Direct Imaging in Reflected Light: Characterization of Older, Temperate Exoplanets With 30-m Telescopes

Direct detection, also known as direct imaging, is a method for discovering and characterizing the atmospheres of planets at intermediate and wide separations. It is the only means of obtaining spectra of non-transiting exoplanets. Characterizing the atmospheres of planets in the <5 AU regime, where RV surveys have revealed an abundance of other worlds, requires a 30-m-class aperture in combination with an advanced adaptive optics system, coronagraph, and suite of spectrometers and imagers - this concept underlies planned instruments for both TMT (the Planetary Systems Imager, or PSI) and the GMT (GMagAO-X). These instruments could provide astrometry, photometry, and spectroscopy of an unprecedented sample of rocky planets, ice giants, and gas giants. For the first time habitable zone exoplanets will become accessible to direct imaging, and these instruments have the potential to detect and characterize the innermost regions of nearby M-dwarf planetary systems in reflected light. High-resolution spectroscopy will not only illuminate the physics and chemistry of exo-atmospheres, but may also probe rocky, temperate worlds for signs of life in the form of atmospheric biomarkers (combinations of water, oxygen and other molecular species). By completing the census of non-transiting worlds at a range of separations from their host stars, these instruments will provide the final pieces to the puzzle of planetary demographics. This whitepaper explores the science goals of direct imaging on 30-m telescopes and the technology development needed to achieve them.Comment: (March 2018) Submitted to the Exoplanet Science Strategy committee of the NA

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions

IMPORTANCE Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk. OBJECTIVE To develop and validate a machine-learning algorithm to predict opioid overdose risk among Medicare beneficiaries with at least 1 opioid prescription. DESIGN, SETTING, AND PARTICIPANTS A prognostic study was conducted between September 1, 2017, and December 31, 2018. Participants (n = 560 057) included fee-for-service Medicare beneficiaries without cancer who filled 1 or more opioid prescriptions from January 1, 2011, to December 31, 2015. Beneficiaries were randomly and equally divided into training, testing, and validation samples. EXPOSURES Potential predictors (n = 268), including sociodemographics, health status, patterns of opioid use, and practitioner-level and regional-level factors, were measured in 3-month windows, starting 3 months before initiating opioids until loss of follow-up or the end of observation. MAIN OUTCOMES AND MEASURES Opioid overdose episodes from inpatient and emergency department claims were identified. Multivariate logistic regression (MLR), least absolute shrinkage and selection operator-type regression (LASSO), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN) were applied to predict overdose risk in the subsequent 3 months after initiation of treatment with prescription opioids. Prediction performance was assessed using the C statistic and other metrics (eg, sensitivity, specificity, and number needed to evaluate [NNE] to identify one overdose). The Youden index was used to identify the optimized threshold of predicted score that balanced sensitivity and specificity. RESULTS Beneficiaries in the training (n = 186 686), testing (n = 186 685), and validation (n = 186 686) samples had similar characteristics (mean [SD] age of 68.0 [14.5] years, and approximately 63% were female, 82% were white, 35% had disabilities, 41% were dual eligible, and 0.60% had at least 1 overdose episode). In the validation sample, the DNN (C statistic = 0.91; 95% CI, 0.88-0.93) and GBM (C statistic = 0.90; 95% CI, 0.87-0.94) algorithms outperformed the LASSO (C statistic = 0.84; 95% CI, 0.80-0.89), RF (C statistic = 0.80; 95% CI, 0.75-0.84), and MLR (C statistic = 0.75; 95% CI, 0.69-0.80) methods for predicting opioid overdose. At the optimized sensitivity and specificity, DNN had a sensitivity of 92.3%, specificity of 75.7%, NNE of 542, positive predictive value of 0.18%, and negative predictive value of 99.9%. The DNN classified patients into low-risk (76.2%[142 180] of the cohort), medium-risk (18.6%[34 579] of the cohort), and high-risk (5.2%[9747] of the cohort) subgroups, with only 1 in 10 000 in the low-risk subgroup having an overdose episode. More than 90% of overdose episodes occurred in the high-risk and medium-risk subgroups, although positive predictive values were low, given the rare overdose outcome. CONCLUSIONS AND RELEVANCE Machine-learning algorithms appear to perform well for risk prediction and stratification of opioid overdose, especially in identifying low-risk subgroups that have minimal risk of overdose.NIH/National Institute on Drug Abuse [R01DA044985]; Pharmaceutical Research and Manufacturers of America Foundation Research Starter AwardOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Bacillus Calmette-Guérin vaccination as defense against SARS-CoV-2 (BADAS):a randomized controlled trial to protect healthcare workers in the USA by enhanced trained immune responses

Background: A large epidemic, such as that observed with SARS-CoV-2, seriously challenges available hospital capacity, and this would be augmented by infection of healthcare workers (HCW). Bacillus Calmette-Guérin (BCG) is a vaccine against tuberculosis, with protective non-specific effects against other respiratory tract infections in vitro and in vivo. Preliminary analyses suggest that regions of the world with existing BCG vaccination programs have lower incidence and mortality from COVID-19. We hypothesize that BCG vaccination can reduce SARS-CoV-2 infection and disease severity. Methods: This will be a placebo-controlled adaptive multi-center randomized controlled trial. A total of 1800 individuals considered to be at high risk, including those with comorbidities (hypertension, diabetes, obesity, reactive airway disease, smokers), racial and ethnic minorities, elderly, teachers, police, restaurant wait-staff, delivery personnel, health care workers who are defined as personnel working in a healthcare setting, at a hospital, medical center or clinic (veterinary, dental, ophthalmology), and first responders (paramedics, firefighters, or law enforcement), will be randomly assigned to two treatment groups. The treatment groups will receive intradermal administration of BCG vaccine or placebo (saline) with groups at a 1:1 ratio. Individuals will be tracked for evidence of SARS-CoV-2 infection and severity as well as obtaining whole blood to track immunological markers, and a sub-study will include cognitive function and brain imaging. The majority of individuals will be followed for 6 months, with an option to extend for another 6 months, and the cognitive sub-study duration is 2 years. We will plot Kaplan-Meier curves that will be plotted comparing groups and hazard ratios and p-values reported using Cox proportional hazard models. Discussion: It is expected this trial will allow evaluation of the effects of BCG vaccination at a population level in high-risk healthcare individuals through a mitigated clinical course of SARS-CoV-2 infection and inform policy making during the ongoing epidemic. Trial registration: ClinicalTrials.gov NCT04348370. Registered on April 16, 2020.</p

Role of Adjuvant Multimodality Therapy After Curative-Intent Resection of Ampullary Carcinoma

Importance: Ampullary adenocarcinoma is a rare malignant neoplasm that arises within the duodenal ampullary complex. The role of adjuvant therapy (AT) in the treatment of ampullary adenocarcinoma has not been clearly defined. Objective: To determine if long-term survival after curative-intent resection of ampullary adenocarcinoma may be improved by selection of patients for AT directed by histologic subtype. Design, setting, and participants: This multinational, retrospective cohort study was conducted at 12 institutions from April 1, 2000, to July 31, 2017, among 357 patients with resected, nonmetastatic ampullary adenocarcinoma receiving surgery alone or AT. Cox proportional hazards regression was used to identify covariates associated with overall survival. The surgery alone and AT cohorts were matched 1:1 by propensity scores based on the likelihood of receiving AT or by survival hazard from Cox modeling. Overall survival was compared with Kaplan-Meier estimates. Exposures: Adjuvant chemotherapy (fluorouracil- or gemcitabine-based) with or without radiotherapy. Main outcomes and measures: Overall survival. Results: A total of 357 patients (156 women and 201 men; median age, 65.8 years [interquartile range, 58-74 years]) underwent curative-intent resection of ampullary adenocarcinoma. Patients with intestinal subtype had a longer median overall survival compared with those with pancreatobiliary subtype (77 vs 54 months; P = .05). Histologic subtype was not associated with AT administration (intestinal, 52.9% [101 of 191]; and pancreatobiliary, 59.5% [78 of 131]; P = .24). Patients with pancreatobiliary histologic subtype most commonly received gemcitabine-based regimens (71.0% [22 of 31]) or combinations of gemcitabine and fluorouracil (12.9% [4 of 31]), whereas treatment of those with intestinal histologic subtype was more varied (fluorouracil, 50.0% [17 of 34]; gemcitabine, 44.1% [15 of 34]; P = .01). In the propensity score-matched cohort, AT was not associated with a survival benefit for either histologic subtype (intestinal: hazard ratio, 1.21; 95% CI, 0.67-2.16; P = .53; pancreatobiliary: hazard ratio, 1.35; 95% CI, 0.66-2.76; P = .41). Conclusions and relevance: Adjuvant therapy was more frequently used in patients with poor prognostic factors but was not associated with demonstrable improvements in survival, regardless of tumor histologic subtype. The value of a multimodality regimen remains poorly defined

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven\u27t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics

Detailed Analysis of a Contiguous 22-Mb Region of the Maize Genome

Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on ∼1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses

Direct Imaging in Reflected Light: Characterization of Older, Temperate Exoplanets With 30-m Telescopes

Direct detection, also known as direct imaging, is a method for discovering and characterizing the atmospheres of planets at intermediate and wide separations. It is the only means of obtaining spectra of non-transiting exoplanets. Characterizing the atmospheres of planets in the <5 AU regime, where RV surveys have revealed an abundance of other worlds, requires a 30-m-class aperture in combination with an advanced adaptive optics system, coronagraph, and suite of spectrometers and imagers - this concept underlies planned instruments for both TMT (the Planetary Systems Imager, or PSI) and the GMT (GMagAO-X). These instruments could provide astrometry, photometry, and spectroscopy of an unprecedented sample of rocky planets, ice giants, and gas giants. For the first time habitable zone exoplanets will become accessible to direct imaging, and these instruments have the potential to detect and characterize the innermost regions of nearby M-dwarf planetary systems in reflected light. High-resolution spectroscopy will not only illuminate the physics and chemistry of exo-atmospheres, but may also probe rocky, temperate worlds for signs of life in the form of atmospheric biomarkers (combinations of water, oxygen and other molecular species). By completing the census of non-transiting worlds at a range of separations from their host stars, these instruments will provide the final pieces to the puzzle of planetary demographics. This whitepaper explores the science goals of direct imaging on 30-m telescopes and the technology development needed to achieve them

Identifying viable regulatory and innovation pathways for regenerative medicine:A case study of cultured red blood cells

The creation of red blood cells for the blood transfusion markets represents a highly innovative application of regenerative medicine with a medium term (5–10 year) prospect for first clinical studies. This article describes a case study analysis of a project to derive red blood cells from human embryonic stem cells, including the systemic challenges arising from (i) the selection of appropriate and viable regulatory protocols and (ii) technological constraints related to stem cell manufacture and scale up to clinical Good Manufacturing Practice (GMP) standard. The method used for case study analysis (Analysis of Life Science Innovation Systems (ALSIS)) is also innovative, demonstrating a new approach to social and natural science collaboration to foresight product development pathways. Issues arising along the development pathway include cell manufacture and scale-up challenges, affected by regulatory demands emerging from the innovation ecosystem (preclinical testing and clinical trials). Our discussion reflects on the efforts being made by regulators to adapt the current pharmaceuticals-based regulatory model to an allogeneic regenerative medicine product and the broader lessons from this case study for successful innovation and translation of regenerative medicine therapies, including the role of methodological and regulatory innovation in future development in the field

Six RNA Viruses and Forty-One Hosts: Viral Small RNAs and Modulation of Small RNA Repertoires in Vertebrate and Invertebrate Systems

We have used multiplexed high-throughput sequencing to characterize changes in small RNA populations that occur during viral infection in animal cells. Small RNA-based mechanisms such as RNA interference (RNAi) have been shown in plant and invertebrate systems to play a key role in host responses to viral infection. Although homologs of the key RNAi effector pathways are present in mammalian cells, and can launch an RNAi-mediated degradation of experimentally targeted mRNAs, any role for such responses in mammalian host-virus interactions remains to be characterized. Six different viruses were examined in 41 experimentally susceptible and resistant host systems. We identified virus-derived small RNAs (vsRNAs) from all six viruses, with total abundance varying from “vanishingly rare” (less than 0.1% of cellular small RNA) to highly abundant (comparable to abundant micro-RNAs “miRNAs”). In addition to the appearance of vsRNAs during infection, we saw a number of specific changes in host miRNA profiles. For several infection models investigated in more detail, the RNAi and Interferon pathways modulated the abundance of vsRNAs. We also found evidence for populations of vsRNAs that exist as duplexed siRNAs with zero to three nucleotide 3′ overhangs. Using populations of cells carrying a Hepatitis C replicon, we observed strand-selective loading of siRNAs onto Argonaute complexes. These experiments define vsRNAs as one possible component of the interplay between animal viruses and their hosts