Motoneurons secrete angiogenin to induce RNA cleavage in astroglia.

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder affecting motoneurons. Mutations in angiogenin, encoding a member of the pancreatic RNase A superfamily, segregate with ALS. We previously demonstrated that angiogenin administration shows promise as a neuroprotective therapeutic in studies using transgenic ALS mice and primary motoneuron cultures. Its mechanism of action and target cells in the spinal cord, however, are largely unknown. Using mixed motoneuron cultures, motoneuron-like NSC34 cells, and primary astroglia cultures as model systems, we here demonstrate that angiogenin is a neuronally secreted factor that is endocytosed by astroglia and mediates neuroprotection in paracrine. We show that wild-type angiogenin acts unidirectionally to induce RNA cleavage in astroglia, while the ALS-associated K40I mutant is also secreted and endocytosed, but fails to induce RNA cleavage. Angiogenin uptake into astroglia requires heparan sulfate proteoglycans, and engages clathrin-mediated endocytosis. We show that this uptake mechanism exists for mouse and human angiogenin, and delivers a functional RNase output. Moreover, we identify syndecan 4 as the angiogenin receptor mediating the selective uptake of angiogenin into astroglia. Our data provide new insights into the paracrine activities of angiogenin in the nervous system, and further highlight the critical role of non-neuronal cells in the pathogenesis of ALS

Automating the packing heuristic design process with genetic programming

The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains

PROPHETIC: Prospective Identification of Pneumonia in Hospitalized Patients in the Intensive Care Unit

BACKGROUND: Pneumonia is the leading infection-related cause of death. Using simple clinical criteria and contemporary epidemiology to identify patients at high risk of nosocomial pneumonia should enhance prevention efforts and facilitate development of new treatments in clinical trials. RESEARCH QUESTION: What are the clinical criteria and contemporary epidemiology trends helpful in identifying patients at high risk of nosocomial pneumonia? STUDY DESIGN AND METHODS: Within the intensive care units of 28 United States hospitals, we conducted a prospective cohort study among adults hospitalized more than 48 hours and considered high risk for pneumonia (defined as treatment with invasive or noninvasive ventilatory support or high levels of supplemental oxygen). We estimated the proportion of high-risk patients developing nosocomial pneumonia. Using multivariable logistic regression, we identified patient characteristics and treatment exposures associated with increased risk of pneumonia development during the intensive care unit admission. RESULTS: Between February 6, 2016 and October 7, 2016, 4613 high-risk patients were enrolled. Among 1464/4613 (32%) high-risk patients treated for possible nosocomial pneumonia, 537/1464 (37%) met the study pneumonia definition. Among high-risk patients, a multivariable logistic model was developed to identify key patient characteristics and treatment exposures associated with increased risk of nosocomial pneumonia development (c-statistic 0.709, 95% confidence interval 0.686 to 0.731). Key factors associated with increased odds of nosocomial pneumonia included an admission diagnosis of trauma or cerebrovascular accident, receipt of enteral nutrition, documented aspiration risk, and receipt of systemic antibacterials within the preceding 90 days. INTERPRETATION: Treatment for nosocomial pneumonia is common among intensive care unit patients receiving high levels of respiratory support, yet more than half of patients treated do not fulfill standard diagnostic criteria for pneumonia. Application of simple clinical criteria may improve the feasibility of clinical trials of pneumonia prevention and treatment by facilitating prospective identification of patients at highest risk

PROPHETIC EU: Prospective Identification of Pneumonia in Hospitalized Patients in the Intensive Care Unit in European and United States Cohorts

Background The prospective identification of patients at high risk for hospital-acquired/ventilator-associated bacterial pneumonia may improve clinical trial feasibility and foster antibacterial development. In a prior study conducted in the United States, clinical criteria were used to prospectively identify these patients; however, these criteria have not been applied in a European population. Methods Adults considered high risk for pneumonia (treatment with ventilation or high levels of supplemental oxygen) in the intensive care units of 7 European hospitals were prospectively enrolled from June 12 to December 27, 2017. We estimated the proportion of high-risk patients developing pneumonia according to US Food and Drug Administration guidance and a subset potentially eligible for antibacterial trial enrollment. We compared patient characteristics, treatment exposures, and pneumonia incidence in a European cohort and a previously described US cohort. Results Of 888 high-risk patients, 211/888 (24%) were treated for possible pneumonia, and 150/888 (17%) met the Food and Drug Administration definition for hospital-acquired/ventilator-associated bacterial pneumonia. A higher proportion of European patients treated for possible pneumonia met the pneumonia definition (150/211 [71%] vs 537/1464 [37%]; P < .001). Among patients developing pneumonia, a higher proportion of European patients met antibacterial trial eligibility criteria (124/150 [83%] vs 371/537 [69%]; P < .001). Conclusions Clinical criteria prospectively identified high-risk patients with high rates of pneumonia in the European cohort. Despite higher rates of established risk factors and incident pneumonia, European patients were significantly less likely to receive antibiotics for possible pneumonia than US patients. Different treatment practices may contribute to lower rates of antibacterial trial enrollment in the United States

Upper limits on the strength of periodic gravitational waves from PSR J1939+2134

The first science run of the LIGO and GEO gravitational wave detectors presented the opportunity to test methods of searching for gravitational waves from known pulsars. Here we present new direct upper limits on the strength of waves from the pulsar PSR J1939+2134 using two independent analysis methods, one in the frequency domain using frequentist statistics and one in the time domain using Bayesian inference. Both methods show that the strain amplitude at Earth from this pulsar is less than a few times $10^{-22}$.Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 200

Improving the sensitivity to gravitational-wave sources by modifying the input-output optics of advanced interferometers

We study frequency dependent (FD) input-output schemes for signal-recycling interferometers, the baseline design of Advanced LIGO and the current configuration of GEO 600. Complementary to a recent proposal by Harms et al. to use FD input squeezing and ordinary homodyne detection, we explore a scheme which uses ordinary squeezed vacuum, but FD readout. Both schemes, which are sub-optimal among all possible input-output schemes, provide a global noise suppression by the power squeeze factor, while being realizable by using detuned Fabry-Perot cavities as input/output filters. At high frequencies, the two schemes are shown to be equivalent, while at low frequencies our scheme gives better performance than that of Harms et al., and is nearly fully optimal. We then study the sensitivity improvement achievable by these schemes in Advanced LIGO era (with 30-m filter cavities and current estimates of filter-mirror losses and thermal noise), for neutron star binary inspirals, and for narrowband GW sources such as low-mass X-ray binaries and known radio pulsars. Optical losses are shown to be a major obstacle for the actual implementation of these techniques in Advanced LIGO. On time scales of third-generation interferometers, like EURO/LIGO-III (~2012), with kilometer-scale filter cavities, a signal-recycling interferometer with the FD readout scheme explored in this paper can have performances comparable to existing proposals. [abridged]Comment: Figs. 9 and 12 corrected; Appendix added for narrowband data analysi

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Roadmap on optical energy conversion

For decades, progress in the field of optical (including solar) energy conversion was dominated by advances in the conventional concentrating optics and materials design. In recent years, however, conceptual and technological breakthroughs in the fields of nanophotonics and plasmonics combined with a better understanding of the thermodynamics of the photon energy-conversion processes reshaped the landscape of energy-conversion schemes and devices. Nanostructured devices and materials that make use of size quantization effects to manipulate photon density of states offer a way to overcome the conventional light absorption limits. Novel optical spectrum splitting and photon-recycling schemes reduce the entropy production in the optical energy-conversion platforms and boost their efficiencies. Optical design concepts are rapidly expanding into the infrared energy band, offering new approaches to harvest waste heat, to reduce the thermal emission losses, and to achieve noncontact radiative cooling of solar cells as well as of optical and electronic circuitries. Light–matter interaction enabled by nanophotonics and plasmonics underlie the performance of the third- and fourth-generation energy-conversion devices, including up- and down-conversion of photon energy, near-field radiative energy transfer, and hot electron generation and harvesting. Finally, the increased market penetration of alternative solar energy-conversion technologies amplifies the role of cost-driven and environmental considerations. This roadmap on optical energy conversion provides a snapshot of the state of the art in optical energy conversion, remaining challenges, and most promising approaches to address these challenges. Leading experts authored 19 focused short sections of the roadmap where they share their vision on a specific aspect of this burgeoning research field. The roadmap opens up with a tutorial section, which introduces major concepts and terminology. It is our hope that the roadmap will serve as an important resource for the scientific community, new generations of researchers, funding agencies, industry experts, and investors.United States. Department of Energy (DE-AC36-086038308