Lack of growth enhancement by exogenous growth hormone treatment in yellow perch (Perca flavescens) in four separate experiments

Author Posting. © The Authors, 2005. This is the author's version of the work. It is posted here by permission of Elsevier B. V. for personal use, not for redistribution. The definitive version was published in Aquaculture 250 (2005): 471-479, doi:10.1016/j.aquaculture.2005.03.019.The effect of exogenous growth hormone (GH) treatment on the growth of juvenile yellow perch (Perca flavescens) was investigated in four experiments. In the first two experiments, juvenile yellow perch were reared at either 13°C or 21°C, and injected weekly with bovine GH (bGH) at 0.1, 1.0 or 10.0 μg/g body weight for 84 days. No significant growth enhancement in GH-treated fish was measured in fish in either of the experiments. In the third experiment, juvenile yellow perch were treated with estradiol-17β (E2, 15 μg/g of diet), bGH (1.0 μg/g body weight) injected weekly or both hormones for 70 days at 21°C. E2 alone stimulated growth, but no further growth stimulation occurred in the E2 + bGH-treated fish. In addition, no growth enhancement was found in fish treated with bGH alone. We measured no difference in serum insulin-like growth factor-I (IGF-I) levels between the treatment groups at 12 and 24 h after the final injection of GH; however, a drop in IGF-I levels after 24 h was observed. In a fourth study, the effect of recombinant yellow perch GH (rypGH, 0.2 or 1.0 μg/g body weight) injected weekly was evaluated in yellow perch juveniles. The fish were reared for 42 days at 18°C. Neither GH dosages improved growth compared to control-injected and non-injected fish. Taken together, the lack of effect of mammalian GH or rypGH in our experiments suggests (1) low binding affinity between these hormones and the GH receptor in yellow perch, (2) that the endogenous GH levels were already at biologically maximal levels or (3) that other endocrine factors are needed in order for GH to promote yellow perch growth. The reduction in IGF-I levels 24 h after handling suggests a negative effect of handling stress on the GH-IGF-I axis in yellow perch.This work was supported by the University of Wisconsin-Madison College of Agricultural and Life Sciences and School of Natural Resources; the Wisconsin Department of Natural Resources; the University of Wisconsin Sea Grant College Program, National Oceanic and Atmospheric Administration, US Department of Commerce; the State of Wisconsin (Federal Grant NA46RG0481, Project No. R/AQ-38); and the USDA NOAA Project R/A-05-99, grant #NA86RG0048 to FG and SR. This study was also funded by the Norwegian Research Council (NFR)

c-Type Cytochrome-Dependent Formation of U(IV) Nanoparticles by Shewanella oneidensis

Modern approaches for bioremediation of radionuclide contaminated environments are based on the ability of microorganisms to effectively catalyze changes in the oxidation states of metals that in turn influence their solubility. Although microbial metal reduction has been identified as an effective means for immobilizing highly-soluble uranium(VI) complexes in situ, the biomolecular mechanisms of U(VI) reduction are not well understood. Here, we show that c-type cytochromes of a dissimilatory metal-reducing bacterium, Shewanella oneidensis MR-1, are essential for the reduction of U(VI) and formation of extracelluar UO (2) nanoparticles. In particular, the outer membrane (OM) decaheme cytochrome MtrC (metal reduction), previously implicated in Mn(IV) and Fe(III) reduction, directly transferred electrons to U(VI). Additionally, deletions of mtrC and/or omcA significantly affected the in vivo U(VI) reduction rate relative to wild-type MR-1. Similar to the wild-type, the mutants accumulated UO (2) nanoparticles extracellularly to high densities in association with an extracellular polymeric substance (EPS). In wild-type cells, this UO (2)-EPS matrix exhibited glycocalyx-like properties and contained multiple elements of the OM, polysaccharide, and heme-containing proteins. Using a novel combination of methods including synchrotron-based X-ray fluorescence microscopy and high-resolution immune-electron microscopy, we demonstrate a close association of the extracellular UO (2) nanoparticles with MtrC and OmcA (outer membrane cytochrome). This is the first study to our knowledge to directly localize the OM-associated cytochromes with EPS, which contains biogenic UO (2) nanoparticles. In the environment, such association of UO (2) nanoparticles with biopolymers may exert a strong influence on subsequent behavior including susceptibility to oxidation by O (2) or transport in soils and sediments

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Resistance to kinase inhibition through shortened target engagement

Imatinib, a selective inhibitor of the breakpoint cluster region (BCR)-ABL kinase, is the poster child for targeted cancer therapeutics. However, its efficacy is limited by resistance mutations. Using a quantitative bioluminescence resonance energy transfer assay in living cells, we identified ABL kinase mutations that could cause imatinib resistance by altering drug residence time

Structure of the Kinase Domain of an Imatinib-Resistant Abl Mutant in Complex with the Aurora Kinase Inhibitor VX-680. Cancer Res

Abstract We present a high-resolution (2.0 Å ) crystal structure of the catalytic domain of a mutant form of the Abl tyrosine kinase (H396P; Abl-1a numbering) that is resistant to the Abl inhibitor imatinib. The structure is determined in complex with the small-molecule inhibitor VX-680 (Vertex Pharmaceuticals, Cambridge, MA), which blocks the activity of various imatinib-resistant mutant forms of Abl, including one (T315I) that is resistant to both imatinib and BMS-354825 (dasatinib), a dual Src/Abl inhibitor that seems to be clinically effective against all other imatinib-resistant forms of BCR-Abl. VX-680 is shown to have significant inhibitory activity against BCR-Abl bearing the T315I mutation in patient-derived samples. The Abl kinase domain bound to VX-680 is not phosphorylated on the activation loop in the crystal structure but is nevertheless in an active conformation, previously unobserved for Abl and inconsistent with the binding of imatinib. The adoption of an active conformation is most likely the result of synergy between the His 396 Pro mutation, which destabilizes the inactive conformation required for imatinib binding, and the binding of VX-680, which favors the active conformation through hydrogen bonding and steric effects. VX-680 is bound to Abl in a mode that accommodates the substitution of isoleucine for threonine at residue 315 (the ''gatekeeper'' position). The avoidance of the innermost cavity of the Abl kinase domain by VX-680 and the specific recognition of the active conformation explain the effectiveness of this compound against mutant forms of BCRAbl, including those with mutations at the gatekeeper position

Conformation-Selective Analogues of Dasatinib Reveal Insight into Kinase Inhibitor Binding and Selectivity

In the kinase field, there are many widely held tenets about conformation-selective inhibitors that have yet to be validated using controlled experiments. We have designed, synthesized, and characterized a series of kinase inhibitor analogues of dasatinib, an FDA-approved kinase inhibitor that binds the active conformation. This inhibitor series includes two Type II inhibitors that bind the DFG-out inactive conformation and two inhibitors that bind the αC-helix-out inactive conformation. Using this series of compounds, we analyze the impact that conformation-selective inhibitors have on target binding and kinome-wide selectivity

Uncovering semantic bias in neural network models using a knowledge graph

While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not sufficient to show deeper systematic preferences and potential biases of the model that apply consistently across examples. In this paper we apply rule mining using knowledge graphs in combination with neural network explanation methods to uncover such systematic preferences of trained neural models and capture them in the form of conjunctive rules. We test our approach in the context of text classification tasks and show that such rules are able to explain a substantial part of the model behaviour as well as indicate potential causes of misclassifications when the model is applied outside of the initial training context.non-peer-reviewe

Uncovering semantic bias in neural network models using a knowledge graph

While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not sufficient to show deeper systematic preferences and potential biases of the model that apply consistently across examples. In this paper we apply rule mining using knowledge graphs in combination with neural network explanation methods to uncover such systematic preferences of trained neural models and capture them in the form of conjunctive rules. We test our approach in the context of text classification tasks and show that such rules are able to explain a substantial part of the model behaviour as well as indicate potential causes of misclassifications when the model is applied outside of the initial training context