Molecular diagnostics of myeloproliferative neoplasms

Since the discovery of the JAK2 V617F mutation in the majority of the myeloproliferative neoplasms (MPN) of polycythemia vera, essential thrombocythemia and primary myelofibrosis ten years ago, further MPN-specific mutational events, notably in JAK2 exon 12, MPL exon 10 and CALR exon 9 have been identified. These discoveries have been rapidly incorporated into evolving molecular diagnostic algorithms. While many of these mutations appear to have prognostic implications, establishing MPN diagnosis is of immediate clinical importance with selection, implementation and the continual evaluation of the appropriate laboratory methodology to achieve this diagnosis similarly vital. The advantages and limitations of these approaches in identifying and quantitating the common MPN-associated mutations is considered herein with particular regard to their clinical utility. The evolution of molecular diagnostic applications and platforms has occurred in parallel with the discovery of MPN-associated mutations and it therefore appears likely that emerging technologies such as next-generation sequencing and digital PCR will in the future, play an increasing role in the molecular diagnosis of MPN. 

Handling Sequential Observations in Intelligent Surveillance

Demand for intelligent surveillance in public transport systems is growing due to the increased threats of terrorist attack, vandalism and litigation. The aim of intelligent surveillance is in-time reaction to information received from various monitoring devices, especially CCTV systems. However, video analytic algorithms can only provide static assertions, whilst in reality, many related events happen in sequence and hence should be modeled sequentially. Moreover, analytic algorithms are error-prone, hence how to correct the sequential analytic results based on new evidence (external information or later sensing discovery) becomes an interesting issue. In this paper, we introduce a high-level sequential observation modeling framework which can support revision and update on new evidence. This framework adapts the situation calculus to deal with uncertainty from analytic results. The output of the framework can serve as a foundation for event composition. We demonstrate the significance and usefulness of our framework with a case study of a bus surveillance project.

Gamma-ray diagnostics of Type Ia supernovae. Predictions of observables from three-dimensional modeling

Context. Although the question of progenitor systems and detailed explosion mechanisms still remains a matter of discussion, it is commonly believed that Type Ia supernovae (SNe Ia) are production sites of large amounts of radioactive nuclei. Even though the gamma-ray emission due to radioactive decays is responsible for powering the light curves of SNe Ia, gamma rays themselves are of particular interest as a diagnostic tool because they directly lead to deeper insight into the nucleosynthesis and the kinematics of these explosion events. Aims: We study the evolution of gamma-ray line and continuum emission of SNe Ia with the objective of analyzing the relevance of observations in this energy range. We seek to investigate the chances for the success of future MeV missions regarding their capabilities for constraining the intrinsic properties and the physical processes of SNe Ia. Methods: Focusing on two of the most broadly discussed SN Ia progenitor scenarios - a delayed detonation in a Chandrasekhar-mass white dwarf (WD) and a violent merger of two WDs - we used three-dimensional explosion models and performed radiative transfer simulations to obtain synthetic gamma-ray spectra. Both chosen models produce the same mass of 56Ni and have similar optical properties that are in reasonable agreement with the recently observed supernova SN 2011fe. We examine the gamma-ray spectra with respect to their distinct features and draw connections to certain characteristics of the explosion models. Applying diagnostics, such as line and hardness ratios, the detection prospects for future gamma-ray missions with higher sensitivities in the MeV energy range are discussed. Results: In contrast to the optical regime, the gamma-ray emission of our two chosen models proves to be quite different. The almost direct connection of the emission of gamma rays to fundamental physical processes occurring in SNe Ia permits additional constraints concerning several explosion model properties that are not easily accessible within other wavelength ranges. Proposed future MeV missions such as GRIPS will resolve all spectral details only for nearby SNe Ia, but hardness ratio and light curve measurements still allow for a distinction of the two different models at 10 Mpc and 16 Mpc for an exposure time of 106 s. The possibility of detecting the strongest line features up to the Virgo distance will offer the opportunity to build up a first sample of SN Ia detections in the gamma-ray energy range and underlines the importance of future space observatories for MeV gamma rays.

A potentiometric biosensor for rapid on-site disease diagnostics

Quantitative point-of-care (POC) devices are the next generation for serological disease diagnosis. Whilst pathogen serology is typically performed by centralized laboratories using Enzyme-Linked ImmunoSorbent Assay (ELISA), faster on-site diagnosis would infer improved disease management and treatment decisions. Using the model pathogen Bovine Herpes Virus-1 (BHV-1) this study employs an extended-gate field-effect transistor (FET) for direct potentiometric serological diagnosis. BHV-1 is a major viral pathogen of Bovine Respiratory Disease (BRD), the leading cause of economic loss ($2 billion annually in the US only) to the cattle and dairy industry. To demonstrate the sensor capabilities as a diagnostic tool, BHV-1 viral protein gE was expressed and immobilized on the sensor surface to serve as a capture antigen for a BHV-1-specific antibody (anti-gE), produced in cattle in response to viral infection. The gE-coated immunosensor was shown to be highly sensitive and selective to anti-gE present in commercially available anti-BHV-1 antiserum and in real serum samples from cattle with results being in excellent agreement with Surface Plasmon Resonance (SPR) and ELISA. The FET sensor is significantly faster than ELISA (<10 min), a crucial factor for successful disease intervention. This sensor technology is versatile, amenable to multiplexing, easily integrated to POC devices, and has the potential to impact a wide range of human and animal diseases.

Immunohistochemistry should undergo robust validation equivalent to that of molecular diagnostics

Immunohistochemistry (IHC) is a widely available and highly utilised tool in diagnostic histopathology and is used to guide treatment options as well as provide prognostic information. IHC is subjected to qualitative and subjective assessment, which has been criticised for a lack of stringency, while PCR-based molecular diagnostic validations by comparison are regarded as very rigorous. It is essential that IHC tests are validated through evidence-based procedures. With the move to ISO15189 (2012), not just of the accuracy, specificity and reproducibility of each test need to be determined and managed, but also the degree of uncertainty and the delivery of such tests. The recent update to ISO 15189 (2012) states that it is appropriate to consider the potential uncertainty of measurement of the value obtained in the laboratory and how that may impact on prognostic or predictive thresholds. In order to highlight the problems surrounding IHC validity, we reviewed the measurement of Ki67and p53 in the literature. Both of these biomarkers have been incorporated into clinical care by pathology laboratories worldwide. The variation seen appears excessive even when measuring centrally stained slides from the same cases. We therefore propose in this paper to establish the basis on which IHC laboratories can bring the same level of robust validation seen in the molecular pathology laboratories and the principles applied to all routine IHC tests.

Establishing the Evidence Bar for Molecular Diagnostics in Personalised Cancer Care

While personalised cancer medicine holds great promise, targeting therapies to the biological characteristics of patients is limited by the number of validated biomarkers currently available. The implementation of biomarkers has undergone many challenges with few biomarkers reaching cancer patients in the clinic. There have been many biomarkers that have been published and claimed to be therapeutically useful, but few become part of the clinical decision-making process due to technical, validation and market access issues. To reduce this attrition rate, there is a significant need for policy makers and reimbursement agencies to define specific evidence requirements for the introduction of biomarkers into clinical practice. Once these requirements are more clearly defined, in an analogous manner to pharmaceuticals, researchers and diagnostic companies can better focus their biomarker research and development on meeting these specific requirements, which should lead to the more rapid introduction of new molecular oncology tests for patient benefit.

Electron-Impact Uncertainty Analysis and its Impact on Certain Temperature Diagnostics

In this study we calculate the electron-impact uncertainties in atomic data for direct ionization and recombination and investigate the role of these uncertainties on spectral diagnostics. We outline a systematic approach to assigning meaningful uncertainties that vary with electron temperature. Once these uncertainty parameters have been evaluated, we can then calculate the uncertainties on key diagnostics through a Monte Carlo routine, using the Astrophysical Emission Code (APEC) [Smith et al. 2001]. We incorporate these uncertainties into well known temperature diagnostics, such as the Lyman alpha versus resonance line ratio and the G ratio. We compare these calculations to a study performed by [Testa et al. 2004], where significant discrepancies in the two diagnostic ratios were observed. We conclude that while the atomic physics uncertainties play a noticeable role in the discrepancies observed by Testa, they do not explain all of them. This indicates that there is another physical process occurring in the system that is not being taken into account. This work is supported in part by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant no. 1262851 and by the Smithsonian Institution.