Gaussian entanglement distribution with gigahertz bandwidth

The distribution of entanglement with Gaussian statistic can be used to generate a mathematically-proven secure key for quantum cryptography. The distributed secret key rate is limited by the {entanglement strength, the entanglement bandwidth and the bandwidth of the photo-electric detectors}. The development of a source for strongly, bi-partite entangled light with high bandwidth promises an increased measurement speed and a linear boost in the secure data rate. Here, we present the experimental realization of a Gaussian entanglement source with a bandwidth of more than 1.25\,GHz. The entanglement spectrum was measured with balanced homodyne detectors and was quantified via the inseparability criterion introduced by Duan and coworkers with a critical value of 4 below which entanglement is certified. Our measurements yielded an inseparability value of about 1.8 at a frequency of 300\,MHz to about 2.8 at 1.2\,GHz extending further to about 3.1 at 1.48\,GHz. In the experiment we used two 2.6\,mm long monolithic periodically poled potassium titanyl phosphate (PPKTP) resonators to generate two squeezed fields at the telecommunication wavelength of 1550\,nm. Our result proves the possibility of generating and detecting strong continuous-variable entanglement with high speed.Comment: 5 pages, 3 figures, published in Optics Letter

Reduction of Classical Measurement Noise via Quantum-Dense Metrology

Quantum-dense metrology (QDM) constitutes a special case of quantum metrology in which two orthogonal phase space projections of a signal are simultaneously sensed beyond the shot noise limit. Previously it was shown that the additional sensing channel that is provided by QDM contains information that can be used to identify and to discard corrupted segments from the measurement data. Here, we demonstrate a proof-of-principle experiment in which this information is used for improving the sensitivity without discarding any measurement segments. Our measurement reached sub-shot-noise performance although initially strong classical noise polluted the data

The signal sequence influences post-translational ER translocation at distinct stages

The metazoan Sec61 translocon transports polypeptides into and across the membrane of the endoplasmic reticulum via two major routes, a well-established co-translational pathway and a post-translational alternative. We have used two model substrates to explore the elements of a secretory protein precursor that preferentially direct it towards a co- or post-translational pathway for ER translocation. Having first determined the capacity of precursors to enter ER derived microsomes post-translationally, we then exploited semi-permeabilized mammalian cells specifically depleted of key membrane components using siRNA to address their contribution to the membrane translocation process. These studies suggest precursor chain length is a key factor in the post-translational translocation at the mammalian ER, and identify Sec62 and Sec63 as important components acting on this route. This role for Sec62 and Sec63 is independent of the signal sequence that delivers the precursor to the ER. However, the signal sequence can influence the subsequent membrane translocation process, conferring sensitivity to a small molecule inhibitor and dictating reliance on the molecular chaperone BiP. Our data support a model where secretory protein precursors that fail to engage the signal recognition particle, for example because they are short, are delivered to the ER membrane via a distinct route that is dependent upon both Sec62 and Sec63. Although this requirement for Sec62 and Sec63 is unaffected by the specific signal sequence that delivers a precursor to the ER, this region can influence subsequent events, including both Sec61 mediated transport and the importance of BiP for membrane translocation. Taken together, our data suggest that an ER signal sequence can regulate specific aspects of Sec61 mediated membrane translocation at a stage following Sec62/Sec63 dependent ER delivery.Nicholas Johnson, Sarah Haßdenteufel, Melanie Theis, Adrienne W. Paton, James C. Paton, Richard Zimmermann, Stephen Hig

Simultaneous silencing of isoamylases ISA1, ISA2 and ISA3 by multi-target RNAi in potato tubers leads to decreased starch content and an early sprouting phenotype

<div><p>Isoamylases hydrolyse (1–6)-alpha-D-glucosidic linkages in starch and are involved in both starch granule formation and starch degradation. In plants, three isoamylase isoforms with distinct functions in starch synthesis (ISA1 and ISA2) and degradation (ISA3) have been described. Here, we created transgenic potato plants with simultaneously decreased expression of all three isoamylases using a chimeric RNAi construct targeting all three isoforms. Constitutive expression of the hairpin RNA using the 35S CaMV promoter resulted in efficient silencing of all three isoforms in leaves, growing tubers, and sprouting tubers. Neither plant growth nor tuber yield was effected in isoamylase-deficient potato lines. Interestingly, starch metabolism was found to be impaired in a tissue-specific manner. While leaf starch content was unaffected, tuber starch was significantly reduced. The reduction in tuber starch content in the transgenic plants was accompanied by a decrease in starch granules size, an increased sucrose content and decreased hexose levels. Despite the effects on granule size, only little changes in chain length composition of soluble and insoluble glucose polymers were detected. The transgenic tubers displayed an early sprouting phenotype that was accompanied by an increased level of sucrose in parenchyma cells below the outgrowing bud. Since high sucrose levels promote sprouting, we propose that the increased number of small starch granules may cause an accelerated turnover of glucan chains and hence a more rapid synthesis of sucrose. This observation links alterations in starch structure/degradation with developmental processes like meristem activation and sprout outgrowth in potato tubers.</p></div

Impact of <i>ISA</i> silencing on tuber sprouting.

<p>Tubers of 5 plants each from wild type (WT) and transgenic lines 7, 16 and 39 were stored after harvest at room temperature in darkness. A) Sprouting kinetics. To monitor the impact on dormancy length, 2–5 similar sized tubers from each plant were picked (n = 13–20) and their sprouting behaviour was regularly scored over a 15-week period until 100% sprouting had been reached in wild-type tubers. A tuber was considered to sprout when sprouts of 2 mm length became visible. B) Photographs of transgenic (lines 7, 16, 39) and control tubers taken after 13 weeks of storage showing that the transgenic lines sprout earlier than the wild-type controls (WT). C) Number of sprouts per tuber. Number of sprouts formed per tuber were counted from 13–20 individual tubers. Values represent the mean +/- SE. Significant differences to wild type were calculated using two-tailed t-test assuming equal variances and are indicated by asterisks (**p<0.01, *p<0.05).</p

Starch structure determined as relative chain length distribution.

<p>Starch from sprouting tubers was either isolated from parenchyma associated with the sprout (A) or (B) from parenchyma not associated with the sprout. Line 7 (blue), line 16 (red), line 39 (grey) and the wild-type control (WT; black). Values represent mean +/- SE of 3–4 biological replicates.</p

Starch granule size distribution.

<p>Size distribution was determined as pixels’ size from ca. 150 starch granules of each replicate using ImageJ software as schematically shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0181444#pone.0181444.g005" target="_blank">Fig 5</a>. A) Granules were compiled into groups and the number of granules within a specific range (e.g. >25, >50, >75, etc.) were counted, calculated as relative percentage of total number and values cumulatively plotted. The inset shows the median granule size of each genotype. B) Bar charts of selected groups of relative starch granule sizes subjected to t-test test analysis. Values represent means +/- SE from 3 individual tubers (n = 3). Significant differences to wild type are indicated by asterisks (*p<0.05). Line 7 (light grey), line 16 (dark grey), line 39 (white) wild-type control (WT; black).</p