Anti-CASP6 monoclonal antibody

Ketamine is a widely used pharmaceutical that has been detected in water sources worldwide. Zebrafish embryos were used in this study to investigate the oxidative stress and apoptotic signals following a 24h exposure to different ketamine concentrations (0, 50, 70 and 90 mg L-1). Early blastula embryos (similar to 2 h post fertilisation-hpf) were exposed for 24 h and analysed at 8 and 26 hpf. Reactive oxygen species and apoptotic cells were identified in vivo, at 26 hpf. Enzymatic activities (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), lactate dehydrogenase (LDH) and acetylcholinesterase (AChE)), glutathione levels (oxidised (GSSG) and reduced (GSH)), oxidative damage (lipid peroxidation (LPO) and protein carbonyls (CO)) as well as oxidative stress (gcic, gstpl, sodl and cat), apoptosis (casp3a, casp6, casp8, casp9, aiftn1 and tp53) and cell proliferation (pcna) related-genes were evaluated at 8 and 26 hpf. Caspase (3 and 9) activity was also determined at both time-points by colorimetric methods. Superoxide dismutase (SOD), catalase (CAT), glutathione levels (GSSG), caspase-9 and reactive oxygen species (ROS) were shown to be affected by ketamine exposure while in vivo analysis showed no difference in ROS. A significant up -regulation of superoxide dismutase (sod1) and catalase (cat) genes expression was also perceived. Ketamine-induced apoptosis was observed in vivo and confirmed by the apoptotic-related genes up-regulation. The overall results suggest that ketamine induced oxidative stress and apoptosis through the involvement of p53-dependent pathways in zebrafish embryos which could be important for the evaluation of the overall risk of ketamine in aquatic environments. (C) 2018 Elsevier Ltd. All rights reserved.

Protein structure prediction provides valuable insights into function, and comparative modeling is one of the most reliable methods to predict 3D structures directly from amino acid sequences. However, critical problems arise during the selection of the correct templates and the alignment of query sequences therewith. We have developed an automatic protein structure prediction server, (PS)(2), which uses an effective consensus strategy both in template selection, which combines PSI-BLAST and IMPALA, and target-template alignment integrating PSI-BLAST, IMPALA and T-Coffee. (PS)(2) was evaluated for 47 comparative modeling targets in CASP6 (Critical Assessment of Techniques for Protein Structure Prediction). For the benchmark dataset, the predictive performance of (PS)(2), based on the mean GTD_TS score, was superior to 10 other automatic servers. Our method is based solely on the consensus sequence and thus is considerably faster than other methods that rely on the additional structural consensus of templates. Our results show that (PS)(2), coupled with suitable consensus strategies and anew similarity score, can significantly improve structure prediction. Our approach should be useful in structure prediction and modeling. The (PS)(2) is available through the website at http://ps2.life.nctu.edu.tw/.