Endless Journey of Adenosine Signaling in Cardioprotective Mechanism of Conditioning Techniques: Clinical Evidences.

Myocardial ischemic injury is a primary cause of death among various cardiovascular disorders. The condition occurs due to interrupted blood supply and vital nutrients (necessary for normal cellular activities and viability) to the myocardium, eventually leading to damage. Restoration of blood supply to ischemic tissue is noted to cause even more lethal reperfusion injury. Various strategies, including some conditioning techniques like preconditioning & postconditioning have been developed to check detrimental effects of reperfusion injury. Many endogenous substances have been proposed to act as initiator, mediators and end effectors of these conditioning techniques. Substances like adenosine, bradykinin, acetylcholine, angiotensin, norepinephrine, opioids, etc., have been reported to mediate cardioprotective activity. Among these agents, adenosine has been widely studied and suggested to have the most pronounced cardioprotective effects. The current review article highlights the role of adenosine signaling in the cardioprotective mechanism of conditioning techniques. The article also provides an insight into various clinical studies that substantiate the applicability of adenosine as a cardioprotective agent in myocardial-reperfusion injury.

A comprehensive survey on gait analysis: History, parameters, approaches, pose estimation, and future work.

Human gait is a periodic motion of body segments-the analysis of motion and related studies is termed gait analysis. Gait Analysis has gained much popularity because of its applications in clinical diagnosis, rehabilitation methods, gait biometrics, robotics, sports, and biomechanics. Traditionally, subjective assessment of the gait was conducted by health experts; however, with the advancement in technology, gait analysis can now be performed objectively and empirically for better and more reliable assessment. State-of-the-art semi-subjective and objective techniques for gait analysis have limitations that can be mitigated using advanced machine learning-based approaches. This paper aims to provide a narrative and a comprehensive analysis of cutting-edge gait analysis techniques and insight into clinical gait analysis. The literature of the previous surveys during the last decade is discussed. This paper presents an elaborated schema, including gait analysis history, parameters, machine learning approaches for marker-based and marker-less analysis, applications, and performance measures. This paper also explores the pose estimation techniques for clinical gait analysis that open future research directions in this area.