Effect of male age in rainbow trout (Oncorhynchus mykiss) on duration of sperm motility, spermatocrite and eyed egg rate production

Effects of three levels of Rainbow Trout male age (2+, 3+ and 4+ years old), on duration of sperm motility, spermatocrite and eyed egg rate in rainbow trout were studied in Kelardasht Fish Breeding Center. The sperm from 2+ year old males activated by water showed the shortest motility (24.86 sec) (P= 0.007), while those of the 3+ and 4+ years old revealed the longest sperm motility. No significant difference was found between sperm motility of the 3+ and 4+ males. The average spermatocrite in different age groups of male fish was significantly different. This was showed to be 32.66% in 2+ years and 2126 % in 3+ year's male age groups respectively. Eyed egg rate was highest in 2+ years age (86/82%), and was significantly different with the 3+ age group (P=0.02). The eyed egg rate of the 4+ age group was not significantly different with those of the 2+ and 3+ age groups

Comparison of digestive enzyme activity in the stomach, pyloric caeca and intestine in diploid and triploid female of rainbow trout (Oncorhynchus mykiss)

The effects of chromosome manipulation on the digestive enzyme activity in the rainbow trout were studied. The enzymes included Pepsin, Trypsin, Chymotrypsin, cileimylase, Lipase and Alkaline Phosphatase which were assessed in diploid and triploid female of rainbow trout. Pepsin activity in the stomach of the assessed fish showed no significant difference between the diploid and triploid fish (P>0.05). The measurement of Trypsin and Chymotrypsin activity in the intestine and pyloric caeca revealed no significant difference in the treated and untreated fish (P>0.05). The activity of a-Amylase, Lipase and Alkaline Phosphatase showed no significant difference in the intestine and pyloric caeca of the diploid and triploid fish (P>0.05).The results indicated that chromosome manipulation in rainbow trout had no effects on digestive enzyme activity

A Bayesian Approach to Parameter Inference in Queueing Networks

The application of queueing network models to real-world applications often involves the task of estimating the service demand placed by requests at queueing nodes. In this article, we propose a methodology to estimate service demands in closed multiclass queueing networks based on Gibbs sampling. Our methodology requires measurements of the number of jobs at resources and can accept prior probabilities on the demands. Gibbs sampling is challenging to apply to estimation problems for queueing networks since it requires one to efficiently evaluate a likelihood function on the measured data. This likelihood function depends on the equilibrium solution of the network, which is difficult to compute in closed models due to the presence of the normalizing constant of the equilibrium state probabilities. To tackle this obstacle, we define a novel iterative approximation of the normalizing constant and show the improved accuracy of this approach, compared to existing methods, for use in conjunction with Gibbs sampling. We also demonstrate that, as a demand estimation tool, Gibbs sampling outperforms other popular Markov Chain Monte Carlo approximations. Experimental validation based on traces from a cloud application demonstrates the effectiveness of Gibbs sampling for service demand estimation in real-world studies

A novel multiplex assay combining autoantibodies plus PSA has potential implications for classification of prostate cancer from non-malignant cases

<p>Abstract</p> <p>Background</p> <p>The lack of sufficient specificity and sensitivity among conventional cancer biomarkers, such as prostate specific antigen (PSA) for prostate cancer has been widely recognized after several decades of clinical implications. Autoantibodies (autoAb) among others are being extensively investigated as potential substitute markers, but remain elusive. One major obstacle is the lack of a sensitive and multiplex approach for quantifying autoAb against a large panel of clinically relevant tumor-associated antigens (TAA).</p> <p>Methods</p> <p>To circumvent preparation of phage lysates and purification of recombinant proteins, we identified B cell epitopes from a number of previously defined prostate cancer-associated antigens (PCAA). Peptide epitopes from cancer/testis antigen NY-ESO-1, XAGE-1b, SSX-2,4, as well as prostate cancer overexpressed antigen AMACR, p90 autoantigen, and LEDGF were then conjugated with seroMAP microspheres to allow multiplex measurement of autoAb present in serum samples. Moreover, simultaneous quantification of autoAb plus total PSA was achieved in one reaction, and termed the "A+PSA" assay.</p> <p>Results</p> <p>Peptide epitopes from the above 6 PCAA were identified and confirmed that autoAb against these peptide epitopes reacted specifically with the full-length protein. A pilot study was conducted with the A+PSA assay using pre-surgery sera from 131 biopsy-confirmed prostate cancer patients and 121 benign prostatic hyperplasia and/or prostatitis patients. A logistic regression-based A+PSA index was found to enhance sensitivities and specificities over PSA alone in distinguishing prostate cancer from nonmalignant cases. The A+PSA index also reduced false positive rate and improved the area under a receiver operating characteristic curve.</p> <p>Conclusions</p> <p>The A+PSA assay represents a novel platform that integrates autoAb signatures with a conventional cancer biomarker, which may aid in the diagnosis and prognosis of prostate cancer and others.</p

Harmonizing semantic annotations for computational models in biology

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol.Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the Computational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation

Contamination of Zayandeh Rud sediments with some heavy metals and chemical parameters

Background: The Zayandeh Rud, as a main river in the center of Iran, is the most important source of water for irrigation, industrial development and municipal use. The aim of this study was to evaluate the changes in contamination of Zayandeh Rud sediments. Materials and Methods: Samples were taken from the 6 stations along the river. Electrical conductivity, pH, organic matter and concentration of Pb, Cd and Ni were determined in the sediment samples.Results: The results showed a much sharper increase in electrical conductivity from station no.4 (Ejieh) to station no. 6 (Gavkhuni). Also, the sediment pH of Zayandeh Rud was alkaline with a minimum of 7.3 in station no. 2 (Chom) and a maximum of 7.9 in station no. 4. Concentration of Ni and content of organic matter increased from station no. 1 (Siosepol) to station no. 3 (Ziyar). The highest concentration of Pb was 72.1 mg/kg in station no. 2. Conclusion: According to the results of this study, concentration of Pb in urban areas was higher than the downstream. Concentration of Cd was 2 mg/kg in station no. 5 and in another stations was very low. Therefore, the sediments of the river are not contaminated with cadmium