8 resultados para mussel counts
em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain
Resumo:
The effects of exposure to the type species for Karlodinium veneficum (PLY # 103) on immune function and histopathology in the blue mussel Mytilus edulis were investigated. Mussels from Whitsand Bay, Cornwall (UK) were exposed to K. veneficum (PLY # 103) for 3 and 6 days. Assays for immune function included total and differential cells counts, phagocytosis and release of extra cellular reactive oxygen species. Histology was carried out on digestive gland and mantle tissues. The toxin cell quota for K. veneficum (PLY #103) was measured by liquid chromatography-mass spectrometry detecting two separable toxins KvTx1 (11.6 ± 5.4 ng/ml) and KvTx2 (47.7 ± 4.2 ng/ml). There were significant effects of K. veneficum exposure with increasing phagocytosis and release of reactive oxygen species following 6 days exposure. There were no significant effects on total cell counts. However, differential cell counts did show significant effects after 3 days exposure to the toxic alga. All mussels produced faeces but not pseudofaeces indicating that algae were not rejected prior to ingestion. Digestive glands showed ingestion of the algae and hemocyte infiltration after 3 days of exposure, whereas mantle tissue did not show differences between treatments. As the effects of K. veneficum were not observed in the mantle tissue it can be hypothesized that the algal concentration was not high enough, or exposure long enough, to affect all the tissues. Despite being in culture for more than 50 years the original K. veneficum isolate obtained by Mary Parke still showed toxic effects on mussels.
Resumo:
The harmful dinoflagellate Prorocentrum minimum has different effects upon various species of grazing bivalves, and these effects also vary with life-history stage. Possible effects of this dinoflagellate upon mussels have not been reported; therefore, experiments exposing adult blue mussels, Mytilus edulis, to P. minimum were conducted. Mussels were exposed to cultures of toxic P. minimum or benign Rhodomonas sp. in glass aquaria. After a short period of acclimation, samples were collected on day 0 (before the exposure) and after 3, 6, and 9 days of continuous-exposure experiment. Hemolymph was extracted for flow-cytometric analyses of hemocyte, immune-response functions, and soft tissues were excised for histopathology. Mussels responded to P. minimum exposure with diapedesis of hemocytes into the intestine, presumably to isolate P. minimum cells within the gut, thereby minimizing damage to other tissues. This immune response appeared to have been sustained throughout the 9-day exposure period, as circulating hemocytes retained hematological and functional properties. Bacteria proliferated in the intestines of the P. minimum-exposed mussels. Hemocytes within the intestine appeared to be either overwhelmed by the large number of bacteria or fully occupied in the encapsulating response to P. minimum cells; when hemocytes reached the intestine lumina, they underwent apoptosis and bacterial degradation. This experiment demonstrated that M. edulis is affected by ingestion of toxic P. minimum; however, the specific responses observed in the blue mussel differed from those reported for other bivalve species. This finding highlights the need to study effects of HABs on different bivalve species, rather than inferring that results from one species reflect the exposure responses of all bivalves.
Resumo:
Mussels (Mytilus edulis) were exposed to cultures of the toxic dinoflagellate Alexandrium fundyense or the non-toxic alga Rhodomonas sp. to evaluate the effects of the harmful alga on the mussels and to study recovery after discontinuation of the A. fundyense exposure. Mussels were exposed for 9 days to the different algae and then all were fed Rhodomonas sp. for 6 more days. Samples of hemolymph for hemocyte analyses and tissues for histology were collected before the exposure and periodically during exposure and recovery periods. Mussels filtered and ingested both microalgal cultures, producing fecal pellets containing degraded, partially degraded, and intact cells of both algae. Mussels exposed to A. fundyense had an inflammatory response consisting of degranulation and diapedesis of hemocytes into the alimentary canal and, as the exposure continued, hemocyte migration into the connective tissue between the gonadal follicles. Evidence of lipid peroxidation, similar to the detoxification pathway described for various xenobiotics, was found; insoluble lipofuchsin granules formed (ceroidosis), and hemocytes carried the granules to the alimentary canal, thus eliminating putative dinoflagellate toxins in feces. As the number of circulating hemocytes in A. fundyense-exposed mussels became depleted, mussels were immunocompromised, and pathological changes followed, i.e., increased prevalences of ceroidosis and trematodes after 9 days of exposure. Moreover, the total number of pathological changes increased from the beginning of the exposure until the last day (day 9). After 6 days of the exposure, mussels in one of the three tanks exposed to A. fundyense mass spawned; these mussels showed more severe effects of the toxic algae than non-spawning mussels exposed to A. fundyense. No significant differences were found between the two treatments during the recovery period, indicating rapid homeostatic processes in tissues and circulating hemocytes.
Resumo:
The log-ratio methodology makes available powerful tools for analyzing compositionaldata. Nevertheless, the use of this methodology is only possible for those data setswithout null values. Consequently, in those data sets where the zeros are present, aprevious treatment becomes necessary. Last advances in the treatment of compositionalzeros have been centered especially in the zeros of structural nature and in the roundedzeros. These tools do not contemplate the particular case of count compositional datasets with null values. In this work we deal with \count zeros" and we introduce atreatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichletprobability distribution as a prior and we estimate the posterior probabilities. Then weapply a multiplicative modi¯cation for the non-zero values. We present a case studywhere this new methodology is applied.Key words: count data, multiplicative replacement, composition, log-ratio analysis
Resumo:
Nota sobre les conseqüències de la invasió del mol·lusc d'aigua dolça, Anodonta woodiana, a la Península Ibèrica
Resumo:
Background: Several studies have reported alterations in finger and a-b ridge counts, and theirderived measures of asymmetry, in schizophrenia compared to controls. Because ridges are fully formed by the end of the second trimester, they may provide clues to disturbed early development. The aim of this study was to assess these measures in a sample of patients with psychosis and normal controls.Methods: Individuals with psychosis (n = 240), and normal controls (n = 228) were drawn from a catchment-area case-control study. Differences in finger and a-b ridge count and Fluctuating Asymmetry were assessed in three group comparisons (non-affective psychosis versus controls; affective psychosis versus controls; non-affective psychosis versus affective psychosis). The analyses were performed separately for males and females. Results: There were no significant group differences for finger nor a-b ridge counts. While there were no group difference for Directional Asymmetry, for Fluctuating Asymmetry measures men with non-affective psychosis had significantly higher fluctuating asymmetry of the index finger ridge count (a) when compared to controls (FA-correlation score, p = 0.02), and (b) when compared to affective psychosis (adjusted FA-difference score, p = 0.04). Conclusion: Overall, measures of finger and a-b ridge counts, and their derived measures of directional and fluctuating asymmetry were not prominent features of psychosis in this sample. While directional asymmetry in cerebral morphology is reduced in schizophrenia, this is not reflected in dermatoglyphic variables.