48 research outputs found

    High times: The effect of medical marijuana laws on student time use

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    Medical marijuana laws (MMLs) represent a major change of marijuana policy in the U.S. Previous research shows that these laws increase marijuana use among adults. In this paper, we estimate the effects of MMLs on secondary and post-secondary students’ time use using data from the American Time Use Survey. We apply a difference-in-differences research design and estimate flexible fixed effects models that condition on state fixed effects and state-specific time trends. We find no effect of MMLs on secondary students’ time use. However, we find that college students in MML states spend approximately 20% less time on education-related activities and 20% more time on leisure activities than their counterparts in non-MML states. These behavioral responses largely occur during weekends and summer when students have more spare time. Finally, the impacts of MMLs are heterogeneous and stronger among part-time college students, who are more likely to be first-generation college goers and to come from underrepresented racial and ethnic groups

    Gender gap in upward mobility: What is the role of non-cognitive traits?

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    Do non-cognitive traits contribute to the gender gap in supervisory status and promotion? We use a large linked employer-employee dataset collected from six former socialist countries to assess the link between non-cognitive traits and upward mobility. Controlling for on workplace heterogeneity, we find that gender differences in locus of control, the preference for challenge versus affiliation, and adherence to work ethic together can explain about 7–18% of the gender gap in supervisory status and promotions Overall, non-cognitive traits provide an important, though incomplete, explanation for the gender gap in upward mobility

    Economic development and intergenerational earnings mobility: Evidence from Taiwan

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    How economic development affects intergenerational earnings elasticity is not well-documented. In this paper, we estimate intergenerational earnings elasticities between fathers and sons in two periods. In the current period, 2005–2010, Taiwan is already a developed economy with slower economic growth. We apply the two-sample approach developed by Björklund and Jäntti (1997) and find that intergenerational earnings elasticity is around 0.4–0.5 in this period. In the earlier period, 1990–1994, Taiwan was still a developing economy with fast economic growth. We mimic the Björklund-Jäntti two-sample approach and use average earnings by occupation as a proxy for fathers’ earnings. To quantify potential bias, we apply the same method to the 2005–2010 data. Our proxy method yields similar estimates in both the early 1990s and late 2000s. These results suggest stable intergenerational transmission of economic status in Taiwan, despite its rapid economic development

    Non-Cognitive Abilities And Labor Market Outcomes: The Role Of Work Ethic And Personality Traits On Supervisory Status And Promotion

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    A growing literature suggests that noncognitive abilities are important determinants of earnings. But empirical research on nonwage labor market outcomes is still limited due to data availability. In this paper, we collect employer-employee linked data from six former socialist countries and estimate three noncognitive abilities: adherence to work ethic, the preference for challenge versus affiliation, and locus of control, and their relationship with workers’ supervisory status and promotions. We find that these noncognitive abilities are strong predictors of the likelihood of being a supervisor and being promoted as well as the number of supervisees and promotions. We also study the role of noncognitive abilities in the gender gap in these labor market outcomes. Based on a Blinder-Oaxaca decomposition, gender differences in these noncognitive abilities can explain a modest proportion of the gender gap in supervisory status and promotions

    Do medical marijuana laws increase hard drug use?

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    Medical marijuana laws generate significant policy debates regarding drug policy. In particular, if marijuana is a complement or a gateway drug to hard drugs, these laws would increase not only the usage of marijuana but hard drugs such as cocaine and heroin. In this paper, I empirically study the relationships between marijuana and cocaine or heroin by analyzing data on drug possession arrests and rehabilitation treatment admissions. I find that medical marijuana laws increase marijuana arrests and treatments by 10–20%. However, there is no evidence that cocaine and heroin usage increases after the passage of medical marijuana laws. In fact, the estimates on cocaine and heroin arrests or treatments are uniformly negative. From the arrest data, the estimates indicate a 0–20% decrease in possession arrests for cocaine and heroin combined. From the treatment data, the estimates show a 20% decrease in heroin treatments but no significant effect on cocaine treatments. These results suggest that marijuana could be a substitute for heroin

    Non-Cognitive Abilities And Labor Market Outcomes: The Role Of Work Ethic And Personality Traits On Supervisory Status And Promotion

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    A growing literature suggests that noncognitive abilities are important determinants of earnings. But empirical research on nonwage labor market outcomes is still limited due to data availability. In this paper, we collect employer-employee linked data from six former socialist countries and estimate three noncognitive abilities: adherence to work ethic, the preference for challenge versus affiliation, and locus of control, and their relationship with workers’ supervisory status and promotions. We find that these noncognitive abilities are strong predictors of the likelihood of being a supervisor and being promoted as well as the number of supervisees and promotions. We also study the role of noncognitive abilities in the gender gap in these labor market outcomes. Based on a Blinder-Oaxaca decomposition, gender differences in these noncognitive abilities can explain a modest proportion of the gender gap in supervisory status and promotions

    Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

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    Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019

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    Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
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