Effects of an acute α-lactalbumin manipulation on mood and food hedonics in high- and low-trait anxiety individuals

Serotonergic hypofunction is associated with a depressive mood state, an increased drive to eat and preference for sweet (SW) foods. High-trait anxiety individuals are characterised by a functional shortage of serotonin during stress, which in turn increases their susceptibility to experience a negative mood and an increased drive for SW foods. The present study examined whether an acute dietary manipulation, intended to increase circulating serotonin levels, alleviated the detrimental effects of a stress-inducing task on subjective appetite and mood sensations, and preference for SW foods in high-trait anxiety individuals. Thirteen high- (eleven females and two males; anxiety scores 45·5 (sd 5·9); BMI 22·9 (sd 3·0)kg/m2) and twelve low- (ten females and two males; anxiety scores 30·4 (sd 4·8); BMI 23·4 (sd 2·5) kg/m2) trait anxiety individuals participated in a placebo-controlled, two-way crossover design. Participants were provided with 40 g α-lactalbumin (LAC; l-tryptophan (Trp):large neutral amino acids (LNAA) ratio of 7·6) and 40 g casein (placebo) (Trp:LNAA ratio of 4·0) in the form of a snack and lunch on two test days. On both the test days, participants completed a stress-inducing task 2 h after the lunch. Mood and appetite were assessed using visual analogue scales. Changes in food hedonics for different taste and nutrient combinations were assessed using a computer task. The results demonstrated that the LAC manipulation did not exert any immediate effects on mood or appetite. However, LAC did have an effect on food hedonics in individuals with high-trait anxiety after acute stress. These individuals expressed a lower liking (P = 0·012) and SW food preference (P = 0·014) after the stressful task when supplemented with LAC.

Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences

Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ``best practices'' for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science.

Analysis for the use of cumulative plots for travel time estimation on signalized network

This paper provides fundamental understanding for the use of cumulative plots for travel time estimation on signalized urban networks. Analytical modeling is performed to generate cumulative plots based on the availability of data: a) Case-D, for detector data only; b) Case-DS, for detector data and signal timings; and c) Case-DSS, for detector data, signal timings and saturation flow rate. The empirical study and sensitivity analysis based on simulation experiments have observed the consistency in performance for Case-DS and Case-DSS, whereas, for Case-D the performance is inconsistent. Case-D is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

Continuous intravenous infusion of glucose induces endogenous hyperinsulinaemia and lamellar histopathology in Standardbred horses

Endocrinopathic laminitis is frequently associated with hyperinsulinaemia but the role of glucose in the pathogenesis of the disease has not been fully investigated. This study aimed to determine the endogenous insulin response to a quantity of glucose equivalent to that administered during a laminitis-inducing, euglycaemic, hyperinsulinaemic clamp, over 48. h in insulin-sensitive Standardbred racehorses. In addition, the study investigated whether glucose infusion, in the absence of exogenous insulin administration, would result in the development of clinical and histopathological evidence of laminitis. Glucose (50% dextrose) was infused intravenously at a rate of 0.68 mL/kg/h for 48. h in treated horses (n = 4) and control horses (n = 3) received a balanced electrolyte solution (0.68 mL/kg/h). Lamellar histology was examined at the conclusion of the experiment. Horses in the treatment group were insulin sensitive (M value 0.039 ± 0.0012. mmol/kg/min and M-to-I ratio (100×) 0.014 ± 0.002) as determined by an approximated hyperglycaemic clamp. Treated horses developed glycosuria, hyperglycaemia (10.7 ± 0.78. mmol/L) and hyperinsulinaemia (208 ± 26.1. μIU/mL), whereas control horses did not. None of the horses became lame as a consequence of the experiment but all of the treated horses developed histopathological evidence of laminitis in at least one foot. Combined with earlier studies, the results showed that laminitis may be induced by either insulin alone or a combination of insulin and glucose, but that it is unlikely to be due to a glucose overload mechanism. Based on the histopathological data, the potential threshold for insulin toxicity (i.e. laminitis) in horses may be at or below a serum concentration of ∼200. μIU/mL.

Standard preanalytical coding for biospecimens: Review and implementation of the Sample PREanalytical Code (SPREC)

The first version of the Standard PREanalytical Code (SPREC) was developed in 2009 by the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group to facilitate documentation and communication of the most important preanalytical quality parameters of different types of biospecimens used for research. This same Working Group has now updated the SPREC to version 2.0, presented here, so that it contains more options to allow for recent technological developments. Existing elements have been fine tuned. An interface to the Biospecimen Reporting for Improved Study Quality (BRISQ) has been defined, and informatics solutions for SPREC implementation have been developed. A glossary with SPRECrelated definitions has also been added.