I\u27ll Return, Mother Darling, to You

https://digitalcommons.library.umaine.edu/mmb-vp/5298/thumbnail.jp

Strengths and Weaknesses of National Agricultural Research Systems: Attracting the Next Generation of Grasslands Researchers

In the 1960s and 1970s the world faced up to the poverty and hunger facing a significant proportion of the global population, which at the time was around 4 billion people. The efforts of Norman Borlaug and the Green Revolution resulted in food production increasing as the technologies and knowledge known at the time were directed to that task. The success of the Green Revolution was such that governments and the world communities turned attention to other issues and agricultural development slid down the list of priorities. The world population is now over 7 billion and projected to be over 9 billion by 2050. FAO (2012b) estimates that around 870 million people were under-nourished (in terms of dietary energy supply) in the period 2010–12; one in eight people globally. Food production will need to increase by 50 to 70% by 2050 to meet food security demands and this increase will have to be achieved through productivity gains given the limitation on global productive lands. Food production faces competition from biofuels, mining and urban sprawl for those lands, making productivity gains an even greater imperative

Long-term safety of siltuximab in patients with idiopathic multicentric Castleman disease: a prespecified, open-label, extension analysis of two trials.

BACKGROUND:Siltuximab is recommended by international consensus as a first-line treatment for idiopathic multicentric Castleman disease on the basis of durable efficacy and safety data. This study was done to assess the long-term safety and activity of siltuximab over up to 6 years of treatment. METHODS:This study is a prespecified open-label extension analysis of a phase 1 trial (NCT00412321) and a phase 2 trial (NCT01024036), done at 26 hospitals worldwide. Patients in both studies were at least 18 years old with histologically confirmed, symptomatic Castleman disease. This extension study enrolled 60 patients who completed the previous trials without disease progression on siltuximab. Patients received siltuximab infusions of 11 mg/kg every 3 weeks (which could be extended to 6 weeks) for up to 6 years. Descriptive statistics were used to summarise the data. No formal hypothesis testing was performed. The primary endpoint was the safety of siltuximab, assessed at each dosing cycle. The study was registered with ClinicalTrials.gov, number NCT01400503 and with EudraCT, number 2010-022837-27. FINDINGS:Patient enrolment into the phase 1 trial was from June 20, 2005, to Sept 15, 2009, and enrolment into the phase 2 trial was from Feb 9, 2010, to Feb 3, 2012. Patients were enrolled in this long-term extension from April 1, 2011, to Jan 15, 2014. Median follow-up was 6 years (IQR 5·11-7·76). Median treatment duration, from the beginning of the previous trials to the end of the present study, was 5·5 years (IQR 4·26-7·14). Siltuximab was well tolerated; however, adverse events of grade 3 or worse were reported in 36 (60%) of 60 patients with the most common being hypertension (eight [13%]), fatigue (five [8%]), nausea (four [7%]), neutropenia (four [7%]), and vomiting (three [5%]). 25 (42%) patients reported at least one serious adverse event, which most commonly was an infection (eight [13%]). Only two serious adverse events, polycythaemia and urinary retention, were considered related to siltuximab treatment. 18 patients discontinued before study completion, either to receive siltuximab locally (eight) or because of progressive disease (two), adverse events (two), or other reasons (six). No deaths were reported. INTERPRETATION:These results show that siltuximab is well tolerated long term and provides important evidence for the feasibility of the life-long use required by patients with idiopathic multicentric Castleman disease. FUNDING:Janssen R&D and EUSA Pharma

Setting and motivation in the decision to participate: An approach to the engagement of diverse samples in mobile research.

Internet and mobile based research are powerful tools in the creation of large, cohort studies (eCohort). However, recent analysis indicates that an underrepresentation of minority and low income groups in these studies might exceed that found in traditional research [1-5]. In this report, we present findings from an experiment in research engagement using the Eureka Research Platform developed to enroll diverse populations in support of biomedical clinical research. This experiment involved the recruitment of African American and Latino participants in a smartphone based survey at a temporary, charitable, dental event sponsored, in part, by the research team, in order to explore the impact of setting and approach on recruitment outcomes. 211 participants enrolled including a significant representation of African Americans (51%) and Latinos (31%) and those with education levels at high school or less (37%). Interviews conducted after the study confirmed that our recruitment efforts within the context of a service event affected the decision to participate. While further research is necessary, this experiment holds promise for the engagement of underrepresented groups in research

Integration of thermochemical water splitting with CO₂ direct air capture

Renewable production of fuels and chemicals from direct air capture (DAC) of CO₂ is a highly desired goal. Here, we report the integration of the DAC of CO₂ with the thermochemical splitting of water to produce CO₂, H₂, O₂, and electricity. The produced CO₂ and H₂ can be converted to value-added chemicals via existing technologies. The integrated process uses thermal solar energy as the only energy input and has the potential to provide the dual benefits of combating anthropogenic climate change while creating renewable chemicals. A sodium–manganese–carbonate (Mn–Na–CO₂) thermochemical water-splitting cycle that simultaneously drives renewable H₂ production and DAC of CO₂ is demonstrated. An integrated reactor is designed and fabricated to conduct all steps of the thermochemical water-splitting cycle that produces close to stoichiometric amounts (∼90%) of H₂ and O₂ (illustrated with 6 consecutive cycles). The ability of the cycle to capture 75% of the ∼400 ppm CO₂ from air is demonstrated also. A technoeconomic analysis of the integrated process for the renewable production of H₂, O₂, and electricity, as well as DAC of CO₂ shows that the proposed scheme of solar-driven H₂ production from thermochemical water splitting coupled with CO₂ DAC may be economically viable under certain circumstances

Comparison of Estimation Procedures for Multilevel AR(1) Models

To estimate a time series model for multiple individuals, a multilevel model may be used.In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo.Furthermore, we examine the difference between modeling fixed and random individual parameters.To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25), the number of individuals per sample (10 or 25), the mean of the autocorrelation (-0.6 to 0.6 inclusive, in steps of 0.3) and the standard deviation of the autocorrelation (0.25 or 0.40).We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators.The fixed estimators profit slightly more from a higher number of time points than the random estimators.When possible, random estimation is preferred to fixed estimation.The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates).Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures