Thermotolerance and molecular chaperone function of the small heat shock protein HSP20 from hyperthermophilic archaeon, Sulfolobus solfataricus P2

Small heat shock proteins are ubiquitous in all three domains (Archaea, Bacteria and Eukarya) and possess molecular chaperone activity by binding to unfolded polypeptides and preventing aggregation of proteins in vitro. The functions of a small heat shock protein (S.so-HSP20) from the hyperthermophilic archaeon, Sulfolobus solfataricus P2 have not been described. In the present study, we used real-time polymerase chain reaction analysis to measure mRNA expression of S.so-HSP20 in S. solfataricus P2 and found that it was induced by temperatures that were substantially lower (60°C) or higher (80°C) than the optimal temperature for S. solfataricus P2 (75°C). The expression of S.so-HSP20 mRNA was also up-regulated by cold shock (4°C). Escherichia coli cells expressing S.so-HSP20 showed greater thermotolerance in response to temperature shock (50°C, 4°C). By assaying enzyme activities, S.so-HSP20 was found to promote the proper folding of thermo-denatured citrate synthase and insulin B chain. These results suggest that S.so-HSP20 promotes thermotolerance and engages in chaperone-like activity during the stress response

Genomes of multicellular algal sisters to land plants illuminate signaling network evolution

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum. We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

Investment Cycles and Startup Innovation * Investment Cycles and Startup Innovation

Abstract We find that VC-backed firms receiving their initial investment in hot markets are less likely to IPO, but conditional on going public are valued higher on the day of their IPO, have more patents and have more citations to their patents. Our results suggest that VCs invest in riskier and more innovative startups in hot markets (rather than just worse firms). This is true even for the most experienced VCs. Furthermore, our results suggest that the flood of capital in hot markets also plays a causal role in shifting investments to more novel startups -by lowering the cost of experimentation for early stage investors and allowing them to make riskier, more novel, investments. JEL Classification: G24, G32, O31 Key Words: Venture Capital, Innovation, Market Cycles, Financing Risk * Soldiers Field Road, Boston, MA 02163, USA. Email: [email protected] and [email protected]. We are grateful to Bo Becker, Shai Bernstein, Michael Ewens, Bill Kerr, Paul Gompers, Robin Greenwood, Thomas Hellmann, Josh Lerner, David Scharfstein, Antoinette Schoar and Rick Townsend for fruitful discussion and comments, and to the seminar participants at MIT, UT Austin, Tuck School of Business, Harvard, Houston University, Northeastern University, University of Lausanne, Notre Dame, Hong Kong University. We thank Oliver Heimes and Sarah Wolverton for research assistance, and the Division of Faculty Research and Development at HBS and the Kauffman Foundation for financial support. All errors are our own. 1 Investment Cycles and Startup Innovation Abstract We find that VC-backed firms receiving their initial investment in hot markets are less likely to IPO, but conditional on going public are valued higher on the day of their IPO, have more patents and have more citations to their patents. Our results suggest that VCs invest in riskier and more innovative startups in hot markets (rather than just worse firms). This is true even for the most experienced VCs. Furthermore, our results suggest that the flood of capital in hot markets also plays a causal role in shifting investments to more novel startups -by lowering the cost of experimentation for early stage investors and allowing them to make riskier, more novel, investments. JEL Classification: G24, G32, O3

Investment Cycles and Startup Innovation * Investment Cycles and Startup Innovation

Abstract We find that VC-backed firms receiving their initial investment in hot markets are more likely to go bankrupt, but conditional on going public are valued higher on the day of their IPO, have more patents and have more citations to their patents. Our results suggest that VCs invest in riskier and more innovative startups in hot markets (rather than just worse firms). This is true even for the most experienced VCs. Furthermore, our results suggest that the flood of capital in hot markets also plays a causal role in shifting investments to more novel startups -by lowering the cost of experimentation for early stage investors and allowing them to make riskier, more novel, investments. JEL Classification: G24, G32, O31 Key Words: Venture Capital, Innovation, Market Cycles, Financing Risk * Soldiers Field Road, Boston, MA 02163, USA. Email: [email protected] and [email protected]. We are grateful to Bo Becker, Shai Bernstein, Lee Fleming, Michael Ewens, Bill Kerr, Paul Gompers, Robin Greenwood, Thomas Hellmann, Josh Lerner, David Mowery, David Scharfstein, Antoinette Schoar and Rick Townsend for fruitful discussion and comments, and to the seminar participants at MIT, UT Austin, Tuck School of Business, Harvard, Houston University, UC Berkeley, Northeastern University, University of Lausanne, Notre Dame, Hong Kong University. We thank Oliver Heimes and Sarah Wolverton for research assistance, and the Division of Faculty Research and Development at HBS and the Kauffman Foundation for financial support. All errors are our own. 1 Investment Cycles and Startup Innovation Abstract We find that VC-backed firms receiving their initial investment in hot markets are more likely to go bankrupt, but conditional on going public are valued higher on the day of their IPO, have more patents and have more citations to their patents. Our results suggest that VCs invest in riskier and more innovative startups in hot markets (rather than just worse firms). This is true even for the most experienced VCs. Furthermore, our results suggest that the flood of capital in hot markets also plays a causal role in shifting investments to more novel startups -by lowering the cost of experimentation for early stage investors and allowing them to make riskier, more novel, investments. JEL Classification: G24, G32, O3

THE KNOWLEDGE FILTER, ENTREPRENEURSHIP, AND ECONOMIC GROWTH

This paper explores the relationship between knowledge creation, entrepreneurship, and economic growth in the United States over the last 150 years. According to the “new growth theory,” investments in knowledge and human capital generate economic growth via spillovers of knowledge. But the theory does not explain how or why spillovers occur, or why large investments in R&amp;D do not always result in economic growth. What is missing is “the knowledge filter” - the distinction between general knowledge and economically useful knowledge. Also missing is a mechanism (such as entrepreneurship) converting economically relevant knowledge into economic activity. This paper shows that the unprecedented increase in R&amp;D spending in the United States during and after World War II was converted into economic activity via incumbent firms in the early postwar period and increasingly via new ventures in the last few decades.QC 2012020