Development of Novel Activity-Based Probes for the Detection of Serine Proteases

Cystic Fibrosis (CF) is a genetic disease featuring a chronic cycle of inflammation and infection in the airways of sufferers. Mutations lead to altered ion transport, which in turn causes dehydrated airways and reduced mucociliary clearance which predisposes the patient to infection, resulting in a severe immune response and tissue destruction (1). Airway dehydration is primarily caused by the hyperabsorption of sodium by the epithelial sodium channel (ENaC) (2). ENaC is activated by the action of a number of predominantly trypsin-like Channel Activating Proteases (CAPs) including prostasin, matriptase and furin (3). Additional proteases known to activate ENaC include human airway trypsin (3), plasmin, neutrophil elastase and chymotrypsin (4).

Activity profiling is a valuable technique which involves the use of small inhibitory molecules called Activity-Based Probes (ABPs) which can be used to covalently label the active site of proteases and provide a range of information regarding its structure, catalytic mechanism, location and function within biological systems. The development of novel ABPs for CAPs, would enhance understanding of the role of these proteases in CF airways disease and in particular their role in ENaC activation and airway dehydration. This project investigates the application of a range of novel broad-spectrum ABPs targeting the various subclasses of serine proteases, to include those proteases involved in ENaC activation. Additionally, the application of more selective ABPs in detecting specific serine proteases is investigated.

Compounds were synthesised by Solid-Phase Peptide Synthesis (SPPS) using a standard Fmoc/tBu strategy. Kinetic evaluation of synthesised ABPs against various serine proteases was determined by fluorogenic steady-state enzyme assays. Furthermore, application of ABPs and confirmation of irreversible nature of the compounds was carried out through SDS-PAGE and electroblotting techniques.

Synthesised compounds showed potent irreversible inhibition of serine proteases within their respective targeting class (NAP855 vs Trypsin k3/Ki = 2.60 x 106 M-1 min-1, NFP849 vs Chymotrypsin k3/Ki = 1.28 x 106 M-1 min-1 and NVP800 vs Neutrophil Elastase k3/Ki = 6.41 x 104 M-1 min-1). Furthermore ABPs showed little to no cross-reactivity between classes and so display selectivity between classes. The irreversible nature of compounds was further demonstrated through labelling of proteases, followed by separation and detection via SDS-PAGE and electroblotting techniques. Targeted labelling of active proteases only, was demonstrated by failure of ABPs to detect previously inactivated proteases. Extension of the substrate recognition site within probes resulted in an increased potency and selectivity in the detection of the target proteases. Successful detection of neutrophil elastase from CF sputum samples by NVP800, demonstrated the application of compounds within biological samples and their potential use in identifying further proteases involved in ENaC activation and airway dehydration in CF patients.

Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

On the Privacy of Encrypted Skype Communications

The privacy of voice over IP (VoIP) systems is achieved by compressing and encrypting the sampled data. This paper investigates in detail the leakage of information from Skype, a widely used VoIP application. In this research, it has been demonstrated by using the dynamic time warping (DTW) algorithm, that sentences can be identified with an accuracy of 60%. The results can be further improved by choosing specific training data. An approach involving the Kalman filter is proposed to extract the kernel of all training signals.

Event-driven implicit authentication for mobile access control

In order to protect user privacy on mobile devices, an event-driven implicit authentication scheme is proposed in this paper. Several methods of utilizing the scheme for recognizing legitimate user behavior are investigated. The investigated methods compute an aggregate score and a threshold in real-time to determine the trust level of the current user using real data derived from user interaction with the device. The proposed scheme is designed to: operate completely in the background, require minimal training period, enable high user recognition rate for implicit authentication, and prompt detection of abnormal activity that can be used to trigger explicitly authenticated access control. In this paper, we investigate threshold computation through standard deviation and EWMA (exponentially weighted moving average) based algorithms. The result of extensive experiments on user data collected over a period of several weeks from an Android phone indicates that our proposed approach is feasible and effective for lightweight real-time implicit authentication on mobile smartphones.

Extracellular cathepsin S and intracellular caspase 1 activation are surrogate biomarkers of particulate-induced lysosomal disruption in macrophages

BACKGROUND: Particulate matter has been shown to stimulate the innate immune system and induce acute inflammation. Therefore, while nanotechnology has the potential to provide therapeutic formulations with improved efficacy, there are concerns such pharmaceutical preparations could induce unwanted inflammatory side effects. Accordingly, we aim to examine the utility of using the proteolytic activity signatures of cysteine proteases, caspase 1 and cathepsin S (CTSS), as biomarkers to assess particulate-induced inflammation.

METHODS: Primary peritoneal macrophages and bone marrow-derived macrophages from C57BL/6 mice and ctss(-/-) mice were exposed to micro- and nanoparticulates and also the lysosomotropic agent, L-leucyl-L-leucine methyl ester (LLOME). ELISA and immunoblot analyses were used to measure the IL-1β response in cells, generated by lysosomal rupture. Affinity-binding probes (ABPs), which irreversibly bind to the active site thiol of cysteine proteases, were then used to detect active caspase 1 and CTSS following lysosomal rupture. Reporter substrates were also used to quantify the proteolytic activity of these enzymes, as measured by substrate turnover.

RESULTS: We demonstrate that exposure to silica, alum and polystyrene particulates induces IL-1β release from macrophages, through lysosomal destabilization. IL-1β secretion positively correlated with an increase in the proteolytic activity signatures of intracellular caspase 1 and extracellular CTSS, which were detected using ABPs and reporter substrates. Interestingly IL-1β release was significantly reduced in primary macrophages from ctss(-/-) mice.

CONCLUSIONS: This study supports the emerging significance of CTSS as a regulator of the innate immune response, highlighting its role in regulating IL-1β release. Crucially, the results demonstrate the utility of intracellular caspase 1 and extracellular CTSS proteolytic activities as surrogate biomarkers of lysosomal rupture and acute inflammation. In the future, activity-based detection of these enzymes may prove useful for the real-time assessment of particle-induced inflammation and toxicity assessment during the development of nanotherapeutics.

Towards a threat assessment framework for apps collusion

App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model (PBSM) for Android does not address this threat, as it is rather limited to mitigating risks due to individual apps. This paper presents a technique for assessing the threat of collusion for apps, which is a first step towards quantifying collusion risk, and allows us to narrow down to candidate apps for collusion, which is critical given the high volume of Android apps available. We present our empirical analysis using a classified corpus of over 29000 Android apps provided by Intel Security.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.