Long-distance entanglement-based quantum key distribution over optical fiber

We report the first entanglement-based quantum key distribution (QKD) experiment over a 100-km optical fiber. We used superconducting single photon detectors based on NbN nanowires that provide high-speed single photon detection for the 1.5-µm telecom band, an efficient entangled photon pair source that consists of a fiber coupled periodically poled lithium niobate waveguide and ultra low loss filters, and planar lightwave circuit Mach-Zehnder interferometers (MZIs) with ultra stable operation. These characteristics enabled us to perform an entanglement-based QKD experiment over a 100-km optical fiber. In the experiment, which lasted approximately 8 hours, we successfully generated a 16 kbit sifted key with a quantum bit error rate of 6.9 % at a rate of 0.59 bits per second, from which we were able to distill a 3.9 kbit secure key

Megabits secure key rate quantum key distribution

Quantum cryptography (QC) can provide unconditional secure communication between two authorized parties based on the basic principles of quantum mechanics. However, imperfect practical conditions limit its transmission distance and communication speed. Here we implemented the differential phase shift (DPS) quantum key distribution (QKD) with up-conversion assisted hybrid photon detector (HPD) and achieved 1.3 M bits per second secure key rate over a 10-km fiber, which is tolerant against the photon number splitting (PNS) attack, general collective attacks on individual photons, and any other known sequential unambiguous state discrimination (USD) attacks.Comment: 14 pages, 4 figure

Nonimmunoglobulin target loci of activation-induced cytidine deaminase (AID) share unique features with immunoglobulin genes.

Activation-induced cytidine deaminase (AID) is required for both somatic hypermutation and class-switch recombination in activated B cells. AID is also known to target nonimmunoglobulin genes and introduce mutations or chromosomal translocations, eventually causing tumors. To identify as-yet-unknown AID targets, we screened early AID-induced DNA breaks by using two independent genome-wide approaches. Along with known AID targets, this screen identified a set of unique genes (SNHG3, MALAT1, BCL7A, and CUX1) and confirmed that these loci accumulated mutations as frequently as Ig locus after AID activation. Moreover, these genes share three important characteristics with the Ig gene: translocations in tumors, repetitive sequences, and the epigenetic modification of chromatin by H3K4 trimethylation in the vicinity of cleavage sites

Image informatics approaches to advance cancer drug discovery

High content image-based screening assays utilise cell based models to extract and quantify morphological phenotypes induced by small molecules. The rich datasets produced can be used to identify lead compounds in drug discovery efforts, infer compound mechanism of action, or aid biological understanding with the use of tool compounds. Here I present my work developing and applying high-content image based screens of small molecules across a panel of eight genetically and morphologically distinct breast cancer cell lines. I implemented machine learning models to predict compound mechanism of action from morphological data and assessed how well these models transfer to unseen cell lines, comparing the use of numeric morphological features extracted using computer vision techniques against more modern convolutional neural networks acting on raw image data. The application of cell line panels have been widely used in pharmacogenomics in order to compare the sensitivity between genetically distinct cell lines to drug treatments and identify molecular biomarkers that predict response. I applied dimensional reduction techniques and distance metrics to develop a measure of differential morphological response between cell lines to small molecule treatment, which controls for the inherent morphological differences between untreated cell lines. These methods were then applied to a screen of 13,000 lead-like small molecules across the eight cell lines to identify compounds which produced distinct phenotypic responses between cell lines. Putative hits from a subset of approved compounds were then validated in a three-dimensional tumour spheroid assay to determine the functional effect of these compounds in more complex models, as well as proteomics to determine the responsible pathways. Using data generated from the compound screen, I carried out work towards integrating knowledge of chemical structures with morphological data to infer mechanistic information of the unannotated compounds, and assess structure activity relationships from cell-based imaging data

Field test of quantum key distribution in the Tokyo QKD Network

A novel secure communication network with quantum key distribution in a metropolitan area is reported. Different QKD schemes are integrated to demonstrate secure TV conferencing over a distance of 45km, stable long-term operation, and application to secure mobile phones.Comment: 21 pages, 19 figure