医学硕士研究生《分子生物学》课程体系构建与学生基础科研能力培养的实践

医学研究生的科研探索和创新能力对我国医学事业的发展十分重要,培养研究生的基础科研能力是医学研究生教育的重要方面。本文从课程设计、教学理念、教学内容、教学模式以及成绩评价等要素总结了昆明医科大学《分子生物学》课程体系构建与学生科研创新能力培养的教学实践与思考。该课程体系由"分子生物学理论基础"和"分子生物学实验技术"两个模块组成;前者侧重加强学生的知识储备和引导学生建立科研思维方法,后者注重提高学生的基础实验技能,以培养学生综合运用基本知识分析和解决问题的能力,为从事基础医学和临床医学研究奠定基础。     

浅谈医学人文学教育在研究生临床教学中的重要作用

目的总结医学人文学教育在医学研究生临床教学中的重要作用。方法根据医学研究生的特殊性,分析医学研究生开展人文学教育的必要性和可行性。结果医学研究生开展人文学教育可正确处理医患关系,缓解医患矛盾,确保医疗安全。结论加强医学研究生人文学教育,对培养医学研究生的医德医风,适应现代医学模式的要求具有重要意义。     

探索医学研究生的《分子生物学》教学改革

培养具有创新思维和独立创新能力的高素质人才,是医学研究生教育的培养目标,也是新的历史时期对培养高等医学人才 的要求。《医学分子生物学》课程对于研究生教学至关重要,已成为医学研究生的重要基础课程。我们在多年教学经验的基础上, 通过调整理论教学模式、优化知识结构、合理设置教学内容、扩展前沿知识领域、改善考核方式等多个举措,着重培养研究生的独 立科研创新能力,使得研究生《医学分子生物学》教学改革取得一定成效。     

医学研究生开展转录组学课程必要性的探讨

转录组学是生命科学领域的一门交叉型、发展快速的前沿性学科。随着高通量测序技术的迅猛发展,在收集、整合及数据挖掘的基础上全面系统的研究转录组成为可能。目前,利用转录组学的理论及技术研究疾病的转录组信息,系统全面阐明其基因表达调控规律,构建其基因调控网络,已经成为医学研究领域的热点。通过在医学研究生中开展转录组学这门课程,使研究生掌握其中的科研思维和方法,帮助研究生更清晰地认识疾病发生发展的分子机制,并通过学习这门课程提高研究生的科研能力和水平。     

研究生在基础与临床相结合科研项目中培养方法的几点思考

随着我国科研创新的开展与推进,学生进入实际科研项目已逐渐成为研究生培养的重要方式。基础与,临床相结合的科研项目立论均来自于临床问题,把在患者身上无法实现的方法通过基础实验的手段加以实施和验证,从而达到发现和揭示病因与发病机制的目的,结果甚或对临床产生指导意义。首都医科大学病理与病理生理学系研究生培养点结合这类研究项目的推进,在规范的方法和流程中引导和培养研究生从临床现象中设问、从海量数据中分析和论证的能力,并通过这些训练,使研究生为进一步深入研究奠定基础,共同为转化医学研究做出贡献。     

医学院校生物学专业研究生课程体系改革初探

研究生教育作为我国高等教育体制中最高层次的教育,是培养具有高素质、创新型人才的核心环节。医学院校研究生的素 质教育与创新能力是决定其基础医学研究能力和临床专业技能的重要因素,而研究生课程体系的建设是决定研究生培养过程中 重要的一环。为了提高研究生的创新能力,我校对研究生课程体系进行了一系列的改革。通过总结国内外10 所知名院校生物学 专业研究生课程体系的特点,对比分析我校在此方面存在的不足,进一步明确生物学专业研究生培养的目标,并有针对性的提出 课程体系改革的措施,为后续研究生教育改革奠定基础。     

论将研究组组会纳入课程管理对生命科学研究生培养的意义

研究组组会是导师带教研究生、培养研究生科研能力、了解研究生科研进展的重要手段,是导师对研究生言传身教的重要场所。将组会纳入到研究生课程体系建设中,进一步发挥组会在研究生培养中的作用,实现对组会效果的考核,打通研究生课堂学习和个性化科研能力培养这两个环节,对于培养学生良好的科研习惯和科研分析能力具有重要意义。     

研究生神经生物学教学创新模式探索与实践

结合神经生物学课程的特点与研究生培养要求,提出了将神经生物学理论与方法知识贯穿到多媒体课程学习、文献讨论、学术交流、科研活动等实践环节中,注重培养研究生对神经生物学理论和研究实践的兴趣,强化科研能力创新人才的培养。     

“数据解读卡”文献阅读法在医学研究生文献阅读能力培养中的作用

阅读文献可以促进学生了解科学发现的过程,有利于提高学生解读实验数据的能力,培养科学研究兴趣,是基础医学教学过程中必不可少的环节。因此,有必要探索一些引导和训练学生高效阅读文献的方法。该研究旨在通过“数据解读卡”文献阅读法来引导和规范医学研究生阅读文献的过程,通过分析学生在文献文本和图片上阅读时间分配的动态变化、测试学生文献解读技能和实验设计能力以及调查学生满意度来评价“数据解读卡”文献阅读法在培养和提高医学研究生解读实验数据的能力中的作用。结果表明,“数据解读卡”文献阅读法能明显提高图片相对阅读时间,从第1周20％左右逐步提高到第12周45％左右;学生解读实验数据能力得分从第1周0分左右提高到第6N3分和第12周4分左右;平均86％左右的学生认为有利于提高文献阅读的效率和有助于论文写作。该研究结果表明,“数据解读卡”文献阅读法可以规范和训练研究生阅读文献的能力,是提高学生阅读文献效率的有效途径。     

中药学“阶梯式”实践与创新培养模式研究

随着我国医药市场及研究生教育的变化,高等院校中药学教学的方式、培养模式和目的也随之发生了变化。在多年本科教学、研究生教育和服务医药企业的过程中,我们提出中药学"阶梯式"实践与创新培养模式:大学生创新性计划、大学生"挑战杯"论文大赛、大学生"挑战杯"创业大赛和毕业实习等实践和培养模式结合,提升中药学学科在校大学生的实践能力和科研创新能力。     

继续医学教育项目" 过程管理模式" 体会

继续医学教育项目是开展继续医学教育的重要形式之一,是卫生专业技术人员获取新知识、新理论、新技术、新方法的重要途径。项目执行的质量将直接体现继续医学教育质量。因此规范项目管理程序,建立有效的运行体系,建立严格奖罚制度,进行"过程跟踪管理"是保证项目执行质量的有效措施。     

医学生科研创新能力培养“3+X”模式的探索与实践

针对长期以来培养医学生的科研创新能力主要依靠零散的课外科研活动、受众面窄、没有系统性课程教学及其相关制度保障、致使对医学生科研创新能力培养明显乏力低效这一共性瓶颈教学问题,自2002年起,汕头大学医学院生物化学与分子生物学教学团队,在“科教相辅相佐”、“以学生为中心”、“以问题为导向”等先进教育理念指导下,倚重汕头大学医学院“医者之心”系列课程与书院育人文化之特色,发挥汕头大学的生物学、基础医学和临床医学一级学科均拥有本/硕/博/博后完整人才培养体系之优势,联合其他相关专业教学团队,在建立充分体现医学生科研创新能力培养内涵,覆盖医学本科5年全过程的核心课程体系的基础之上,历经20载的不懈努力,补充修善,成功构建了“3+X”模式,着力培养医学生的科研创新能力。所谓“3”意指对医学生的“全人培养”、“全程培养”和“全方位培养”。所谓“X”意指针对“3+X”模式运行效能的若干个验证性维度,主要包括组织医学生参加各种形式的全国大学生创新实验研究大赛、国际大学生学术研讨会,由医学本科生作为第一作者撰写发表学术论文等。培养医学生科研创新能力的成效十分显著,为有效解决上述共性瓶颈教学问题提供了一个有重要借鉴价值的范例。     

医学生早期教育阶段综合能力培养之探索

现代医学模式要求医务工作者必须是高素质的人才。基础医学教育阶段是医学生培养过程中的基础环节和重要阶段,与临床教学阶段相比,基础教育阶段更有利于学生综合能力培养和开展素质教育。医学生综合能力的培养在医学教育中具有重要的地位,它的实现要靠教育者在教育教学的各个环节中主动施行,积极探讨医学生综合能力培养的有效实施途径和方法。我们课题组根据多年从事医学生人才培养的教育教学经验,针对医学生早期教育阶段的心理、生理、环境、知识结构特点,围绕综合能力培养这个核心课题,强化创新性人才培养,系统有序地按学生学习时间和课程进行各种能力的逐一培养,从学习能力,思维能力,观察能力,动手能力,合作能力,分析问题和解决问题能力,判断是非能力,语言表达能力,写作能力,创新开拓能力等,探索医学生早期教育阶段综合能力培养模式。     

政府补偿与监管机制改革对公立医疗卫生机构科教与学科建设的影响分析

目的 分析政府补偿与监管机制改革对公立医疗卫生机构教学、科研以及学科建设的影响。方法 通过对上海市闵行区的机构调查,收集并分析2008—2012年3所公立综合性医院和12家社区卫生服务中心的医学教育、科研项目、论文发表及重点学科建设状况的相关数据。结果 闵行区公立综合性医院和社区卫生服务中心的医学教育和科研能力有所提升,重点学科建设也有所加强;但仍然存在教学能力薄弱,科研水平层次偏低,缺乏高质量的重点学科等问题。结论 政府补偿与监管机制改革在一定程度上强化了公立医疗机构的医学教育、科研能力和学科建设,但未来需进一步加大对科教和学科建设的鼓励和支持力度。     

浅析基于PBL教学模式下的临床医学教学应用

目的:PBL是"基于问题式学习"的教学法,本文以PBL教学法内涵为理论基础,剖析了在临床医学教学过程中实施PBL教学法的必要性。PBL教学法可以顺应时代发展的要求提高学生的综合能力提升教师的教学水平增进和改善师生关系,并总结归纳出PBL教学法的一般模式和实施过程中常见的主要问题,主观上传统的教育观念根深蒂固,客观上存在师资力量不足、现有教学体系不科学的问题。提出了解决问题的策略:转变教学理念,不断完善教学环境;提高教师队伍素质建设,发挥教师导向作用;逐步建立科学的教育体系。PBL教学法有助于全面培养学习者的学习能力,提高学习者的综合素质,全面推行切合自身实际的PBL教学模式,逐步建立具有中国特色的临床医学教学模式,培养高素质临床医学人才,与现代社会对人才培养的要求基本一致,值得推广和应用。     

Spinal and sacroiliac assessment and treatment techniques used by osteopathic physicians in the United States

Background

Without systematic exposure to biomedical research concepts or applications, osteopathic medical students may be generally under-prepared to efficiently consume and effectively apply research and evidence-based medicine information in patient care. The academic literature suggests that although medical residents are increasingly expected to conduct research in their post graduate training specialties, they generally have limited understanding of research concepts. With grant support from the National Center for Complementary and Alternative Medicine, and a grant from the Osteopathic Heritage Foundation, the University of North Texas Health Science Center (UNTHSC) is incorporating research education in the osteopathic medical school curriculum. The first phase of this research education project involved a baseline assessment of students' understanding of targeted research concepts. This paper reports the results of that assessment and discusses implications for research education during medical school.

Methods

Using a novel set of research competencies supported by the literature as needed for understanding research information, we created a questionnaire to measure students' confidence and understanding of selected research concepts. Three matriculating medical school classes completed the on-line questionnaire. Data were analyzed for differences between groups using analysis of variance and t-tests. Correlation coefficients were computed for the confidence and applied understanding measures. We performed a principle component factor analysis of the confidence items, and used multiple regression analyses to explore how confidence might be related to the applied understanding.

Results

Of 496 total incoming, first, and second year medical students, 354 (71.4%) completed the questionnaire. Incoming students expressed significantly more confidence than first or second year students (F = 7.198, df = 2, 351, P = 0.001) in their ability to understand the research concepts. Factor analyses of the confidence items yielded conceptually coherent groupings. Regression analysis confirmed a relationship between confidence and applied understanding referred to as knowledge. Confidence scores were important in explaining variability in knowledge scores of the respondents.

Conclusion

Medical students with limited understanding of research concepts may struggle to understand the medical literature. Assessing medical students' confidence to understand and objectively measured ability to interpret basic research concepts can be used to incorporate competency based research material into the existing curriculum.     

医学院校培养本科生科研创新能力的认识与思考

科研能力是科学素质的核心,是运用已有的知识和科学方法去探索新的知识和方法,解决新的问题,并在这个过程中形成创新思维的能力。科学技术的创新是医学事业发展的阶梯,科技引领着医学探究生命的本质,通过对各种疾病的根源、机制、发生、后果进行研究,找到预防和治疗疾病的最佳途径,为人类解除疾病带来的痛苦。医学科技创新使医学得到快速发展的同时,为社会培养了高水平、高素质的医学人才。然而,我国的高等教育体制普遍注重教育方法的革新,而忽视学生综合素质和创新能力的培养。特别是医学高等院校,本科生的教育教学工作没有重视与科研相结合。随着高等教育体制改革的不断深入与现代科学技术的迅速发展,本科生的科研创新能力亟待进一步提高。本科生科研能力的培养已经成为当前高等教育改革的一个重要目标。本文针对医学院校本科生培养创新能力的重要性和必要性进行探讨,为医学教育的发展提供参考的资料。     

Big,small or mezzo?

Lessons from science studies for the ongoing debate about ‘big'' versus ‘little'' research projectsDuring the past six decades, the importance of scientific research to the developed world and the daily lives of its citizens has led many industrialized countries to rebrand themselves as ‘knowledge-based economies''. The increasing role of science as a main driver of innovation and economic growth has also changed the nature of research itself. Starting with the physical sciences, recent decades have seen academic research increasingly conducted in the form of large, expensive and collaborative ‘big science'' projects that often involve multidisciplinary, multinational teams of scientists, engineers and other experts.Although laboratory biology was late to join the big science trend, there has nevertheless been a remarkable increase in the number, scope and complexity of research collaborations…Although laboratory biology was late to join the big science trend, there has nevertheless been a remarkable increase in the number, scope and complexity of research collaborations and projects involving biologists over the past two decades (Parker et al, 2010). The Human Genome Project (HGP) is arguably the most well known of these and attracted serious scientific, public and government attention to ‘big biology''. Initial exchanges were polarized and often polemic, as proponents of the HGP applauded the advent of big biology and argued that it would produce results unattainable through other means (Hood, 1990). Critics highlighted the negative consequences of massive-scale research, including the industrialization, bureaucratization and politicization of research (Rechsteiner, 1990). They also suggested that it was not suited to generating knowledge at all; Nobel laureate Sydney Brenner joked that sequencing was so boring it should be done by prisoners: “the more heinous the crime, the bigger the chromosome they would have to decipher” (Roberts, 2001).A recent Opinion in EMBO reports summarized the arguments against “the creeping hegemony” of ‘big science'' over ‘little science'' in biomedical research. First, many large research projects are of questionable scientific and practical value. Second, big science transfers the control of research topics and goals to bureaucrats, when decisions about research should be primarily driven by the scientific community (Petsko, 2009). Gregory Petsko makes a valid point in his Opinion about wasteful research projects and raises the important question of how research goals should be set and by whom. Here, we contextualize Petsko''s arguments by drawing on the history and sociology of science to expound the drawbacks and benefits of big science. We then advance an alternative to the current antipodes of ‘big'' and ‘little'' biology, which offers some of the benefits and avoids some of the adverse consequences.Big science is not a recent development. Among the first large, collaborative research projects were the Manhattan Project to develop the atomic bomb, and efforts to decipher German codes during the Second World War. The concept itself was put forward in 1961 by physicist Alvin Weinberg, and further developed by historian of science Derek De Solla Price in his pioneering book, Little Science, Big Science. “The large-scale character of modern science, new and shining and all powerful, is so apparent that the happy term ‘Big Science'' has been coined to describe it” (De Solla Price, 1963). Weinberg noted that science had become ‘big'' in two ways. First, through the development of elaborate research instrumentation, the use of which requires large research teams, and second, through the explosive growth of scientific research in general. More recently, big science has come to refer to a diverse but strongly related set of changes in the organization of scientific research. This includes expensive equipment and large research teams, but also the increasing industrialization of research activities, the escalating frequency of interdisciplinary and international collaborations, and the increasing manpower needed to achieve research goals (Galison & Hevly, 1992). Many areas of biological research have shifted in these directions in recent years and have radically altered the methods by which biologists generate scientific knowledge.Despite this long history of collaboration, laboratory biology remained ‘small-scale'' until the rising prominence of molecular biology changed the research landscapeUnderstanding the implications of this change begins with an appreciation of the history of collaborations in the life sciences—biology has long been a collaborative effort. Natural scientists accompanied the great explorers in the grand alliance between science and exploration during the sixteenth and seventeenth centuries (Capshew & Rader, 1992), which not only served to map uncharted territories, but also contributed enormously to knowledge of the fauna and flora discovered. These early expeditions gradually evolved into coordinated, multidisciplinary research programmes, which began with the International Polar Years, intended to concentrate international research efforts at the North and South Poles (1882–1883; 1932–1933). The Polar Years became exemplars of large-scale life science collaboration, begetting the International Geophysical Year (1957–1958) and the International Biological Programme (1968–1974).For Weinberg, the potentially negative consequences associated with big science were “adminstratitis, moneyitis, and journalitis”…Despite this long history of collaboration, laboratory biology remained ‘small-scale'' until the rising prominence of molecular biology changed the research landscape. During the late 1950s and early 1960s, many research organizations encouraged international collaboration in the life sciences, spurring the creation of, among other things, the European Molecular Biology Organization (1964) and the European Molecular Biology Laboratory (1974). In addition, international mapping and sequencing projects were developed around model organisms such as Drosophila and Caenorhabditis elegans, and scientists formed research networks, exchanged research materials and information, and divided labour across laboratories. These new ways of working set the stage for the HGP, which is widely acknowledged as the cornerstone of the current ‘post-genomics era''. As an editorial on ‘post-genomics cultures'' put it in the journal Nature, “Like it or not, big biology is here to stay” (Anon, 2001).Just as big science is not new, neither are concerns about its consequences. As early as 1948, the sociologist Max Weber worried that as equipment was becoming more expensive, scientists were losing autonomy and becoming more dependent on external funding (Weber, 1948). Similarly, although Weinberg and De Solla Price expressed wonder at the scope of the changes they were witnessing, they too offered critical evaluations. For Weinberg, the potentially negative consequences associated with big science were “adminstratitis, moneyitis, and journalitis”; meaning the dominance of science administrators over practitioners, the tendency to view funding increases as a panacea for solving scientific problems, and progressively blurry lines between scientific and popular writing in order to woo public support for big research projects (Weinberg, 1961). De Solla Price worried that the bureaucracy associated with big science would fail to entice the intellectual mavericks on which science depends (De Solla Price, 1963). These concerns remain valid and have been voiced time and again.As big science represents a major investment of time, money and manpower, it tends to determine and channel research in particular directions that afford certain possibilities and preclude others (Cook & Brown, 1999). In the worst case, this can result in entire scientific communities following false leads, as was the case in the 1940s and 1950s for Soviet agronomy. Huge investments were made to demonstrate the superiority of Lamarckian over Mendelian theories of heritability, which held back Russian biology for decades (Soyfer, 1994). Such worst-case scenarios are, however, rare. A more likely consequence is that big science can diminish the diversity of research approaches. For instance, plasma fusion scientists are now under pressure to design projects that are relevant to the large-scale International Thermonuclear Experimental Reactor, despite the potential benefits of a wide array of smaller-scale machines and approaches (Hackett et al, 2004). Big science projects can also involve coordination challenges, take substantial time to realize success, and be difficult to evaluate (Neal et al, 2008).Importantly, big science projects allow for the coordination and activation of diverse forms of expertise across disciplinary, national and professional boundariesAnother danger of big science is that researchers will lose the intrinsic satisfaction that arises from having personal control over their work. Dissatisfaction could lower research productivity (Babu & Singh, 1998) and might create the concomitant danger of losing talented young researchers to other, more engaging callings. Moreover, the alienation of scientists from their work as a result of big science enterprises can lead to a loss of personal responsibility for research. In turn, this can increase the likelihood of misconduct, as effective social control is eroded and “the satisfactions of science are overshadowed by organizational demands, economic calculations, and career strategies” (Hackett, 1994).Practicing scientists are aware of these risks. Yet, they remain engaged in large-scale projects because they must, but also because of the real benefits these projects offer. Importantly, big science projects allow for the coordination and activation of diverse forms of expertise across disciplinary, national and professional boundaries to solve otherwise intractable basic and applied problems. Although calling for international and interdisciplinary collaboration is popular, practicing it is notably less popular and much harder (Weingart, 2000). Big science projects can act as a focal point that allows researchers from diverse backgrounds to cooperate, and simultaneously advances different scientific specialties while forging interstitial connections among them. Another major benefit of big science is that it facilitates the development of common research standards and metrics, allowing for the rapid development of nascent research frontiers (Fujimura, 1996). Furthermore, the high profile of big science efforts such as the HGP and CERN draw public attention to science, potentially enhancing scientific literacy and the public''s willingness to support research.Rather than arguing for or against big science, molecular biology would best benefit from strategic investments in a diverse portfolio of big, little and ‘mezzo'' research projectsBig science can also ease some of the problems associated with scientific management. In terms of training, graduate students and junior researchers involved in big science projects can gain additional skills in problem-solving, communication and team working (Court & Morris, 1994). The bureaucratic structure and well-defined roles of big science projects also make leadership transitions and researcher attrition easier to manage compared with the informal, refractory organization of most small research projects. Big science projects also provide a visible platform for resource acquisition and the recruitment of new scientific talent. Moreover, through their sheer size, diversity and complexity, they can also increase the frequency of serendipitous social interactions and scientific discoveries (Hackett et al, 2008). Finally, large-scale research projects can influence scientific and public policy. Big science creates organizational structures in which many scientists share responsibility for, and expectations of, a scientific problem (Van Lente, 1993). This shared ownership and these shared futures help coordinate communication and enable researchers to present a united front when advancing the potential benefits of their projects to funding bodies.Given these benefits and pitfalls of big science, how might molecular biology best proceed? Petsko''s response is that, “[s]cientific priorities must, for the most part, be set by the free exchange of ideas in the scientific literature, at meetings and in review panels. They must be set from the bottom up, from the community of scientists, not by the people who control the purse strings.” It is certainly the case, as Petsko also acknowledges, that science has benefited from a combination of generous public support and professional autonomy. However, we are less sanguine about his belief that the scientific community alone has the capacity to ascertain the practical value of particular lines of inquiry, determine the most appropriate scale of research, and bring them to fruition. In fact, current mismatches between the production of scientific knowledge and the information needs of public policy-makers strongly suggest that the opposite is true (Sarewitz & Pielke, 2007).Instead, we maintain that these types of decision should be determined through collective decision-making that involves researchers, governmental funding agencies, science policy experts and the public. In fact, the highly successful HGP involved such collaborations (Lambright, 2002). Taking into account the opinions and attitudes of these stakeholders better links knowledge production to the public good (Cash et al, 2003)—a major justification for supporting big biology. We do agree with Petsko, however, that large-scale projects can develop pathological characteristics, and that all programmes should therefore undergo regular assessments to determine their continuing worth.Rather than arguing for or against big science, molecular biology would best benefit from strategic investments in a diverse portfolio of big, little and ‘mezzo'' research projects. Their size, duration and organizational structure should be determined by the research question, subject matter and intended goals (Westfall, 2003). Parties involved in making these decisions should, in turn, aim at striking a profitable balance between differently sized research projects to garner the benefits of each and allow practitioners the autonomy to choose among them.This will require new, innovative methods for supporting and coordinating research. An important first step is ensuring that funding is made available for all kinds of research at a range of scales. For this to happen, the current funding model needs to be modified. The practice of allocating separate funds for individual investigator-driven and collective research projects is a positive step in the right direction, but it does not discriminate between projects of different sizes at a sufficiently fine resolution. Instead, multiple funding pools should be made available for projects of different sizes and scales, allowing for greater accuracy in project planning, funding and evaluation.It is up to scientists and policymakers to discern how to benefit from the advantages that ‘bigness'' has to offer, while avoiding the pitfalls inherent in doing soSecond, science policy should consciously facilitate the ‘scaling up'', ‘scaling down'' and concatenation of research projects when needed. For instance, special funds might be established for supporting small-scale but potentially transformative research with the capacity to be scaled up in the future. Alternatively, small-scale satellite research projects that are more nimble, exploratory and risky, could complement big science initiatives or be generated by them. This is also in line with Petsko''s statement that “the best kind of big science is the kind that supports and generates lots of good little science.” Another potentially fruitful strategy we suggest would be to fund independent, small-scale research projects to work on co-relevant research with the later objective of consolidating them into a single project in a kind of building-block assembly. By using these and other mechanisms for organizing research at different scales, it could help to ameliorate some of the problems associated with big science, while also accruing its most important benefits.Within the life sciences, the field of ecology perhaps best exemplifies this strategy. Although it encompasses many small-scale laboratory and field studies, ecologists now collaborate in a variety of novel organizations that blend elements of big, little and mezzo science and that are designed to catalyse different forms of research. For example, the US National Center for Ecological Analysis and Synthesis brings together researchers and data from many smaller projects to synthesize their findings. The Long Term Ecological Research Network consists of dozens of mezzo-scale collaborations focused on specific sites, but also leverages big science through cross-site collaborations. While investments are made in classical big science projects, such as the National Ecological Observatory Network, no one project or approach has dominated—nor should it. In these ways, ecologists have been able to reap the benefits of big science whilst maintaining diverse research approaches and individual autonomy and still being able to enjoy the intrinsic satisfaction associated with scientific work.Big biology is here to stay and is neither a curse nor a blessing. It is up to scientists and policy-makers to discern how to benefit from the advantages that ‘bigness'' has to offer, while avoiding the pitfalls inherent in so doing. The challenge confronting molecular biology in the coming years is to decide which kind of research projects are best suited to getting the job done. Molecular biology itself arose, in part, from the migration of physicists to biology; as physics research projects and collaborations grew and became more dependent on expensive equipment, appreciating the saliency of one''s own work became increasingly difficult, which led some to seek refuge in the comparatively little science of biology (Dev, 1990). The current situation, which Petsko criticizes in his Opinion article, is thus the result of an organizational and intellectual cycle that began more than six decades ago. It would certainly behoove molecular biologists to heed his warnings and consider the best paths forward.? Open in a separate windowNiki VermeulenOpen in a separate windowJohn N. ParkerOpen in a separate windowBart Penders     

综合医院大数据应用需求调查与分析

目的 分析综合医院对于大数据应用的内在需求,为医院的大数据研发与应用提供导向和依据。方法 采用德尔菲法自制医院大数据应用需求调查问卷,随机抽取中国研究型医院学会医疗分会64家会员单位进行调查,获得有效问卷104份,有效回收率为94.55%。结果 精准医疗（4.31±0.42）分,精益管理（4.23±0.56）分,科学研究（4.19±0.52）分,健康管理（4.16±0.52）分,数字医疗（4.06±0.60）分,教育培训（3.69±0.69）分。不同性别、年龄、职称、岗位组间的需求差异有统计学意义（P＜0.05）。多元线性回归分析结果显示,医学人工智能（b=0.324,P=0.000）和互联网+医疗（b=0.161,P=0.047）的需求程度会对医院大数据应用前景态度产生显著的正向影响关系。结论 综合性医院对大数据具有较强的、多样化的应用需求,应以实际需求为导向,重点推进精准医疗、医学人工智能和互联网+医疗等相关应用的研发。