Description

Patients face difficulties when they are readmitted to primary care due to the integration of new medications into their daily routine and the involvement of multiple healthcare providers in various settings. To tailor counseling support, it is essential to clarify the needs of patients. Rabbits that have been Genetically Modified (GM) are excellent animal models for the study of human genetic and acquired diseases. As a result, GM rabbits with human genes have been extensively utilized as cardiovascular disease models. Prokaryotic microinjection is used to alter the genetic makeup of rabbits. Genes are inserted randomly into the rabbit genome as a result of this procedure. Additionally, gene targeting in Embryonic Stem (ES) cells is an effective method for gaining an understanding of how genes work. However, rabbits lack ES cell lines that are stable. As a result, rabbits cannot target genes dependent on ES. Nevertheless, the RNA interference method is rapidly gaining popularity as a useful experimental tool that enables the genetic modification of rabbits by suppressing particular gene expression. Major advancements in rabbit gene targeting have occurred recently as a result of the development of cutting-edge genetic techniques like Zinc-Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), and CRISPR-associated protein 9 (CRISPR/Cas9).Researchers have successfully modified knockout rabbit models by utilizing these novel genetic techniques.

Cardiovascular Medicine

 The purpose of this paper is to discuss the most recent developments in GM technology using rabbits as models for cardiovascular medicine. The metaverse, a novel interactive mix of digital worlds that combines augmented reality and virtual reality, was sparked by the recent pandemic and accelerated the adoption of telemedicine by cardiovascular health. A theoretical term for cardiovascular medicine's embrace of the metaverse, the CardioVerse introduces new dimensions to disease education, prevention, and diagnosis and encompasses the endless possibilities as well as the challenges that it presents. It can be used for a lot of things, like increasing the number of visits to the doctor, supporting cardiovascular interventions, and changing how medical education is taught. The use of non-fungible tokens as a security asset for patient data appears to be a potential solution, despite the fact that challenges are anticipated in a variety of domains, including technical, legislative, and regulatory, as well as security. Over the course of the last 10 years, the steady advancement in science and innovations has given creative medication particles that address explicit sickness systems in this way opening the time of medications focusing on the basic pathophysiology of the illness. Small molecules that can interfere with sarcomere contractile proteins have led to the development of a new modulation paradigm in this scenario. Heart muscle disease and various forms of heart failure are potential applications, but promising targets also include skeletal muscle diseases like degenerative neuromuscular diseases. A cardiac myosin stimulator, omecamtiv mecarbil, has been shown to be effective in heart failure patients with reduced systolic function, reducing heart failure-related events and cardiovascular deaths.

Two inhibitors, mavacamten and aficamten, have been shown to reduce hypercontractility and improve functional capacity in randomized trials targeting hypertrophic cardiomyopathy. These agents are the prototypes of active pipelines that have the potential to deliver a variety of molecules in the near future. They are the result of years of intensive basic and translational research. Myosin modulation in cardiovascular medicine is the subject of this review, which examines the existing evidence as well as potential future perspectives. Computational algorithms that iteratively improve their capacity to recognize patterns in data are referred to as "Machine Learning" (ML).An abundance of data from electronic health records, imaging, wearable, and sensors is being generated by the digitization of our healthcare infrastructure. These data can be analyzed by machine learning algorithms to generate personalized risk assessments and support guideline-directed medical management. The potential to negatively impact patient privacy, safety, health equity, and clinical interpretability must be balanced with ML's strength in generating insights from complex medical data to guide clinical decisions. Key developments in ML for the prevention of cardiovascular disease and their potential effects on clinical practice are discussed in this overview. The genetic basis of cardiovascular diseases has undergone rapid development. The sequencing of the human genome, the readily available and decreasing cost of next-generation sequencing technologies, and dedicated research in well-phenotype CVD patients have all contributed to this. The era of precision medicine has been heralded by this increased understanding of the genetic basis of CVDs.

Cardiovascular Illness

Improved diagnosis, family screening, assistance with reproductive decisions, targeted therapeutics guided by both phenotype and genotype, and important insights into risk stratification and prognosis are just a few of the many components that fall under this umbrella. In addition, exciting future endeavors that will alter established clinical approaches include novel insights into genetic mechanisms, the clinical rollout of polygenic risk scores for common cardiovascular diseases, and the promise of genome editing approaches to effectively cure disease. The foundations and fundamental aspects of precision medicine are the focus of this first installment of a five-part series. Numerous Natural Products (NPs) have been used for centuries and have made significant contributions to cardiovascular medicine. Cardiovascular illness is the main source of grimness and mortality around the world. Throughout recent years, roughly half of recently evolved cardiovascular medications depended on NPs, proposing that NPs give fundamental skeletal designs to the revelation of novel meds. NPs have recently regained scientific and commercial attention, leveraging the wealth of knowledge provided by multi-omics, combinatorial biosynthesis, synthetic biology, integrative pharmacology, and analytical and computational technologies. This comes after a period of lower productivity since the 1990s.In addition, Traditional Chinese Medicine, which is an essential component of complementary and alternative medicine, is increasingly being recognized as a significant source of NPs for cardiovascular drug discovery. One of the most valuable sources of drugs and drug leads are NPs because of their biological activity and structural diversity. We summarized the characteristics and classification of NPs in CVDs in this review. The therapeutic potential and underlying mechanisms of action of NPs in CVDs, as well as the current outlook and potential for developing safer and more effective cardiovascular drugs based on NPs, are then discussed in detail. Hand-Held Ultrasound (HHU) machines of varying capacities and features have recently become available. All of the HHU devices are more sensitive than clinical assessment in identifying cardiovascular abnormalities and offer the potential for faster diagnoses, despite their individual differences. They are also more portable, have the potential to shorten the time it takes to get full echocardiograms, and they could save money on healthcare costs. It is anticipated that HHU has significant potential for expansion as a tool for facilitating patient care when carried out by competent and well-trained providers. The characteristics, advantages, drawbacks, and perspectives for the future of HHU devices are discussed in this paper.

 The broad term "Artificial Intelligence" (AI) refers to the combination of sophisticated mathematical models and computation, which paves the way for the creation of intricate algorithms that can imitate human intelligence in areas like problem-solving and learning. It is designed to bring about a significant shift in the way medical knowledge is understood in the most diverse fields. In contrast, coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other conditions are all included in the extensive field of cardiology, which focuses on diseases of the heart and the circulatory system. In cardiovascular medicine, Artificial Intelligence (AI) has emerged as a promising tool for enhancing the effectiveness of cardiologists and providing patients with better care. It can aid in decision-making and enhance diagnostic and prognostic accuracy. In addition, efforts have been made to investigate novel genotypes and phenotypes that are associated with existing cardiovascular diseases, to enhance the standard of patient care, and to enable cost-effectiveness by lowering the rates of readmission and mortality. The integration of AI and laboratory medicine as an accelerator of personalized care in cardiovascular medicine is the topic of our review. This is because of the need for services that create value and provide precision.