Development and clinical validation of a loop-mediated isothermal amplification method for the rapid detection of Neisseria meningitidis

Loop-mediated isothermal amplification (LAMP) is an innovative technique that allows the rapid detection of target nucleic acid sequences under isothermal conditions without the need for complex instrumentation. The development, optimization, and clinical validation of a LAMP assay targeting the ctrA gene for the rapid detection of capsular Neisseria meningitidis were described. Highly specific detection of capsular N. meningitidis type strains and clinical isolates was demonstrated, with no cross-reactivity with other Neisseria spp. or with a comprehensive panel of other common human pathogens. The lower limit of detection was 6 ctrA gene copies detectable in 48 min, with positive reactions readily identifiable visually via a simple color change. Higher copy numbers could be detected in as little as 16 min. When applied to a total of 394 clinical specimens, the LAMP assay in comparison to a conventional TaqMan® based real-time polymerase chain reaction system demonstrated a sensitivity of 100% and a specificity of 98.9% with a ? coefficient of 0.942. The LAMP method represents a rapid, sensitive, and highly specific technique for the detection of N. meningitidis and has the potential to be used as a point-of-care molecular test and in resource-poor settings.

COHERENCE AND DOUBLE-PASS AMPLIFICATION IN GE SOFT-X-RAY LASER

From measurements of spatial coherence and beam divergence of Ge soft x-ray laser at a far field, the x-ray laser beam has been characterized as a partially coherent Gaussian beam. Double-pass amplification will improve spatial and temporal coherence, spectral brightness and efficiency. Close to 100% geometrical coupling efficiency has been obtained in double pass amplification in Ge. Transient loss of feedback is attributed to mirror structure damage within the build-up time of the x-ray laser. Prospect for generation of coherent x-ray laser beam is discussed.

Illumination invariant facial recognition using a piecewise-constant lighting model

In this paper we demonstrate a simple and novel illumination model that can be used for illumination invariant facial recognition. This model requires no prior knowledge of the illumination conditions and can be used when there is only a single training image per-person. The proposed illumination model separates the effects of illumination over a small area of the face into two components; an additive component modelling the mean illumination and a multiplicative component, modelling the variance within the facial area. Illumination invariant facial recognition is performed in a piecewise manner, by splitting the face image into blocks, then normalizing the illumination within each block based on the new lighting model. The assumptions underlying this novel lighting model have been verified on the YaleB face database. We show that magnitude 2D Fourier features can be used as robust facial descriptors within the new lighting model. Using only a single training image per-person, our new method achieves high (in most cases 100%) identification accuracy on the YaleB, extended YaleB and CMU-PIE face databases.

Identification of MET genomic amplification, protein expression and alternative splice isoforms in neuroblastomas

Crizotinib, a dual anaplastic lymphoma kinase (ALK) and mesenchymal-epithelial transition (MET) tyrosine kinase inhibitor, is currently being evaluated for the treatment of neuroblastoma. Its effects are thought to be mediated mainly via its activity against ALK. Although MET genomic/protein expression status might conceivably affect crizotinib efficacy, this issue has hitherto not received attention in neuroblastomas.

Invariant Information Local Sub-map Filter (IILSF) for Efficient Simultaneous Localisation and Mapping of Large Environments

This paper presents an Invariant Information Local Sub-map Filter (IILSF) as a technique for consistent Simultaneous Localisation and Mapping (SLAM) in a large environment. It harnesses the benefits of sub-map technique to improve the consistency and efficiency of Extended Kalman Filter (EKF) based SLAM. The IILSF makes use of invariant information obtained from estimated locations of features in independent sub-maps, instead of incorporating every observation directly into the global map. Then the global map is updated at regular intervals. Applying this technique to the EKF based SLAM algorithm: (a) reduces the computational complexity of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. Simulation results show that the method was able to accurately fuse local map observations to generate an efficient and consistent global map, in addition to significantly reducing computational cost and data association ambiguities.