The United States produces 41% of the world's corn and 38% of the world's soybeans. These crops comprise two of the four largest sources of caloric energy produced and are thus critical for world food supply. We pair a panel of county-level yields for these two crops, plus cotton (a warmer-weather crop), with a new fine-scale weather dataset that incorporates the whole distribution of temperatures within each day and across all days in the growing season. We find that yields increase with temperature up to 29°C for corn, 30°C for soybeans, and 32°C for cotton but that temperatures above these thresholds are very harmful. The slope of the decline above the optimum is significantly steeper than the incline below it. The same nonlinear and asymmetric relationship is found when we isolate either time-series or cross-sectional variations in temperatures and yields. This suggests limited historical adaptation of seed varieties or management practices to warmer temperatures because the cross-section includes farmers' adaptations to warmer climates and the time-series does not. Holding current growing regions fixed, area-weighted average yields are predicted to decrease by 30 -46% before the end of the century under the slowest (B1) warming scenario and decrease by 63-82% under the most rapid warming scenario (A1FI) under the Hadley III model. agriculture ͉ panel analysis ͉ time series ͉ cross section ͉ farmer adaptation W ith evidence accumulating that greenhouse gas concentrations are warming the world's climate, research focuses increasingly on estimating impacts that may occur under different warming scenarios and how economies might adapt to changing climatic conditions. Agriculture is a key focus because of its direct connection to climate. Although agriculture comprises a small share of GDP in the United States, the U.S. persists in being the world's largest agricultural producer and exporter of agricultural commodities, so impacts in the U.S. could have broad implications for food supply and prices worldwide. At the same time, debate continues about whether warming will be a net gain or loss for agriculture in currently temperate climates like that of the United States (1-8).In this paper, we estimate the link between weather and yields for the three crops with the largest production value in the United States: corn, soybeans, and cotton. Corn and soybeans, the nation's most prevalent crops, are the predominant source of feed grains used in cattle, dairy, poultry, and hog production. Corn is also the main source of U.S. ethanol. Cotton is the fourth-largest crop in acres planted, but more valuable on a per-acre basis and more suited to warmer climates than are corn and soybeans. Estimating the correct relationship between weather and yields for these major crops is a critical first step before more elaborate models can be used to examine how crop-planting choices, food and fiber supply, and prices will ultimately shift in response to climate change.Our data are comprised of new fine-scale weather outcomes merged...

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A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level data set on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased carbon dioxide and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale.

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Francisella tularensis is a gram-negative, facultative intracellular pathogen that causes the highly infectious zoonotic disease tularemia. We have discovered a ca. 30-kb pathogenicity island of F. tularensis (FPI) that includes four large open reading frames (ORFs) of 2.5 to 3.9 kb and 13 ORFs of 1.5 kb or smaller. Previously, two small genes located near the center of the FPI were shown to be needed for intramacrophage growth. In this work we show that two of the large ORFs, located toward the ends of the FPI, are needed for virulence. Although most genes in the FPI encode proteins with amino acid sequences that are highly conserved between high-and low-virulence strains, one of the FPI genes is present in highly virulent type A F. tularensis, absent in moderately virulent type B F. tularensis, and altered in F. tularensis subsp. novicida, which is highly virulent for mice but avirulent for humans. The G؉C content of a 17.7-kb stretch of the FPI is 26.6%, which is 6.6% below the average G؉C content of the F. tularensis genome. This extremely low G؉C content suggests that the DNA was imported from a microbe with a very low G؉C-containing chromosome.

The rapid development of new anticancer drugs that are safe and effective is a common goal shared by basic scientists, clinicians and patients. The current review discusses one such agent, namely niclosamide, which has been used in the clinic for the treatment of intestinal parasite infections. Recent studies repeatedly identified niclosamide as a potential anticancer agent by various high-throughput screening campaigns. Niclosamide not only inhibits the Wnt/β-catenin, mTORC1, STAT3, NF-κB and Notch signaling pathways, but also targets mitochondria in cancer cells to induce cell cycle arrest, growth inhibition and apoptosis. A number of studies have established the anticancer activities of niclosamide in both in vitro and in vivo models. Moreover, the inhibitory effects of niclosamide on cancer stem cells provide further evidence for its consideration as a promising drug for cancer therapy. This article reviews various aspects of niclosamide as they relate to its efficacy against cancer and associated molecular mechanisms.

We present a new framework to identify demand and supply elasticities of agricultural commodities using yield shocks -deviations from a time trend of output per area, which are predominantly caused by weather fluctuations. Demand is identified using current-period shocks that give rise to exogenous shifts in supply. Supply is identified using past shocks, which affect expected future prices through inventory accretion or depletion. We use our estimated elasticities to evaluate the impact of ethanol subsidies and mandates on world food commodity prices, quantities, and food consumers' surplus. The current US ethanol mandate requires that about 5 percent of world caloric production from corn, wheat, rice, and soybeans be used for ethanol generation. As a result, world food prices are predicted to increase by about 30 percent and global consumer surplus from food consumption is predicted to decrease by 155 billion dollars annually. If a third of the biofuel calories are recycled as feed stock for livestock, the predicted price increase scales back to 20 percent. While commodity demand is extremely inelastic, price response is muted by a significant supply response that is obscured if futures prices are not instrumented. The resulting expansion of agricultural growing area potentially offsets the CO2 emission benefits from biofuels.