Future tonne-scale liquefied noble gas detectors depend on efficient light detection in the VUV range. In the past years Silicon Photomultipliers (SiPMs) have emerged as a valid alternative to standard photomultiplier tubes or large area avalanche photodiodes. The next generation double beta decay experiment, nEXO, with a 5 tonne liquid xenon time projection chamber, will use SiPMs for detecting the 175 nm xenon scintillation light, in order to achieve an energy resolution of σ/Qββ = 1 %. This paper presents recent measurements of the VUV-HD generation SiPMs from Fondazione Bruno Kessler in two complementary setups. It includes measurements of the photon detection efficiency with gaseous xenon scintillation light in a vacuum setup and dark measurements in a dry nitrogen gas setup. We report improved photon detection efficiency at 175 nm compared to previous generation devices, that would meet the criteria of nEXO. Furthermore, we present the projected nEXO detector light collection and energy resolution that could be achieved by using these SiPMs. Index Terms-silicon photomultiplier, xenon detectors, photo detectors, vacuum ultra-violet light, nEXO I. NEUTRINO-LESS DOUBLE BETA DECAY AND NEXO N eutrino-less double beta decay (0νββ) is a hypothetical nuclear decay where two neutrons decay into two protons and two electrons are emitted but no anti-neutrinos are present in the final state. The observation of this process would have a fundamental impact on the Standard Model of Particle Physics, specifically showing a violation of lepton number conservation (|∆L| = 2), and would imply that the neutrino is a Majorana fermion [1], independently of the actual process enabling the decay [2]. Furthermore, the half-life of the decay would shed light on the absolute neutrino mass scale [3]. The nEXO collaboration plans to build a cylindrical singlephase time projection chamber (TPC) filled with 5 tonnes of liquid xenon (LXe), with 90 % enrichment in 136 Xe [4]. nEXO takes advantage of the experience from its predecessor EXO-200 [5], but will incorporate new light and charge detectors [6]. Together with cold electronics sitting inside the LXe, this allows nEXO to achieve an energy resolution of σ/Q ββ = 1 % for the 0νββ decay of 136 Xe (2458.07 ± 0.31 keV [7], [8]).In particular, instead of the EXO-200 Large Area Avalanche Photo-diodes (LAAPDs), nEXO will use Silicon Photomultipliers (SiPMs) for the detection of xenon scintillation light. The SiPMs will fully cover the lateral surface of the cylinder with a total photo-sensitive area of about 4 m 2 , as shown in Figure 1. The devices will be immersed in LXe and placed in the high field region behind the field shaping rings of the TPC field cage [9]. The performance of SiPMs has improved significantly over the past decade and they are especially interesting because of their high gain, on the order of 10 6 , and their single photon resolution capability.The half-life sensitivity of nEXO to the 0νββ decay of 136 Xe is projected to be 9.5 × 10 27 yr for 90 % C.L. after 10 years o...

No abstract

No abstract

We have obtained the structure of the bacterial diterpene synthase, tuberculosinol/iso-tuberculosinol synthase (Rv3378c) from Mycobacterium tuberculosis, a target for anti-infective therapies that block virulence factor formation. This phosphatase adopts the same fold as found in the Z- or cis-prenyltransferases. We also obtained structures containing the tuberculosinyl diphosphate substrate together with one bisphosphonate inhibitor-bound structure. These structures together with the results of site-directed mutagenesis suggest an unusual mechanism of action involving two Tyr residues. Given the similarity in local and global structure between Rv3378c and the M. tuberculosis cis-decaprenyl diphosphate synthase (DPPS; Rv2361c), the possibility exists for the development of inhibitors that target not only virulence but also cell wall biosynthesis, based in part on the structures reported here.

No abstract

Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) have overlapping symptoms, and accurate differential diagnosis is important for targeted intervention and treatment. Previous studies suggest that the deep learning (DL) techniques have the potential to solve the differential diagnosis problem of FTD, AD and normal controls (NCs), but its performance is still unclear. In addition, existing DL-assisted diagnostic studies still rely on hypothesis-based expert-level preprocessing. On the one hand, it imposes high requirements on clinicians and data themselves; On the other hand, it hinders the backtracking of classification results to the original image data, resulting in the classification results cannot be interpreted intuitively. In the current study, a large cohort of 3D T1-weighted structural magnetic resonance imaging (MRI) volumes (n = 4,099) was collected from two publicly available databases, i.e., the ADNI and the NIFD. We trained a DL-based network directly based on raw T1 images to classify FTD, AD and corresponding NCs. And we evaluated the convergence speed, differential diagnosis ability, robustness and generalizability under nine scenarios. The proposed network yielded an accuracy of 91.83% based on the most common T1-weighted sequence [magnetization-prepared rapid acquisition with gradient echo (MPRAGE)]. The knowledge learned by the DL network through multiple classification tasks can also be used to solve subproblems, and the knowledge is generalizable and not limited to a specified dataset. Furthermore, we applied a gradient visualization algorithm based on guided backpropagation to calculate the contribution graph, which tells us intuitively why the DL-based networks make each decision. The regions making valuable contributions to FTD were more widespread in the right frontal white matter regions, while the left temporal, bilateral inferior frontal and parahippocampal regions were contributors to the classification of AD. Our results demonstrated that DL-based networks have the ability to solve the enigma of differential diagnosis of diseases without any hypothesis-based preprocessing. Moreover, they may mine the potential patterns that may be different from human clinicians, which may provide new insight into the understanding of FTD and AD.

No abstract

In this study, the accuracy (precision and trueness) of digital impressions and the fitness of single crowns manufactured based on digital impressions were evaluated. #14-17 epoxy resin dentitions were made, while full-crown preparations of extracted natural teeth were embedded at #16. (1) To assess precision, deviations among repeated scan models made by intraoral scanner TRIOS and MHT and model scanner D700 and inEos were calculated through best-fit algorithm and three-dimensional (3D) comparison. Root mean square (RMS) and color-coded difference images were offered. (2) To assess trueness, micro computed tomography (micro-CT) was used to get the reference model (REF). Deviations between REF and repeated scan models (from (1)) were calculated. (3) To assess fitness, single crowns were manufactured based on TRIOS, MHT, D700 and inEos scan models. The adhesive gaps were evaluated under stereomicroscope after cross-sectioned. Digital impressions showed lower precision and better trueness. Except for MHT, the means of RMS for precision were lower than 10 μm. Digital impressions showed better internal fitness. Fitness of single crowns based on digital impressions was up to clinical standard. Digital impressions could be an alternative method for single crowns manufacturing.