A review of recent evidence relating to sugars, insulin resistance and diabetes

The potential impact on health of diets rich in free sugars, and particularly fructose, is of major concern. The focus of this review is the impact of these sugars on insulin resistance and obesity, and the associated risk of developing type 2 diabetes. Much of the concern is focussed on specific metabolic effects of fructose, which are argued to lead to increased fat deposition in the liver and skeletal muscle with subsequent insulin resistance and increased risk of diabetes. However, much of the evidence underpinning these arguments is based on animal studies involving very large intakes of the free sugars. Recent human studies, in the past 5 years, provide a rather different picture, with a clear dose response link between fructose intake and metabolic changes. In particular, the most marked effects are observed when a high sugars intake is accompanied by an excess energy intake. This does not mean that a high intake of free sugars does not have any detrimental impact on health, but rather that such an effect seems more likely to be a result of the high sugars intake increasing the chances of an excessive energy intake rather than it leading to a direct detrimental effect on metabolism

Existence Advertising, Price Competition, and Asymmetric Market Structure

We examine a two stage duopoly game in which firms advertise their existence to consumers in stage 1 and compete in prices in stage 2. Whenever the advertising technology generates positive overlap in customer bases the equilib- rium for the stage 1 game is asymmetric in that one firm chooses to remain small in comparison to its competitor. For a specific random advertising technology we show that one firm will always be half as large as the other. No equilibrium in pure price strategies exists in the stage 2 game and as long as there is some overlap in customer bases the mixed strategy equilibrium is far from the Bertrand equilibrium.Existence advertising; price dispersion; Bertrand paradox; information; duopoly

Spam - solutions and their problems

We analyze the success of filtering as a solution to the spam problem when used alone or concurrently with sender and/or receiver pricing. We find that filters alone may exacerbate the spam problem if the spammer attempts to evade them by sending multiple variants of the message to each consumer. Sender and receiver prices can effectively reduce or eliminating spam, either on their own or when used together with filtering. Finally, we discuss the impli- cations for social welfare of using the different spam controls.Spam; filtering; email; receiver pricing; sender pricing

Spam: solutions and their problems

We analyze the success of filtering as a solution to the spam problem when used alone or concurrently with sender and/or receiver pricing. We find that filters alone may exacerbate the spam problem if the spammer attempts to evade them by sending multiple variants of the message to each consumer. Sender and receiver prices can effectively reduce or eliminating spam, either on their own or when used together with filtering. Finally, we discuss the implications for social welfare of using the different spam controls

A W:B4C multilayer phase retarder for broadband polarization analysis of soft x-ray radiation \ud

A W:B4C multilayer phase retarder has been designed and characterized which shows a nearly constant phase retardance between 640 and 850 eV photon energies when operated near the Bragg condition. This freestanding transmission multilayer was used successfully to determine, for the first time, the full polarization vector at soft x-ray energies above 600 eV, which was not possible before due to the lack of suitable optical elements. Thus, quantitative polarimetry is now possible at the 2p edges of the magnetic substances Fe, Co, and Ni for the benefit of magnetic circular dichroism spectroscopy employing circularly polarized synchrotron radiatio

Dose–response effect of a whey protein preload on within-day energy intake in lean subjects

The effect of consuming different amounts of whey protein on appetite and energy intake was investigated in two separate studies using randomised, crossover designs. Healthy-weight men and women (range: BMI 19·0–25·0 kg/m2, age 19·4–40·4 years) consumed one of four 400 ml liquid preloads, followed by an ad libitum test meal 90 min later. In study 1, preloads were 1675 kJ with 12·5, 25 or 50 % of energy from protein, and in study 2, preloads were 1047 kJ with 10, 20 or 40 % energy from protein. Flavoured water was used as the control in both the studies. Appetite ratings were collected immediately before 30, 60 and 90 min after consuming the preloads; and immediately, 30 and 60 min after consuming the test meal. In study 1, energy intake following the control preload (4136 (sem 337) kJ) was significantly higher than each of the 12·5 % (3520 (sem 296) kJ), 25 % (3384 (sem 265) kJ) and 50 % (2853 (sem 244) kJ) protein preloads (P < 0·05). Intake after the 12·5 % preload was significantly higher than following 25 and 50 % preloads (P < 0·05). In study 2, energy intake following the control preload (4801 (sem 325) kJ) was higher than following the 10 % (4205 (sem 310) kJ), 20 % (3988 (sem 250) kJ) and 40 % (3801 (sem 245) kJ) protein preloads (P < 0·05). There were no differences in subjective appetite ratings between preloads in either study. These findings indicate a dose–response effect of protein content of the preload on energy intake at a subsequent meal

Exercise metabolism in non-obese patients with type 2 diabetes following the acute restoration of normoglycaemia

This study investigated how acute restoration of normoglycaemia affected energy metabolism during exercise in nonobese patients with type 2 diabetes. Six subjects (mean ± SEM) aged 56.2 ± 2.7 years, with a BMI of 24.5 ± 1.5 kg/m2 and a VO2 peak of 28.7 ml/kg/min, attended the lab on two randomised occasions for a four-hour resting infusion of insulin or saline, followed by 30 minutes cycling at 50% VO2 peak. During the 4 h resting infusion, there was a greater (P < 0 0001) reduction in blood glucose in insulin treatment (INS) (from 11.2 ± 0.6 to 5.6 ± 0.1 mmol/l) than in saline treatment/control (CON) (from 11.5 ± 0.7 to 8.5 ± 0.6 mmol/l). This was associated with a lower (P < 0 05) resting metabolic rate in INS (3.87 ± 0.17) than in CON (4.39 ± 0.30 kJ/min). During subsequent exercise, blood glucose increased significantly in INS from 5.6 ± 0.1 at 0 min to 6.3 ± 0.3 mmol/l at 30 min (P < 0 01), which was accompanied by a lower blood lactate response (P < 0 05). Oxygen uptake, rates of substrate utilization, heart rate, and ratings of perceived exertion were not different between trials. Insulin-induced normoglycaemia increased blood glucose during subsequent exercise without altering overall substrate utilization

A comparison of two different software packages for the analysis of body composition using computed tomography images

Objectives: Body composition analysis from computed tomography (CT) imaging has become widespread. However, the methodology used is far from established. Two main software packages are in common usage for body composition analysis, with results used interchangeably. However, the equivalence of these has not been well established. The aim of this study was to compare the results of body composition analysis performed using the two software packages to assess their equivalence. Methods: Tri-phasic abdominal CT scans from 50 patients were analysed for a range of body composition measures at the third vertebral level using OsiriX (v7.5.1, Pixmeo, Switzerland) and SliceOmatic (v5.0, TomoVision, Montreal, Canada) software packages. Measures analysed were skeletal muscle index (SMI), fat mass (FM), fat free mass (FFM) and mean skeletal muscle Hounsfield Units (SMHU). Results: The overall mean SMI calculated using the two software packages was significantly different (SliceOmatic 51.33 vs. OsiriX 53.77, p<0.0001), and this difference remained significant for non-contrast and arterial scans. When FM and FFM were considered, again the results were significantly different (SliceOmatic 33.7kg vs. OsiriX 33.1kg, p<0.0001; SliceOmatic 52.1kg vs. OsiriX 54.2kg, p<0.0001, respectively), and this difference remained for all phases of CT. Finally, when mean SMHU was analysed, this was also significantly different (SliceOmatic 32.7 HU vs. OsiriX 33.1 HU, p=0.046). Conclusions: All four body composition measures were statistically significantly different by the software package used for analysis, however the clinical significance of these differences is doubtful. Nevertheless, the same software package should be utilised if serial measurements are being performed