Rethinking climate engineering categorization in the context of climate change mitigation and adaptation

The portfolio of approaches to respond to the challenges posed by anthropogenic climate change has broadened beyond mitigation and adaptation with the recent discussion of potential climate engineering options. How to define and categorize climate engineering options has been a recurring issue in both public and specialist discussions. We assert here that current definitions of mitigation, adaptation, and climate engineering are ambiguous, overlap with each other and thus contribute to confusing the discourse on how to tackle anthropogenic climate change. We propose a new and more inclusive categorization into five different classes: anthropogenic emissions reductions (AER), territorial or domestic removal of atmospheric CO2 and other greenhouse gases (D-GGR), trans-territorial removal of atmospheric CO2 and other greenhouse gases (T-GGR), regional to planetary targeted climate modification (TCM), and climate change adaptation measures (including local targeted climate and environmental modification, abbreviated CCAM). Thus, we suggest that techniques for domestic greenhouse gas removal might better be thought of as forming a separate category alongside more traditional mitigation techniques that consist of emissions reductions. Local targeted climate modification can be seen as an adaptation measure as long as there are no detectable remote environmental effects. In both cases, the scale and intensity of action are essential attributes from the technological, climatic, and political viewpoints. While some of the boundaries in this revised classification depend on policy and judgement, it offers a foundation for debating on how to define and categorize climate engineering options and differentiate them from both mitigation and adaptation measures to climate change

Controlled levels of protein modification through a chromatography-mediated bioconjugation.

Synthetically modified proteins are increasingly finding applications as well-defined scaffolds for materials. In practice it remains difficult to construct bioconjugates with precise levels of modification because of the limited number of repeated functional groups on proteins. This article describes a method to control the level of protein modification in cases where there exist multiple potential modification sites. A protein is first tagged with a handle using any of a variety of modification chemistries. This handle is used to isolate proteins with a particular number of modifications via affinity chromatography, and then the handle is elaborated with a desired moiety using an oxidative coupling reaction. This method results in a sample of protein with a well-defined number of modifications, and we find it particularly applicable to systems like protein homomultimers in which there is no way to discern between chemically identical subunits. We demonstrate the use of this method in the construction of a protein-templated light-harvesting mimic, a type of system which has historically been difficult to make in a well-defined manner

Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection

Machine learning based solutions have been successfully employed for automatic detection of malware in Android applications. However, machine learning models are known to lack robustness against inputs crafted by an adversary. So far, the adversarial examples can only deceive Android malware detectors that rely on syntactic features, and the perturbations can only be implemented by simply modifying Android manifest. While recent Android malware detectors rely more on semantic features from Dalvik bytecode rather than manifest, existing attacking/defending methods are no longer effective. In this paper, we introduce a new highly-effective attack that generates adversarial examples of Android malware and evades being detected by the current models. To this end, we propose a method of applying optimal perturbations onto Android APK using a substitute model. Based on the transferability concept, the perturbations that successfully deceive the substitute model are likely to deceive the original models as well. We develop an automated tool to generate the adversarial examples without human intervention to apply the attacks. In contrast to existing works, the adversarial examples crafted by our method can also deceive recent machine learning based detectors that rely on semantic features such as control-flow-graph. The perturbations can also be implemented directly onto APK's Dalvik bytecode rather than Android manifest to evade from recent detectors. We evaluated the proposed manipulation methods for adversarial examples by using the same datasets that Drebin and MaMadroid (5879 malware samples) used. Our results show that, the malware detection rates decreased from 96% to 1% in MaMaDroid, and from 97% to 1% in Drebin, with just a small distortion generated by our adversarial examples manipulation method.Comment: 15 pages, 11 figure

Generating Generalized Distributions from Dynamical Simulation

We present a general molecular-dynamics simulation scheme, based on the Nose' thermostat, for sampling according to arbitrary phase space distributions. We formulate numerical methods based on both Nose'-Hoover and Nose'-Poincare' thermostats for two specific classes of distributions; namely, those that are functions of the system Hamiltonian and those for which position and momentum are statistically independent. As an example, we propose a generalized variable temperature distribution that designed to accelerate sampling in molecular systems.Comment: 10 pages, 3 figure

Site-selective protein modification via disulfide rebridging for fast tetrazine/trans-cyclooctene bioconjugation

An inverse electron demand Diels–Alder reaction between tetrazine and trans-cyclooctene (TCO) holds great promise for protein modification and manipulation. Herein, we report the design and synthesis of a tetrazine-based disulfide rebridging reagent, which allows the site-selective installation of a tetrazine group into disulfide-containing peptides and proteins such as the hormone somatostatin (SST) and the antigen binding fragment (Fab) of human immunoglobulin G (IgG). The fast and efficient conjugation of the tetrazine modified proteins with three different TCO-containing substrates to form a set of bioconjugates in a site-selective manner was successfully demonstrated for the first time. Homogeneous, well-defined bioconjugates were obtained underlining the great potential of our method for fast bioconjugation in emerging protein therapeutics. The formed bioconjugates were stable against glutathione and in serum, and they maintained their secondary structure. With this work, we broaden the scope of tetrazine chemistry for site-selective protein modification to prepare well-defined SST and Fab conjugates with preserved structures and good stability under biologically relevant conditions

A general framework for quantifying the effects of DNA repair inhibitors on radiation sensitivity as a function of dose

Purpose. Current methods for quantifying effects of DNA repair modifiers on radiation sensitivity assume a constant effect independent of the radiation dose received. The aim of this study was to develop and evaluate a modelling strategy by which radiation dose dependent effects of DNA repair inhibitors on clonogenic survival might be identified and their significance assessed. Methods. An indicator model that allowed quantification of the Sensitiser Effect on Radiation response as a function of Dose (SERD) was developed. This model was fitted to clonogenic survival data derived from human tumour and rodent fibroblast cell lines irradiated in the presence and absence of chemical inhibitors of poly(ADP-ribose) polymerase (PARP) activity. Results. PARP inhibition affected radiation response in a cell cycle and radiation dose dependent manner, and was also associated with significant radiation-independent effects on clonogenic survival. Application of the SERD method enabled identification of components of the radiation response that were significantly affected by PARP inhibition and indicated the magnitude of the effects on each component. Conclusion. The proposed approach improves on current methods of analysing effects of DNA repair modification on radiation response. Furthermore, it may be generalised to account for other parameters such as proliferation or dose rate to enable its use in the context of fractionated or continuous radiation exposures

Tumour cell labelling by magnetic nanoparticles with determination of intracellular iron content and spatial distribution of the intracellular iron

Abstract: Magnetically labelled cells are used for in vivo cell tracking by MRI, used for the clinical translation of cell-base therapies. Studies involving magnetic labelled cells may include separation of labelled cells, targeted delivery and controlled release of drugs, contrast enhanced MRI and magnetic hyperthermia for the in situ ablation of tumours. Dextran-coated super-paramagnetic iron oxide (SPIO) ferumoxides are used clinically as an MR contrast agents primarily for hepatic imaging. The material is also widely used for in vitro cell labelling, as are other SPIO-based particles. Our results on the uptake by human cancer cell lines of ferumoxides indicate that electroporation in the presence of protamine sulphate (PS) results in rapid high uptake of SPIO nanoparticles (SPIONs) by parenchymal tumour cells without significant impairment of cell viability. Quantitative determination of cellular iron uptake performed by colorimetric assay is in agreement with data from the literature. These results on intracellular iron content together with the intracellular distribution of SPIONs by magnetic force microscopy (MFM) following in vitro uptake by parenchymal tumour cells confirm the potential of this technique for clinical tumour cell detection and destruction