Sex differences in sepsis hospitalisations and outcomes in older women and men: A prospective cohort study

Purpose: To examine the association of sex with hospitalisation due to sepsis and related outcomes. Methods: Prospective cohort study of 264,678 adults, average age 62.7 years at recruitment (2006–2009) in Australia. Participants were followed for sepsis hospitalisation identified using the International Classification of Diseases coding. Outcomes included sex differences in the risk of an incident sepsis hospitalisation, mortality, length of ICU and hospital stay and readmissions during the following year. Results: Over 2,070,343 years of follow-up there were 12,912 sepsis hospitalisations, 59.6% in men. Age-standardised risk of hospitalisation was higher in men versus women (10.37 vs 6.77 per 1,000 person years; age-adjusted HR 1.58; 95% CI 1.53–1.59) and did not attenuate after adjusting for sociodemographics, health behaviours and co-morbidities. Relative risks were similar for sepsis-related ICU admissions (adjusted HR 1.72; 95% CI 1.57–1.88). Death at one year was more common in men than women (39.3% vs 33.7% p<0.001). After adjusting for age, men had a longer hospital (12.0 vs 11.2 days; p<0.001) and ICU (6.5 vs 5.8 days; p<0.001) stays and were more likely to be readmitted to hospital for sepsis (22.3 vs 19.4%; p<0.001) or any reason (73.0% vs 70.7%; p<0.001) at one year. Conclusion: In older adults, compared to women, men are at an increased risk of sepsis hospitalisation, sepsis-related ICU admission, death and readmission to hospital within one year after a sepsis hospitalisation. Understanding these sex differences and their mechanisms may offer opportunities for better prevention and management and improved patient outcomes

A Genome-wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology

We provide microarray data comparing genome-wide differential expression and pathology throughout life in four lines of "amyloid" transgenic mice (mutant human APP, PSEN1, or APP/PSEN1) and "TAU" transgenic mice (mutant human MAPT gene). Microarray data were validated by qPCR and by comparison to human studies, including genome-wide association study (GWAS) hits. Immune gene expression correlated tightly with plaques whereas synaptic genes correlated negatively with neurofibrillary tangles. Network analysis of immune gene modules revealed six hub genes in hippocampus of amyloid mice, four in common with cortex. The hippocampal network in TAU mice was similar except that Trem2 had hub status only in amyloid mice. The cortical network of TAU mice was entirely different with more hub genes and few in common with the other networks, suggesting reasons for specificity of cortical dysfunction in FTDP17. This Resource opens up many areas for investigation. All data are available and searchable at http://www.mouseac.org

Rethinking Indian monsoon rainfall prediction in the context of recent global warming

Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models’ inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP–ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical–empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989–2012 and a 92-year retrospective forecast skill of 0.64 for 1921–2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP–ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability

A 4D Light-Field Dataset and CNN Architectures for Material Recognition

We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories, each with 100 images taken with a Lytro Illum, from which we extract about 30,000 patches in total. To the best of our knowledge, this is the first mid-size dataset for light-field images. Our main goal is to investigate whether the additional information in a light-field (such as multiple sub-aperture views and view-dependent reflectance effects) can aid material recognition. Since recognition networks have not been trained on 4D images before, we propose and compare several novel CNN architectures to train on light-field images. In our experiments, the best performing CNN architecture achieves a 7% boost compared with 2D image classification (70% to 77%). These results constitute important baselines that can spur further research in the use of CNNs for light-field applications. Upon publication, our dataset also enables other novel applications of light-fields, including object detection, image segmentation and view interpolation.Comment: European Conference on Computer Vision (ECCV) 201

Enhanced efficiency of solid-state NMR investigations of energy materials using an external automatic tuning/matching (eATM) robot.

We have developed and explored an external automatic tuning/matching (eATM) robot that can be attached to commercial and/or home-built magic angle spinning (MAS) or static nuclear magnetic resonance (NMR) probeheads. Complete synchronization and automation with Bruker and Tecmag spectrometers is ensured via transistor-transistor-logic (TTL) signals. The eATM robot enables an automated "on-the-fly" re-calibration of the radio frequency (rf) carrier frequency, which is beneficial whenever tuning/matching of the resonance circuit is required, e.g. variable temperature (VT) NMR, spin-echo mapping (variable offset cumulative spectroscopy, VOCS) and/or in situ NMR experiments of batteries. This allows a significant increase in efficiency for NMR experiments outside regular working hours (e.g. overnight) and, furthermore, enables measurements of quadrupolar nuclei which would not be possible in reasonable timeframes due to excessively large spectral widths. Additionally, different tuning/matching capacitor (and/or coil) settings for desired frequencies (e.g. $^{7}$Li and $^{31}$P at 117 and 122MHz, respectively, at 7.05 T) can be saved and made directly accessible before automatic tuning/matching, thus enabling automated measurements of multiple nuclei for one sample with no manual adjustment required by the user. We have applied this new eATM approach in static and MAS spin-echo mapping NMR experiments in different magnetic fields on four energy storage materials, namely: (1) paramagnetic $^{7}$Li and $^{31}$P MAS NMR (without manual recalibration) of the Li-ion battery cathode material LiFePO$_{4}$; (2) paramagnetic $^{17}$O VT-NMR of the solid oxide fuel cell cathode material La$_{2}$NiO$_{4+δ}$; (3) broadband $^{93}$Nb static NMR of the Li-ion battery material BNb$_{2}$O$_{5}$; and (4) broadband static $^{127}$I NMR of a potential Li-air battery product LiIO$_{3}$. In each case, insight into local atomic structure and dynamics arises primarily from the highly broadened (1-25MHz) NMR lineshapes that the eATM robot is uniquely suited to collect. These new developments in automation of NMR experiments are likely to advance the application of in and ex situ NMR investigations to an ever-increasing range of energy storage materials and systems.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 655444 (O.P.). D.M.H. acknowledges funding from the Cambridge Commonwealth Trusts. J.L. gratefully acknowledges Trinity College, Cambridge (UK) for funding. K.J.G. gratefully acknowledges funding from the Winston Churchill Foundation of the United States and the Herchel Smith Scholarship. M.B. is the CEO of NMR Service GmbH (Erfurt, Germany), which manufactures the eATM device; M.B. acknowledges funding of the Central Innovation Programme for small and medium-sized enterprises (SMEs; Zentrales Innovationsprogramm Mittelstand, ZIM) of the German Federal Ministry of Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie, BMWi) under the Grant No. KF 2845501UWF. DFT calculations were performed on (1) the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council and (2) the Center for Functional Nanomaterials cluster, Brookhaven National Laboratory, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10886

Topoisomer Differentiation of Molecular Knots by FTICR MS: Lessons from Class II Lasso Peptides

Lasso peptides constitute a class of bioactive peptides sharing a knotted structure where the C-terminal tail of the peptide is threaded through and trapped within an N-terminalmacrolactamring. The structural characterization of lasso structures and differentiation from their unthreaded topoisomers is not trivial and generally requires the use of complementary biochemical and spectroscopic methods. Here we investigated two antimicrobial peptides belonging to the class II lasso peptide family and their corresponding unthreaded topoisomers: microcin J25 (MccJ25), which is known to yield two-peptide product ions specific of the lasso structure under collisioninduced dissociation (CID), and capistruin, for which CID does not permit to unambiguously assign the lasso structure. The two pairs of topoisomers were analyzed by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) upon CID, infrared multiple photon dissociation (IRMPD), and electron capture dissociation (ECD). CID and ECDspectra clearly permitted to differentiate MccJ25 from its non-lasso topoisomer MccJ25-Icm, while for capistruin, only ECD was informative and showed different extent of hydrogen migration (formation of c\bullet/z from c/z\bullet) for the threaded and unthreaded topoisomers. The ECD spectra of the triply-charged MccJ25 and MccJ25-lcm showed a series of radical b-type product ions {\eth}b0In{\TH}. We proposed that these ions are specific of cyclic-branched peptides and result from a dual c/z\bullet and y/b dissociation, in the ring and in the tail, respectively. This work shows the potentiality of ECD for structural characterization of peptide topoisomers, as well as the effect of conformation on hydrogen migration subsequent to electron capture

How Much Does It Cost to Go Off-Grid with Renewables? A Case Study of a Polygeneration System for a Neighbourhood in Hermosillo, Mexico

As governments and companies struggle to meet their own objectives for the energy transition, more innovative social and technological measures are needed to reduce Greenhouse Gas (GHG) emissions. For this purpose, an assessment of an off-grid polygeneration system, which can serve the electric and cooling demand of a neighbourhood in Hermosillo, Mexico, has been conducted. Energy computations have been done, the energy demand of one dwelling has been measured to ascertain the correctness of the computations, and a demand model for the entire neighbour-hood has been created. Based on the model, an off-grid polygeneration system has been designed, which uses a biodiesel engine, PV panels, and an absorption chiller. The system has been optimized for its economic performance and is compared to the currently used system. The results show that the polygeneration system with higher energy efficiency could reduce GHG emissions down to 14%. However, electricity in Hermosillo is heavily subsidized making it harder for innovative systems to compete. Moreover, even without the state subsidies to the end-user, the polygeneration system has still a nearly 30% higher Net Present Cost (NPC) than the conventional system over its project lifetime of 20 years. Nonetheless, with precise political incentives and further advances in the applied technologies, small-scale renewable polygeneration systems could become cost-efficient alternatives in the near future.Postprint (author's final draft

Butterfly Detection and Classification Based on Integrated YOLO Algorithm

Insects are abundant species on the earth, and the task of identification and identification of insects is complex and arduous. How to apply artificial intelligence technology and digital image processing methods to automatic identification of insect species is a hot issue in current research. In this paper, the problem of automatic detection and classification recognition of butterfly photographs is studied, and a method of bio-labeling suitable for butterfly classification is proposed. On the basis of YOLO algorithm, by synthesizing the results of YOLO models with different training mechanisms, a butterfly automatic detection and classification recognition algorithm based on YOLO algorithm is proposed. It greatly improves the generalization ability of YOLO algorithm and makes it have better ability to solve small sample problems. The experimental results show that the proposed annotation method and integrated YOLO algorithm have high accuracy and recognition rate in butterfly automatic detection and recognition.Comment: 13th ICGEC 2019: Qingdao, Chin