Clinostomum marginatum metacercaria: Incidence in Smallmouth Bass from a North Arkansas Stream and in vitro Oxygen Consumption Studies

Small mouth bass (Micropterus dolomieui) captured from Crooked Creek (Marion Co., Arkansas) in the summers of 1977 and 1987 were found to have a high incidence of infection with the metacercaria of Clinostomum marginatum (yellow grub). Of 41 fish collected in 1977, 32 (78%) were found infected with metacercariae with some fish containing large numbers of parasites. The number of larvae per fish ranged from 1 to 184, with an average of 23.2 ± 38 per smallmouth. Eighty-six percent of the bass collected in 1987 were found positive for C. marginatum. The number of metacercariae per fish ranged from 1 to 227 with an average of 32.7 ± 54 per fish. Fish from both collection groups ranged in size from 12 to 34 cm. No significant correlation could be found between the number of metacercariae per fish and the length of the host. Using metacercariae removed from host tissue, the effect on oxygen consumption by glucose, serotonin and insulin, singularly or in combination, was measured by manometric methods. Glucose alone did not stimulate oxygen utilization, serotonin alone and with glucose was stimulatory, and insulin with glucose also increased oxygen consumption

Clinostomum marginatum (Yellow Grub) Metacercaris in Black Bass From the Caddo River in West Arkansas

Seventy-two bass (Micropterus-spp.), mostly smallmouth, were collected from three areas of the Caddo River in west Arkansas and examined for the presence of Clinostomum marginatum metacercariae. Prevalence, mean abundance, and abundance for all fish were 68%, and 4.2 ±6.5, and 30, respectively. Fish from the upstream area near the headwaters were more heavily infested than those from further downstream. A gill/total body larval ratio of seven, was found for bass from another Arkansas stream, was examined as a predictor for total Clinostomum populations instream bass. Using the formula gill parasites X seven divided by N(72), a value of 3.3 was found for mean abundance. The gill/total body ratio for Caddo bass was found to be higher at 8.9 but the ratio of 7 gives a reasonable estimate of Clinostomum burdens in a stream bass population. Use of this ratio allows bass hosts to be examined without necropsy thus preserving the host population in its environment

Does pride really come before a fall? Longitudinal analysis of older English adults

OBJECTIVE: To test whether high levels of reported pride are associated with subsequent falls. DESIGN: Secondary analysis of the English Longitudinal Study of Ageing (ELSA) dataset. SETTING: Multi-wave longitudinal sample of non-institutionalised older English adults. PARTICIPANTS: ELSA cohort of 6415 participants at wave 5 (baseline, 2010/11), of whom 4964 were available for follow-up at wave 7 (follow-up, 2014/15). MAIN OUTCOME MEASURES: Self reported pride at baseline (low/moderate/high) and whether the participant had reported having fallen during the two years before follow-up. RESULTS: The findings did not support the contention that "pride comes before a fall." Unadjusted estimates indicate that the odds of reported falls were significantly lower for people with high pride levels compared with those who had low pride (odds ratio 0.69, 95% confidence interval 0.58 to 0.81, P < 0.001). This association remained after adjustment for age, sex, household wealth, and history of falls (odds ratio 0.81, 0.68 to 0.97, P < 0.05). It was partially attenuated after further adjustment for mobility problems, eyesight problems, the presence of a limiting long term illness, a diagnosis of arthritis or osteoporosis, medication use, cognitive function, and pain and depression (odds ratio 0.86, 0.72 to 1.03, P < 0.1). Because the confidence interval exceeded 1 in the final model, it remains possible that pride may not be an independent predictor of falls when known risk factors are considered. People with moderate pride did not have lower odds of having fallen than those with low pride in adjusted models. Participants lost to follow-up did not differ from those retained in terms of key variables, and weighting the analyses to account for selective attrition did not produce different results. CONCLUSIONS: Contrary to the well known saying "pride comes before a fall," these findings suggest that pride may actually be a protective factor against falling in older adults. Future studies may seek to investigate the mechanisms underpinning this relation

Microstructural strain memory and associated plasticity in superelastic niti under low cycle fatigue

When cyclically loaded in tension, superelastic Nickel Titanium (NiTi) undergoes a characteristic shakedown behavior which dramatically changes its hysteretic stress–strain response. As many uses of superelastic NiTi involve cyclic loading, a detailed understanding of the interaction between phase transformation and associated plasticity is necessary to predict the lifetime behavior of NiTi devices. Earlier macroscopic studies have dealt with this phenomenon on a bulk material level, but its microstructural origin and small scale analogues remain largely uninvestigated. To that end, low cycle, low strain-rate fatigue tests were performed on superelastic NiTi sheet to examine the local damage and accumulation of plastic deformation that contribute to the evolution of its stress strain response. Local strain measured in situ with Scanning Electron Microscopy Digital Image Correlation was matched with individual microstructural features – such as individual parent grains and grain neighborhoods – measured with Electron Backscatter Diffraction. Martensitic transformation associated with superelasticity was inferred from the full-field strain maps captured each load cycle. Special attention was paid to the particular martensite variants and twinning modes that nucleate in the first cycle and their similitude to subsequent martensite transformation. In addition, cyclic behavior such as martensite retention and ratcheting, strain memory of both martensite and austenite configurations, and damage accumulation are also considered

A Discriminant Analysis Model of Alaskan Biomes Based on Spatial Climatic and Environmental Data

Classification of high-latitude landscapes into their appropriate biomes is important for many climate and global change-related issues. Unfortunately, large-scale, high-spatial-resolution observations of plant assemblages associated with these regions are generally unavailable, so accurate modeling of plant assemblages and biome boundaries is often needed. We built different discriminant analysis models and used them to “convert” various combinations of spatial climatic data (surface temperature and precipitation) and spatial environmental data (topography, soil, permafrost) into a biome-level map of Alaska. Five biomes (alpine tundra and ice fi elds, Arctic tundra, shrublands, boreal forest, and coastal rainforest) and one biome transition zone are modeled. Mean annual values of climatic variables were less useful than their annual extrema in this context. A quadratic discriminant analysis, combined with climate, topography, permafrost, and soil information, produced the most accurate Alaskan biome classification (skill = 74% when compared to independent data). The multivariate alteration detection transformation was used to identify Climatic Transition Zones (CTZs) with large interannual variability, and hence, less climatic consistency than other parts of Alaska. Biome classification was the least accurate in the CTZs, leading to the conclusion that large interannual climatic variability does not favor a unique biome. We interpret the CTZs as “transition biome areas” or ecotones between the five “core biomes” cited above. Both disturbance events (e.g., fires and subsequent plant succession sequences) and the partial intersection of the environmental variables used to characterize Alaskan biomes further complicate biome classification. Alaskan results obtained from the data-driven quadratic discriminant model compare favorably (based on Kappa statistics) with those produced by an equilibrium-based biome model for regions of Canada ecologically similar to the biomes we studied in Alaska. Climatic statistics are provided for each biome studied. Le classement des paysages de hautes latitudes dans les biomes adéquats revêt de l'importance dans le cadre de nombreux enjeux relatifs aux changements climatiques et à d'autres changements d'envergure mondiale. Malheureusement et en règle générale, il n'existe pas d'observations spatiales de haute résolution et à grande échelle pour ce qui est des assemblages de végétaux pour ces régions. C'est pourquoi il faut souvent procéder à la modélisation des assemblages de végétaux et des limites des biomes. Nous avons élaboré différents modèles d'analyses discriminantes dont nous nous sommes servis pour « transformer » divers ensembles de données climatiques spatiales (température de la surface et précipitation) et diverses données sur l'environnement spatial (topographie, sol, pergélisol) en carte des biomes de l'Alaska. La modélisation porte sur cinq biomes (toundra alpine et champs de glace, toundra arctique, arbustaie, forêt boréale et forêt pluviale côtière) et sur une zone de transition de biome. Les valeurs moyennes annuelles des variables climatiques ont été moins utiles que leurs extremas annuels dans ce contexte. Une analyse discriminante quadratique, combinée aux données relatives au climat, à la topographie, au pergélisol et au sol, a permis d'aboutir au classement de biomes alaskiens le plus précis (habileté = 74 % lorsque comparé aux données indépendantes). Nous avons recouru à la transformation de la détection de l'altération à variables multiples (multivariate alteration detection transformation) pour identifi er les zones de transition climatique (ZTC) ayant une importante variabilité interannuelle et, par conséquent, une moins grande uniformité climatique que d'autres parties de l'Alaska. Le classement des biomes était moins précis dans les ZTC, ce qui nous a amenés à conclure que l'importante variabilité climatique interannuelle ne favorise pas un biome unique. Nous interprétons les ZTC comme des « régions de biomes de transition » ou des écotones entre les cinq « biomes principaux » dont il est question ci-dessus. Les deux perturbations (c'est-à-dire les incendies et les séquences subséquentes des végétaux) et l'intersection partielle des variables environnementales utilisées pour caractériser les biomes alaskiens compliquent davantage le classement des biomes. Les résultats alaskiens obtenus à partir du modèle discriminant quadratique dérivant des données se comparent favorablement (en fonction des statistiques kappa) à ceux obtenus par un modèle de biome en équilibre pour des régions du Canada similaires du point de vue écologique aux biomes que nous avons étudiés en Alaska. Des statistiques climatiques sont fournies pour chaque biome étudié