Increased neuroplasticity may protect against cardiovascular disease

Integrating neuroplasticity and evolution

Neuroplasticity and evolutionary biology have been prominent fields of study for well over a century. However, they have advanced largely independently, without consideration of the benefits of integration. We propose a new framework by which researchers can begin to examine the evolutionary causes and consequences of neuroplasticity. Neuroplasticity can be defined as changes to the structure, function or connections of the nervous system in response to individual experience. Evolution can alter levels of neuroplasticity if there is variation in neuroplasticity traits within and between populations. Neuroplasticity may be favored or disfavored by natural selection depending on the variability of the environment and the costs of neuroplasticity. Additionally, neuroplasticity may affect rates of genetic evolution in many ways: for example, decreasing rates of evolution by buffering against selection or increasing them via the Baldwin effect, by increasing genetic variation or by incorporating evolved peripheral changes to the nervous system. These mechanisms can be tested using comparative and experimental approaches and by examining patterns and consequences of variation in neuroplasticity among species, populations and individuals.

The role of frailty in advanced HF and cardiac transplantation

Frailty is a complex, multi-system condition often associated with multimorbidity. It has become an important prognostic maker across a range of conditions and is particularly relevant in patients with cardiovascular disease. Frailty encompasses a range of domains including, physical, psychological, and social. There are currently a range of validated tools available to measure frailty. It is an especially important measurement in advanced HF, because frailty occurs in up to 50% of HF patients and is potentially reversible with therapies such as mechanical circulatory support and transplantation. Moreover, frailty is dynamic, and therefore serial measurements are important. This review delves into the measurement of frailty, mechanisms, and its role in different cardiovascular cohorts. Understanding frailty will help determine patients that will benefit from therapies, as well as prognosticate outcomes.

Identification of a High-Risk Group of New-Onset Cardiovascular Disease in Occupational Drivers by Analyzing Heart Rate Variability

Purpose: This cohort study evaluated the effectiveness of noninvasive heart rate variability (HRV) analysis to assess the risk of cardiovascular disease over a period of 8 years. Methods: Personal and working characteristics were collected before biochemistry examinations and 5 min HRV tests from the Taiwan Bus Driver Cohort Study (TBDCS) in 2005. This study eventually identified 161 drivers with cardiovascular disease (CVD) and 627 without between 2005 and 2012. Estimation of the hazard ratio was analyzed by using the Cox proportional-hazards model. Results: Subjects with CVD had an overall lower standard deviation of NN intervals (SDNN) than their counterparts did. The SDNN index had a strong association with CVD, even after adjusting for risk factors. Using a median split for SDNN, the hazard ratio of CVD was 1.83 (95% CI = 1.10–3.04) in Model 1 and 1.87 (95% CI = 1.11–3.13) in Model 2. Furthermore, the low-frequency (LF) index was associated with a risk of CVD in the continuous approach. For hypertensive disease, the SDNN index was associated with increased risks in both the continuous and dichotomized approaches. When the root-mean-square of the successive differences (RMSSDs), high frequency (HF), and LF were continuous variables, significant associations with hypertensive disease were observed. Conclusions: This cohort study suggests that SDNN and LF levels are useful for predicting 8 year CVD risk, especially for hypertensive disease. Further research is required to determine preventive measures for modifying HRV dysfunction, as well as to investigate whether these interventions could decrease CVD risk among professional drivers.

Brain signalling systems: A target for treating type I diabetes mellitus

From early to later stages of Type I Diabetes Mellitus (TIDM), signalling molecules including brain indolamines and protein kinases are altered significantly, and that has been implicated in the Metabolic Disorders (MD) as well as impairment of retinal, renal, neuronal and cardiovascular systems. Considerable attention has been focused to the effects of diabetes on these signalling systems. However, the exact pathophysiological mechanisms of these signals are not completely understood in TIDM, but it is likely that hyperglycemia, acidosis, and insulin resistance play significant roles. Insulin maintains normal glycemic levels and it acts by binding to its receptor, so that it activates the receptor's tyrosine kinase activity, resulting in phosphorylation of several substrates. Those substrates provide binding/interaction sites for signalling molecules, including serine/threonine kinases and indolamines. For more than two decades, our research has been focused on the mechanisms of protein kinases, CaM Kinase and Serotonin transporter mediated alterations of indolamines in TIDM. In this review, we have also discussed how discrete areas of brain respond to insulin or some of the pharmacological agents that triggers or restores these signalling molecules, and it may be useful for the treatment of specific region wise changes/disorders of diabetic brain.