Deep forecasting of translational impact in medical research.

The value of biomedical research-a $1.7 trillion annual investment-is ultimately determined by its downstream, real-world impact, whose predictability from simple citation metrics remains unquantified. Here we sought to determine the comparative predictability of future real-world translation-as indexed by inclusion in patents, guidelines, or policy documents-from complex models of title/abstract-level content versus citations and metadata alone. We quantify predictive performance out of sample, ahead of time, across major domains, using the entire corpus of biomedical research captured by Microsoft Academic Graph from 1990-2019, encompassing 43.3 million papers. We show that citations are only moderately predictive of translational impact. In contrast, high-dimensional models of titles, abstracts, and metadata exhibit high fidelity (area under the receiver operating curve [AUROC] > 0.9), generalize across time and domain, and transfer to recognizing papers of Nobel laureates. We argue that content-based impact models are superior to conventional, citation-based measures and sustain a stronger evidence-based claim to the objective measurement of translational potential

Mechanistic interplay between ceramide and insulin resistance

Recent research adds to a growing body of literature on the essential role of ceramides in glucose homeostasis and insulin signaling, while the mechanistic interplay between various components of ceramide metabolism remains to be quantified. We present an extended model of C16:0 ceramide production through both the de novo synthesis and the salvage pathways. We verify our model with a combination of published models and independent experimental data. In silico experiments of the behavior of ceramide and related bioactive lipids in accordance with the observed transcriptomic changes in obese/diabetic murine macrophages at 5 and 16 weeks support the observation of insulin resistance only at the later phase. Our analysis suggests the pivotal role of ceramide synthase, serine palmitoyltransferase and dihydroceramide desaturase involved in the de novo synthesis and the salvage pathways in influencing insulin resistance versus its regulation

Daksha: On Alert for High Energy Transients

We present Daksha, a proposed high energy transients mission for the study of electromagnetic counterparts of gravitational wave sources, and gamma ray bursts. Daksha will comprise of two satellites in low earth equatorial orbits, on opposite sides of earth. Each satellite will carry three types of detectors to cover the entire sky in an energy range from 1 keV to >1 MeV. Any transients detected on-board will be announced publicly within minutes of discovery. All photon data will be downloaded in ground station passes to obtain source positions, spectra, and light curves. In addition, Daksha will address a wide range of science cases including monitoring X-ray pulsars, studies of magnetars, solar flares, searches for fast radio burst counterparts, routine monitoring of bright persistent high energy sources, terrestrial gamma-ray flashes, and probing primordial black hole abundances through lensing. In this paper, we discuss the technical capabilities of Daksha, while the detailed science case is discussed in a separate paper.Comment: 9 pages, 3 figures, 1 table. Additional information about the mission is available at https://www.dakshasat.in

Science with the Daksha High Energy Transients Mission

We present the science case for the proposed Daksha high energy transients mission. Daksha will comprise of two satellites covering the entire sky from 1~keV to $>1$~MeV. The primary objectives of the mission are to discover and characterize electromagnetic counterparts to gravitational wave source; and to study Gamma Ray Bursts (GRBs). Daksha is a versatile all-sky monitor that can address a wide variety of science cases. With its broadband spectral response, high sensitivity, and continuous all-sky coverage, it will discover fainter and rarer sources than any other existing or proposed mission. Daksha can make key strides in GRB research with polarization studies, prompt soft spectroscopy, and fine time-resolved spectral studies. Daksha will provide continuous monitoring of X-ray pulsars. It will detect magnetar outbursts and high energy counterparts to Fast Radio Bursts. Using Earth occultation to measure source fluxes, the two satellites together will obtain daily flux measurements of bright hard X-ray sources including active galactic nuclei, X-ray binaries, and slow transients like Novae. Correlation studies between the two satellites can be used to probe primordial black holes through lensing. Daksha will have a set of detectors continuously pointing towards the Sun, providing excellent hard X-ray monitoring data. Closer to home, the high sensitivity and time resolution of Daksha can be leveraged for the characterization of Terrestrial Gamma-ray Flashes.Comment: 19 pages, 7 figures. Submitted to ApJ. More details about the mission at https://www.dakshasat.in

Estimating PM 2.5 concentrations in Xi'an City using a generalized additive model with multi-source monitoring data

© 2015 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5

Field and spaceborne imagery data for evaluation of the paleo-stress regime during formation of the Jurassic dike swarms in the Kalateh Alaeddin Mountain area, Shahrood, north Iran

© 2019, Saudi Society for Geosciences. Dike swarms are commonly linked with extensional structures in diverse geodynamic environments. Mafic dyke swarms are typically used to reconstruct the paleo-stress fields of a given region. These dikes are considered paleo-stress indicators and excellent time marker (if related geochronological data are available) of the local and regional stress fields. In the Middle-Late Jurassic, swarms of mafic dikes emplaced into the Neoproterozoic schists and amphibolites in the Kalateh Alaeddin Mountain area in south Shahrood, north Iran. These dikes with different thicknesses show a general east–west strike direction, with mostly a steep dip angle. In this paper, we present structural data of these dike swarms for the sake of assessing the paleo-stress state and the magma pressure ratio at the time of their emplacement. Field and structural data are integrated with ASTER Global Digital Elevation Model (GDEM) and Centre National d’Etudes Spatiales (CNES)/SPOT imagery data, to extract important parameters of the investigated dikes and controlling fault/joint sets. Orientation of the principal paleo-stress axes, quantification of the stress ratio, and the associated magma pressure ratio (driving stress ratio) were calculated using the stereographic projection and Mohr’s circle reconstruction techniques. The results reveal that the maximum paleo-stress component (σ1) was sub-vertical and the intermediate (σ2) and minimum (σ3) paleo-stresses components were sub-horizontal in N264° E and N173° E trends, respectively. Due to the low value of the driving stress ratio (R = 0.05), these dikes developed perpendicular to the minimum principal stress (in E–W direction). The stress ratio value (ø = 0.66) indicates a moderately oblate stress ellipsoid. The orientation of the principal paleo-stress axes and the oblate ellipsoid are indicative of the dike emplacement during a N–S-directed tectonic extension, in agreement with the Jurassic subsidence phase and N–S stretching described for the Kalateh Alaeddin Mountain area

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Not AvailableTwo major bacterial blight (BB) resistance genes (Xa21 and xa13) and a major gene for blast resistance (Pi54) were introgressed into an Indian rice variety MTU1010 through marker-assisted backcross breeding. Improved Samba Mahsuri (possessing Xa21 and xa13) and NLR145 (possessing Pi54) were used as donor parents. Marker-assisted backcrossing was continued till BC2 generation wherein PCR based functional markers specific for the resistance genes were used for foreground selection and a set of parental polymorphic microsatellite markers were used for background selection at each stage of backcrossing. Selected BC2F1 plants from both crosses, having the highest recoveries of MTU1010 genome (90% and 92%, respectively), were intercrossed to obtain intercross F1 (ICF1) plants, which were then selfed to generate 880 ICF2 plants possessing different combinations of the BB and blast resistance genes. Among the ICF2 plants, seven triple homozygous plants (xa13xa13Xa21Xa21Pi54Pi54) with recurrent parent genome recovery ranging from 82% to 92% were identified. All the seven ICF2 plants showed high resistance against the bacterial blight disease with a lesion lengths of only 0.53–2.28 cm, 1%–5% disease leaf areas and disease scoring values of ‘1’ or ‘3’. The seven ICF2 plants were selfed to generate ICF3, which were then screened for blast resistance, and all were observed to be highly resistant to the diseases. Several ICF3 lines possessing high level of resistance against BB and blast, coupled with yield, grain quality and plant type on par with MTU1010 were identified and advanced for further selection and evaluation.Department of Biotechnology (DBT), Government of India (Grant No. BT/PR11705/AGR/02/646/2008)