RNA delivery by extracellular vesicles in mammalian cells and its applications.

The term 'extracellular vesicles' refers to a heterogeneous population of vesicular bodies of cellular origin that derive either from the endosomal compartment (exosomes) or as a result of shedding from the plasma membrane (microvesicles, oncosomes and apoptotic bodies). Extracellular vesicles carry a variety of cargo, including RNAs, proteins, lipids and DNA, which can be taken up by other cells, both in the direct vicinity of the source cell and at distant sites in the body via biofluids, and elicit a variety of phenotypic responses. Owing to their unique biology and roles in cell-cell communication, extracellular vesicles have attracted strong interest, which is further enhanced by their potential clinical utility. Because extracellular vesicles derive their cargo from the contents of the cells that produce them, they are attractive sources of biomarkers for a variety of diseases. Furthermore, studies demonstrating phenotypic effects of specific extracellular vesicle-associated cargo on target cells have stoked interest in extracellular vesicles as therapeutic vehicles. There is particularly strong evidence that the RNA cargo of extracellular vesicles can alter recipient cell gene expression and function. During the past decade, extracellular vesicles and their RNA cargo have become better defined, but many aspects of extracellular vesicle biology remain to be elucidated. These include selective cargo loading resulting in substantial differences between the composition of extracellular vesicles and source cells; heterogeneity in extracellular vesicle size and composition; and undefined mechanisms for the uptake of extracellular vesicles into recipient cells and the fates of their cargo. Further progress in unravelling the basic mechanisms of extracellular vesicle biogenesis, transport, and cargo delivery and function is needed for successful clinical implementation. This Review focuses on the current state of knowledge pertaining to packaging, transport and function of RNAs in extracellular vesicles and outlines the progress made thus far towards their clinical applications

Integrity and Continuity of Sensor-Based Collision Warning Systems Using Vehicle-to-Vehicle Communication

This paper describes the design and implementation of a new safety risk evaluation method for a sensor-based automotive collision warning system using vehicle-to-vehicle (V2V) communication. The paper provides an overview of the V2V basic safety message (BSM) format and of surrogate measures of safety (SMS) used to parameterize a vehicle encounter. BSM and SMS are then employed to quantify risk of collision and risk of false alerts. Preliminary simulations illustrate the methodology in an example multi-sensor intersection movement assist system.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Analysis of ARAIM Against EOP GPS-Galileo Faults on LPV-200 Precision Approach

This paper presents a detection algorithm for constellation faults on LPV-200 precision approach. In particular, this work focuses on the Earth Orientation Parameters (EOP) faults which are the only Constellation Wide Fault listed in the current GPS Standard Positioning Service and Performance Standard. These faults are particularly hazardous for single-constellation RAIM algorithms since they cannot be detected by measurement redundancy. This paper investigates the properties of the rotation of the ephemeris-based satellite positions caused by EOP fault and its impact in the pseudorange fault vector. This work will show that EOP faults are constrained, aspect that can be exploited in the pseudorange domain. Under a dual constellation GPS-Galileo scenario, we develop an Integrity Risk evaluation method based on Residual Based RAIM specifically designed to account for EOP faults. In addition, this paper investigates different EOP constellation fault scenarios based on the independence of the fault across constellations. We finally show that EOP determination process at the ground and satellite ephemeris updating method play an essential role in the availability performance

Quantifying Feature Association Error in Camera-based Positioning

Camera-based visual navigation techniques can provide six degrees-of-freedom estimates of position and orientation (or pose), and can be implemented at low cost in applications including autonomous driving, indoor positioning, and drone landing. However, feature matching errors may occur when associating measured features in camera images with mapped features in a landmark database, especially when repetitive patterns are in view. A typical example of repetitive patterns is that of regularly spaced windows on building walls. Quantifying the data association risk and its impact on navigation system integrity is essential in safety critical applications. But, literature on vision-based navigation integrity is sparse. This work aims at quantifying and bounding the integrity risk caused by incorrect associations in visual navigation using extended Kalman filters

URA/SISA Analysis for GPS-Galileo ARAIM Integrity Support Message

This paper presents a URA/SISA analysis to support ARAIM based on a time-dependent statistical characterization of orbit and clock errors observations. For each individual GPS and Galileo satellites, by comparing precise orbits to broadcast ephemeris data, this work computes the Signal in Space Range Error (SISRE) which needs to be overbounded by the URA/SISA value included in the ISM. Over seven years of service history data for GPS and four months for Galielo are computed in this analysis, showing that range error is manly driven by satellite's clock performance. Satellites that historically have presented well behaved $\sigma_{SISRE}$ are equipped with stable clocks which display small error dispersion. A particular example is provided through GPS SVN65/PRN24 whose Cesium clock worsens satellite's performance as compared to the rest of the GPS block IIF equipped with Rubidium clocks. Time-dependent results show that orbit and clock error distributions are not zero mean on a monthly basis, although they do not exhibit a significant bias in a long-term scale. This fact might open the possibility of a short-time adaptable $b_{nom}$ and $\sigma_{URA}$ overbounding parameters contained in the ISM

Overbounding Sequential Estimation Errors Due to Non-Gaussian Correlated Noise

In this paper, we develop, analyze, and implement a new recursive method to conservatively account for non-Gaussian measurement errors with an uncertain correlation structure in Kalman filters (KFs). Under the assumptions of symmetric overbounding, the method guarantees a CDF overbound on the entire KF estimation error distribution. First, we leverage previous work on symmetric overbounding and frequency-domain overbounding to show how to transform a measurement domain CDF overbound into a position domain overbound. The second part of the paper evaluates the proposed method through Monte Carlo simulation for a GPS-based position estimation problem. Specifically, we show that while frequency domain overbounding produces a position domain overbound for Gaussian noise with an uncertain correlation structure, combination with symmetric overbounding is required to ensure position domain overbounding for non-Gaussian correlated noise

Overbounding GNSS/INS Integration with Uncertain GNSS Gauss-Markov Error Parameters

The integration of GNSS with Inertial Navigation Systems (INS) has the potential to achieve high levels of continuity and availability as compared to standalone GNSS and therefore to satisfy stringent navigation requirements. However, robustly accounting for time-correlated measurement errors is a challenge when designing the Kalman filter (KF) used for GNSS/INS coupling. In particular, if the error processes are not fully known, the KF estimation error covariance can be misleading, which is problematic in safety-critical applications. In this paper, we design a GNSS/INS integration scheme that guarantees upper bounds on the estimation error variance assuming that measurement errors are first-order Gauss-Markov processes with parameters only known to reside within pre-established bounds. We evaluate the filter performance and guaranteed estimation by covariance analysis for a simulated precision approach procedure