Near-field photocurrent nanoscopy on bare and encapsulated graphene

Opto-electronic devices utilizing graphene have already demonstrated unique capabilities, which are much more difficult to realize with conventional technologies. However, the requirements in terms of material quality and uniformity are very demanding. A major roadblock towards high-performance devices are the nanoscale variations of graphene properties, which strongly impact the macroscopic device behaviour. Here, we present and apply opto-electronic nanoscopy to measure locally both the optical and electronic properties of graphene devices. This is achieved by combining scanning near-field infrared nanoscopy with electrical device read-out, allowing infrared photocurrent mapping at length scales of tens of nanometers. We apply this technique to study the impact of edges and grain boundaries on spatial carrier density profiles and local thermoelectric properties. Moreover, we show that the technique can also be applied to encapsulated graphene/hexagonal boron nitride (h-BN) devices, where we observe strong charge build-up near the edges, and also address a device solution to this problem. The technique enables nanoscale characterization for a broad range of common graphene devices without the need of special device architectures or invasive graphene treatment

A passive transmitter for quantum key distribution with coherent light

Signal state preparation in quantum key distribution schemes can be realized using either an active or a passive source. Passive sources might be valuable in some scenarios; for instance, in those experimental setups operating at high transmission rates, since no externally driven element is required. Typical passive transmitters involve parametric down-conversion. More recently, it has been shown that phase-randomized coherent pulses also allow passive generation of decoy states and Bennett-Brassard 1984 (BB84) polarization signals, though the combination of both setups in a single passive source is cumbersome. In this paper, we present a complete passive transmitter that prepares decoy-state BB84 signals using coherent light. Our method employs sum-frequency generation together with linear optical components and classical photodetectors. In the asymptotic limit of an infinite long experiment, the resulting secret key rate (per pulse) is comparable to the one delivered by an active decoy-state BB84 setup with an infinite number of decoy settings.Comment: 10 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1009.383

Down Syndrome detection with Swin Transformer architecture

Objective: Down Syndrome, also known as Trisomy 21, is a severe genetic disease caused by an extra chromosome 21. For the detection of Trisomy 21, despite those statistical methods have been widely used for screening, karyotyping remains the gold standard and the first level of testing for diagnosis. Due to karyotyping being a time-consuming and labour-intensive procedure, Computer Vision methodologies have been explored to automate the karyotyping process for decades. However, few studies have focused on Down Syndrome detection with the Transformer technique. This study develops a Down-Syndrome-Detector (DSD) architecture based on the Transformer structure, which includes a segmentation module, an alignment module, a classification module, and a Down Syndrome indicator. Methods: The segmentation and classification modules are designed by homogeneous transfer learning at the model level. Transfer learning techniques enable a network to share weights learned from the source domain (e.g., millions of data in ImageNet) and optimize the weights with limited labeled data in the target domain (e.g., less than 6,000 images in BioImLab). The Align-Module is designed to process the segmentation output to fit the classification dataset, and the Down Syndrome Indicator identifies a Down Syndrome case from the classification output. Results: Experiments are first performed on two public datasets BioImLab (119 cases) and Advanced Digital Imaging Research (ADIR, 180 cases). Our performance metrics indicate the good ability of segmentation and classification modules of DSD. Then, the DS detection performance of DSD is evaluated on a private dataset consisting of 1084 cells (including 20 DS cells from 2 singleton cases): 90.0% and 86.1% for cell-level TPR and TNR; 100% and 96.08% for case-level TPR and TNR, respectively. Conclusion: This study develops a pipeline based on the modern Transformer architecture for the detection of Down Syndrome from original metaphase micrographs. Both segmentation and classification models developed in this study are assessed using public datasets with commonly used metrics, and both achieved good results. The DSDproposed in this study reported satisfactory singleton case-specific DS detection results. Significance: As verified by a medical specialist, the developed method may improve Down Syndrome detection efficiency by saving human labor and improving clinical practice

Fully Automatic Karyotyping via Deep Convolutional Neural Networks

Chromosome karyotyping is an important yet labor-intensive procedure for diagnosing genetic diseases. Automating such a procedure drastically reduces the manual work of cytologists and increases congenital disease diagnosing precision. Researchers have contributed to chromosome segmentation and classification for decades. However, very few studies integrate the two tasks as a unified, fully automatic procedure or achieved a promising performance. This paper addresses the gap by presenting: 1) A novel chromosome segmentation module named ChrRender, with the idea of rendering the chromosome instances by combining rich global features from the backbone and coarse mask prediction from Mask R-CNN; 2) A devised chromosome classification module named ChrNet4 that pays more attention to channel-wise dependencies from aggregated informative features and calibrating the channel interdependence; 3) An integrated Render-Attention-Architecture to accomplish fully automatic karyotyping with segmentation and classification modules; 4) A strategy for eliminating differences between training data and segmentation output data to be classified. These proposed methods are implemented in three ways on the public Q-band BioImLab dataset and a G-band private dataset. The results indicate promising performance: 1) on the joint karyotyping task, which predicts a karyotype image by first segmenting an original microscopical image, then classifying each segmentation output with a precision of 89.75% and 94.22% on the BioImLab and private dataset, respectively; 2) On the separate task with two datasets, ChrRender obtained AP50 of 96.652% and 96.809% for segmentation, ChrNet4 achieved 95.24% and 94.07% for classification, respectively. The COCO format annotation files of BioImLab used in this paper are available at https://github.com/Alex17swim/BioImLab The study introduces an integrated workflow to predict a karyotyping image from a Microscopical Chromosome Image. With state-of-the-art performance on a public dataset, the proposed Render-Attention-Architecture has accomplished fully automatic chromosome karyotyping

Device-independent quantum key distribution secure against collective attacks

Device-independent quantum key distribution (DIQKD) represents a relaxation of the security assumptions made in usual quantum key distribution (QKD). As in usual QKD, the security of DIQKD follows from the laws of quantum physics, but contrary to usual QKD, it does not rely on any assumptions about the internal working of the quantum devices used in the protocol. We present here in detail the security proof for a DIQKD protocol introduced in [Phys. Rev. Lett. 98, 230501 (2008)]. This proof exploits the full structure of quantum theory (as opposed to other proofs that exploit the no-signalling principle only), but only holds again collective attacks, where the eavesdropper is assumed to act on the quantum systems of the honest parties independently and identically at each round of the protocol (although she can act coherently on her systems at any time). The security of any DIQKD protocol necessarily relies on the violation of a Bell inequality. We discuss the issue of loopholes in Bell experiments in this context.Comment: 25 pages, 3 figure

Nicotinic acid phosphoribosyltransferase regulates cancer cell metabolism, susceptibility to NAMPT inhibitors and DNA repair.

In the last decade, substantial efforts have been made to identify NAD(+) biosynthesis inhibitors, specifically against nicotinamide phosphoribosyltransferase (NAMPT), as preclinical studies indicate their potential efficacy as cancer drugs. However, the clinical activity of NAMPT inhibitors has proven limited, suggesting that alternative NAD(+) production routes exploited by tumors confer resistance. Here, we show the gene encoding nicotinic acid phosphoribosyltransferase (NAPRT), a second NAD(+)-producing enzyme, is amplified and overexpressed in a subset of common types of cancer, including ovarian cancer, where NAPRT expression correlates with a BRCAness gene expression signature. Both NAPRT and NAMPT increased intracellular NAD(+) levels. NAPRT silencing reduced energy status, protein synthesis, and cell size in ovarian and pancreatic cancer cells. NAPRT silencing sensitized cells to NAMPT inhibitors both in vitro and in vivo; similar results were obtained with the NAPRT inhibitor 2-hydroxynicotinic acid. Reducing NAPRT levels in a BRCA2-deficient cancer cell line exacerbated DNA damage in response to chemotherapeutics. In conclusion, NAPRT-dependent NAD(+) biosynthesis contributes to cell metabolism and to the DNA repair process in a subset of tumors. This knowledge could be used to increase the efficacy of NAMPT inhibitors and chemotherapy. Cancer Res; 77(14); 3857-69. ©2017 AACR

Potentiation of thrombus instability: a contributory mechanism to the effectiveness of antithrombotic medications

© The Author(s) 2018The stability of an arterial thrombus, determined by its structure and ability to resist endogenous fibrinolysis, is a major determinant of the extent of infarction that results from coronary or cerebrovascular thrombosis. There is ample evidence from both laboratory and clinical studies to suggest that in addition to inhibiting platelet aggregation, antithrombotic medications have shear-dependent effects, potentiating thrombus fragility and/or enhancing endogenous fibrinolysis. Such shear-dependent effects, potentiating the fragility of the growing thrombus and/or enhancing endogenous thrombolytic activity, likely contribute to the clinical effectiveness of such medications. It is not clear how much these effects relate to the measured inhibition of platelet aggregation in response to specific agonists. These effects are observable only with techniques that subject the growing thrombus to arterial flow and shear conditions. The effects of antithrombotic medications on thrombus stability and ways of assessing this are reviewed herein, and it is proposed that thrombus stability could become a new target for pharmacological intervention.Peer reviewedFinal Published versio

Characteristics and outcome of Streptococcus pneumoniae endocarditis in the XXI Century: a systematic review of 111 cases (2000-2013)

Streptococcus pneumoniae is an infrequent cause of severe infectious endocarditis (IE). The aim of our study was to describe the epidemiology, clinical and microbiological characteristics, and outcome of a series of cases of S. pneumoniae IE diagnosed in Spain and in a series of cases published since 2000 in the medical literature. We prospectively collected all cases of IE diagnosed in a multicenter cohort of patients from 27 Spanish hospitals (n = 2539). We also performed a systematic review of the literature since 2000 and retrieved all cases with complete clinical data using a pre-established protocol. Predictors of mortality were identified using a logistic regression model. We collected 111 cases of pneumococcal IE: 24 patients from the Spanish cohort and 87 cases from the literature review. Median age was 51 years, and 23 patients (20.7%) were under 15 years. Men accounted for 64% of patients, and infection was community-acquired in 96.4% of cases. The most important underlying conditions were liver disease (27.9%) and immunosuppression (10.8%). A predisposing heart condition was present in only 18 patients (16.2%). Pneumococcal IE affected a native valve in 93.7% of patients. Left-sided endocarditis predominated (aortic valve 53.2% and mitral valve 40.5%). The microbiological diagnosis was obtained from blood cultures in 84.7% of cases. In the Spanish cohort, nonsusceptibility to penicillin was detected in 4.2%. The most common clinical manifestations included fever (71.2%), a new heart murmur (55%), pneumonia (45.9%), meningitis (40.5%), and Austrian syndrome (26.1%). Cardiac surgery was performed in 47.7% of patients. The in-hospital mortality rate was 20.7%. The multivariate analysis revealed the independent risk factors for mortality to be meningitis (OR, 4.3; 95% CI, 1.4-12.9; P < 0.01). Valve surgery was protective (OR, 0.1; 95% CI, 0.04-0.4; P < 0.01). Streptococcus pneumoniae IE is a community-acquired disease that mainly affects native aortic valves. Half of the cases in the present study had concomitant pneumonia, and a considerable number developed meningitis. Mortality was high, mainly in patients with central nervous system (CNS) involvement. Surgery was protective