Glycemic index, glycemic load, and risk of digestive tract neoplasms: a systematic review and meta-analysis

Background: Habitual consumption of diets with a high glycemic index (GI) and a high glycemic load (GL) may influence cancer risk via hyperinsulinemia and the insulin-like growth factor axis.
Objective: The objective was to conduct a systematic review to assess the association between GI, GL, and risk of digestive tract cancers.
Design: Medline and Embase were searched for relevant publications from inception to July 2008. When possible, adjusted results from a comparison of cancer risk of the highest compared with the lowest category of GI and GL intake were combined by using random-effects meta-analyses.
Results: Cohort and case-control studies that examined the risk between GI or GL intake and colorectal cancer (n = 12) and adenomas (n = 2), pancreatic cancer (n = 6), gastric cancer (n = 2), and squamous-cell esophageal carcinoma (n = 1) were retrieved. Most case-control studies observed positive associations between GI and GL intake and these cancers. However, pooled cohort study results showed no associations between colorectal cancer risk and GI intake [relative risk (RR): 1.04; 95% CI: 0.92, 1.12; n = 7 studies] or GL intake (RR: 1.06; 95% CI: 0.95, 1.17; n = 8 studies). Furthermore, no significant associations were observed in meta-analyses of cohort study results of colorectal cancer subsites and GI and GL intake. Similarly, no significant associations emerged between pancreatic cancer risk and GI intake (RR: 0.99; 95% CI: 0.83, 1.19; n = 5 studies) or GL intake (RR: 1.01; 95% CI: 0.86, 1.19; n = 6 studies) in combined cohort studies.
Conclusions: The findings from our meta-analyses indicate that GI and GL intakes are not associated with risk of colorectal or pancreatic cancers. There were insufficient data available regarding other digestive tract cancers to make any conclusions about GI or GL intake and risk.

A new method of measuring plastic limit of fine materials

Index properties such as the liquid limit and plastic limit are widely used to evaluate certain geotechnical parameters of fine-grained soils. Measurement of the liquid limit is a mechanical process, and the possibility of errors occurring during measurement is not significant. However, this is not the case for plastic limit testing, despite the fact that the current method of measurement is embraced by many standards around the world. The method in question relies on a fairly crude procedure known widely as the ‘thread rolling' test, though it has been the subject of much criticism in recent years. It is essential that a new, more reliable method of measuring the plastic limit is developed using a mechanical process that is both consistent and easily reproducible. The work reported in this paper concerns the development of a new device to measure the plastic limit, based on the existing falling cone apparatus. The force required for the test is equivalent to the application of a 54 N fast-static load acting on the existing cone used in liquid limit measurements. The test is complete when the relevant water content of the soil specimen allows the cone to achieve a penetration of 20 mm. The new technique was used to measure the plastic limit of 16 different clays from around the world. The plastic limit measured using the new method identified reasonably well the water content at which the soil phase changes from the plastic to the semi-solid state. Further evaluation was undertaken by conducting plastic limit tests using the new method on selected samples and comparing the results with values reported by local site investigation laboratories. Again, reasonable agreement was found.

Do dynamic work instructions provide an advantage over static instructions in a small scale assembly task?

Recent studies exploring the effects of instructional animations on learning compared to static graphics have yielded mixed results. Few studies have explored their effectiveness in portraying procedural-motor information. Opportunities exist within an applied (manufacturing) context for instructional animations to be used to facilitate build performance on an assembly line. The present study compares build time performance across successive builds when using animation, static diagrams or text instructions to convey an assembly sequence for a handheld device. Although an immediate facilitating effect of animation was found, yielding a significantly faster build time for Build 1, this advantage had disappeared by Build 3. (C) 2009 Elsevier Ltd. All rights reserved.

Influence of social status on the welfare of sows in static and dynamic groups

Forty-eight Large White x Landrace multiparous sows were mixed into twelve groups of four animals after their piglets were weaned. These groups were defined as static, with no animals being added to or removed from the groups after their formation. Aggressive and submissive behaviours were recorded continuously for 9 h after the sows were mixed, and the sows were assigned high or low social status on the basis of their relative aggressiveness and success in aggressive interactions. After five weeks, each static group was mixed into a dynamic group of 40+/-2 sows for an 11-week period. Three static groups (ie 12 animals) at a time were added to the dynamic group at three-week intervals; the same number of animals was removed at these time-points in order to maintain the group number at 40+/-2. Injury levels increased significantly with the transition from static groups to the dynamic group (P

NADPH oxidase-4 mediates protection against chronic load-induced stress in mouse hearts by enhancing angiogenesis

Cardiac failure occurs when the heart fails to adapt to chronic stresses. Reactive oxygen species (ROS)-dependent signaling is implicated in cardiac stress responses but the role of different ROS sources remains unclear. Here, we report that NADPH oxidase-4 (Nox4) facilitates cardiac adaptation to chronic stress. Unlike other Nox proteins, Nox4 activity is regulated mainly by its expression level which increased in cardiomyocytes during stresses such as pressure overload or hypoxia. To investigate the functional role of Nox4 during the cardiac response to stress, we generated mice with a genetic deletion of Nox4 or a cardiomyocyte-targeted overexpression of Nox4. Basal cardiac function was normal in both models but Nox4-null animals developed exaggerated contractile dysfunction, hypertrophy and cardiac dilatation during exposure to chronic overload whereas Nox4-transgenic mice were protected. Investigation of mechanisms underlying this protective effect revealed a significant Nox4-dependent preservation of myocardial capillary density after pressure overload. Nox4 enhanced stress-induced activation of cardiomyocyte Hif1 and the release of VEGF, resulting in an increased paracrine angiogenic activity. These data indicate that cardiomyocyte Nox4 is a novel inducible regulator of myocardial angiogenesis, a key determinant of cardiac adaptation to overload stress. Our results also have wider relevance to the use of non-specific antioxidant approaches in cardiac disease and may provide an explanation for the failure of such strategies in many settings.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.