Economically optimal timing for crop disease control under uncertainty: an options approach

Severe large-scale disease and pest infestations in agricultural regions can cause significant economic damage. Understanding if and when disease control measures should be taken in the presence of risk and uncertainty is a key issue. We develop a framework to examine the economically optimal timing of treatment. The decision to treat should only be undertaken when the benefits exceed the costs by a certain amount and not if they are merely equal to or greater than the costs as standard net-present-value (NPV) analysis suggests. This criterion leads to a reduction in fungicide use. We investigate the effect of the model for disease progress on the value required for immediate treatment by comparing two standard models for disease increase (exponential and logistic growth). Analyses show that the threshold value of benefits required for immediate release of treatment varies significantly with the relative duration of the agricultural season, the intrinsic rate of increase of the disease and the level of uncertainty in disease progression. In comparing the performance of the delay strategy introduced here with the conventional NPV approach, we show how the degree of uncertainty affects the benefits of delaying control

Policy recommendations from the 13th ICABR conference on the emerging bioeconomy

The International Consortium on Agricultural Biotechnology Research held its 13th annual conference in Ravello, Italy in June 2009. The theme of the conference was the bioeconomy,and this topic was addressed through research presentations from academia, government, and industry. Numerous presentations from developing countries highlighted the benefits of agricultural biotechnology in these nations. The broad range of presentations provided a wealth of insights, resulting in three policy recommendations regarding future funding, international regulation, and technology transfer.global food crisis, biofuels, food safety, innovation

Immune related endonucleases and GTPases are not associated with tumor response in patients with advanced non-small cell lung cancer treated with checkpoint inhibitors

Immune related endonucleases have recently been described as potential therapeutic targets and predictors of response to treatment with immune checkpoint inhibitors (ICI). The aim is to evaluate the association between the expression of 5 biomarkers involved in the immune response (CD73, CD39, VISTA, Arl4d and Cytohesin-3) in parallel with the more common ICI-predictive markers, PD-L1 expression and Tumor Mutation Burden (TMB) with response to ICI therapy in an advanced non-small cell lung cancer (NSCLC) cohort. METHODS: Patients with advanced NSCLC treated with ICI single agent were divided into responders and non-responders according to RECIST v1.1 and duration of response (DOR) criteria. Immunohistochemistry was performed on pretreatment tumor tissue samples for PD-L1, CD73, CD39, VISTA, Arl4d, and Cytohesin-3 expression. TMB was estimated with NEOplus v2 RUO (NEO New Oncology GmbH) hybrid capture next generation sequencing assay. Resistance mutations in STK11/KEAP1 and positive predictive mutations in ARID1A/POLE were also evaluated. RESULTS: Included were 56 patients who were treated with ICI single agent. The median progression-free and overall survival for the whole cohort was 3.0 (95% CI, 2.4-3.6) and 15 (95% CI, 9.7-20.2) months, respectively. The distribution of CD73 in tumor cells and CD39, VISTA, Arl4d and Cytohesin-3 expression in immune cells were not different between responders and non-responders. Also, PD-L1 and TMB were not predictive for response. The frequency of STK11, KEAP1 and ARID1A mutations was low and only observed in the non-responder group. CONCLUSION: Separate and combined expression of 5 biomarkers involved in the immune response (CD73, CD39, VISTA, Arl4d, and Cytohesin-3) was not associated with response in our cohort of advanced NSCLC patients receiving single agent ICI. To confirm our findings the analysis of independent larger cohorts is warranted

Investing in antibiotics to alleviate future catastrophic outcomes : what is the value of having an effective antibiotic to mitigate pandemic influenza?

Over 95% of post-mortem samples from the 1918 pandemic, which caused 50 to 100 million deaths, showed bacterial infection complications. The introduction of antibiotics in the 1940s has since reduced the risk of bacterial infections, but growing resistance to antibiotics could increase the toll from future influenza pandemics if secondary bacterial infections are as serious as in 1918, or even if they are less severe. We develop a valuation model of the option to withhold wide use of an antibiotic until significant outbreaks such as pandemic influenza or foodborne diseases are identified. Using real options theory, we derive conditions under which withholding wide use is beneficial, and calculate the option value for influenza pandemic scenarios that lead to secondary infections with a resistant Staphylococcus aureus strain. We find that the value of withholding an effective novel oral antibiotic can be positive and significant unless the pandemic is mild and causes few secondary infections with the resistant strain or if most patients can be treated intravenously. Although the option value is sensitive to parameter uncertainty, our results suggest that further analysis on a case-by-case basis could guide investment in novel agents as well as strategies on how to use them

Policy recommendations from the 13th ICABR conference on the emerging bioeconomy

The International Consortium on Agricultural Biotechnology Research held its 13th annual conference in Ravello, Italy in June 2009. The theme of the conference was the bioeconomy,and this topic was addressed through research presentations from academia, government, and industry. Numerous presentations from developing countries highlighted the benefits of agricultural biotechnology in these nations. The broad range of presentations provided a wealth of insights, resulting in three policy recommendations regarding future funding, international regulation, and technology transfer

The ethics of psychopharmacological research in legal minors

Research in psychopharmacology for children and adolescents is fraught with ethical problems and tensions. This has practical consequences as it leads to a paucity of the research that is essential to support the treatment of this vulnerable group. In this article, we will discuss some of the ethical issues which are relevant to such research, and explore their implications for both research and standard care. We suggest that finding a way forward requires a willingness to acknowledge and discuss the inherent conflicts between the ethical principles involved. Furthermore, in order to facilitate more, ethically sound psychopharmacology research in children and adolescents, we suggest more ethical analysis, empirical ethics research and ethics input built into psychopharmacological research design

The highly potent AhR agonist picoberin modulates Hh-dependent osteoblast differentiation

Identification and analysis of small molecule bioactivity in target-agnostic cellular assays and monitoring changes in phenotype followed by identification of the biological target are a powerful approach for the identification of novel bioactive chemical matter in particular when the monitored phenotype is disease-related and physiologically relevant. Profiling methods that enable the unbiased analysis of compound-perturbed states can suggest mechanisms of action or even targets for bioactive small molecules and may yield novel insights into biology. Here we report the enantioselective synthesis of natural-product-inspired 8-oxotetrahydroprotoberberines and the identification of Picoberin, a low picomolar inhibitor of Hedgehog (Hh)-induced osteoblast differentiation. Global transcriptome and proteome profiling revealed the aryl hydrocarbon receptor (AhR) as the molecular target of this compound and identified a cross talk between Hh and AhR signaling during osteoblast differentiation