12 research outputs found
Predicting consequences through cyberattack descriptions
No full textThreat modeling is a process by which the security designers and re- searchers analyze the security of a system against known threats and vulnerabilities. There is a myriad of threat intelligence and vulnerability databases that security experts use day-to-day to make important decisions. Security experts and incident responders require the right set of skills and tools to recognize attack consequences and convey them to various stakeholders. To the best of our knowledge, the literature lacks a threat modeling technique, which is user-centric and perceives the security features and dimensions from the user’s perspective. For example, the taxonomies may describe what asset the attacker may target and the various methods or vulnerabilities that can be exploited but not how the attack will impact the user. Moreover, the consequences of attacks are often too technical for non-technical users with little-to-no-background in cybersecurity. To this end, we introduce a user-centric threat model called UC-STRIDE, which extends Microsoft’s STRIDE model, to incorporate the consequences of the cyberattacks from both technical and non-technical perspectives. We introduce a repository called CogSec, which consists of cyberattack descriptions annotated with their immediate technical and non-technical consequences.
Furthermore, this dissertation focuses on using natural language processing (NLP) and machine learning techniques to analyze cyberattack text descriptions and predict its consequences. This can be useful to quickly analyze new attacks discovered in the wild and help security practitioners take requisite action and also convey the consequences to stakeholders in a simple way as they may not have adequate background in cybersecurity. Research has shown that users become sensitized to repeated text warnings and alerts and thus can lead users to be more susceptible to cyberattacks. This dissertation explores whether the consequences of cyber threats can be conveyed to the users’ using non-speech natural sounds known as sonifications similar to text warnings."Embargo status: Restricted until 09/2172. To request the author grant access, click on the PDF link to the left
Microscale hydrodynamic confinements: shaping liquids across length scales as a toolbox in life sciences
No full textHydrodynamic phenomena can be leveraged to confine a range of biological and chemical species without needing physical walls. In this review, we list methods for the generation and manipulation of microfluidic hydrodynamic confinements in free-flowing liquids and near surfaces, and elucidate the associated underlying theory and discuss their utility in the emerging area of open space microfluidics applied to life-sciences. Microscale hydrodynamic confinements are already starting to transform approaches in fundamental and applied life-sciences research from precise separation and sorting of individual cells, allowing localized bio-printing to multiplexing for clinical diagnosis. Through the choice of specific flow regimes and geometrical boundary conditions, hydrodynamic confinements can confine species across different length scales from small molecules to large cells, and thus be applied to a wide range of functionalities. We here provide practical examples and implementations for the formation of these confinements in different boundary conditions - within closed channels, in between parallel plates and in an open liquid volume. Further, to enable non-microfluidics researchers to apply hydrodynamic flow confinements in their work, we provide simplified instructions pertaining to their design and modelling, as well as to the formation of hydrodynamic flow confinements in the form of step-by-step tutorials and analytical toolbox software. This review is written with the idea to lower the barrier towards the use of hydrodynamic flow confinements in life sciences research.LMIS
Quantifying Antibody Binding Kinetics on Fixed Cells and Tissues via Fluorescence Lifetime Imaging
No full textISSN:1520-6882ISSN:0003-2700ISSN:0003-270
Formation of multicompartment structures through aging of protein-RNA condensates
No full textISSN:0006-3495ISSN:1542-0086ISSN:1542-008
Formation of Multi-Compartment Condensates through Aging of Protein-RNA Condensates
No full textCells can dynamically organize reactions through the formation of biomolecular condensates. These viscoelastic networks exhibit complex material properties and mesoscale architectures, including the ability to form multi-phase assemblies. Understanding the molecular mechanisms underlying the formation of compartmentalized condensates has implications not only in biology but also in the development of advanced materials. In this study, we demonstrate that the aging of heterotypic protein-RNA condensates can lead to the formation of double-emulsion structures. By combining fluorescence-based techniques with theoretical modeling, we show that, as the condensates age, the strengthening of homotypic protein-protein interactions induces the release of RNA molecules from the dense phase. Notably, when condensates exceed a critical size, the slow diffusion of RNA molecules triggers the nucleation of a dilute phase within the protein-rich condensates, ultimately resulting in the formation of double-emulsion structures. These findings illustrate a new mechanism for a formation of dynamic multi-compartment condensates
Awake intubation using lightwand in patients with cervical spine injuries: A comparison of nasal and oral routes
No full text
Quantifying Antibody Binding Kinetics on Fixed Cells and Tissues <i>via</i> Fluorescence Lifetime Imaging
No full textWe present a method for monitoring spatially localized
antigen–antibody
binding events on physiologically relevant substrates (cell and tissue
sections) using fluorescence lifetime imaging. Specifically, we use
the difference between the fluorescence decay times of fluorescently
tagged antibodies in free solution and in the bound state to track
the bound fraction over time and hence deduce the binding kinetics.
We make use of a microfluidic probe format to minimize the mass transport
effects and localize the analysis to specific regions of interest
on the biological substrates. This enables measurement of binding
constants (kon) on surface-bound antigens
and on cell blocks using model biomarkers. Finally, we directly measure
p53 kinetics with differential biomarker expression in ovarian cancer
tissue sections, observing that the degree of expression corresponds
to the changes in kon, with values of
3.27–3.50 × 103 M–1 s–1 for high biomarker expression and 2.27–2.79
× 103 M–1 s–1 for
low biomarker expression
Droplet Microfluidics for the Label-Free Extraction of Complete Phase Diagrams and Kinetics of Liquid-Liquid Phase Separation in Finite Volumes
No full textISSN:1613-6810ISSN:1613-6829ISSN:1613-682
In situ complexation of sgRNA and Cas12a improves the performance of a one-pot RPA–CRISPR-Cas12 assay
No full textDue to their ability to selectively target pathogen-specific nucleic acids, CRISPR-Cas systems are increasingly being employed as diagnostic tools. “One pot” assays that combine nucleic acid amplification and CRISPR-Cas systems (NAAT–CRISPR-Cas) in a single step have emerged as one of the most popular CRISPR-Cas biosensing formats. However, operational simplicity comes at a cost, with one-pot assays typically being less sensitive than corresponding two-step NAAT–CRISPR-Cas assays and often failing to detect targets at low concentrations. It is thought that these performance reductions result from the competition between the two enzymatic processes driving the assay, namely Cas-mediated cis-cleavage and polymerase-mediated amplification of the target DNA. Herein, we describe a novel one-pot RPA–Cas12a assay that circumvents this issue by leveraging in situ complexation of the target-specific sgRNA and Cas12a to purposefully limit the concentration of active Cas12a during the early stages of the assay. Using a clinically relevant assay against a DNA target for HPV-16, we show how this in situ format reduces competition between target cleavage and amplification and engenders significant improvements in detection limit when compared to the traditional one-pot assay format, even in patient-derived samples. Finally, to gain further insight into the assay, we use experimental data to formulate a mechanistic model describing the competition between the Cas enzyme and nucleic acid amplification. These findings suggest that purposefully limiting cis-cleavage rates of Cas proteins is a viable strategy for improving the performance of one-pot NAAT–CRISPR-Cas assays
