Force variability in the short- and long-term type 2 diabetes mellitus

2022

IJERPH

The plateau effect in training is a significant obstacle for professional athletes and average subjects. It evolves from both the muscle-nerve-axis-associated performance and various cardiorespiratory parameters. Compensatory adaptation mechanisms contribute to a lack of continuous improvement with most exercise regimens. Attempts to overcome this plateau in exercise have been only partially successful, and it remains a significant unmet need in both healthy subjects and those suffering from chronic neuromuscular, cardiopulmonary, and metabolic diseases. Variability patterns characterize many biological processes, from cellular to organ levels. The present review discusses the significant obstacles in overcoming the plateau in training and establishes a platform to implement subject-tailored variability patterns to prevent and overcome this plateau in muscle and cardiorespiratory performance.

Section: Entropy Variability and Randomness Characterize Biological S...mentioning

confidence: 96%

Section: Variability In Biological Systems Characterizes the Typical ...mentioning

confidence: 99%

Section: Variability In Biological Systems Characterizes the Typical ...mentioning

confidence: 99%

See 1 more Smart Citation

A Subject-Tailored Variability-Based Platform for Overcoming the Plateau Effect in Sports Training: A Narrative Review

Gelman

Berg

2022

IJERPH

“…Non-linear systems can function far from equilibrium, and their dynamicity is part of the plasticity required for optimizing their function ( 203 , 215 – 217 ). Biological variability is desirable for the evolutionary dynamics that contribute to stability through adaptation ( 153 , 160 , 180 , 218 , 219 ). It should be regarded as a method used for generating “new order,” assisting in overcoming errors in assembly and functions ( 166 , 220 ).…”

Section: Introductionmentioning

confidence: 99%

Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes

2020

Front. Digit. Health

Artificial intelligence (AI) digital health systems have drawn much attention over the last decade. However, their implementation into medical practice occurs at a much slower pace than expected. This paper reviews some of the achievements of first-generation AI systems, and the barriers facing their implementation into medical practice. The development of second-generation AI systems is discussed with a focus on overcoming some of these obstacles. Second-generation systems are aimed at focusing on a single subject and on improving patients' clinical outcomes. A personalized closed-loop system designed to improve end-organ function and the patient's response to chronic therapies is presented. The system introduces a platform which implements a personalized therapeutic regimen and introduces quantifiable individualized-variability patterns into its algorithm. The platform is designed to achieve a clinically meaningful endpoint by ensuring that chronic therapies will have sustainable effect while overcoming compensatory mechanisms associated with disease progression and drug resistance. Second-generation systems are expected to assist patients and providers in adopting and implementing of these systems into everyday care.

“…Interdependency between different network properties, which is applicable to many immune processes, many of which behave randomly, can be quantified. The dynamic systems theory suggests that biological systems are self-organized according to environmental, biochemical, and morphological constraints to find the most balanced state (143). It has been proposed that a patient-tailored variable regimen can overcome this adaptation, thereby improving the short- and long-term responses to anti-TNFs.…”

Section: Overcoming Immune System Adaptation To Anti-tnfs By Introducmentioning

confidence: 99%

Introducing Patterns of Variability for Overcoming Compensatory Adaptation of the Immune System to Immunomodulatory Agents: A Novel Method for Improving Clinical Response to Anti-TNF Therapies

Khoury

2019

Front. Immunol.

Primary lack of response and secondary loss of response (LOR) are major obstacles to the use of anti–tumor necrosis factor (TNF)-based therapies in patients with rheumatoid arthritis or inflammatory bowel disease. Here, we review the mechanisms and methods for predicting LOR and the currently used methods for overcoming the ineffectiveness of anti-TNFs. The complex functions of TNF and anti-TNF antibodies, which can promote both pro- or anti-inflammatory actions, and the factors that affect the induction of immune tolerance to their effects are presented. The lack of rules and the continuous dynamics of the immune processes partly underlie the unpredictability of the response to anti-TNFs. Variability is inherent to biological systems, including immune processes, and intra/inter-patient variability has been described in the response to drugs. This variability is viewed as a compensatory adaptation mechanism of the immune system in response to drugs and may contribute to treatment LOR. Dose reductions and drug holidays have been tested in patients treated with anti-TNFs. Regular dose-based regimens may be incompatible with physiological variability, further contributing to treatment inefficacy. We present the concept of overcoming immune system adaptation to anti-TNFs by introducing patient-tailored patterns of variability to treatment regimens.