Designing Climate Mitigation Policy

This paper provides an exhaustive review of critical issues in the design of climate mitigation policy by pulling together key findings and controversies from diverse literatures on mitigation costs, damage valuation, policy instrument choice, technological innovation, and international climate policy. We begin with the broadest issue of how high assessments suggest the near and medium term price on greenhouse gases would need to be, both under cost-effective stabilization of global climate and under net benefit maximization or Pigouvian emissions pricing. The remainder of the paper focuses on the appropriate scope of regulation, issues in policy instrument choice, complementary technology policy, and international policy architectures.global warming damages, mitigation cost, climate policy, instrument choice, technology policy

Designing Climate Mitigation Policy

This paper provides an exhaustive review of critical issues in the design of climate mitigation policy by pulling together key findings and controversies from diverse literatures on mitigation costs, damage valuation, policy instrument choice, technological innovation, and international climate policy. We begin with the broadest issue of how high assessments suggest the near and medium term price on greenhouse gases would need to be, both under cost-effective stabilization of global climate and under net benefit maximization or Pigouvian emissions pricing. The remainder of the paper focuses on the appropriate scope of regulation, issues in policy instrument choice, complementary technology policy, and international policy architectures.

Comparative analysis of genome-encoded viral sequences reveals the evolutionary history of flavivirids (family Flaviviridae)

The flavivirids (family Flaviviridae) are a group of positive-strand RNA viruses that pose serious risks to human and animal health on a global scale. Here we use flavivirid-derived DNA sequences, identified in animal genomes, to reconstruct the long-term evolutionary history of family Flaviviridae. We demonstrate that flavivirids are >100 million years old and show that this timing can be combined with dates inferred from co-phyletic analysis to produce a cohesive overview of their evolution, distribution and diversity wherein the main flavivirid subgroups originate in early animals and broadly co-diverge with major animal phyla. In addition, we reveal evidence that the ‘classical flaviviruses’ of vertebrates, most of which are transmitted via blood-feeding arthropod vectors, originally evolved in hematophagous arachnids and later acquired the capacity to be transmitted by insects. Our findings imply that the biological properties of flavivirids have been acquired gradually over the course of animal evolution. Thus, broad-scale comparative analysis will likely reveal fundamental insights into their biology. We therefore published our results via an open, extensible, database (Flavivirid-GLUE), which we constructed to facilitate the wider utilisation of genomic data and evolution-related domain knowledge in flavivirid research

Enabling precision medicine in neonatology, an integrated repository for preterm birth research.

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research

Prescription and Other Medication Use in Pregnancy

OBJECTIVE: To characterize prescription and other medication use in a geographically and ethnically diverse cohort of women in their first pregnancy. METHODS: In a prospective, longitudinal cohort study of nulliparous women followed through pregnancy from the first trimester, medication use was chronicled longitudinally throughout pregnancy. Structured questions and aids were used to capture all medications taken as well as reasons they were taken. Total counts of all medications taken including number in each category and class were captured. Additionally, reasons the medications were taken were recorded. Trends in medications taken across pregnancy and in the first trimester were determined. RESULTS: Of the 9,546 study participants, 9,272 (97.1%) women took at least one medication during pregnancy with 9,139 (95.7%) taking a medication in the first trimester. Polypharmacy, defined as taking at least five medications, occurred in 2,915 (30.5%) women. Excluding vitamins, supplements, and vaccines, 73.4% of women took a medication during pregnancy with 55.1% taking one in the first trimester. The categories of drugs taken in pregnancy and in the first trimester include the following: gastrointestinal or antiemetic agents (34.3%, 19.5%), antibiotics (25.5%, 12.6%), and analgesics (23.7%, 15.6%, which includes 3.6%; 1.4% taking an opioid pain medication). CONCLUSION: In this geographically and ethnically diverse cohort of nulliparous pregnant women, medication use was nearly universal and polypharmacy was common

Risk perception influences athletic pacing strategy.

PURPOSE: The objective of this study is to examine risk taking and risk perception associations with perceived exertion, pacing, and performance in athletes. METHODS: Two experiments were conducted in which risk perception was assessed using the domain-specific risk taking (DOSPERT) scale in 20 novice cyclists (experiment 1) and 32 experienced ultramarathon runners (experiment 2). In experiment 1, participants predicted their pace and then performed a 5-km maximum effort cycling time trial on a calibrated Kingcycle mounted bicycle. Split times and perceived exertion were recorded every kilometer. In experiment 2, each participant predicted their split times before running a 100-km ultramarathon. Split times and perceived exertion were recorded at seven checkpoints. In both experiments, higher and lower risk perception groups were created using median split of DOSPERT scores. RESULTS: In experiment 1, pace during the first kilometer was faster among lower risk perceivers compared with higher risk perceivers (t(18) = 2.0, P = 0.03) and faster among higher risk takers compared with lower risk takers (t(18) = 2.2, P = 0.02). Actual pace was slower than predicted pace during the first kilometer in both the higher risk perceivers (t(9) = -4.2, P = 0.001) and lower risk perceivers (t(9) = -1.8, P = 0.049). In experiment 2, pace during the first 36 km was faster among lower risk perceivers compared with higher risk perceivers (t(16) = 2.0, P = 0.03). Irrespective of risk perception group, actual pace was slower than predicted pace during the first 18 km (t(16) = 8.9, P < 0.001) and from 18 to 36 km (t(16) = 4.0, P < 0.001). In both experiments, there was no difference in performance between higher and lower risk perception groups. CONCLUSIONS: Initial pace is associated with an individual's perception of risk, with low perceptions of risk being associated with a faster starting pace. Large differences between predicted and actual pace suggest that the performance template lacks accuracy, perhaps indicating greater reliance on momentary pacing decisions rather than preplanned strategy.This is the author accepted manuscript. The final version is available from Wolters Kluwer via http://dx.doi.org/10.1249/MSS.000000000000050

Sleep During Pregnancy: The nuMoM2b Pregnancy and Sleep Duration and Continuity Study

Study Objectives: To characterize sleep duration, timing and continuity measures in pregnancy and their association with key demographic variables. Methods: Multisite prospective cohort study. Women enrolled in the nuMoM2b study (nulliparous women with a singleton gestation) were recruited at the second study visit (16-21 weeks of gestation) to participate in the Sleep Duration and Continuity substudy. Women <18 years of age or with pregestational diabetes or chronic hypertension were excluded from participation. Women wore a wrist activity monitor and completed a sleep log for 7 consecutive days. Time in bed, sleep duration, fragmentation index, sleep efficiency, wake after sleep onset, and sleep midpoint were averaged across valid primary sleep periods for each participant. Results: Valid data were available from 782 women with mean age of 27.3 (5.5) years. Median sleep duration was 7.4 hours. Approximately 27.9% of women had a sleep duration of 9 hours. In multivariable models including age, race/ethnicity, body mass index, insurance status, and recent smoking history, sleep duration was significantly associated with race/ethnicity and insurance status, while time in bed was only associated with insurance status. Sleep continuity measures and sleep midpoint were significantly associated with all covariates in the model, with the exception of age for fragmentation index and smoking for wake after sleep onset. Conclusions: Our results demonstrate the relationship between sleep and important demographic characteristics during pregnancy