Lessons and recommendations from three decades as an NSF REU site: A call for systems‐based assessment

For more than 30 years, the US National Science Foundation's Research Experiences for Undergraduates (REU) program has supported thousands of undergraduate researchers annually and provides many students with their first research experiences in field ecology or evolution. REUs embed students in scientific communities where they apprentice with experienced researchers, build networks with their peers, and help students understand research cultures and how to work within them. REUs are thought to provide formative experiences for developing researchers that differ from experiences in a college classrooms, laboratories, or field trips. REU assessments have improved through time but they are largely ungrounded in educational theory. Thus, evaluation of long‐term impacts of REUs remains limited and best practices for using REUs to enhance student learning are repeatedly re‐invented. We describe how one sociocultural learning framework, cultural–historical activity theory (CHAT), could be used to guide data collection to characterize the effects of REU programs on participant's learning in an educationally meaningful context. CHAT embodies a systems approach to assessment that accounts for social and cultural factors that influence learning. We illustrate how CHAT has guided assessment of the Harvard Forest Summer Research Program in Ecology (HF‐SRPE), one of the longest‐running REU sites in the United States. Characterizing HF‐SRPE using CHAT helped formalize thoughts and language for the program evaluation, reflect on potential barriers to success, identify assessment priorities, and revealed important oversights in data collection.     

Case studies on the use of biotechnologies and on biosafety provisions in four African countries

This review is based on a study commissioned by the European Commission on the evaluation of scientific, technical and institutional challenges, priorities and bottlenecks for biotechnologies and regional harmonisation of biosafety in Africa. Biotechnology was considered within four domains: agricultural biotechnologies (‘Green’), industrial biotechnologies and biotechnologies for environmental remediation (‘White’), biotechnologies in aquaculture (‘Blue’) and biotechnologies for healthcare (‘Red’). An important consideration was the decline in partnerships between the EU and developing countries because of the original public antipathy to some green biotechnologies, particularly genetically modified organisms (GMOs) and food from GM crops in Europe. The study focus reported here was West Africa (Ghana, Senegal, Mali and Burkina Faso).The overall conclusion was that whereas high-quality research was proceeding in the countries visited, funding is not sustained and there is little evidence of practical application of biotechnology and benefit to farmers and the wider community. Research and development that was being carried out on genetically modified crop varieties was concentrating on improving food security and therefore unlikely to have significant impact on EU markets and consumers. However, there is much non-controversial green biotechnology such as molecular diagnostics for plant and animal disease and marker-assisted selection for breeding that has great potential application. Regarding white biotechnology, it is currently occupying only a very small industrial niche in West Africa, basically in the sole sector of the production of liquid biofuels (i.e., bio-ethanol) from indigenous and locally planted biomass (very often non-food crops). The presence of diffused small-scale fish production is the basis to develop and apply new (Blue) aquaculture technologies and, where the research conditions and the production sector can permit, to increase this type of production and the economy of this depressed areas. However, the problems bound to environmental protection must not be forgotten; priority should be given to monitor the risks of introduction of foreign species. Red biotechnologies potentially bring a vast domain of powerful tools and processes to achieve better human health, most notably improved diagnostics by molecular techniques, better targeting of pathogens and a better knowledge of their sensitivities to drugs to permit better treatment.Biosafety regulatory frameworks had been initiated in several countries, starting with primary biosafety law. However, disparate attitudes to the purpose of biosafety regulation (e.g., fostering informed decision-making versus ‘giving the green-light for a flood of GMOs’) currently prevent a needed consensus for sub-regional harmonisation. To date, most R&D funding has come from North America with some commercial interests from Asia, but African biotechnology workers expressed strong desire for (re-)engagement with interested parties from the European Union. Although in some of the visited countries there are very well qualified personnel in molecular biology and biosafety/regulation, the main message received is that human resources and capacity building in-house are still needed. This could be achieved through home-based courses and capacity-building including funds for post-degree research to motivate and retain trained staff.     

Assessing the effects of cognitive experiments on the welfare of captive chimpanzees (Pan troglodytes) by direct comparison of activity budget between wild and captive chimpanzees

We investigated the effects of cognitive experiments by direct comparison of activity budgets between wild and captive chimpanzees. One goal of captive management is to ensure that the activity budgets of captive animals are as similar as possible to those of their wild counterparts. However, such similarity has rarely been achieved. We compared the activity budget among three groups of chimpanzees: wild chimpanzees in Bossou (Guinea, n = 10), and captive chimpanzees who participated in cognitive experiments (experimental chimpanzees, n = 6) or did not participate in the experiments (nonexperimental chimpanzees, n = 6) at the Primate Research Institute (Japan). The experimental chimpanzees voluntarily participated in computer‐controlled cognitive tasks and small pieces of fruits were provided as rewards. The data from captivity were obtained on the experimental days (weekdays) and nonexperimental days (weekends). In both study sites, we followed each chimpanzee from about 7 a.m. until the time when chimpanzees started to rest in the evening. The behaviors were recorded every 1 min. The results showed that on weekdays, feeding time and resting time of the experimental chimpanzees were almost the same as those of wild chimpanzees. However, for the nonexperimental chimpanzees, feeding time was significantly shorter and resting time was longer than those of the wild chimpanzees. In contrast, no difference was found in feeding time or resting time of the two groups of captive chimpanzees on weekends. The results suggested that the cognitive experiments worked as an efficient method for food‐based enrichment. Am. J. Primatol. 73:1231–1238, 2011. © 2011 Wiley Periodicals, Inc.     

The importance of incorporating age and sex when backcalculating length in bullhead Cottus gobio

The present study backcalculated body length for a data set of a bullhead Cottus gobio population located at different sampling sites in a river network. Model comparison between various growth models, which included successively new parameters, showed the effect and importance of taking sex, age and the location in the river network into account. The data sets obtained by backcalculation were fitted by the von Bertalanffy growth function, which revealed the effect of the backcalculation formula on the estimation of the von Bertalanffy growth parameters. Fitting results and parameter estimates showed again the importance of incorporating age and sex when backcalculating body length in the C. gobio population studied.     

The role of non-profits in the mammogram debate

With immediate access to new information on breast cancer research, more and more people are turning to non-profits for guidance. With no template describing exactly how to find a cure for such a destructive disease, it is hard for the general public to understand all the twists and turns along the way. Non-profits play off their emotional connection to educate on the scientific side of cancer research. Women and those affected by the disease have come to rely on these organizations to find support, information, and, eventually, a cure. This perspective piece follows the non-profit world full circle to try to better understand the fondness masses have toward non-profit organizations.     

罕见疾病及孤儿药物研究现状及进展

文中简述了罕见疾病的定义、发病原因、分类,总结了国内外罕见疾病研究和孤儿药物研发的现状,分析了生物技术的研究手段在罕见疾病药物研发方面的应用,进一步阐述了罕见疾病研究和孤儿药物开发的必要性和紧迫性,对推动科学技术的进步和人类健康事业的发展具有深远的意义。     

公立医院改革与管理研究现状及其展望 ——基于文献计量学的视角

公立医院作为一个复杂的系统,由于改革涉及的利益格局调整较大,部门间存在的认识分歧较多,对决策支持工作提出了较高的要求。虽然针对公立医院管理与改革文献较多,但真正转化为政策和干预措施的却很少。系统描述了我国公立医院改革与管理的文献研究现状,分析的热点问题和研究的空白领域,为我国公立医院改革政策和研究规划的制定、研究团队的培养以及研究方向的调整提供科学的决策依据。     

Limits of Data Analysis in Scientific Inference: Reply to Sleep et al.

ABSTRACT Statistical inference is an important element of science, but these inferences are constrained within the framework established by the objectives and design of a study. The choice of approach to data analysis, while important, has far less consequence on scientific inference than claimed by Sleep et al. (2007). Their principal assertion—that when model selection is used as the approach to data analysis, all studies provide a reliable foundation for distinguishing among mechanistic explanatory hypotheses—is incorrect and encourages faulty inferences. Sleep et al. (2007) overlook the critical distinction between inferences that result from studies designed a priori to discriminate among a set of candidate explanations versus inferences that result from exploring data post hoc from studies designed originally to meet pattern-based objectives. No approach to data analysis, including model selection, has the power to overcome fundamental limitations on inferences imposed by study design. The comments by Sleep et al. (2007) reinforce the need for scientists to understand clearly the inferential basis for their scientific claims, including the roles and limitations of data analysis.