Leucine and tissue distribution of bulky and small neutral amino acids in rats: Dissociation between transport and insulin-mediated effects

The mechanism of the observed decrease in the plasma concentration of several amino acids in the presence of high levels of Leu has remained unexplained. In the present study a decrease in the plasma concentration of Ile, Val, Phe, Tyr, Met, Ala, Pro and Gly was observed after the intraperitoneal injection of Leu to weanling rats. Decreases in net intracellular concentrations in muscle accompanied the decrease in plasma of all of these amino acids except Pro and Gly. An increase in the distribution ratio muscle/plasma was observed exclusively for Gly after administration of Leu or of a non-insulinogenic transport system L analogue. Diazoxide suppressed the Leu-induced decreases in plasma and muscle intracellular concentrations of Ile and Val as well as of Pro in plasma. An increase in the distribution ratio liver/plasma was observed for Pro and Gly in the absence but not in the presence of diazoxide. All the above changes were statistically significant. Hence insulin probably mediates Leu effects, promoting an increased utilization of Ile and Val in muscle and of Pro in liver. A more direct effect of Leu appears to be involved in the apparent increased utilization of Phe, Tyr and Ala in the same tissue. Gly depletion in plasma can be explained by its trapping by inhibitory action of Leu on the exodus of Gly through transport system L.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42495/1/10545_2005_Article_BF01800357.pd

International agricultural research to reduce food risks: case studies on aflatoxins

Despite massive expansion of human and livestock populations, fuelled by agricultural innovations, nearly one billion people are hungry and 2 billion are sickened each year from the food they eat. Agricultural and food systems are intimately connected to health outcomes, but health policy and programs often stop at the clinic door. A consensus is growing that the disconnection between agriculture, health and nutrition is at least partly responsible for the disease burden associated with food and farming. Mycotoxins produced by fungi are one of the most serious food safety problems affecting staple crops (especially maize and groundnuts). Aflatoxins, the best studied of these mycotoxins, cause around 90,000 cases of liver cancer each year and are strongly associated with stunting and immune suppression in children. Mycotoxins also cause major economic disruptions through their impacts on trade and livestock production. In this paper we use the case of fungal toxins to explore how agricultural research can produce innovations, understand incentives and enable institutions to improve, simultaneously, food safety, food accessibility for poor consumers and access to markets for smallholder farmers, thus making the case for research investors to support research into agricultural approaches for enhancing food safety in value chains. We first discuss the evolution of food safety research within the CGIAR. Then we show how taking an epidemiological and economic perspective on aflatoxin research connects health and nutrition outcomes. Finally, we present three case studies illustrating the traditional strengths of CGIAR research: breeding better varieties and developing new technologies

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed