Publications by authors named "Ravi Iyengar"

123 Publications

Protein structure-based gene expression signatures.

Proc Natl Acad Sci U S A 2021 May;118(19)

Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029;

Gene expression signatures (GES) connect phenotypes to differential messenger RNA (mRNA) expression of genes, providing a powerful approach to define cellular identity, function, and the effects of perturbations. The use of GES has suffered from vague assessment criteria and limited reproducibility. Because the structure of proteins defines the functional capability of genes, we hypothesized that enrichment of structural features could be a generalizable representation of gene sets. We derive structural gene expression signatures (sGES) using features from multiple levels of protein structure (e.g., domain and fold) encoded by the mRNAs in GES. Comprehensive analyses of data from the Genotype-Tissue Expression Project (GTEx), the all RNA-seq and ChIP-seq sample and signature search (ARCHS4) database, and mRNA expression of drug effects on cardiomyocytes show that sGES are useful for characterizing biological phenomena. sGES enable phenotypic characterization across experimental platforms, facilitates interoperability of expression datasets, and describe drug action on cells.
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http://dx.doi.org/10.1073/pnas.2014866118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126868PMC
May 2021

The Human ApoE4 Variant Reduces Functional Recovery and Neuronal Sprouting After Incomplete Spinal Cord Injury in Male Mice.

Front Cell Neurosci 2021 18;15:626192. Epub 2021 Feb 18.

National Center for the Medical Consequences of Spinal Cord Injury, James J. Peters VA Medical Center, New York, NY, United States.

Spinal cord injury (SCI) is a devastating form of neurotrauma. Patients who carry one or two apolipoprotein E (ApoE)4 alleles show worse functional outcomes and longer hospital stays after SCI, but the cellular and molecular underpinnings for this genetic link remain poorly understood. Thus, there is a great need to generate animal models to accurately replicate the genetic determinants of outcomes after SCI to spur development of treatments that improve physical function. Here, we examined outcomes after a moderate contusion SCI of transgenic mice expressing human ApoE3 or ApoE4. ApoE4 mice have worse locomotor function and coordination after SCI. Histological examination revealed greater glial staining in ApoE4 mice after SCI associated with reduced levels of neuronal sprouting markers. Bulk RNA sequencing revealed that subcellular processes (SCPs), such as extracellular matrix organization and inflammatory responses, were highly ranked among upregulated genes at 7 days after SCI in ApoE4 variants. Conversely, SCPs related to neuronal action potential and neuron projection development were increased in ApoE3 mice at 21 days. In summary, our results reveal a clinically relevant SCI mouse model that recapitulates the influence of ApoE genotypes on post SCI function in individuals who carry these alleles and suggest that the mechanisms underlying worse recovery for ApoE4 animals involve glial activation and loss of sprouting and synaptic activity.
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http://dx.doi.org/10.3389/fncel.2021.626192DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930340PMC
February 2021

Rationale and design of the Kidney Precision Medicine Project.

Kidney Int 2021 03;99(3):498-510

Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Renal Section, Veterans Administration Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.
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http://dx.doi.org/10.1016/j.kint.2020.08.039DOI Listing
March 2021

Physiology of cardiomyocyte injury in COVID-19.

medRxiv 2020 Nov 13. Epub 2020 Nov 13.

COVID-19 affects multiple organs. Clinical data from the Mount Sinai Health System shows that substantial numbers of COVID-19 patients without prior heart disease develop cardiac dysfunction. How COVID-19 patients develop cardiac disease is not known. We integrate cell biological and physiological analyses of human cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSCs) infected with SARS-CoV-2 in the presence of interleukins, with clinical findings, to investigate plausible mechanisms of cardiac disease in COVID-19 patients. We infected hiPSC-derived cardiomyocytes, from healthy human subjects, with SARS-CoV-2 in the absence and presence of interleukins. We find that interleukin treatment and infection results in disorganization of myofibrils, extracellular release of troponin-I, and reduced and erratic beating. Although interleukins do not increase the extent, they increase the severity of viral infection of cardiomyocytes resulting in cessation of beating. Clinical data from hospitalized patients from the Mount Sinai Health system show that a significant portion of COVID-19 patients without prior history of heart disease, have elevated troponin and interleukin levels. A substantial subset of these patients showed reduced left ventricular function by echocardiography. Our laboratory observations, combined with the clinical data, indicate that direct effects on cardiomyocytes by interleukins and SARS-CoV-2 infection can underlie the heart disease in COVID-19 patients.

One Sentence Summary: Cardiomyocytes derived from human induced pluripotent stem cells treated with interleukins and infected with SARS-CoV-2 in cultures, show increased release of troponin, disorganization of myofibrils, and changes in beating mirroring specific pathologies in some COVID-19 patients.
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http://dx.doi.org/10.1101/2020.11.10.20229294DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668750PMC
November 2020

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Physiol Genomics 2021 01 16;53(1):1-11. Epub 2020 Nov 16.

Washington University in Saint Louis School of Medicine, St. Louis, Missouri.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.
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http://dx.doi.org/10.1152/physiolgenomics.00104.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847045PMC
January 2021

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model.

Lancet Digit Health 2020 10 22;2(10):e516-e525. Epub 2020 Sep 22.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Background: The COVID-19 pandemic has affected millions of individuals and caused hundreds of thousands of deaths worldwide. Predicting mortality among patients with COVID-19 who present with a spectrum of complications is very difficult, hindering the prognostication and management of the disease. We aimed to develop an accurate prediction model of COVID-19 mortality using unbiased computational methods, and identify the clinical features most predictive of this outcome.

Methods: In this prediction model development and validation study, we applied machine learning techniques to clinical data from a large cohort of patients with COVID-19 treated at the Mount Sinai Health System in New York City, NY, USA, to predict mortality. We analysed patient-level data captured in the Mount Sinai Data Warehouse database for individuals with a confirmed diagnosis of COVID-19 who had a health system encounter between March 9 and April 6, 2020. For initial analyses, we used patient data from March 9 to April 5, and randomly assigned (80:20) the patients to the development dataset or test dataset 1 (retrospective). Patient data for those with encounters on April 6, 2020, were used in test dataset 2 (prospective). We designed prediction models based on clinical features and patient characteristics during health system encounters to predict mortality using the development dataset. We assessed the resultant models in terms of the area under the receiver operating characteristic curve (AUC) score in the test datasets.

Findings: Using the development dataset (n=3841) and a systematic machine learning framework, we developed a COVID-19 mortality prediction model that showed high accuracy (AUC=0·91) when applied to test datasets of retrospective (n=961) and prospective (n=249) patients. This model was based on three clinical features: patient's age, minimum oxygen saturation over the course of their medical encounter, and type of patient encounter (inpatient outpatient and telehealth visits).

Interpretation: An accurate and parsimonious COVID-19 mortality prediction model based on three features might have utility in clinical settings to guide the management and prognostication of patients affected by this disease. External validation of this prediction model in other populations is needed.

Funding: National Institutes of Health.
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http://dx.doi.org/10.1016/S2589-7500(20)30217-XDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508513PMC
October 2020

Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity.

Nat Commun 2020 09 23;11(1):4809. Epub 2020 Sep 23.

Department of Pharmacological Sciences and Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood, and its prediction remains challenging. We obtain transcriptional profiles of human heart-derived primary cardiomyocyte like cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with the cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.
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http://dx.doi.org/10.1038/s41467-020-18396-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511315PMC
September 2020

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

Nat Rev Nephrol 2020 11 16;16(11):686-696. Epub 2020 Sep 16.

Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.
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http://dx.doi.org/10.1038/s41581-020-00335-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012202PMC
November 2020

Clinical predictors of COVID-19 mortality.

medRxiv 2020 May 22. Epub 2020 May 22.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029, USA.

Background: The coronavirus disease 2019 (COVID-19) pandemic has affected over millions of individuals and caused hundreds of thousands of deaths worldwide. It can be difficult to accurately predict mortality among COVID-19 patients presenting with a spectrum of complications, hindering the prognostication and management of the disease.

Methods: We applied machine learning techniques to clinical data from a large cohort of 5,051 COVID-19 patients treated at the Mount Sinai Health System in New York City, the global COVID-19 epicenter, to predict mortality. Predictors were designed to classify patients into Deceased or Alive mortality classes and were evaluated in terms of the area under the receiver operating characteristic (ROC) curve (AUC score).

Findings: Using a development cohort (n=3,841) and a systematic machine learning framework, we identified a COVID-19 mortality predictor that demonstrated high accuracy (AUC=0.91) when applied to test sets of retrospective (n= 961) and prospective (n=249) patients. This mortality predictor was based on five clinical features: age, minimum O2 saturation during encounter, type of patient encounter (inpatient vs. various types of outpatient and telehealth encounters), hydroxychloroquine use, and maximum body temperature.

Interpretation: An accurate and parsimonious COVID-19 mortality predictor based on five features may have utility in clinical settings to guide the management and prognostication of patients affected by this disease.
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http://dx.doi.org/10.1101/2020.05.19.20103036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273288PMC
May 2020

Evaluation of a gender-affirming healthcare curriculum for second-year medical students.

Postgrad Med J 2020 Sep 11;96(1139):515-519. Epub 2019 Dec 11.

Department of Psychiatry, Road Home Program, Rush University Medical Center, Chicago, Illinois, USA.

Background: Transgender medicine is an emergent subfield with clearly identified educational gaps.

Aims: This manuscript evaluates a gender-affirming healthcare curriculum for second-year medical (M2) students.

Methods: Students received a survey assessing Gender Identity Competency in terms of skills, knowledge and attitudes regarding transgender and gender non-conforming (TGNC) issues. The authors administered the survey before and after the delivery of the curriculum. The curriculum included five online modules, a quiz, a 3-hour case-based workshop and a 2-hour interactive patient-provider panel.

Results: Approximately 60% of M2 students (n=77) completed both preassessments and postassessments. The following showed a statistically significant improvement from preassessment to postassessment: student Gender Identity Competency, (76) = -11.07, p<0.001; skills, (76) = -15.22, p<0.001; and self-reported knowledge, (76) = -4.36, p<0.001. Negative attitudes did not differ (p=0.378). Interest in TGNC issues beyond healthcare settings did not change (p=0.334). M2 students reported a significant change in experience role-playing chosen pronouns in a clinical setting, (76) = -8.95, p<0.001.

Conclusions: The curriculum improved students' gender-affirming medical competency, knowledge and skills. The development of a sustained, longitudinal curriculum is recommended in addition to the continuing education of faculty to reinforce this expanding knowledge and skills base and to address discomfort working with this population.
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http://dx.doi.org/10.1136/postgradmedj-2019-136683DOI Listing
September 2020

Wilm's tumor 1 promotes memory flexibility.

Nat Commun 2019 08 21;10(1):3756. Epub 2019 Aug 21.

Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, 10029, NY, USA.

Under physiological conditions, strength and persistence of memory must be regulated in order to produce behavioral flexibility. In fact, impairments in memory flexibility are associated with pathologies such as post-traumatic stress disorder or autism; however, the underlying mechanisms that enable memory flexibility are still poorly understood. Here, we identify transcriptional repressor Wilm's Tumor 1 (WT1) as a critical synaptic plasticity regulator that decreases memory strength, promoting memory flexibility. WT1 is activated in the hippocampus following induction of long-term potentiation (LTP) or learning. WT1 knockdown enhances CA1 neuronal excitability, LTP and long-term memory whereas its overexpression weakens memory retention. Moreover, forebrain WT1-deficient mice show deficits in both reversal, sequential learning tasks and contextual fear extinction, exhibiting impaired memory flexibility. We conclude that WT1 limits memory strength or promotes memory weakening, thus enabling memory flexibility, a process that is critical for learning from new experiences.
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http://dx.doi.org/10.1038/s41467-019-11781-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704057PMC
August 2019

Geometric principles of second messenger dynamics in dendritic spines.

Sci Rep 2019 08 12;9(1):11676. Epub 2019 Aug 12.

Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, 92093-0411, CA, United States.

Dendritic spines are small, bulbous protrusions along dendrites in neurons and play a critical role in synaptic transmission. Dendritic spines come in a variety of shapes that depend on their developmental state. Additionally, roughly 14-19% of mature spines have a specialized endoplasmic reticulum called the spine apparatus. How does the shape of a postsynaptic spine and its internal organization affect the spatio-temporal dynamics of short timescale signaling? Answers to this question are central to our understanding the initiation of synaptic transmission, learning, and memory formation. In this work, we investigated the effect of spine and spine apparatus size and shape on the spatio-temporal dynamics of second messengers using mathematical modeling using reaction-diffusion equations in idealized geometries (ellipsoids, spheres, and mushroom-shaped). Our analyses and simulations showed that in the short timescale, spine size and shape coupled with the spine apparatus geometries govern the spatiotemporal dynamics of second messengers. We show that the curvature of the geometries gives rise to pseudo-harmonic functions, which predict the locations of maximum and minimum concentrations along the spine head. Furthermore, we showed that the lifetime of the concentration gradient can be fine-tuned by localization of fluxes on the spine head and varying the relative curvatures and distances between the spine apparatus and the spine head. Thus, we have identified several key geometric determinants of how the spine head and spine apparatus may regulate the short timescale chemical dynamics of small molecules that control synaptic plasticity.
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http://dx.doi.org/10.1038/s41598-019-48028-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691135PMC
August 2019

OSCI: standardized stem cell ontology representation and use cases for stem cell investigation.

BMC Bioinformatics 2019 Apr 25;20(Suppl 5):180. Epub 2019 Apr 25.

Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.

Background: Stem cells and stem cell lines are widely used in biomedical research. The Cell Ontology (CL) and Cell Line Ontology (CLO) are two community-based OBO Foundry ontologies in the domains of in vivo cells and in vitro cell line cells, respectively.

Results: To support standardized stem cell investigations, we have developed an Ontology for Stem Cell Investigations (OSCI). OSCI imports stem cell and cell line terms from CL and CLO, and investigation-related terms from existing ontologies. A novel focus of OSCI is its application in representing metadata types associated with various stem cell investigations. We also applied OSCI to systematically categorize experimental variables in an induced pluripotent stem cell line cell study related to bipolar disorder. In addition, we used a semi-automated literature mining approach to identify over 200 stem cell gene markers. The relations between these genes and stem cells are modeled and represented in OSCI.

Conclusions: OSCI standardizes stem cells found in vivo and in vitro and in various stem cell investigation processes and entities. The presented use cases demonstrate the utility of OSCI in iPSC studies and literature mining related to bipolar disorder.
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http://dx.doi.org/10.1186/s12859-019-2723-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509805PMC
April 2019

Systems pharmacology-based integration of human and mouse data for drug repurposing to treat thoracic aneurysms.

JCI Insight 2019 06 6;4(11). Epub 2019 Jun 6.

Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Marfan syndrome (MFS) is associated with mutations in fibrillin-1 that predispose afflicted individuals to progressive thoracic aortic aneurysm (TAA) leading to dissection and rupture of the vessel wall. Here we combined computational and experimental approaches to identify and test FDA-approved drugs that may slow or even halt aneurysm progression. Computational analyses of transcriptomic data derived from the aortas of MFS patients and MFS mice (Fbn1mgR/mgR mice) predicted that subcellular pathways associated with reduced muscle contractility are key TAA determinants that could be targeted with the GABAB receptor agonist baclofen. Systemic administration of baclofen to Fbn1mgR/mgR mice validated our computational prediction by mitigating arterial disease progression at the cellular and physiological levels. Interestingly, baclofen improved muscle contraction-related subcellular pathways by upregulating a different set of genes than those downregulated in the aorta of vehicle-treated Fbn1mgR/mgR mice. Distinct transcriptomic profiles were also associated with drug-treated MFS and wild-type mice. Thus, systems pharmacology approaches that compare patient- and mouse-derived transcriptomic data for subcellular pathway-based drug repurposing represent an effective strategy to identify potential new treatments of human diseases.
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http://dx.doi.org/10.1172/jci.insight.127652DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629138PMC
June 2019

Genomic signatures defining responsiveness to allopurinol and combination therapy for lung cancer identified by systems therapeutics analyses.

Mol Oncol 2019 08 10;13(8):1725-1743. Epub 2019 Jul 10.

Department of Pharmacological Sciences, Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

The ability to predict responsiveness to drugs in individual patients is limited. We hypothesized that integrating molecular information from databases would yield predictions that could be experimentally tested to develop transcriptomic signatures for specific drugs. We analyzed lung adenocarcinoma patient data from The Cancer Genome Atlas and identified a subset of patients in which xanthine dehydrogenase (XDH) expression correlated with decreased survival. We tested allopurinol, an FDA-approved drug that inhibits XDH, on human non-small-cell lung cancer (NSCLC) cell lines obtained from the Broad Institute Cancer Cell Line Encyclopedia and identified sensitive and resistant cell lines. We utilized the transcriptomic profiles of these cell lines to identify six-gene signatures for allopurinol-sensitive and allopurinol-resistant cell lines. Transcriptomic networks identified JAK2 as an additional target in allopurinol-resistant lines. Treatment of resistant cell lines with allopurinol and CEP-33779 (a JAK2 inhibitor) resulted in cell death. The effectiveness of allopurinol alone or allopurinol and CEP-33779 was verified in vivo using tumor formation in NCR-nude mice. We utilized the six-gene signatures to predict five additional allopurinol-sensitive NSCLC cell lines and four allopurinol-resistant cell lines susceptible to combination therapy. We searched the transcriptomic data from a library of patient-derived NSCLC tumors from the Jackson Laboratory to identify tumors that would be predicted to be sensitive to allopurinol or allopurinol + CEP-33779 treatment. Patient-derived tumors showed the predicted drug sensitivity in vivo. These data indicate that we can use integrated molecular information from cancer databases to predict drug responsiveness in individual patients and thus enable precision medicine.
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http://dx.doi.org/10.1002/1878-0261.12521DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6670022PMC
August 2019

Dynamic balance between vesicle transport and microtubule growth enables neurite outgrowth.

PLoS Comput Biol 2019 05 1;15(5):e1006877. Epub 2019 May 1.

Department of Pharmacological Sciences and Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.

Whole cell responses involve multiple subcellular processes (SCPs). To understand how balance between SCPs controls the dynamics of whole cell responses we studied neurite outgrowth in rat primary cortical neurons in culture. We used a combination of dynamical models and experiments to understand the conditions that permitted growth at a specified velocity and when aberrant growth could lead to the formation of dystrophic bulbs. We hypothesized that dystrophic bulb formation is due to quantitative imbalances between SCPs. Simulations predict redundancies between lower level sibling SCPs within each type of high level SCP. In contrast, higher level SCPs, such as vesicle transport and exocytosis or microtubule growth characteristic of each type need to be strictly coordinated with each other and imbalances result in stalling of neurite outgrowth. From these simulations, we predicted the effect of changing the activities of SCPs involved in vesicle exocytosis or microtubule growth could lead to formation of dystrophic bulbs. siRNA ablation experiments verified these predictions. We conclude that whole cell dynamics requires balance between the higher-level SCPs involved and imbalances can terminate whole cell responses such as neurite outgrowth.
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http://dx.doi.org/10.1371/journal.pcbi.1006877DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546251PMC
May 2019

Spectrum of immune checkpoint inhibitors-induced endocrinopathies in cancer patients: a scoping review of case reports.

Clin Diabetes Endocrinol 2019 22;5. Epub 2019 Jan 22.

1Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan, 24 Frank Lloyd Wright Drive, Ann Arbor, MI 48106 USA.

Background: Since 2011 six immune checkpoint inhibitors (ICI) have been approved to treat patients with many advanced solid tumor and hematological malignancies to improve their prognosis. Case reports of their endocrine immune-related adverse events [irAEs]) are increasingly published as more real-world patients with these malignancies are treated with these drugs. They alert physicians of a drug's AEs (which may change during a drug's life cycle) and contribute to post-marketing safety surveillance. Using a modified framework of Arksey and O'Malley, we conducted a scoping review of the spectrum and characteristics of ICI-induced endocrinopathies case reports before and after ICIs are marketed.

Methods: In July 2017, we searched, without date and language restrictions, 4 citation databases for ICI-induced endocrinopathies. We also hand-searched articles' references, contents of relevant journals, and ran supplemental searches to capture recent reports through January 2018. For this study, a case should have information on type of cancer, type of ICI, clinical presentation, biochemical tests, treatment plus temporal association of ICI initiation with endocrinopathies. Two endocrinologists independently extracted the data which were then summarized and categorized.

Results: One hundred seventy nine articles reported 451 cases of ICI-induced endocrinopathies - 222 hypopituitarism, 152 thyroid disorders, 66 diabetes mellitus, 6 primary adrenal insufficiencies, 1 ACTH-dependent Cushing's syndrome, 1 hypoparathyroidism and 3 diabetes insipidus cases. Their clinical presentations reflect hormone excess or deficiency. Some were asymptomatic and others life-threatening. One or more endocrine glands could be affected. Polyglandular endocrinopathies could present simultaneously or in sequence. Many occur within 5 months of therapy initiation; a few occurred after ICI was stopped. Mostly irreversible, they required long-term hormone replacement. High dose steroids were used when non-endocrine AEs coexisted or as therapy in adrenal insufficiency. There was variability of information in the case reports but all met the study criteria to make a diagnosis.

Conclusions: The spectrum of ICI-induced endocrinopathies is wide (5 glands affected) and their presentation varied (12 endocrinopathies). Clinical reasoning integrating clinical, biochemical and treatment information is needed to properly diagnose and manage them. Physicians should be vigilant for their occurrence and be able to diagnose, investigate and manage them appropriately at onset and follow-up.
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http://dx.doi.org/10.1186/s40842-018-0073-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343255PMC
January 2019

Systems biology primer: the basic methods and approaches.

Essays Biochem 2018 10 26;62(4):487-500. Epub 2018 Oct 26.

Department of Pharmacological Sciences and Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY 10029, U.S.A.

Systems biology is an integrative discipline connecting the molecular components within a single biological scale and also among different scales (e.g. cells, tissues and organ systems) to physiological functions and organismal phenotypes through quantitative reasoning, computational models and high-throughput experimental technologies. Systems biology uses a wide range of quantitative experimental and computational methodologies to decode information flow from genes, proteins and other subcellular components of signaling, regulatory and functional pathways to control cell, tissue, organ and organismal level functions. The computational methods used in systems biology provide systems-level insights to understand interactions and dynamics at various scales, within cells, tissues, organs and organisms. In recent years, the systems biology framework has enabled research in quantitative and systems pharmacology and precision medicine for complex diseases. Here, we present a brief overview of current experimental and computational methods used in systems biology.
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http://dx.doi.org/10.1042/EBC20180003DOI Listing
October 2018

Systems Pharmacology: Defining the Interactions of Drug Combinations.

Annu Rev Pharmacol Toxicol 2019 01 27;59:21-40. Epub 2018 Sep 27.

Department of Pharmacological Sciences, Systems Biology Center, Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; email:

The majority of diseases are associated with alterations in multiple molecular pathways and complex interactions at the cellular and organ levels. Single-target monotherapies therefore have intrinsic limitations with respect to their maximum therapeutic benefits. The potential of combination drug therapies has received interest for the treatment of many diseases and is well established in some areas, such as oncology. Combination drug treatments may allow us to identify synergistic drug effects, reduce adverse drug reactions, and address variability in disease characteristics between patients. Identification of combination therapies remains challenging. We discuss current state-of-the-art systems pharmacology approaches to enable rational identification of combination therapies. These approaches, which include characterization of mechanisms of disease and drug action at a systems level, can enable understanding of drug interactions at the molecular, cellular, physiological, and organismal levels. Such multiscale understanding can enable precision medicine by promoting the rational development of combination therapy at the level of individual patients for many diseases.
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http://dx.doi.org/10.1146/annurev-pharmtox-010818-021511DOI Listing
January 2019

Inpatient Glycemic Management in the Setting of Renal Insufficiency/Failure/Dialysis.

Curr Diab Rep 2018 08 15;18(10):75. Epub 2018 Aug 15.

Department of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Domino's Farms (Lobby G, Suite 1500) 24 Frank Lloyd Wright Drive, Ann Arbor, MI, 48106, USA.

Purpose Of This Review: Chronic diabetic nephropathy and renal dysfunction from other causes are common in hospitalized patients with diabetes. Available diabetes management guidelines aim to reduce hyperglycemia and hypoglycemia, both independent risk factors for hospital outcomes. Renal dysfunction, which increases the risk of hypoglycemia, adds a layer of complexity in diabetes management. Therefore, modified glucose goals and treatment regimens may be required.

Recent Findings: Recent prospective and retrospective studies provide direction on safe insulin therapy for diabetes inpatients with renal compromise. Studies of newer diabetes pharmacotherapy provide data on oral agent use in the inpatient setting. Diabetes therapy should be modified with changing renal function. Glucose management in patients on peritoneal or hemodialysis is challenging. Reducing weight-based doses of insulin and use of newer insulins can reduce hypoglycemia risk. Safety and efficacy of DPP-4 inhibitors has been evaluated in the hospital and nursing home setting. Metformin, SGLT-2 inhibitors, and GLP1 receptor agonists can be used in several stages of renal dysfunction prior to and at discharge.
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http://dx.doi.org/10.1007/s11892-018-1044-yDOI Listing
August 2018

Validating Antibodies for Quantitative Western Blot Measurements with Microwestern Array.

Sci Rep 2018 07 27;8(1):11329. Epub 2018 Jul 27.

Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Fluorescence-based western blots are quantitative in principal, but require determining linear range for each antibody. Here, we use microwestern array to rapidly evaluate suitable conditions for quantitative western blotting, with up to 192 antibody/dilution/replicate combinations on a single standard size gel with a seven-point, two-fold lysate dilution series (~100-fold range). Pilot experiments demonstrate a high proportion of investigated antibodies (17/24) are suitable for quantitative use; however this sample of antibodies is not yet comprehensive across companies, molecular weights, and other important antibody properties, so the ubiquity of this property cannot yet be determined. In some cases microwestern struggled with higher molecular weight membrane proteins, so the technique may not be uniformly applicable to all validation tasks. Linear range for all validated antibodies is at least 8-fold, and up to two orders of magnitude. Phospho-specific and total antibodies do not have discernable trend differences in linear range or limit of detection. Total antibodies generally required higher working concentrations, but more comprehensive antibody panels are required to better establish whether this trend is general or not. Importantly, we demonstrate that results from microwestern analyses scale to normal "macro" western for a subset of antibodies.
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http://dx.doi.org/10.1038/s41598-018-29436-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063895PMC
July 2018

Cell Type-Specific Contributions of the Angiotensin II Type 1a Receptor to Aorta Homeostasis and Aneurysmal Disease-Brief Report.

Arterioscler Thromb Vasc Biol 2018 03 25;38(3):588-591. Epub 2018 Jan 25.

From the Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York.

Objective: Two were the aims of this study: first, to translate whole-genome expression profiles into computational predictions of functional associations between signaling pathways that regulate aorta homeostasis and the activity of angiotensin II type 1a receptor (At1ar) in either vascular endothelial or smooth muscle cells; and second, to characterize the impact of endothelial cell- or smooth muscle cell-specific At1ar disruption on the development of thoracic aortic aneurysm in fibrillin-1 hypomorphic ( ) mice, a validated animal model of early onset progressively severe Marfan syndrome. APPROACH AND RESULTS: and transgenic mice were used to inactivate the At1ar-coding gene () in either intimal or medial cells of both wild type and Marfan syndrome mice, respectively. Computational analyses of differentially expressed genes predicted dysregulated signaling pathways of cell survival and matrix remodeling in aortas and of cell adhesion and contractility in aortas. Characterization of mice revealed increased median survival associated with mitigated aneurysm growth and media degeneration, as well as reduced levels of phosphorylated (p-) Erk1/2 but not p-Smad2. By contrast, levels of both p-Erk1/2 and p-Smad2 proteins were normalized in aortas in spite of them showing no appreciable changes in thoracic aortic aneurysm pathology.

Conclusions: Physiological At1ar signaling in the intimal and medial layers is associated with distinct regulatory processes of aorta homeostasis and function; improper At1ar activity in the vascular endothelium is a significant determinant of thoracic aortic aneurysm development in Marfan syndrome mice.
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http://dx.doi.org/10.1161/ATVBAHA.117.310609DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823778PMC
March 2018

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

Sci Rep 2017 12 18;7(1):17689. Epub 2017 Dec 18.

Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the Molecular Biology of the Cell Ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,384 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed SCP networks for predictive modeling of emergent whole cell functions.
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http://dx.doi.org/10.1038/s41598-017-16627-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5735158PMC
December 2017

Cell shape information is transduced through tension-independent mechanisms.

Nat Commun 2017 12 15;8(1):2145. Epub 2017 Dec 15.

Department of Pharmacological Sciences and Systems Biology Center New York, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

The shape of a cell within tissues can represent the history of chemical and physical signals that it encounters, but can information from cell shape regulate cellular phenotype independently? Using optimal control theory to constrain reaction-diffusion schemes that are dependent on different surface-to-volume relationships, we find that information from cell shape can be resolved from mechanical signals. We used microfabricated 3-D biomimetic chips to validate predictions that shape-sensing occurs in a tension-independent manner through integrin β signaling pathway in human kidney podocytes and smooth muscle cells. Differential proteomics and functional ablation assays indicate that integrin β is critical in transduction of shape signals through ezrin-radixin-moesin (ERM) family. We used experimentally determined diffusion coefficients and experimentally validated simulations to show that shape sensing is an emergent cellular property enabled by multiple molecular characteristics of integrin β. We conclude that 3-D cell shape information, transduced through tension-independent mechanisms, can regulate phenotype.
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http://dx.doi.org/10.1038/s41467-017-02218-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732205PMC
December 2017

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.

Cell Syst 2018 01 29;6(1):13-24. Epub 2017 Nov 29.

BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.
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http://dx.doi.org/10.1016/j.cels.2017.11.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799026PMC
January 2018

A Comparison of mRNA Sequencing with Random Primed and 3'-Directed Libraries.

Sci Rep 2017 11 7;7(1):14626. Epub 2017 Nov 7.

Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Creating a cDNA library for deep mRNA sequencing (mRNAseq) is generally done by random priming, creating multiple sequencing fragments along each transcript. A 3'-end-focused library approach cannot detect differential splicing, but has potentially higher throughput at a lower cost, along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) that correct PCR bias. Here, we compare an implementation of such a 3'-digital gene expression (3'-DGE) approach with "conventional" random primed mRNAseq. Given our particular datasets on cultured human cardiomyocyte cell lines, we find that, while conventional mRNAseq detects ~15% more genes and needs ~500,000 fewer reads per sample for equivalent statistical power, the resulting differentially expressed genes, biological conclusions, and gene signatures are highly concordant between two techniques. We also find good quantitative agreement at the level of individual genes between two techniques for both read counts and fold changes between given conditions. We conclude that, for high-throughput applications, the potential cost savings associated with 3'-DGE approach are likely a reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable many larger scale studies focusing on not only differential expression analysis, but also quantitative transcriptome profiling.
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http://dx.doi.org/10.1038/s41598-017-14892-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676863PMC
November 2017

Fragility of foot process morphology in kidney podocytes arises from chaotic spatial propagation of cytoskeletal instability.

PLoS Comput Biol 2017 03 16;13(3):e1005433. Epub 2017 Mar 16.

R. D. Berlin Center for Cell Analysis & Modeling, U. Connecticut School of Medicine, Farmington, CT, United States of America.

Kidney podocytes' function depends on fingerlike projections (foot processes) that interdigitate with those from neighboring cells to form the glomerular filtration barrier. The integrity of the barrier depends on spatial control of dynamics of actin cytoskeleton in the foot processes. We determined how imbalances in regulation of actin cytoskeletal dynamics could result in pathological morphology. We obtained 3-D electron microscopy images of podocytes and used quantitative features to build dynamical models to investigate how regulation of actin dynamics within foot processes controls local morphology. We find that imbalances in regulation of actin bundling lead to chaotic spatial patterns that could impair the foot process morphology. Simulation results are consistent with experimental observations for cytoskeletal reconfiguration through dysregulated RhoA or Rac1, and they predict compensatory mechanisms for biochemical stability. We conclude that podocyte morphology, optimized for filtration, is intrinsically fragile, whereby local transient biochemical imbalances may lead to permanent morphological changes associated with pathophysiology.
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http://dx.doi.org/10.1371/journal.pcbi.1005433DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373631PMC
March 2017

A biomimetic gelatin-based platform elicits a pro-differentiation effect on podocytes through mechanotransduction.

Sci Rep 2017 03 6;7:43934. Epub 2017 Mar 6.

Department of Chemistry Columbia University, New York, NY 10027, USA.

Using a gelatin microbial transglutaminase (gelatin-mTG) cell culture platform tuned to exhibit stiffness spanning that of healthy and diseased glomeruli, we demonstrate that kidney podocytes show marked stiffness sensitivity. Podocyte-specific markers that are critical in the formation of the renal filtration barrier are found to be regulated in association with stiffness-mediated cellular behaviors. While podocytes typically de-differentiate in culture and show diminished physiological function in nephropathies characterized by altered tissue stiffness, we show that gelatin-mTG substrates with Young's modulus near that of healthy glomeruli elicit a pro-differentiation and maturation response in podocytes better than substrates either softer or stiffer. The pro-differentiation phenotype is characterized by upregulation of gene and protein expression associated with podocyte function, which is observed for podocytes cultured on gelatin-mTG gels of physiological stiffness independent of extracellular matrix coating type and density. Signaling pathways involved in stiffness-mediated podocyte behaviors are identified, revealing the interdependence of podocyte mechanotransduction and maintenance of their physiological function. This study also highlights the utility of the gelatin-mTG platform as an in vitro system with tunable stiffness over a range relevant for recapitulating mechanical properties of soft tissues, suggesting its potential impact on a wide range of research in cellular biophysics.
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http://dx.doi.org/10.1038/srep43934DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5338254PMC
March 2017

Modeling susceptibility to drug-induced long QT with a panel of subject-specific induced pluripotent stem cells.

Elife 2017 01 30;6. Epub 2017 Jan 30.

Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, United States.

A large number of drugs can induce prolongation of cardiac repolarization and life-threatening cardiac arrhythmias. The prediction of this side effect is however challenging as it usually develops in some genetically predisposed individuals with normal cardiac repolarization at baseline. Here, we describe a platform based on a genetically diverse panel of induced pluripotent stem cells (iPSCs) that reproduces susceptibility to develop a cardiotoxic drug response. We generated iPSC-derived cardiomyocytes from patients presenting in vivo with extremely low or high changes in cardiac repolarization in response to a pharmacological challenge with sotalol. In vitro, the responses to sotalol were highly variable but strongly correlated to the inter-individual differences observed in vivo. Transcriptomic profiling identified dysregulation of genes (, ) involved in downstream regulation of cardiac repolarization machinery as underlying high sensitivity to sotalol. Our findings offer novel insights for the development of iPSC-based screening assays for testing individual drug reactions.
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http://dx.doi.org/10.7554/eLife.19406DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5279943PMC
January 2017

MEDICINE. Personalization in practice.

Science 2015 Oct;350(6258):282-3

Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

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http://dx.doi.org/10.1126/science.aad5204DOI Listing
October 2015