Risk assessment of vehicle cornering events in GNSS data driven insurance telematics

We propose a framework for the detection of dangerous vehicle cornering events, based on statistics related to the no-sliding and no-rollover conditions. The input variables are estimated using an unscented Kalman filter applied to global navigation satellite system (GNSS) measurements of position, speed, and bearing. The resulting test statistic is evaluated in a field study where three smartphones are used as measurement probes. A general framework for performance evaluation and estimator calibration is presented as depending on a generic loss function. Further, we introduce loss functions designed for applications aiming to either minimize the number of missed detections and false alarms, or to estimate the risk level in each cornering event. Finally, performance characteristics of the estimator is presented as depending on the detection threshold, and on design parameters describing the driving behavior. Since the estimation only uses GNSS measurements, the framework is particularly well-suited for smartphone-based insurance telematics applications, aiming to avoid the logistic and monetary costs associated with e.g., on-board-diagnostics or black-box dependent solutions. The design of the estimation algorithm allows for instant feedback to be given to the driver, and hence, supports the inclusion of real time value added services in usage-basedinsurance programs.QC 20150316</p

Zero-Velocity Detection - A Bayesian Approach to Adaptive Thresholding

A Bayesian zero-velocity detector for foot-mounted inertial navigation systems is presented. The detector extends existing zero-velocity detectors based on the likelihood-ratio test, and allows, possibly time-dependent, prior information about the two hypotheses - the sensors being stationary or in motion - to be incorporated into the test. It is also possible to incorporate information about the cost of a missed detection or a false alarm. Specifically, we consider an hypothesis prior based on the velocity estimates provided by the navigation system and an exponential model for how the cost of a missed detection increases with the time since the last zero-velocity update. Thereby, we obtain a detection threshold that adapts to the motion characteristics of the user. Thus, the proposed detection framework efficiently solves one of the key challenges in current zero-velocity-aided inertial navigation systems: the tuning of the zero-velocity detection threshold. A performance evaluation on data with normal and fast gait demonstrates that the proposed detection framework outperforms any detector that chooses two separate fixed thresholds for the two gait speeds

Efficient internalization into low-passage glioma cell lines using adenoviruses other than type 5: an approach for improvement of gene delivery to brain tumours

There is a need for improvement of the commonly used adenovirus vectors based on serotype 5. This study was performed on three adenovirus serotypes with a CAR-binding motif (Ad4p, Ad5p and Ad17p) and three non-CAR-binding serotypes (Ad11p, Ad16p and Ad21p). The capacity of these alternative adenovirus vector candidates to deliver DNA into low-passage glioma cell lines from seven different donors was evaluated. The non-CAR-binding serotype Ad16p was the most efficient serotype with regard to import of its DNA, as well as initiation of hexon protein expression. Ad16p established hexon expression in 60–80 % of the cell population in gliomas from all donors tested. The other non-CAR-binding serotypes, Ad11p and Ad21p, showed hexon expression in 25–60 and 40–80 % of cells, respectively. The corresponding figure for the best CAR-binding serotype, Ad5p, was only 25–65 %, indicating greater variability between cells from different donors than serotype Ad16p had. The other CAR-binding serotypes, Ad4p and Ad17p, were refractory to some of the gliomas, giving a maximum of only 45 and 40 % hexon expression, respectively, in the most permissive cells. Interestingly, the transduction capacity of the CAR-binding serotypes was not correlated to the level of CAR expression on the cells

A prospective adaptive utility trial to validate performance of a novel urine exosome gene expression assay to predict high-grade prostate cancer in patients with prostate-specific antigen 2-10ng/ml at initial biopsy

BACKGROUND: Discriminating indolent from clinically significant prostate cancer (PCa) in the initial biopsy setting remains an important issue. Prospectively evaluated diagnostic assays are necessary to ensure efficacy and clinical adoption. OBJECTIVE: Performance and utility assessment of ExoDx Prostate (IntelliScore) (EPI) urine exosome gene expression assay versus standard clinical parameters for discriminating Grade Group (GG) ≥2 PCa from GG1 PCa and benign disease on initial biopsy. DESIGN, SETTING, AND PARTICIPANTS: A two-phase adaptive clinical utility study (NCT03031418) comparing EPI results with biopsy outcomes in men, with age ≥50 yr and prostate-specific antigen (PSA) 2-10ng/ml, scheduled for initial prostate biopsy. After EPI performance assessment during phase I, a clinical implementation document (ie, CarePath) was developed for utilizing the EPI test in phase II, where the biopsy decision is uncertain. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Performance evaluation of the EPI test in patients enrolled in phase I and publication of a consensus CarePath for phase II. RESULTS AND LIMITATIONS: In a total of 503 patients, with median age of 64 yr, median PSA 5.4ng/ml, 14% African American, 70% Caucasian, 53% positive biopsy rate (22% GG1, 17% GG2, and 15% ≥ GG3), EPI was superior to an optimized model of standard clinical parameters with an area under the curve (AUC) 0.70 versus 0.62, respectively, comparable with previously published results (n=519 patients, EPI AUC 0.71). Validated cut-point 15.6 would avoid 26% of unnecessary prostate biopsies and 20% of total biopsies, with negative predictive value (NPV) 89% and missing 7% of ≥GG2 PCa. Alternative cut-point 20 would avoid 40% of unnecessary biopsies and 31% of total biopsies, with NPV 89% and missing 11% of ≥GG2 PCa. The clinical investigators reached consensus recommending use of the 15.6 cut-point for phase II. Outcome of the decision impact cohort in phase II will be reported separately. CONCLUSIONS: EPI is a noninvasive, easy-to-use, gene expression urine assay, which has now been successfully validated in over 1000 patients across two prospective validation trials to stratify risk of ≥GG2 from GG1 cancer and benign disease. The test improves identification of patients with higher grade disease and would reduce the total number of unnecessary biopsies. PATIENT SUMMARY: It is challenging to predict which men are likely to have high-grade prostate cancer (PCa) at initial biopsy with prostate-specific antigen 2-10ng/ml. This study further demonstrates that the ExoDx Prostate (IntelliScore) test can predict ≥GG2 PCa at initial biopsy and defer unnecessary biopsies better than existing risk calculator\u27s and standard clinical data

Short Course in Extracellular Vesicles – The Transition from Tissue to Liquid Biopsies

Extracellular vesicles (EVs), including exosomes and microvesicles, carry a variety of bio-macromolecules, including mRNA, microRNA, other non-coding RNAs, proteins and lipids. EVs have emerged as a promising, minimally invasive (liquid biopsies) and novel source of material for molecular diagnostics, and may provide a surrogate to tissue biopsy-based biomarkers for a variety of diseases. Although EVs can be easily identified and collected from biological fluids using commercial kits, further research and proper validation is needed in order for them to be useful in the clinical setting. Currently, several EV-based research and diagnostic companies have developed research-based kits and are in the process of working with clinical laboratories to develop and validate EV-based assays for a variety of diseases. The successful clinical application of EV-based diagnostic assays will require close collaboration between industry, academia, regulatory agencies and access to patient samples. We expect that international, integrative and interdisciplinary translational research teams, along with the emergence of FDA-approved platforms, will set the framework for EV-based diagnostics. We recognize that the EV field offers new promise for personalized/precision medicine and targeted treatment in a variety of diseases. A short course was held as a four-session webinar series in September and October 2014, presented by pioneers and experts in the EV domain, covering a broad range of topics from an overview of the field to its applications, and the current state and challenges of the commercialization of EVs for research and an introduction to the clinic. It was concluded with a panel discussion on the regulatory aspects and funding opportunities in this field. A summary of the short course is presented as a meeting dispatch

Alternative Methods for Characterization of Extracellular Vesicles

Extracellular vesicles (ECVs) are nano-sized vesicles released by all cells in vitro as well as in vivo. Their role has been implicated mainly in cell–cell communication, but also in disease biomarkers and more recently in gene delivery. They represent a snapshot of the cell status at the moment of release and carry bioreactive macromolecules such as nucleic acids, proteins, and lipids. A major limitation in this emerging new field is the availability/awareness of techniques to isolate and properly characterize ECVs. The lack of gold standards makes comparing different studies very difficult and may potentially hinder some ECVs-specific evidence. Characterization of ECVs has also recently seen many advances with the use of Nanoparticle Tracking Analysis, flow cytometry, cryo-electron microscopy instruments, and proteomic technologies. In this review, we discuss the latest developments in translational technologies involving characterization methods including the facts in their support and the challenges they face

Standardization of sample collection, isolation and analysis methods in extracellular vesicle research

The emergence of publications on extracellular RNA (exRNA) and extracellular vesicles (EV) has highlighted the potential of these molecules and vehicles as biomarkers of disease and therapeutic targets. These findings have created a paradigm shift, most prominently in the field of oncology, prompting expanded interest in the field and dedication of funds for EV research. At the same time, understanding of EV subtypes, biogenesis, cargo and mechanisms of shuttling remains incomplete. The techniques that can be harnessed to address the many gaps in our current knowledge were the subject of a special workshop of the International Society for Extracellular Vesicles (ISEV) in New York City in October 2012. As part of the &#x201C;ISEV Research Seminar: Analysis and Function of RNA in Extracellular Vesicles (evRNA)&#x201D;, 6 round-table discussions were held to provide an evidence-based framework for isolation and analysis of EV, purification and analysis of associated RNA molecules, and molecular engineering of EV for therapeutic intervention. This article arises from the discussion of EV isolation and analysis at that meeting. The conclusions of the round table are supplemented with a review of published materials and our experience. Controversies and outstanding questions are identified that may inform future research and funding priorities. While we emphasize the need for standardization of specimen handling, appropriate normative controls, and isolation and analysis techniques to facilitate comparison of results, we also recognize that continual development and evaluation of techniques will be necessary as new knowledge is amassed. On many points, consensus has not yet been achieved and must be built through the reporting of well-controlled experiments

miR-21 in the Extracellular Vesicles (EVs) of Cerebrospinal Fluid (CSF): A Platform for Glioblastoma Biomarker Development

Glioblastoma cells secrete extra-cellular vesicles (EVs) containing microRNAs (miRNAs). Analysis of these EV miRNAs in the bio-fluids of afflicted patients represents a potential platform for biomarker development. However, the analytic algorithm for quantitative assessment of EV miRNA remains under-developed. Here, we demonstrate that the reference transcripts commonly used for quantitative PCR (including GAPDH, 18S rRNA, and hsa-miR-103) were unreliable for assessing EV miRNA. In this context, we quantitated EV miRNA in absolute terms and normalized this value to the input EV number. Using this method, we examined the abundance of miR-21, a highly over-expressed miRNA in glioblastomas, in EVs. In a panel of glioblastoma cell lines, the cellular levels of miR-21 correlated with EV miR-21 levels (p<0.05), suggesting that glioblastoma cells actively secrete EVs containing miR-21. Consistent with this hypothesis, the CSF EV miR-21 levels of glioblastoma patients (n=13) were, on average, ten-fold higher than levels in EVs isolated from the CSF of non-oncologic patients (n=13, p<0.001). Notably, none of the glioblastoma CSF harbored EV miR-21 level below 0.25 copies per EV in this cohort. Using this cut-off value, we were able to prospectively distinguish CSF derived from glioblastoma and non-oncologic patients in an independent cohort of twenty-nine patients (Sensitivity=87%; Specificity=93%; AUC=0.91, p<0.01). Our results suggest that CSF EV miRNA analysis of miR-21 may serve as a platform for glioblastoma biomarker development