progenitor Cells ◽  
Cardiac Disease ◽  
Cardiac Tissue ◽  
Cardiac Repair ◽  
Cardiac Diseases ◽  
Cardiac Progenitor Cells ◽  
Biotechnology Company ◽  
Cardiovascular Medicine

The scale of cardiac diseases, and in particular heart failure and acute myocardial infarction, emphasises the need for radically new approaches, such as cell therapy, to address the underlying cause of the disease, the loss of functional myocardium. Stem cell-based therapies, whether through transplanted cells or directing innate repair, may provide regenerative approaches to cardiac diseases by halting, or even reversing, the events responsible for progression of organ failure. Cardio3 BioSciences, a leading Belgian biotechnology company focused on the discovery and development of regenerative and protective therapies for the treatment of cardiac disease, was founded in this context in 2004. The company is developing a highly innovative cell therapy approach based on a platform designed to reprogramme the patient’s own stem cells into cardiac progenitor cells. The underlying rationale behind this approach is that, in order to reconstruct cardiac tissue, stem cells need to be specific to cardiac tissue. The key is therefore to provide cardiac-specific progenitor cells to the failing heart to induce cardiac repair.

New forms of physical exercise for patients with cardiac diseases

2017 ◽  
Vol 18 (6) ◽  
pp. 555-560
Author(s):  
T.T. Kakuchaya ◽  
T.G. Dzhitava ◽  
N.V. Pachuashvili
Keyword(s):  
Physical Exercise ◽  
Cardiac Diseases

Exercise as a platform for pharmacotherapy development in cardiac diseases

2015 ◽  
Vol 21 (30) ◽  
pp. 4409-4416 ◽  
Author(s):  
Yihua Bei ◽  
Qiulian Zhou ◽  
Qi Sun ◽  
Junjie Xiao
Keyword(s):  
Cardiac Diseases

scholarly journals P4521Comparative prevalence and diagnostic yield of family screening in inherited cardiac diseases. 10K single centre registry

2017 ◽  
Vol 38 (suppl_1) ◽  
Author(s):  
D. Lopez Cuenca ◽  
M.C. Olmo ◽  
F. Castro ◽  
J.P. Hernandez Del Rincon ◽  
F. Pastor ◽  
...  
Keyword(s):  
Diagnostic Yield ◽  
Cardiac Diseases ◽  
Single Centre ◽  
Family Screening

scholarly journals Structural and Functional Remodeling of Mitochondria in Cardiac Diseases

2021 ◽  
Vol 22 (8) ◽  
pp. 4167
Author(s):  
Xiaonan Sun ◽  
Jalen Alford ◽  
Hongyu Qiu
Keyword(s):  
Regulatory Network ◽  
Molecular Basis ◽  
Therapeutic Potential ◽  
Research Direction ◽  
Future Research ◽  
Cardiac Diseases ◽  
Functional Remodeling ◽  
Underlying Mechanisms ◽  
Mitochondrial Remodeling ◽  
Normal Cellular Function

Mitochondria undergo structural and functional remodeling to meet the cell demand in response to the intracellular and extracellular stimulations, playing an essential role in maintaining normal cellular function. Merging evidence demonstrated that dysregulation of mitochondrial remodeling is a fundamental driving force of complex human diseases, highlighting its crucial pathophysiological roles and therapeutic potential. In this review, we outlined the progress of the molecular basis of mitochondrial structural and functional remodeling and their regulatory network. In particular, we summarized the latest evidence of the fundamental association of impaired mitochondrial remodeling in developing diverse cardiac diseases and the underlying mechanisms. We also explored the therapeutic potential related to mitochondrial remodeling and future research direction. This updated information would improve our knowledge of mitochondrial biology and cardiac diseases’ pathogenesis, which would inspire new potential strategies for treating these diseases by targeting mitochondria remodeling.

Stem cell‐based therapies for cardiac diseases: The critical role of angiogenic exosomes

BioFactors ◽  
2021 ◽  
Author(s):  
Sara Ghodrat ◽  
Seyed Javad Hoseini ◽  
Shiva Asadpour ◽  
Simin Nazarnezhad ◽  
Fariba Alizadeh Eghtedar ◽  
...  
Keyword(s):  
Stem Cell ◽  
Critical Role ◽  
Cardiac Diseases

BioSignal modelling for prediction of cardiac diseases using intra group selection method

2021 ◽  
Vol 15 (1) ◽  
pp. 151-160
Author(s):  
Hemant P. Kasturiwale ◽  
Sujata N. Kale
Keyword(s):  
Machine Learning ◽  
Nervous System ◽  
Random Forest ◽  
Normal Sinus Rhythm ◽  
Heart Defects ◽  
Support Vector ◽  
Autonomous Nervous System ◽  
Cardiac Diseases ◽  
Vast Number ◽  
Proposed Model

The Autonomous Nervous System (ANS) controls the nervous system and Heart Rate Variability (HRV) can be used as a diagnostic tool to diagnose heart defects. HRV can be classified into linear and nonlinear HRV indices which are used mostly to measure the efficiency of the model. For prediction of cardiac diseases, the selection and extraction features of machine learning model are effective. The available model used till date is based on HRV indices to predict the cardiac diseases accurately. The model could hardly throw light on specifics of indices, selection process and stability of the model. The proposed model is developed considering all facet electrocardiogram amplitude (ECG), frequency components, sampling frequency, extraction methods and acquisition techniques. The machine learning based model and its performance shall be tested using the standard BioSignal method, both on the data available and on the data obtained by the author. This is unique model developed by considering the vast number of mixtures sets and more than four complex cardiac classes. The statistical analysis is performed on a variety of databases such as MIT/BIH Normal Sinus Rhythm (NSR), MIT/BIH Arrhythmia (AR) and MIT/BIH Atrial Fibrillation (AF) and Peripheral Pule Analyser using feature compatibility techniques. The classifiers are trained for prediction with approximately 40000 sets of parameters. The proposed model reaches an average accuracy of 97.87 percent and is sensitive and précised. The best features are chosen from the different HRV features that will be used for classification. The present model was checked under all possible subject scenarios, such as the raw database and the non-ECG signal. In this sense, robustness is defined not only by the specificity parameter, but also by other measuring output parameters. Support Vector Machine (SVM), K-nearest Neighbour (KNN), Ensemble Adaboost (EAB) with Random Forest (RF) are tested in a 5% higher precision band and a lower band configuration. The Random Forest has produced better results, and its robustness has been established.

Thinking beyond infections in children with recurrent/persistent pneumonia

2021 ◽  
pp. 004947552110020
Author(s):  
Devki Nandan ◽  
Hema Mittal ◽  
Anu Sharma ◽  
Kavita Srivastava
Keyword(s):  
Interstitial Lung Disease ◽  
Early Diagnosis ◽  
Lung Disease ◽  
Bronchial Asthma ◽  
Reflux Disease ◽  
Morbidity And Mortality ◽  
Oesophageal Reflux ◽  
Cardiac Diseases ◽  
Cardiopulmonary Disease ◽  
Underlying Causes

Children with recurrent or persistent pneumonia often have underlying chronic cardiopulmonary disease, but few reports on this subject have been published. Children with isolated common cardiac diseases, uncomplicated bronchial asthma or with incomplete records were excluded. Of 4361 children followed during a five-year period, 107 were included in our study. Underlying causes were identified in 99.0%: immunodeficiency disorders (20.2%), cardiothoracic malformations (18.3%), syndromic conditions (14.4%), infections (10.6%) bronchiectasis (10.6%), gastro-oesophageal reflux disease (6.6%), interstitial lung disease (3.8%) and other miscellaneous conditions (15.4%). Thus, children with recurrent or persistent pneumonia should be carefully evaluated for an underlying aetiology, as early diagnosis and appropriate management will decrease morbidity and mortality in most of these children.

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