Zebrafish cerebrospinal fluid mediates cell survival through a retinoid signaling pathway

Cerebrospinal fluid (CSF) includes conserved factors whose function is largely unexplored. To assess the role of CSF during embryonic development, CSF was repeatedly drained from embryonic zebrafish brain ventricles soon after their inflation. Removal of CSF increased cell death in the diencephalon, indicating a survival function. Factors within the CSF are required for neuroepithelial cell survival as injected mouse CSF but not artificial CSF could prevent cell death after CSF depletion. Mass spectrometry analysis of the CSF identified retinol binding protein 4 (Rbp4), which transports retinol, the precursor to retinoic acid (RA). Consistent with a role for Rbp4 in cell survival, inhibition of Rbp4 or RA synthesis increased neuroepithelial cell death. Conversely, ventricle injection of exogenous human RBP4 plus retinol, or RA alone prevented cell death after CSF depletion. Zebrafish rbp4 is highly expressed in the yolk syncytial layer, suggesting Rbp4 protein and retinol/RA precursors can be transported into the CSF from the yolk. In accord with this suggestion, injection of human RBP4 protein into the yolk prevents neuroepithelial cell death in rbp4 loss-of-function embryos. Together, these data support the model that Rbp4 and RA precursors are present within the CSF and used for synthesis of RA, which promotes embryonic neuroepithelial survival

Koala cathelicidin PhciCath5 has antimicrobial activity, including against Chlamydia pecorum.

Devastating fires in Australia over 2019-20 decimated native fauna and flora, including koalas. The resulting population bottleneck, combined with significant loss of habitat, increases the vulnerability of remaining koala populations to threats which include disease. Chlamydia is one disease which causes significant morbidity and mortality in koalas. The predominant pathogenic species, Chlamydia pecorum, causes severe ocular, urogenital and reproductive tract disease. In marsupials, including the koala, gene expansions of an antimicrobial peptide family known as cathelicidins have enabled protection of immunologically naïve pouch young during early development. We propose that koala cathelicidins are active against Chlamydia and other bacteria and fungi. Here we describe ten koala cathelicidins, five of which contained full length coding sequences that were widely expressed in tissues throughout the body. Focusing on these five, we investigate their antimicrobial activity against two koala C. pecorum isolates from distinct serovars; MarsBar and IPTaLE, as well as other bacteria and fungi. One cathelicidin, PhciCath5, inactivated C. pecorum IPTaLE and MarsBar elementary bodies and significantly reduced the number of inclusions compared to the control (p<0.0001). Despite evidence of cathelicidin expression within tissues known to be infected by Chlamydia, natural PhciCath5 concentrations may be inadequate in vivo to prevent or control C. pecorum infections in koalas. PhciCath5 also displayed antimicrobial activity against fungi and Gram negative and positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA). Electrostatic interactions likely drive PhciCath5 adherence to the pathogen cell membrane, followed by membrane permeabilisation leading to cell death. Activity against E. coli was reduced in the presence of 10% serum and 20% whole blood. Future modification of the PhciCath5 peptide to enhance activity, including in the presence of serum/blood, may provide a novel solution to Chlamydia infection in koalas and other species

Asymptomatic members with SOD1 mutation in a large kindred with familial amyotrophic lateral sclerosis have abnormal water diffusion characterisitcs

DTI was carried out in FALS/SALS patients and familial members with SOD1 mutation (AFALS) who may be in a pre-symptomatic phase of ALS. The changes in FA and TT were investigated in CBT/CST and in whole brain. In FALS/SALS, diffusion pattern changes were found in cerebral peduncle, internal capsule, sub-cortical white matter, cerebellum and frontal lobe while in AFALS, abnormal pattern could also be detected in the cerebral peduncle, cerebellum and frontal lobe but with a smaller extent. Our study indicates that DTI can show early diffusion changes in members with SOD1 mutation in FALS prior to symptom-onset.published_or_final_versio

Experimental demonstration of a hyper-entangled ten-qubit Schr\"odinger cat state

Coherent manipulation of an increasing number of qubits for the generation of entangled states has been an important goal and benchmark in the emerging field of quantum information science. The multiparticle entangled states serve as physical resources for measurement-based quantum computing and high-precision quantum metrology. However, their experimental preparation has proved extremely challenging. To date, entangled states up to six, eight atoms, or six photonic qubits have been demonstrated. Here, by exploiting both the photons' polarization and momentum degrees of freedom, we report the creation of hyper-entangled six-, eight-, and ten-qubit Schr\"odinger cat states. We characterize the cat states by evaluating their fidelities and detecting the presence of genuine multi-partite entanglement. Small modifications of the experimental setup will allow the generation of various graph states up to ten qubits. Our method provides a shortcut to expand the effective Hilbert space, opening up interesting applications such as quantum-enhanced super-resolving phase measurement, graph-state generation for anyonic simulation and topological error correction, and novel tests of nonlocality with hyper-entanglement.Comment: 11 pages, 5 figures, comments welcom

Superpartner spectrum of minimal gaugino-gauge mediation

We evaluate the sparticle mass spectrum in the minimal four-dimensional construction that interpolates between gaugino and ordinary gauge mediation at the weak scale. We find that even in the hybrid case -- when the messenger scale is comparable to the mass of the additional gauge particles -- both the right-handed as well as the left-handed sleptons are lighter than the bino in the low-scale mediation regime. This implies a chain of lepton production and, consequently, striking signatures that may be probed at the LHC already in the near future.Comment: 8 pages, 3 figures; V2: refs and a few comments added; V3 title change

Mapping Materials and Molecules

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the “big data” revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities. It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them. This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses. The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

Mapping Materials and Molecules.

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the "big data" revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities.It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them.This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses.The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

On the Importance of Countergradients for the Development of Retinotopy: Insights from a Generalised Gierer Model

During the development of the topographic map from vertebrate retina to superior colliculus (SC), EphA receptors are expressed in a gradient along the nasotemporal retinal axis. Their ligands, ephrin-As, are expressed in a gradient along the rostrocaudal axis of the SC. Countergradients of ephrin-As in the retina and EphAs in the SC are also expressed. Disruption of any of these gradients leads to mapping errors. Gierer's (1981) model, which uses well-matched pairs of gradients and countergradients to establish the mapping, can account for the formation of wild type maps, but not the double maps found in EphA knock-in experiments. I show that these maps can be explained by models, such as Gierer's (1983), which have gradients and no countergradients, together with a powerful compensatory mechanism that helps to distribute connections evenly over the target region. However, this type of model cannot explain mapping errors found when the countergradients are knocked out partially. I examine the relative importance of countergradients as against compensatory mechanisms by generalising Gierer's (1983) model so that the strength of compensation is adjustable. Either matching gradients and countergradients alone or poorly matching gradients and countergradients together with a strong compensatory mechanism are sufficient to establish an ordered mapping. With a weaker compensatory mechanism, gradients without countergradients lead to a poorer map, but the addition of countergradients improves the mapping. This model produces the double maps in simulated EphA knock-in experiments and a map consistent with the Math5 knock-out phenotype. Simulations of a set of phenotypes from the literature substantiate the finding that countergradients and compensation can be traded off against each other to give similar maps. I conclude that a successful model of retinotopy should contain countergradients and some form of compensation mechanism, but not in the strong form put forward by Gierer

Observation of eight-photon entanglement

Using ultra-bright sources of pure-state entangled photons from parametric down conversion, an eight-photon interferometer and post-selection detection, we demonstrate the ability to experimentally manipulate eight individual photons and report the creation of an eight-photon Schr\"odinger cat state with an observed fidelity of $0.708 \pm 0.016$.Comment: 6 pages, 4 figure