Ga^+ beam lithography for nanoscale silicon reactive ion etching

By using a dry etch chemistry which relies on the highly preferential etching of silicon, over that of gallium (Ga), we show resist-free fabrication of precision, high aspect ratio nanostructures and microstructures in silicon using a focused ion beam (FIB) and an inductively coupled plasma reactive ion etcher (ICP-RIE). Silicon etch masks are patterned via Ga^+ ion implantation in a FIB and then anisotropically etched in an ICP-RIE using fluorinated etch chemistries. We determine the critical areal density of the implanted Ga layer in silicon required to achieve a desired etch depth for both a Pseudo Bosch (SF_6/C_4F_8) and cryogenic fluorine (SF_6/O_2) silicon etching. High fidelity nanoscale structures down to 30 nm and high aspect ratio structures of 17:1 are demonstrated. Since etch masks may be patterned on uneven surfaces, we utilize this lithography to create multilayer structures in silicon. The linear selectivity versus implanted Ga density enables grayscale lithography. Limits on the ultimate resolution and selectivity of Ga lithography are also discussed

Frequent Cross-Species Transmission of Parvoviruses among Diverse Carnivore Hosts

Although parvoviruses are commonly described in domestic carnivores, little is known about their biodiversity in nondomestic species. A phylogenetic analysis of VP2 gene sequences from puma, coyote, gray wolf, bobcat, raccoon, and striped skunk revealed two major groups related to either feline panleukopenia virus (“FPV-like”) or canine parvovirus (“CPV-like”). Crossspecies transmission was commonplace, with multiple introductions into each host species but, with the exception of raccoons, relatively little evidence for onward transmission in nondomestic species

The depression in visual impairment trial (DEPVIT): trial design and protocol

<b>Background</b> The prevalence of depression in people with a visual disability is high but screening for depression and referral for treatment is not yet an integral part of visual rehabilitation service provision. One reason for this may be that there is no good evidence about the effectiveness of treatments in this patient group. This study is the first to evaluate the effect of depression treatments on people with a visual impairment and co morbid depression.<p></p> <b>Methods/design</b> The study is an exploratory, multicentre, individually randomised waiting list controlled trial. Participants will be randomised to receive Problem Solving Therapy (PST), a ‘referral to the GP’ requesting treatment according to the NICE’s ‘stepped care’ recommendations or the waiting list arm of the trial. The primary outcome measure is change (from randomisation) in depressive symptoms as measured by the Beck’s Depression Inventory (BDI-II) at 6 months. Secondary outcomes include change in depressive symptoms at 3 months, change in visual function as measured with the near vision subscale of the VFQ-48 and 7 item NEI-VFQ at 3 and 6 months, change in generic health related quality of life (EQ5D), the costs associated with PST, estimates of incremental cost effectiveness, and recruitment rate estimation.<p></p> <b>Discussion</b> Depression is prevalent in people with disabling visual impairment. This exploratory study will establish depression screening and referral for treatment in visual rehabilitation clinics in the UK. It will be the first to explore the efficacy of PST and the effectiveness of NICE’s ‘stepped care’ approach to the treatment of depression in people with a visual impairment.<p></p&gt

Discovering cancer genes by integrating network and functional properties

<p>Abstract</p> <p>Background</p> <p>Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes.</p> <p>Methods</p> <p>Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1.</p> <p>Results</p> <p>Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1.</p> <p>Conclusion</p> <p>Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.</p

Phase transition in Random Circuit Sampling

Quantum computers hold the promise of executing tasks beyond the capability of classical computers. Noise competes with coherent evolution and destroys long-range correlations, making it an outstanding challenge to fully leverage the computation power of near-term quantum processors. We report Random Circuit Sampling (RCS) experiments where we identify distinct phases driven by the interplay between quantum dynamics and noise. Using cross-entropy benchmarking, we observe phase boundaries which can define the computational complexity of noisy quantum evolution. We conclude by presenting an RCS experiment with 70 qubits at 24 cycles. We estimate the computational cost against improved classical methods and demonstrate that our experiment is beyond the capabilities of existing classical supercomputers

Characterization of 4-HNE Modified L-FABP Reveals Alterations in Structural and Functional Dynamics

4-Hydroxynonenal (4-HNE) is a reactive α,β-unsaturated aldehyde produced during oxidative stress and subsequent lipid peroxidation of polyunsaturated fatty acids. The reactivity of 4-HNE towards DNA and nucleophilic amino acids has been well established. In this report, using proteomic approaches, liver fatty acid-binding protein (L-FABP) is identified as a target for modification by 4-HNE. This lipid binding protein mediates the uptake and trafficking of hydrophobic ligands throughout cellular compartments. Ethanol caused a significant decrease in L-FABP protein (P<0.001) and mRNA (P<0.05), as well as increased poly-ubiquitinated L-FABP (P<0.001). Sites of 4-HNE adduction on mouse recombinant L-FABP were mapped using MALDI-TOF/TOF mass spectrometry on apo (Lys57 and Cys69) and holo (Lys6, Lys31, His43, Lys46, Lys57 and Cys69) L-FABP. The impact of 4-HNE adduction was found to occur in a concentration-dependent manner; affinity for the fluorescent ligand, anilinonaphthalene-8-sulfonic acid, was reduced from 0.347 µM to Kd1 = 0.395 µM and Kd2 = 34.20 µM. Saturation analyses revealed that capacity for ligand is reduced by approximately 50% when adducted by 4-HNE. Thermal stability curves of apo L-FABP was also found to be significantly affected by 4-HNE adduction (ΔTm = 5.44°C, P<0.01). Computational-based molecular modeling simulations of adducted protein revealed minor conformational changes in global protein structure of apo and holo L-FABP while more apparent differences were observed within the internal binding pocket, revealing reduced area and structural integrity. New solvent accessible portals on the periphery of the protein were observed following 4-HNE modification in both the apo and holo state, suggesting an adaptive response to carbonylation. The results from this study detail the dynamic process associated with L-FABP modification by 4-HNE and provide insight as to how alterations in structural integrity and ligand binding may a contributing factor in the pathogenesis of ALD

Readout of a quantum processor with high dynamic range Josephson parametric amplifiers

We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 $\Omega$ environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250-300 MHz, with input saturation powers up to -95 dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimate of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs.Comment: 9 pages, 8 figure

Measurement-Induced State Transitions in a Superconducting Qubit: Within the Rotating Wave Approximation

Superconducting qubits typically use a dispersive readout scheme, where a resonator is coupled to a qubit such that its frequency is qubit-state dependent. Measurement is performed by driving the resonator, where the transmitted resonator field yields information about the resonator frequency and thus the qubit state. Ideally, we could use arbitrarily strong resonator drives to achieve a target signal-to-noise ratio in the shortest possible time. However, experiments have shown that when the average resonator photon number exceeds a certain threshold, the qubit is excited out of its computational subspace, which we refer to as a measurement-induced state transition. These transitions degrade readout fidelity, and constitute leakage which precludes further operation of the qubit in, for example, error correction. Here we study these transitions using a transmon qubit by experimentally measuring their dependence on qubit frequency, average photon number, and qubit state, in the regime where the resonator frequency is lower than the qubit frequency. We observe signatures of resonant transitions between levels in the coupled qubit-resonator system that exhibit noisy behavior when measured repeatedly in time. We provide a semi-classical model of these transitions based on the rotating wave approximation and use it to predict the onset of state transitions in our experiments. Our results suggest the transmon is excited to levels near the top of its cosine potential following a state transition, where the charge dispersion of higher transmon levels explains the observed noisy behavior of state transitions. Moreover, occupation in these higher energy levels poses a major challenge for fast qubit reset