Studying membrane trafficking in the worm C. elegans by RNA interference

A powerful approach to gain understanding of molecular machinery responsible for membrane trafficking is through inactivation of gene function by RNA interference (RNAi). RNAi-mediated gene silencing occurs when a double-stranded RNA is introduced into cells and targets a complementary mRNA for degradation. The subsequent lack of mRNA prevents the synthesis of the corresponding protein and ultimately causes depletion of a particular gene product from the cell. The effects of such depletion can then by analyzed by functional, morphological, and biochemical assays. RNAi-mediated knockdowns of numerous gene products in cultured cells of mammalian and other species origins have provided significant new insight into traffic regulation and represent standard approaches in current cell biology. However, RNAi in the multicellular nematode Caenorhabditis elegans model allows RNAi studies within the context of a whole organism, and thus provides an unprecedented opportunity to explore effects of specific trafficking regulators within the context of distinct developmental stages and diverse cell types. In addition, various transgenic C. elegans strains have been developed that express marker proteins tagged with fluorescent proteins to facilitate the analysis of trafficking within the secretory and endocytic pathways. This chapter provides a detailed description of a basic RNAi approach that can be used to analyze the function of any gene of interest in secretory and endosomal trafficking in C. elegans. © 2013 Elsevier Inc.

Characterizing Internet worm spatial-temporal infection structures

Since the Morris worm was released in 1988, Internet worms continue to be one of top security threats. For example, the Conficker worm infected 9 to 15 million machines in early 2009 and shut down the service of some critical government and medical networks. Moreover, it constructed a massive peer-to-peer (P2P) botnet. Botnets are zombie networks controlled by attackers setting out coordinated attacks. In recent years, botnets have become the number one threat to the Internet. The objective of this research is to characterize spatial-temporal infection structures of Internet worms, and apply the observations to study P2P-based botnets formed by worm infection. First, we infer temporal characteristics of the Internet worm infection structure, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we apply statistical estimation techniques on Darknet observations. We show analytically and empirically that our proposed estimators can significantly improve the inference accuracy. Second, we reveal two key spatial characteristics of the Internet worm infection structure, i.e., the number of children and the generation of the underlying tree topology formed by worm infection. Specifically, we apply probabilistic modeling methods and a sequential growth model. We show analytically and empirically that the number of children has asymptotically a geometric distribution with parameter 0.5, and the generation follows closely a Poisson distribution. Finally, we evaluate bot detection strategies and effects of user defenses in P2P-based botnets formed by worm infection. Specifically, we apply the observations of the number of children and demonstrate analytically and empirically that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. However, we also point out that future botnets may self-stop scanning to weaken targeted detection, without greatly slowing down the speed of worm infection. We then extend the worm spatial infection structure and show empirically that user defenses, e.g. , patching or cleaning, can significantly mitigate the robustness and the effectiveness of P2P-based botnets. To counterattack, we evaluate a simple measure by future botnets that enhances topology robustness through worm re-infection.

High-resolution pore-water and solid-phase analyses of sediment cores GeoB6520-3 (Hydrate Hole) and GeoB6521-2 (Worm Hole) of the northern Congo Fan

The geochemical cycling of barium was investigated in sediments of pockmarks of the northern Congo Fan, characterized by surface and subsurface gas hydrates, chemosynthetic fauna, and authigenic carbonates. Two gravity cores retrieved from the so-called Hydrate Hole and Worm Hole pockmarks were examined using high-resolution pore-water and solid-phase analyses. The results indicate that, although gas hydrates in the study area are stable with respect to pressure and temperature, they are and have been subject to dissolution due to methane-undersaturated pore waters. The process significantly driving dissolution is the anaerobic oxidation of methane (AOM) above the shallowest hydrate-bearing sediment layer. It is suggested that episodic seep events temporarily increase the upward flux of methane, and induce hydrate formation close to the sediment surface. AOM establishes at a sediment depth where the upward flux of methane from the uppermost hydrate layer counterbalances the downward flux of seawater sulfate. After seepage ceases, AOM continues to consume methane at the sulfate/methane transition (SMT) above the hydrates, thereby driving the progressive dissolution of the hydrates "from above". As a result the SMT migrates downward, leaving behind enrichments of authigenic barite and carbonates that typically precipitate at this biogeochemical reaction front. Calculation of the time needed to produce the observed solid-phase barium enrichments above the present-day depths of the SMT served to track the net downward migration of the SMT and to estimate the total time of hydrate dissolution in the recovered sediments. Methane fluxes were higher, and the SMT was located closer to the sediment surface in the past at both sites. Active seepage and hydrate formation are inferred to have occurred only a few thousands of years ago at the Hydrate Hole site. By contrast, AOM-driven hydrate dissolution as a consequence of an overall net decrease in upward methane flux seems to have persisted for a considerably longer time at the Worm Hole site, amounting to a few tens of thousands of years.

'Cooperative Automated worm Response and Detection ImmuNe ALgorithm (CARDINAL) inspired by T-cell Immunity and Tolerance'

The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.

'Cooperative Automated worm Response and Detection ImmuNe ALgorithm (CARDINAL) inspired by T-cell Immunity and Tolerance'

The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.

Lipid remodelling in the reef-building honeycomb worm, Sabellaria alveolata, reflects acclimation and local adaptation to temperature

Acclimation and adaptation, which are key to species survival in a changing climate, can be observed in terms of membrane lipid composition. Remodelling membrane lipids, via homeoviscous adaptation (HVA), counteracts membrane dysfunction due to temperature in poikilotherms. In order to assess the potential for acclimation and adaptation in the honeycomb worm, Sabellaria alveolata, a reef-building polychaete that supports high biodiversity, we carried out common-garden experiments using individuals from along its latitudinal range. Individuals were exposed to a stepwise temperature increase from 15 °C to 25 °C and membrane lipid composition assessed. Our results suggest that S. alveolata was able to acclimate to higher temperatures, as observed by a decrease in unsaturation index and 20:5n-3. However, over the long-term at 25 °C, lipid composition patterns are not consistent with HVA expectations and suggest a stress response. Furthermore, unsaturation index of individuals from the two coldest sites were higher than those from the two warmest sites, with individuals from the thermally intermediate site being in-between, likely reflecting local adaptation to temperature. Therefore, lipid remodelling appears limited at the highest temperatures in S. alveolata, suggesting that individuals inhabiting warm environments may be close to their upper thermal tolerance limits and at risk in a changing climate.

Spatial choice is biased by chemical cues from conspecifics in the speckeled worm eel Myrophis punctatus

A enguia mirongo-mirim Myrophis punctatus vive em agrupamentos de alta densidade populacional e comumente se enterra ou permanece sob o substrato. Esses comportamentos podem levar a marcas químicas no subtrato e podem, portanto, modular o uso do espaço nessa espécie. Neste estudo, testamos a hipótese de que a preferência espacial da enguia mirongo-mirim é influenciada pela presença de odor do animal coespecífico no subtrato. Mostramos que as enguias evitam a área que contém tal odor, indicando que as decisões de ocupação espacial podem ser influenciadas por pistas químicas de coespecíficos. As enguias claramente detectaram o odor de um animal coespecífico e essa percepção poderia ser um indicativo da presença de um coespecífico enterrado no substrato. Visto que elas evitam uma área contendo tal odor, sugerimos que isso poderia ser uma resposta para evitar invadir o território de um animal residente.

Screening of the 'pathogen box' identifies an approved pesticide with major anthelmintic activity against the barber's pole worm

There is a substantial need to develop new medicines against parasitic diseases via public-private partnerships. Based on high throughput phenotypic screens of largely protozoal pathogens and bacteria, the Medicines for Malaria Venture (MMV) has recently assembled an open-access 'Pathogen Box' containing 400 well-curated chemical compounds. In the present study, we tested these compounds for activity against parasitic stages of the nematode Haemonchus contortus (barber's pole worm). In an optimised, whole-organism screening assay, using exsheathed third-stage (xL3) and fourth-stage (L4) larvae, we measured the inhibition of larval motility, growth and development of H. contortus. We also studied the effect of the 'hit' compound on mitochondrial function by measuring oxygen consumption. Among the 400 Pathogen Box compounds, we identified one chemical, called tolfenpyrad (compound identification code: MMV688934) that reproducibly inhibits xL3 motility as well as L4 motility, growth and development, with IC50 values ranging between 0.02 and 3 μM. An assessment of mitochondrial function showed that xL3s treated with tolfenpyrad consumed significantly less oxygen than untreated xL3s, which was consistent with specific inhibition of complex I of the respiratory electron transport chain in arthropods. Given that tolfenpyrad was developed as a pesticide and has already been tested for absorption, distribution, excretion, biotransformation, toxicity and metabolism, it shows considerable promise for hit-to-lead optimisation and/or repurposing for use against H. contortus and other parasitic nematodes. Future work should assess its activity against hookworms and other pathogens that cause neglected tropical diseases.

Data preprocessing for anomaly based network intrusion detection : a review

Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

The geometric modelling of social frames and contexts

How do humans respond to their social context? This question is becoming increasingly urgent in a society where democracy requires that the citizens of a country help to decide upon its policy directions, and yet those citizens frequently have very little knowledge of the complex issues that these policies seek to address. Frequently, we find that humans make their decisions more with reference to their social setting, than to the arguments of scientists, academics, and policy makers. It is broadly anticipated that the agent based modelling (ABM) of human behaviour will make it possible to treat such social effects, but we take the position here that a more sophisticated treatment of context will be required in many such models. While notions such as historical context (where the past history of an agent might affect its later actions) and situational context (where the agent will choose a different action in a different situation) abound in ABM scenarios, we will discuss a case of a potentially changing context, where social effects can have a strong influence upon the perceptions of a group of subjects. In particular, we shall discuss a recently reported case where a biased worm in an election debate led to significant distortions in the reports given by participants as to who won the debate (Davis et al 2011). Thus, participants in a different social context drew different conclusions about the perceived winner of the same debate, with associated significant differences among the two groups as to who they would vote for in the coming election. We extend this example to the problem of modelling the likely electoral responses of agents in the context of the climate change debate, and discuss the notion of interference between related questions that might be asked of an agent in a social simulation that was intended to simulate their likely responses. A modelling technology which could account for such strong social contextual effects would benefit regulatory bodies which need to navigate between multiple interests and concerns, and we shall present one viable avenue for constructing such a technology. A geometric approach will be presented, where the internal state of an agent is represented in a vector space, and their social context is naturally modelled as a set of basis states that are chosen with reference to the problem space.

Evaluation of Attacks and Countermeasures in Large Scale Networks

Computer worms represent a serious threat for modern communication infrastructures. These epidemics can cause great damage such as financial losses or interruption of critical services which support lives of citizens. These worms can spread with a speed which prevents instant human intervention. Therefore automatic detection and mitigation techniques need to be developed. However, if these techniques are not designed and intensively tested in realistic environments, they may cause even more harm as they heavily interfere with high volume communication flows. We present a simulation model which allows studies of worm spread and counter measures in large scale multi-AS topologies with millions of IP addresses.