Triphala is an Ayurvedic herbal formulation consisting of equal parts of three myrobalans: Terminalia chebula, Terminalia bellerica and Emblica officinalis. We recently reported that chebulagic acid (CA) isolated from Terminalia chebula is a potent COX-2/5-LOX dual inhibitor. In this study, compounds isolated from Terminalia bellerica were tested for inhibition against COX and 5-LOX. One of the fractionated compounds showed potent inhibition against COX enzymes with no inhibition against 5-LOX. It was identified as gallic acid (GA) by LC-MS, NMR and IR analyses.
In the Georgia Centenarian Study (Poon et al., Exceptional Longevity, 2006), centenarian cases and young controls are classified according to three categories (age, ethnic origin, and single nucleotide polymorphisms [SNPs] of candidate longevity genes), where each factor has two possible levels. Here we provide methodologies to determine the minimum sample size needed to detect dependence in 2 x 2 x 2 tables based on Fisher's exact test evaluated exactly or by Markov chain Monte Carlo (MCMC), assuming only the case total L and the control total N are known.
Biomarkers of aging are essential to predict mortality and aging-related diseases. Paradoxically, age itself imposes a limitation on the use of known biomarkers of aging because their associations with mortality generally diminish with age. How this pattern arises is, however, not understood. With meta-analysis we show that human leucocyte telomere length (TL) predicts mortality, and that this mortality association diminishes with age, as found for other biomarkers of aging.
Aging in the world population has increased every year. Superoxide dismutase 2 (Mn-SOD or SOD2) protects against oxidative stress, a main factor influencing cellular longevity. Polymorphisms in SOD2 have been associated with the development of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, as well as psychiatric disorders, such as schizophrenia, depression and bipolar disorder.
Bivariate survival models with discretely distributed frailty based on the major gene concept and applied to the data on related individuals such as twins and sibs can be used to estimate the underlying hazard, the relative risk and the frequency of the longevity allele. To determine the position of the longevity gene, additional genetic markers data are needed. If the action of the longevity allele does not depend on its position in the genome, these two problems can be solved separately using a two-step procedure.
The mitochondrial theory of ageing is one of the main contenders to explain the biochemical basis of the ageing process. An important line of support comes from the observation that mtDNA deletions accumulate over the life course in post-mitotic cells of many species. A single mutant expands clonally and finally replaces the wild-type population of a whole cell. One proposal to explain the driving force behind this accumulation states that the reduced size leads to a shorter replication time, which provides a selection advantage.
It is often claimed that genes affecting health in old age, such as cardiovascular and Alzheimer diseases, are beyond the reach of natural selection. We show in a simulation study based on known genetic (apolipoprotein E) and non-genetic risk factors (gender, diet, smoking, alcohol, exercise) that, because there is a statistical distribution of ages at which these genes exert their influence on morbidity and mortality, the effects of selection are in fact non-negligible.
The growing availability of 'omics' data and high-quality in silico genome-scale metabolic models (GSMMs) provide a golden opportunity for the systematic identification of new metabolic drug targets. Extant GSMM-based methods aim at identifying drug targets that would kill the target cell, focusing on antibiotics or cancer treatments. However, normal human metabolism is altered in many diseases and the therapeutic goal is fundamentally different--to retrieve the healthy state. Here we present a generic metabolic transformation algorithm (MTA) addressing this issue.
Twin Research: The Official Journal of the International Society for Twin Studies
Non-linear epigenetic processes are a potential underlying source of phenotypic differences in development. Simulation studies of twin pairs using simple non-linear development models characterised by chaotic or near-chaotic behavior are presented. The effect of chaotic processes on correlations is to lower them from their initial values, but high initial correlations are affected much less by chaotic and near-chaotic processes than intermediate correlations.
Epigenetics is the study of changes to the genome that can switch genes on or off and determine which proteins are transcribed without altering the DNA sequence. Recently, epigenetic changes have been linked to the development and progression of disease such as psychiatric disorders. High-throughput epigenetic experiments have enabled researchers to measure genome-wide epigenetic profiles and yield data consisting of intensity ratios of immunoprecipitation versus reference samples.