The Translocating RecBCD Enzyme Stimulates Recombination by Directing RecA Protein onto ssDNA in a χ-Regulated Manner

AbstractDouble-stranded DNA break repair and homologous recombination in E. coli are initiated by the RecBCD enzyme, which unwinds and simultaneously degrades DNA from a double-stranded DNA end. This process is stimulated by cis-acting DNA elements, known as χ sites. Using both in vitro pairing and nuclease protection assays, we demonstrate that the translocating RecBCD enzyme, which has been activated by χ, coordinates the preferential loading of the homologous pairing protein, RecA, onto the resultant single-stranded DNA downstream of χ. This facilitated loading of RecA protein results in a substantial increase in both the efficiency and rate of in vitro recombination reactions and offers an explanation for stimulation of recombination and repair in vivo by χ

Adapting the Law of Armed Conflict to Autonomous Weapon Systems

Weapon systems are becoming increasingly automated and arguably some autonomous military systems have been deployed for years. Recent advances in automated systems and the possibilities they portend have generated interest and anxiety within some militaries and defense ministries, and a movement of non-governmental activists seeking to ban fully autonomous weapons. In May 2014, the High Contracting Parties of the UN Convention on Certain Conventional Weapons (CCW) convened an extensive discussion of the legal and ethical issues that autonomous weapons raise, while recognizing that many of these problems lie at an uncertain point in the future. It is important that normative development regarding autonomous weapon systems head down a path that is coherent and practical. By autonomous weapon systems, we mean systems that, once activated, can select and engage targets without further intervention by a human operator. We draw this definition from a 2012 U.S. Department of Defense policy directive, which remains the most extensive public pronouncement by any State on how it intends to proceed with regard to research, development and deployment of autonomous weapon systems. This paper addresses several questions that are critical to charting such a path. First, are autonomous weapon systems different from other new weapon systems, and, if so, how? Second, to the extent they are different, can and should autonomous weapon systems be regulated within the framework of the existing law of armed conflict? If yes, how should States go about doing so? If not, what alternative regulatory approach is appropriate? We conclude that autonomous weapon systems have special features that pose risks and that create challenges in applying the existing law of armed conflict. Nevertheless, we conclude it is possible to adapt the existing framework to account for the features of autonomous weapons, and that the suggested alternative of prohibiting these systems outright is misguided. Instead, we propose a three-tiered process for regulating the development, deployment and use of autonomous systems

Weakly supervised deep learning for the detection of domain generation algorithms

Domain generation algorithms (DGAs) have become commonplace in malware that seeks to establish command and control communication between an infected machine and the botmaster. DGAs dynamically and consistently generate large volumes of malicious domain names, only a few of which are registered by the botmaster, within a short time window around their generation time, and subsequently resolved when the malware on the infected machine tries to access them. Deep neural networks that can classify domain names as benign or malicious are of great interest in the real-time defense against DGAs. In contrast with traditional machine learning models, deep networks do not rely on human engineered features. Instead, they can learn features automatically from data, provided that they are supplied with sufficiently large amounts of suitable training data. Obtaining cleanly labeled ground truth data is difficult and time consuming. Heuristically labeled data could potentially provide a source of training data for weakly supervised training of DGA detectors. We propose a set of heuristics for automatically labeling domain names monitored in real traffic, and then train and evaluate classifiers with the proposed heuristically labeled dataset. We show through experiments on a dataset with 50 million domain names that such heuristically labeled data is very useful in practice to improve the predictive accuracy of deep learning-based DGA classifiers, and that these deep neural networks significantly outperform a random forest classifier with human engineered features

Breaking of valley degeneracy by magnetic field in monolayer MoSe2

Using polarization-resolved photoluminescence spectroscopy, we investigate valley degeneracy breaking by out-of-plane magnetic field in back-gated monolayer MoSe$_2$ devices. We observe a linear splitting of $-0.22 \frac{\text{meV}}{\text{T}}$ between luminescence peak energies in $\sigma_{+}$ and $\sigma_{-}$ emission for both neutral and charged excitons. The optical selection rules of monolayer MoSe$_2$ couple photon handedness to the exciton valley degree of freedom, so this splitting demonstrates valley degeneracy breaking. In addition, we find that the luminescence handedness can be controlled with magnetic field, to a degree that depends on the back-gate voltage. An applied magnetic field therefore provides effective strategies for control over the valley degree of freedom.Comment: expanded discussion section, corrected typo in eq.

Reconstitution of an SOS Response Pathway Derepression of Transcription in Response to DNA Breaks

AbstractE. coli responds to DNA damage by derepressing the transcription of about 20 genes that make up the SOS pathway. Genetic analyses have shown that SOS induction in response to double-stranded DNA (dsDNA) breaks requires LexA repressor, and the RecA and RecBCD enzymes—proteins best known for their role as initiators of dsDNA break repair and homologous recombination. Here we demonstrate that purified RecA protein, RecBCD enzyme, single-stranded DNA-binding (SSB) protein, and LexA repressor respond to dsDNA breaks in vitro by derepressing transcription from an SOS promoter. Interestingly, derepression is more rapid if the DNA containing the dsDNA break has a χ recombination hot spot (5′-GCTGGTGG-3′), suggesting a novel regulatory role for one of the most overrepresented octamers in the E. coli genome

Relocation remembered: Perspectives on senior transitions in the living environment

The experience of aging may necessitate transitions in living environments, either through adaptations to current residences or relocations to more supportive environments. For over a half century, the study of these transitions has informed the work of researchers, health and mental health providers, policymakers, and municipal planners. In the 1970s and ‘80s, knowledge about these transitions advanced through Lawton & Nahemow’s ecological theory of competence and environmental press, Wiseman’s behavioral model of relocation decision-making, and Litwak & Longino’s developmental perspective on senior migrations. This paper revisits influential theoretical frameworks which contribute to our understanding of senior transitions in living environments. These seminal works are shown to inform recent studies of relocation and gerontology. This paper concludes with a call for a view on housing transitions that reflects the contemporary context

Sudden Infant Death Syndrome and prenatal maternal smoking: rising attributed risk in the Back to Sleep era

BACKGROUND: Parental smoking and prone sleep positioning are recognized causal features of Sudden Infant Death. This study quantifies the relationship between prenatal smoking and infant death over the time period of the Back to Sleep campaign in the United States, which encouraged parents to use a supine sleeping position for infants. METHODS: This retrospective cohort study utilized the Colorado Birth Registry. All singleton, normal birth weight infants born from 1989 to 1998 were identified and linked to the Colorado Infant Death registry. Multivariable logistic regression was used to analyze the relationship between outcomes of interest and prenatal maternal cigarette use. Potential confounders analyzed included infant gender, gestational age, and birth year as well as maternal marital status, ethnicity, pregnancy interval, age, education, and alcohol use. RESULTS: We analyzed 488,918 birth records after excluding 5835 records with missing smoking status. Smokers were more likely to be single, non-Hispanic, less educated, and to report alcohol use while pregnant (p < 0.001). The study included 598 SIDS cases of which 172 occurred in smoke-exposed infants. Smoke exposed infants were 1.9 times (95% CI 1.6 to 2.3) more likely to die of SIDS. The attributed risk associating smoking and SIDS increased during the study period from approximately 50% to 80%. During the entire study period 59% (101/172) of SIDS deaths in smoke-exposed infants were attributed to maternal smoking. CONCLUSIONS: Due to a decreased overall rate of SIDS likely due to changing infant sleep position, the attributed risk associating maternal smoking and SIDS has increased following the Back to Sleep campaign. Mothers should be informed of the 2-fold increased rate of SIDS associated with maternal cigarette consumption

Ocean carbon sequestration: Particle fragmentation by copepods as a significant unrecognised factor?

Ocean biology helps regulate global climate by fixing atmospheric CO2 and exporting it to deep waters as sinking detrital particles. New observations demonstrate that particle fragmentation is the principal factor controlling the depth to which these particles penetrate the ocean's interior, and hence how long the constituent carbon is sequestered from the atmosphere. The underlying cause is, however, poorly understood. We speculate that small, particle‐associated copepods, which intercept and inadvertently break up sinking particles as they search for attached protistan prey, are the principle agents of fragmentation in the ocean. We explore this idea using a new marine ecosystem model. Results indicate that explicitly representing particle fragmentation by copepods in biogeochemical models offers a step change in our ability to understand the future evolution of biologically‐mediated ocean carbon storage. Our findings highlight the need for improved understanding of the distribution, abundance, ecology and physiology of particle‐associated copepods