Blood chemistry changes in food-deprived herring gulls

Blood chemistry changes caused by food-stress was measured in fledgling herring gulls (Larus argentatus). Increases of corticosterone, T3, free fatty acids, glucose, cholesterol and alpha-amino n-butyric acid were observed. Significant decreases were found in the concentrations of 14 of the 26 free amino acids studied.     

Nitrite poisoning in herring gulls (Larus argentatus) and ring-billed gulls (Larus delawarensis)

Landfill disposal of a fertilizer manufacturing waste product was associated with a die-off of gulls in New Hanover County, North Carolina. An estimated 250 herring and ring-billed gulls were found dead at the site following the initial disposal of this material. Chemical analyses revealed that the fertilizer waste contained predominately calcium (12.0 to 22.2%) and nitrite (3.0 to 15.2%). Contents of the proventriculi and gizzards of dead gulls also contained calcium (3.0 to 10.9%) and nitrite (1,730 ppm). Fertilizer waste administered orally to 16-day-old domestic turkeys resulted in acute, progressive signs of depression, respiratory distress, pallor, convulsions and death. The mean percentage methemoglobin in blood from convulsing turkeys (90.6) was significantly increased from that of normal control turkeys (3.6). The ante-mortem signs and increased blood methemoglobin concentrations in the experimental turkeys support the conclusion that the toxic principle in the fertilizer waste was nitrite, and that nitrite poisoning was the cause of the die-off of gulls.     

Manipulating daytime sleep in herring gulls (Larus argentatus)

The regular provision of a sufficient quantity of food on the territory of pairs of breeding herring gulls led to an increase in the time individuals spent on the territory during the day, relative to controls. This ‘extra’ time was not used to increase overall sleeping time, as predicted. Instead, the experimental gulls reduced their overall sleep time due to a decline in front-sleep. Back-sleep remained relatively unaffected, with both groups spending similar amounts of time in this posture. The consequences of the two postural types of sleep were examined with respect to the cost of allowing intruders to remain on an owner's territory. Intruders arrived more often on control territories and stayed longer when only one pair member was present. Intruders were seen on control territories for more consecutive scans when the solitary control gull was in a sleep posture, particularly front-sleep. It is concluded that these results imply a difference in the consequences resulting from the two sleep postures and give additional support for the multiple function hypothesis of sleep.     

Optimal learning rules for familiarity detection

It has been suggested that the mammalian memory system has both familiarity and recollection components. Recently, a high-capacity network to store familiarity has been proposed. Here we derive analytically the optimal learning rule for such a familiarity memory using a signal- to-noise ratio analysis. We find that in the limit of large networks the covariance rule, known to be the optimal local, linear learning rule for pattern association, is also the optimal learning rule for familiarity discrimination. In the limit of large networks, the capacity is independent of the sparseness of the patterns and the corresponding information capacity is 0.057 bits per synapse, which is somewhat less than typically found for associative networks.     

Induced minisatellite germline mutations in herring gulls (Larus argentatus) living near steel mills

Despite widespread industrial release of genotoxic contaminants, little is understood of their role in inducing germline mutations in natural populations. We used multilocus DNA fingerprinting to quantify germline minisatellite mutations in families of herring gulls (Larus argentatus) in three nesting categories: (a) near cities with large steel mills operating coking ovens; (b) near cities without steel mills; and (c) in rural locations removed from point sources of contamination. Gulls nesting near integrated steel mills showed significantly higher mutation rates than gulls from rural locations (Fisher's exact, P=0.0004); urban sites without steel mills fell midway between steel and rural sites (difference from rural; Fisher's exact, P=0.19). Distance of the nesting location of herring gulls from the steel industries' coking ovens was negatively correlated with minisatellite mutation rate demonstrating significant risk for induced germline mutations in cities with steel operations (Kendall Tau; tau=0.119; P<0.0001).     

The influence of fasting on blood and plasma composition of herring gulls (Larus argentatus).

Populations of scavenging seabird species in the North Sea may fluctuate with an artificial food source: the availability of fishery waste. To document this impact, it is necessary to assess the birds' nutritional status during periods with decreased fishing activity. Reference data for this purpose was collected from 22 herring gulls investigated during laboratory fasting. After 6 d of food deprivation and body mass losses exceeding 15%, the first birds entered starvation phase 3. Comparatively, this is a rather weak fasting capacity. Plasma levels of total protein and thyroid hormones decreased and beta-hydroxybutyrate increased with fasting duration. The leucocyte proportions were shifted from lymphocytes to heterophils. After 3 d of refeeding, most of the fasting changes were reversed. Plasma enzyme activities increased and hematocrit, hemoglobin, and erythrocyte numbers decreased in both fasting and control birds, most likely as a result of experimental stress and repeated blood sampling. Glucose, cholesterol, monocytes, basophils, and glycosylated hemoglobin remained fairly constant. Triglycerides, free fatty acids, uric acid, and urea varied significantly, but changes were not as clearly a result of fasting. Therefore, total protein, beta-hydroxybutyrate, triiodothyronine, thyroxine, and lymphocyte and heterophil percentages may be the most reliable indicators of the nutritional status and the condition of free-living herring gulls.     

An outbreak of type C botulism in herring gulls (Larus argentatus) in southeastern Sweden

From 2000 to 2004, over 10,000 seabirds, primarily Herring Gulls (Larus argentatus), died from an undetermined cause in the Blekinge archipelago in southeastern Sweden. In June 2004, 24 affected Herring Gulls were examined clinically, killed humanely, and 23 were examined by necropsy. Seven and 10 unaffected Herring Gulls collected from a local landfill site and from Iceland, respectively, served as controls. All affected birds showed similar neurologic signs, ranging from mild incoordination and weakness to severe flaccid paralysis of legs and wings, but generally were alert and responsive. All affected gulls were in normal nutritional condition, but were dehydrated and had empty stomachs. No gross or microscopic lesions, and no bacterial or viral pathogens were identified. Type C botulinum toxin was detected in the sera of 11 of 16 (69%) affected gulls by mouse inoculation. Type C botulism was the proximate cause of disease in 2004. Sera from 31% of birds tested from outbreaks in 2000 to 2003 also had detectable type C botulinum toxin by mouse inoculation. No large-scale botulism outbreak has been documented previously in this area. The source of toxin, initiating conditions, and thus, the ultimate cause of this outbreak are not known. This epidemic might signal environmental change in the Baltic Sea.     

Simple decision rules for classifying human cancers from gene expression profiles

MOTIVATION: Various studies have shown that cancer tissue samples can be successfully detected and classified by their gene expression patterns using machine learning approaches. One of the challenges in applying these techniques for classifying gene expression data is to extract accurate, readily interpretable rules providing biological insight as to how classification is performed. Current methods generate classifiers that are accurate but difficult to interpret. This is the trade-off between credibility and comprehensibility of the classifiers. Here, we introduce a new classifier in order to address these problems. It is referred to as k-TSP (k-Top Scoring Pairs) and is based on the concept of 'relative expression reversals'. This method generates simple and accurate decision rules that only involve a small number of gene-to-gene expression comparisons, thereby facilitating follow-up studies. RESULTS: In this study, we have compared our approach to other machine learning techniques for class prediction in 19 binary and multi-class gene expression datasets involving human cancers. The k-TSP classifier performs as efficiently as Prediction Analysis of Microarray and support vector machine, and outperforms other learning methods (decision trees, k-nearest neighbour and na?ve Bayes). Our approach is easy to interpret as the classifier involves only a small number of informative genes. For these reasons, we consider the k-TSP method to be a useful tool for cancer classification from microarray gene expression data. AVAILABILITY: The software and datasets are available at http://www.ccbm.jhu.edu CONTACT: actan@jhu.edu.     

Data linkage using probabilistic decision rules: a primer

Electronic data linkage is increasingly being used by researchers and health professionals in the birth defects field as a tool for enhancing both research and service/care. However, in many cases, a common pre-existing ID number does not exist across different datasets, and common identifiers, such as names or dates of birth, which could be used to match records, may be known to contain errors or even legitimate differences over time. In such situations, probabilistic matching, which does not require that all identifying fields exactly agree in order for one to conclude that two records belong to the same individual, can be a valuable tool for improving data linkage. However, probabilistic matching is computationally complex and demanding, and not well understood by many who may wish to apply it in their work. Therefore, the purpose of this article is to provide an overview of one approach to probabilistic matching, including the step-by-step procedures involved in the calculation of indices corresponding to the likelihood that two records are a correct match. In addition, the use of multiple iterative protocols, in which several different matching strategies are used in order to maximize the number of linked records, is discussed. Finally, issues related to deduplication and verification of internal-consistency in the linked data set are also reviewed.     

Statistical decision rules concerning synteny or independence between markers

Data on the segregation of human markers in somatic hybrids between permanent rodent cell lines and primary human cells were gathered and statistically analyzed, using various criteria of association. The analysis provides evidence that human chromosomes do not segregate independently in somatic cell hybrids. A statistical decision rule concerning synteny or independence between markers is proposed, and its utility in developing the gene maps of other species by means of somatic cell hybridization is explored.     

Applying voting rules to panel-based decision making in LCA

Background, aim, and scope  Cross-category weighting is one possible way to facilitate internal decision making when dealing with ambiguous impact assessment results, with simple additive weighting being a commonly used method. Yet, the question as to whether the methods applied today can, in fact, identify the most “environmentally friendly” alternative from a group perspective remains unanswered. The aim of this paper is to propose a new method for group decision making that ensures the effective identification of the most preferable alternative. Materials and methods  Common approaches to deduce a single set of weighting factors for application in a group decision situation (e.g., arithmetic mean, consensus) are discussed based on simple mathematics, empirical data, and thought experiments. After proposing an extended definition for “effectiveness” in group decision making, the paper recommends the use of social choice theory whose main focus is to identify the most preferable alternative based on individuals’ rankings of alternatives. The procedure is further supplemented by a Monte Carlo analysis to facilitate the assessment of the result’s robustness. Results  The general feasibility of the method is demonstrated. It generates a complete ranking of alternatives, which does not contain cardinal single scores. In terms of effectiveness, the mathematical structure of the procedure ensures the eligibility for compromise of the group decision proposal. The sensitivity analysis supports the decision makers in understanding the robustness of the proposed group ranking. Discussion  The method is based upon an extended definition of effectiveness which acknowledges the eligibility for compromise as the core requirement in group decision contexts. It is shown that multi-attribute decision-making (MADM) methods in use in life cycle assessment (LCA) today do not necessarily meet this requirement because of their mathematical structure. Further research should focus on empirical proof that the generated group results are indeed more eligible for compromise than results generated by current methods that utilize an averaged group weighting set. This is closely related to the question considering under which mathematical constraints it is even possible to generate an essentially different result. Conclusions  The paper describes a new multi-attribute group decision support system (MGDSS) for the identification of the most preferable alternative(s) for use in panel-based LCA studies. The main novelty is that it refrains from deducing a single set of weighting factors which is supposed to represent the panel as a whole. Instead, it applies voting rules that stem from social choice theory. Because of its mathematical structure, the procedure is deemed superior to common approaches in terms of its effectiveness. Recommendations and perspectives  The described method may be recommended for use in internal, panel-based LCA studies. In addition, the basic approach of the method—the combination of MADM methods with social choice theory—can be recommended for use in all those situations where multi-attribute decisions are to be made in a group context.     

A nondestructive method for obtaining maternal DNA from avian eggshells and its application to embryonic viability determination in herring gulls (Larus argentatus)

Many avian studies, aimed at collecting samples for genetic analysis, rely upon invasive procedures involving the capture and handling of parents and their offspring. Our goal was to develop a nondestructive method for sampling maternal DNA that would not require blood collection from the mother. Herein, we describe a method for isolating genomic DNA from eggshell powder, obtained by filing the outer shell of an avian egg. Comparison of microsatellite profiles, obtained from genomic DNA found within eggshell matrices and their corresponding parents, verified the presence of maternal DNA in the eggshell matrix in 100% of the herring gull nests assessed (n= 11). In addition, the microsatellite profiles of eggshell DNA were identical among eggs from the same clutch. The ability to rapidly obtain a DNA sample from an avian eggshell in a noninvasive manner could aid in a wide range of genetic sampling studies, and in this study, we provide one potential application of this finding: assessing the fertilization status of nonviable herring gull (Larus argentatus) eggs from the Laurentian Great Lakes. Detection of fertilization was successful as the microsatellite profiles of eggshell powder (maternal only) and the fertilized embryonic contents of those eggs did not match. Ideally, the application of such an approach will help to discriminate unfertilized eggs from embryos aborted early in development and provide insights into avian reproductive health.