Oligomerization of amyloid Abeta peptides using hydrogen bonds and hydrophobicity forces

The 16-22 amino acid fragment of the beta-amyloid peptide associated with the Alzheimer's disease, Abeta, is capable of forming amyloid fibrils. Here we study the aggregation mechanism of Abeta(16-22) peptides by unbiased thermodynamic simulations at the atomic level for systems of one, three and six Abeta(16-22) peptides. We find that the isolated Abeta(16-22) peptide is mainly a random coil in the sense that both the alpha-helix and beta-strand contents are low, whereas the three- and six-chain systems form aggregated structures with a high beta-sheet content. Furthermore, in agreement with experiments on Abeta(16-22) fibrils, we find that large parallel beta-sheets are unlikely to form. For the six-chain system, the aggregated structures can have many different shapes, but certain particularly stable shapes can be identified.Comment: 19 pages, 7 figures (to appear in Biophys. J.

Reducing multi-photon rates in pulsed down-conversion by temporal multiplexing

We present a simple technique to reduce the emission rate of higher-order photon events from pulsed spontaneous parametric down-conversion. The technique uses extra-cavity control over a mode locked ultrafast laser to simultaneously increase repetition rate and reduce the energy of each pulse from the pump beam. We apply our scheme to a photonic quantum gate, showing improvements in the non-classical interference visibility for 2-photon and 4-photon experiments, and in the quantum-gate fidelity and entangled state production in the 2-photon case.Comment: 8 pages, 6 figure

On the experimental verification of quantum complexity in linear optics

The first quantum technologies to solve computational problems that are beyond the capabilities of classical computers are likely to be devices that exploit characteristics inherent to a particular physical system, to tackle a bespoke problem suited to those characteristics. Evidence implies that the detection of ensembles of photons, which have propagated through a linear optical circuit, is equivalent to sampling from a probability distribution that is intractable to classical simulation. However, it is probable that the complexity of this type of sampling problem means that its solution is classically unverifiable within a feasible number of trials, and the task of establishing correct operation becomes one of gathering sufficiently convincing circumstantial evidence. Here, we develop scalable methods to experimentally establish correct operation for this class of sampling algorithm, which we implement with two different types of optical circuits for 3, 4, and 5 photons, on Hilbert spaces of up to 50,000 dimensions. With only a small number of trials, we establish a confidence >99% that we are not sampling from a uniform distribution or a classical distribution, and we demonstrate a unitary specific witness that functions robustly for small amounts of data. Like the algorithmic operations they endorse, our methods exploit the characteristics native to the quantum system in question. Here we observe and make an application of a "bosonic clouding" phenomenon, interesting in its own right, where photons are found in local groups of modes superposed across two locations. Our broad approach is likely to be practical for all architectures for quantum technologies where formal verification methods for quantum algorithms are either intractable or unknown.Comment: Comments welcom

No imminent quantum supremacy by boson sampling

It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the platform of photons in linear optics, which has sparked interest as a rapid way to demonstrate this quantum supremacy. Photon statistics are governed by intractable matrix functions known as permanents, which suggests that sampling from the distribution obtained by injecting photons into a linear-optical network could be solved more quickly by a photonic experiment than by a classical computer. The contrast between the apparently awesome challenge faced by any classical sampling algorithm and the apparently near-term experimental resources required for a large boson sampling experiment has raised expectations that quantum supremacy by boson sampling is on the horizon. Here we present classical boson sampling algorithms and theoretical analyses of prospects for scaling boson sampling experiments, showing that near-term quantum supremacy via boson sampling is unlikely. While the largest boson sampling experiments reported so far are with 5 photons, our classical algorithm, based on Metropolised independence sampling (MIS), allowed the boson sampling problem to be solved for 30 photons with standard computing hardware. We argue that the impact of experimental photon losses means that demonstrating quantum supremacy by boson sampling would require a step change in technology.Comment: 25 pages, 9 figures. Comments welcom

Testing foundations of quantum mechanics with photons

The foundational ideas of quantum mechanics continue to give rise to counterintuitive theories and physical effects that are in conflict with a classical description of Nature. Experiments with light at the single photon level have historically been at the forefront of tests of fundamental quantum theory and new developments in photonics engineering continue to enable new experiments. Here we review recent photonic experiments to test two foundational themes in quantum mechanics: wave-particle duality, central to recent complementarity and delayed-choice experiments; and Bell nonlocality where recent theoretical and technological advances have allowed all controversial loopholes to be separately addressed in different photonics experiments.Comment: 10 pages, 5 figures, published as a Nature Physics Insight review articl

Subspace Projection Approaches to Classification and Visualization of Neural Network-Level Encoding Patterns

Recent advances in large-scale ensemble recordings allow monitoring of activity patterns of several hundreds of neurons in freely behaving animals. The emergence of such high-dimensional datasets poses challenges for the identification and analysis of dynamical network patterns. While several types of multivariate statistical methods have been used for integrating responses from multiple neurons, their effectiveness in pattern classification and predictive power has not been compared in a direct and systematic manner. Here we systematically employed a series of projection methods, such as Multiple Discriminant Analysis (MDA), Principal Components Analysis (PCA) and Artificial Neural Networks (ANN), and compared them with non-projection multivariate statistical methods such as Multivariate Gaussian Distributions (MGD). Our analyses of hippocampal data recorded during episodic memory events and cortical data simulated during face perception or arm movements illustrate how low-dimensional encoding subspaces can reveal the existence of network-level ensemble representations. We show how the use of regularization methods can prevent these statistical methods from over-fitting of training data sets when the trial numbers are much smaller than the number of recorded units. Moreover, we investigated the extent to which the computations implemented by the projection methods reflect the underlying hierarchical properties of the neural populations. Based on their ability to extract the essential features for pattern classification, we conclude that the typical performance ranking of these methods on under-sampled neural data of large dimension is MDA>PCA>ANN>MGD

Metabolism within the tumor microenvironment and its implication on cancer progression: an ongoing therapeutic target

Since reprogramming energy metabolism is considered a new hallmark of cancer, tumor metabolism is again in the spotlight of cancer research. Many studies have been carried out and many possible therapies have been developed in the last years. However, tumor cells are not alone. A series of extracellular components and stromal cells, such as endothelial cells, cancer-associated fibroblasts, tumor-associated macrophages and tumor-infiltrating T cells, surround tumor cells in the so-called tumor microenvironment. Metabolic features of these cells are being studied in deep in order to find relationships between metabolism within the tumor microenvironment and tumor progression. Moreover, it cannot be forgotten that tumor growth is able to modulate host metabolism and homeostasis, so that tumor microenvironment is not the whole story. Importantly, the metabolic switch in cancer is just a consequence of the flexibility and adaptability of metabolism and should not be surprising. Treatments of cancer patients with combined therapies including anti-tumor agents with those targeting stromal cell metabolism, anti-angiogenic drugs and/or immunotherapy are being developed as promising therapeutics.Mª Carmen Ocaña is recipient of a predoctoral FPU grant from the Spanish Ministry of Education, Culture and Sport. Supported by grants BIO2014-56092-R (MINECO and FEDER), P12-CTS-1507 (Andalusian Government and FEDER) and funds from group BIO-267 (Andalusian Government). The "CIBER de Enfermedades Raras" is an initiative from the ISCIII (Spain). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript

Emergency department visits, ambulance calls, and mortality associated with an exceptional heat wave in Sydney, Australia, 2011: a time-series analysis

<p>Abstract</p> <p>Background</p> <p>From January 30-February 6, 2011, New South Wales was affected by an exceptional heat wave, which broke numerous records. Near real-time Emergency Department (ED) and ambulance surveillance allowed rapid detection of an increase in the number of heat-related ED visits and ambulance calls during this period. The purpose of this study was to quantify the excess heat-related and all-cause ED visits and ambulance calls, and excess all-cause mortality, associated with the heat wave.</p> <p>Methods</p> <p>ED and ambulance data were obtained from surveillance and administrative databases, while mortality data were obtained from the state death registry. The observed counts were compared with the average counts from the same period from 2006/07 through 2009/10, and a Poisson regression model was constructed to calculate the number of excess ED visits, ambulance and deaths after adjusting for calendar and lag effects.</p> <p>Results</p> <p>During the heat wave there were 104 and 236 ED visits for heat effects and dehydration respectively, and 116 ambulance calls for heat exposure. From the regression model, all-cause ED visits increased by 2% (95% CI 1.01-1.03), all-cause ambulance calls increased by 14% (95% CI 1.11-1.16), and all-cause mortality increased by 13% (95% CI 1.06-1.22). Those aged 75 years and older had the highest excess rates of all outcomes.</p> <p>Conclusions</p> <p>The 2011 heat wave resulted in an increase in the number of ED visits and ambulance calls, especially in older persons, as well as an increase in all-cause mortality. Rapid surveillance systems provide markers of heat wave impacts that have fatal outcomes.</p

Loss of tolerance to gut immunity protein; glycoprotein 2 (GP2) is associated with progressive disease course in primary sclerosing cholangitis

Abstract Glycoprotein 2[GP2] is a specific target of pancreatic autoantibodies[PAbs] in Crohn’s disease(CD) and is involved in gut innate immunity processes. Our aim was to evaluate the prevalence and prognostic potential of PAbs in primary sclerosing cholangitis(PSC). Sixty-five PSC patients were tested for PAbs by indirect immunofluorescence and compared with healthy (n = 100) and chronic liver disease controls(CLD, n = 488). Additionally, a panel of anti-microbial antibodies and secretory (s)IgA levels were measured, as markers of bacterial translocation and immune dysregulation. PAbs were more frequent in PSC(46.2%) compared to controls(healthy:0% and CLD:4.5%), [P < 0.001, for each]. Occurrence of anti-GP2 antibody was 30.8% (20/65) and was exclusively of IgA isotype. Anti-GP2 IgA positive patients had higher sIgA levels (P = 0.021). With flow-cytometry, 68.4% (13/19) of anti-GP2 IgA antibodies were bound with secretory component, suggesting an active retro-transportation of anti-GP2 from the gut lumen to the mucosa. Anti-GP2 IgA was associated with shorter transplant-free survival [PLogRank < 0.01] during the prospective follow-up (median, IQR: 87 [9–99] months) and remained an independent predictor after adjusting for Mayo risk score(HR: 4.69 [1.05–21.04], P = 0.043). These results highlight the significance of gut-liver interactions in PSC. Anti-GP2 IgA might be a valuable tool for risk stratification in PSC and considered as a potential therapeutic target