Modeling pN2 through Geological Time: Implications for Planetary Climates and Atmospheric Biosignatures

Nitrogen is a major nutrient for all life on Earth and could plausibly play a similar role in extraterrestrial biospheres. The major reservoir of nitrogen at Earth's surface is atmospheric N2, but recent studies have proposed that the size of this reservoir may have fluctuated significantly over the course of Earth's history with particularly low levels in the Neoarchean - presumably as a result of biological activity. We used a biogeochemical box model to test which conditions are necessary to cause large swings in atmospheric N2 pressure. Parameters for our model are constrained by observations of modern Earth and reconstructions of biomass burial and oxidative weathering in deep time. A 1-D climate model was used to model potential effects on atmospheric climate. In a second set of tests, we perturbed our box model to investigate which parameters have the greatest impact on the evolution of atmospheric pN2 and consider possible implications for nitrogen cycling on other planets. Our results suggest that (a) a high rate of biomass burial would have been needed in the Archean to draw down atmospheric pN2 to less than half modern levels, (b) the resulting effect on temperature could probably have been compensated by increasing solar luminosity and a mild increase in pCO2, and (c) atmospheric oxygenation could have initiated a stepwise pN2 rebound through oxidative weathering. In general, life appears to be necessary for significant atmospheric pN2 swings on Earth-like planets. Our results further support the idea that an exoplanetary atmosphere rich in both N2 and O2 is a signature of an oxygen-producing biosphere.Comment: 33 pages, 11 figures, 2 tables (includes appendix), published in Astrobiolog

Mercury abundance and isotopic composition indicate subaerial volcanism prior to the end-Archean “whiff” of oxygen

Funding: This study was supported by National Aeronautics and Space Administration Exobiology Grant NNX16AI37G (R.B.) and by the MacArthur Professorship (J.D.B.) at the University of Michigan. M.A.K. acknowledges support from an Agouron Institute postdoctoral fellowship.Earth’s early atmosphere witnessed multiple transient episodes of oxygenation before the Great Oxidation Event 2.4 billion years ago (Ga) [e.g., A. D. Anbar et al., Science 317, 1903–1906 (2007); M. C. Koehler, R. Buick, M. E. Barley, Precambrian Res. 320, 281–290 (2019)], but the triggers for these short-lived events are so far unknown. Here, we use mercury (Hg) abundance and stable isotope composition to investigate atmospheric evolution and its driving mechanisms across the well-studied “whiff” of O2 recorded in the ∼2.5-Ga Mt. McRae Shale from the Pilbara Craton in Western Australia [A. D. Anbar et al., Science 317, 1903–1906 (2007)]. Our data from the oxygenated interval show strong Hg enrichment paired with slightly negative Δ199Hg and near-zero Δ200Hg, suggestive of increased oxidative weathering. In contrast, slightly older beds, which were evidently deposited under an anoxic atmosphere in ferruginous waters [C. T. Reinhard, R. Raiswell, C. Scott, A. D. Anbar, T. W. Lyons, Science 326, 713–716 (2009)], show Hg enrichment coupled with positive Δ199Hg and slightly negative Δ200Hg values. This pattern is consistent with photochemical reactions associated with subaerial volcanism under intense UV radiation. Our results therefore suggest that the whiff of O2 was preceded by subaerial volcanism. The transient interval of O2 accumulation may thus have been triggered by diminished volcanic O2 sinks, followed by enhanced nutrient supply to the ocean from weathering of volcanic rocks causing increased biological productivity.PostprintPeer reviewe

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining

Background Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). Methods The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. Results Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). Conclusions Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness

PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model.

MotivationElectronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.ResultsWe present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes.Availability and implementationPatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu.Supplementary informationSupplementary data are available at Bioinformatics online

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.</jats:p

Angle resolved photoemission spectroscopy of Sr_2CuO_2Cl_2 - a revisit

We have investigated the lowest binding-energy electronic structure of the model cuprate Sr_2CuO_2Cl_2 using angle resolved photoemission spectroscopy (ARPES). Our data from about 80 cleavages of Sr_2CuO_2Cl_2 single crystals give a comprehensive, self-consistent picture of the nature of the first electron-removal state in this model undoped CuO_2-plane cuprate. Firstly, we show a strong dependence on the polarization of the excitation light which is understandable in the context of the matrix element governing the photoemission process, which gives a state with the symmetry of a Zhang-Rice singlet. Secondly, the strong, oscillatory dependence of the intensity of the Zhang-Rice singlet on the exciting photon-energy is shown to be consistent with interference effects connected with the periodicity of the crystal structure in the crystallographic c-direction. Thirdly, we measured the dispersion of the first electron-removal states along G->(pi,pi) and G->(pi,0), the latter being controversial in the literature, and have shown that the data are best fitted using an extended t-J-model, and extract the relevant model parameters. An analysis of the spectral weight of the first ionization states for different excitation energies within the approach used by Leung et al. (Phys. Rev. B56, 6320 (1997)) results in a strongly photon-energy dependent ratio between the coherent and incoherent spectral weight. The possible reasons for this observation and its physical implications are discussed.Comment: 10 pages, 8 figure

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits

Erratum for Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits. [BMC Med Genomics. 2019

Angle-resolved photoemission spectroscopy of the cuprate superconductors

This paper reviews the most recent ARPES results on the cuprate superconductors and their insulating parent and sister compounds, with the purpose of providing an updated summary of the extensive literature in this field. The low energy excitations are discussed with emphasis on some of the most relevant issues, such as the Fermi surface and remnant Fermi surface, the superconducting gap, the pseudogap and d-wave-like dispersion, evidence of electronic inhomogeneity and nano-scale phase separation, the emergence of coherent quasiparticles through the superconducting transition, and many-body effects in the one-particle spectral function due to the interaction of the charge with magnetic and/or lattice degrees of freedom. The first part of the paper introduces photoemission spectroscopy in the context of strongly interacting systems, along with an update on the state-of-the-art instrumentation. The second part provides a brief overview of the scientific issues relevant to the investigation of the low energy electronic structure by ARPES. The rest of the paper is devoted to the review of experimental results from the cuprates and the discussion is organized along conceptual lines: normal-state electronic structure, interlayer interaction, superconducting gap, coherent superconducting peak, pseudogap, electron self energy and collective modes. Within each topic, ARPES data from the various copper oxides are presented.Comment: Reviews of Modern Physics, in press. A HIGH-QUALITY pdf file is available at http://www.physics.ubc.ca/~damascel/RMP_ARPES.pd

High prevalence of epilepsy in onchocerciasis endemic regions in the Democratic Republic of the Congo

Background: An increased prevalence of epilepsy has been reported in many onchocerciasis endemic areas. The objective of this study was to determine the prevalence of epilepsy in onchocerciasis endemic areas in the Democratic Republic of the Congo (DRC) and investigate whether a higher annual intake of Ivermectin was associated with a lower prevalence of epilepsy. Methodology/Principle findings: Between July 2014 and February 2016, house-to-house epilepsy prevalence surveys were carried out in areas with a high level of onchocerciasis endemicity: 3 localities in the Bas-Uele, 24 in the Tshopo and 21 in the Ituri province. Ivermectin uptake was recorded for every household member. This database allowed a matched case-control pair subset to be created that enabled putative risk factors for epilepsy to be tested using univariate logistic regression models. Risk factors relating to onchocerciasis were tested using a multivariate random effects model. To identify presence of clusters of epilepsy cases, the Kulldorff's scan statistic was used. Of 12, 408 people examined in the different health areas 407 (3.3%) were found to have a history of epilepsy. A high prevalence of epilepsy was observed in health areas in the 3 provinces: 6.8–8.5% in Bas-Uele, 0.8–7.4% in Tshopo and 3.6–6.2% in Ituri. Median age of epilepsy onset was 9 years, and the modal age 12 years. The case control analysis demonstrated that before the appearance of epilepsy, compared to the same life period in controls, persons with epilepsy were around two times less likely (OR: 0.52; 95%CI: (0.28, 0.98)) to have taken Ivermectin than controls. After the appearance of epilepsy, there was no difference of Ivermectin intake between cases and controls. Only in Ituri, a significant cluster (p-value = 0.0001) was identified located around the Draju sample site area. Conclusions: The prevalence of epilepsy in health areas in onchocerciasis endemic regions in the DRC was 2–10 times higher than in non-onchocerciasis endemic regions in Africa. Our data suggests that Ivermectin protects against epilepsy in an onchocerciasis endemic region. However, a prospective population based intervention study is needed to confirm this