The effect of the daily intake of inulin on fasting lipid, insulin and glucose concentrations in middle-aged men and women

The present study was carried out to examine the effect of the daily intake of 10 g inulin on fasting blood lipid, glucose and insulin levels in healthy middle-aged men and women with moderately raised total plasma cholesterol (TC) and triacylglycerol (TAG) levels. This study was a doubleblind randomized placebo-controlled parallel study in which fifty-four middle-aged subjects received either inulin or placebo for a period of 8 weeks. Fasting blood samples were collected before the supplementation period (baseline samples 1 and 2, separated by 1 week) and at weeks 4 and 8, with a follow-up at week 12. Compared with baseline values, insulin concentrations were significantly lower at 4 weeks (P,0×01) in the inulin group. There was a trend for TAG values, compared with baseline, to be lower in the inulin group at 8 weeks (P,0×08) returning to baseline concentrations at week 12. On comparison of the inulin and placebo groups, the fasting TAG responses over the 8-week test period were shown to be significantly different (P,0×05, repeated measures ANOVA), which was largely due to lower plasma TAG levels in the inulin group at week 8. The percentage change in TAG levels in the inulin group during the 8-week study was shown to correlate with the initial TAG level of the subjects (rs -0×499, P = 0×004). We therefore conclude that the daily addition of 10 g inulin to the diet significantly reduced fasting insulin concentrations during the 8-week test period and resulted in lower plasma TAG levels, particularly in subjects in whom fasting TAG levels were greater than 1×5 mmol/l. These data support findings from animal studies that fructans influence the formation and/or degradation of TAG-rich lipoprotein particles, and the insulin data are also consistent with recent studies showing attenuation of insulin levels in fructan-treated rats.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

Exposure to environmental oestrogenic chemicals and breast cancer.

The human population is now exposed on a daily basis to a multitude of environmental pollutant chemicals that would not have been present a century ago, and many of these chemicals have been detected in the human breast. The fatty nature of human breast tissue makes it a particular target for lipophilic as well as hydrophilic pollutant chemicals, which may enter the human body through oral, respiratory, or dermal routes. These chemicals possess a range of endocrine-disrupting properties and genotoxic activity, but from a breast cancer perspective the greatest concern has centered around their ability to mimic or interfere with the action of estrogen. The breast is an endocrine target organ and exposure to estrogen is a known risk factor for breast cancer.

A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates

The intensity and distribution of daily precipitation is predicted to change under scenarios of increased greenhouse gases (GHGs). In this paper, we analyse the ability of HadCM2, a general circulation model (GCM), and a high-resolution regional climate model (RCM), both developed at the Met Office's Hadley Centre, to simulate extreme daily precipitation by reference to observations. A detailed analysis of daily precipitation is made at two UK grid boxes, where probabilities of reaching daily thresholds in the GCM and RCM are compared with observations. We find that the RCM generally overpredicts probabilities of extreme daily precipitation but that, when the GCM and RCM simulated values are scaled to have the same mean as the observations, the RCM captures the upper-tail distribution more realistically. To compare regional changes in daily precipitation in the GHG-forced period 2080-2100 in the GCM and the RCM, we develop two methods. The first considers the fractional changes in probability of local daily precipitation reaching or exceeding a fixed 15 mm threshold in the anomaly climate compared with the control. The second method uses the upper one-percentile of the control at each point as the threshold. Agreement between the models is better in both seasons with the latter method, which we suggest may be more useful when considering larger scale spatial changes. On average, the probability of precipitation exceeding the 1% threshold increases by a factor of 2.5 (GCM and RCM) in winter and by I .7 (GCM) or 1.3 (RCM) in summer.

Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.