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Background: Anti-oxidant vitamins have increasingly been used to supplement traditional post-surgical treatment in cardiac transplant recipients. However, the mechanism(s) of action have not been determined. In this study we examined the effects of a novel vitamin E analog, α-tocopheryl polyethylene glycol-100 succinate (α-TPGS), and low-dose cyclosporine (CsA) in the treatment of acute and delayed cardiac rejection. Methods: In situ sonomicrometry, histologic rejection and graft survival were determined in untreated rat cardiac allograft recipients and recipients receiving CsA, α-TPGS or CsA plus α-TPGS. DNA binding of nuclear factor (NF)-κB and AP-1, inducible nitric oxide synthase (iNOS) protein, caspase-3 activity and lymphocyte proliferation were determined. Results: α-TPGS significantly (p < 0.05) prolonged graft survival equipotent to low-dose CsA. Treatment with CsA plus α-TPGS further enhanced graft survival (p < 0.001). CsA or α-TPGS alone decreased rejection, with the greatest decrease seen using combination therapy. Graft fractional shortening was improved by CsA or α-TPGS alone (p < 0.01), whereas distention in systolic and diastolic lengths in untreated allografts was prevented by CsA, α-TPGS and combination therapy. Nitrosylation of heme protein was inhibited by α-TPGS and abolished by CsA or CsA plus α-TPGS. Expression of iNOS was decreased 50% by α-TPGS equipotent to CsA, but apparently via an NF-κB– and AP-1–independent pathway. Caspase-3 activity, an index of apoptosis, was increased only in untreated allografts. In addition, α-TPGS markedly inhibited mitogen-stimulated proliferation by both rat and human lymphocytes. Conclusions: α-TPGS has a significant effect in limiting lymphocyte proliferation and activation. This might explain the equipotent action of α-TPGS vs low-dose CsA and its action to potentiate graft survival and limit graft rejection and dysfunction. [Copyright &y& Elsevier]

Abstract: The endogenous cannabinoid system has been noted for its therapeutic potential, as well as the psychoactivity of cannabinoids such as Δ9-tetrahydrocannabinol (THC). However, less is known about the psychoactivity of anandamide (AEA), an endocannabinoid ligand. Thus, the goals of this study were to establish AEA as a discriminative stimulus in transgenic mice lacking fatty acid amide hydrolase (i.e., FAAH −/− mice unable to rapidly metabolize AEA), evaluate whether THC or oleamide, a fatty acid amide, produced AEA-like responding, and assess for CB1 mediation of AEA''s discriminative stimulus. Mice readily discriminated between 6mg/kg AEA and vehicle in a two-lever drug discrimination task. AEA dose-dependently generalized to itself. THC elicited full AEA-like responding, whereas oleamide failed to substitute. The CB1 antagonist rimonabant attenuated AEA- and THC-induced AEA-appropriate responding, demonstrating CB1 mediation of AEA''s discriminative stimulus. These findings suggest that, in the absence of FAAH, AEA produces intoxication comparable to THC, and consequently to marijuana. [Copyright &y& Elsevier]

Industrial Control Systems (ICSs) were initially designed to be operated in an isolated network. However, recently, ICSs have been increasingly connected to the Internet to expand their capability, such as remote management. This interconnectivity of ICSs exposes them to cyber-attacks. At the same time, cyber-attacks in ICS networks are different compared to traditional Information Technology (IT) networks. Cyber attacks on ICSs usually involve a sequence of actions and a multitude of devices. However, current anomaly detection systems only focus on local analysis, which misses the correlation between devices and the progress of attacks over time. As a consequence, they lack an effective way to detect attacks at an entire network scale and predict possible future actions of an attack, which is of significant interest to security analysts to identify the weaknesses of their network and prevent similar attacks in the future. To address these two key issues, this paper presents a system-wide anomaly detection solution using recurrent neural networks combined with correlation analysis techniques. The proposed solution has a two-layer analysis. The first layer targets attack detection, and the second layer analyses the detected attack to predict the next possible attack actions. The main contribution of this paper is the proof of the concept implementation using two real-world ICS datasets, SWaT and Power System Attack. Moreover, we show that the proposed solution effectively detects anomalies and attacks on the scale of the entire ICS network.