Methodological Bias in Estimates of Strain Composition and Straying of Hatchery‐Produced Steelhead in Lake Michigan Tributaries

Steelhead Oncorhynchus mykiss were first introduced into the Great Lakes in the late 1800s. Subsequently, natural recruitment of steelhead from spawning runs in streams across the basin has been regularly supplemented by hatchery production of strains derived from widely dispersed locales within the species’ native range. Estimates of hatchery contributions to the spawning runs of naturalized populations may be underrepresented by observations of marked fish, as not all hatchery fish are marked prior to release. To assess the potential bias in estimates of the hatchery contribution to steelhead spawning runs in four major rivers in Michigan, we used scale pattern analysis (SPA) to identify nonmarked hatchery fish and multilocus genotypes to estimate the proportional contributions of each hatchery strain to spawning runs. The four hatchery strains currently stocked are significantly genetically distinct (mean FST = 0.077), making it possible to identify specific strains by use of likelihood‐based assignment tests. The differences between direct (mark observations) and indirect (SPA and genetic analysis) estimates of hatchery contribution were mainly due to variations in the percentage of hatchery fish marked by states prior to release and the potential for confusion between certain marks and injuries. By combining direct and indirect assessment methodologies, we estimated that the percentage of hatchery fish returning to the four rivers ranged from 13% to 31% of total spawning runs. The large contribution of hatchery fish to nonstocked rivers differed significantly from expectations of strain‐specific stocking rates across the Lake Michigan basin and for individual streams, indicating high amounts of straying into Michigan streams.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141020/1/nafm1288.pd

Ecosystem Modeling of College Drinking: Parameter Estimation and Comparing Models to Data

Recently we developed a model composed of five impulsive differential equations that describes the changes in drinking patterns (that persist at epidemic level) amongst college students. Many of the model parameters cannot be measured directly from data; thus, an inverse problem approach, which chooses the set of parameters that results in the “best” model to data fit, is crucial for using this model as a predictive tool. The purpose of this paper is to present the procedure and results of an unconventional approach to parameter estimation that we developed after more common approaches were unsuccessful for our specific problem. The results show that our model provides a good fit to survey data for 32 campuses. Using these parameter estimates, we examined the effect of two hypothetical intervention policies: 1) reducing environmental wetness, and 2) penalizing students who are caught drinking. The results suggest that reducing campus wetness may be a very effective way of reducing heavy episodic (binge) drinking on a college campus, while a policy that penalizes students who drink is not nearly as effective

Infections in recipients of liver homografts.

Seventeen patients received liver homografts between 1963 and May, 1968. The eight treated before July, 1967, died within 34 days; seven had progressive infections with gram-negative bacilli, Candida albicans and cytomegalovirus. The infections were similar to but more fulminating than those after renal homotransplantation. In nine later cases, there was more discriminating donor selection, improved immunosuppression, and better organ preservation. In the first five of these nine patients, all infants, lobar hepatic gangrene apparently secondary to delayed right hepatic arterial thrombosis developed. Two died within a few days, two and three and a half months after transplantation. The three who did not die immediately subsequently had multiple bacteremias, fungemias and cytomegalovirus pulmonary infections. One of these children is alive twelve months after transplantation; the others died after four and a half and six months. In contrast, the last four patients, in whom septic liver infarctions were avoided, have been free of serious infections for two to five and a half months

Metabolic effects of diets differing in glycaemic index depend on age and endogenous GIP

Aims/hypothesis High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling. Methods Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr −/− ) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20–26 weeks of intervention, n = 8–10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake. Results Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, p < 0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (p < 0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr −/− vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity. Conclusions/interpretation The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial

Heavy episodic drinking on college campuses: Does changing the legal drinking age make a difference

ABSTRACT. Objective: This article extends the compartmental model previously developed by Scribner et al. in the context of college drinking to a mathematical model of the consequences of lowering the legal drinking age. Method: Using data available from 32 U.S. campuses, the analyses separate underage and legal age drinking groups into an eight-compartment model with different alcohol availability (wetness) for the underage and legal age groups. The model evaluates the likelihood that underage students will incorrectly perceive normative drinking levels to be higher than they actually are (i.e., misperception) and adjust their drinking accordingly by varying the interaction between underage students in social and heavy episodic drinking compartments. Results: The results evaluate the total heavy episodic drinker population and its dependence on the difference in misperception, as well as its dependence on underage wetness, legal age wetness, and drinking age. Conclusions: Results suggest that an unrealistically extreme combination of high wetness and low enforcement would be needed for the policies related to lowering the drinking age to be effective. (J. Stud. Alcohol Drugs, 72