在生理学研究中要正确运用统计学

目的：为从事生理学研究的科研工作者正确运用统计学提供一些有效的技术方法。方法：通过全面系统地阐述"统计学在生理学研究过程中充当了重要的角色"和"使生理学研究课题得出的结论经得起时间和实践检验的关键技术"两个命题,突显出统计学对于科研工作的重要性、解释了统计学难学难用的原因,并提供了正确运用统计学的关键技术。结果：呈现出统计学的三大核心内容,即"如何使课题设计无可挑剔"、"如何严守课题实施的操作规程"和"如何使结论陈述有理有据",使正确运用统计学具有很强的可操作性。结论：在生理学研究中,只要锲而不舍地追求科学严谨的科研作风和精湛的科研技能,就一定能使所获得的科研结论经得起时间和实践的检验。     

在生理学研究中如何严格遵循试验设计四原则

目的：为从事生理学研究的科研工作者严格遵循试验设计四原则（以下简称四原则）提供一些有效的技术方法。方法：通过简单介绍"四原则的概念"、举例阐述"生理学研究中在落实四原则方面出现的常见错误和案例"和简单介绍"生理学研究中如何遵循四原则"来阐述遵循四原则的具体做法。结果：需要根据实际情况,选择合适的随机化方法,分层随机化是常用的好方法;应力求设置合理的对照组,才能真正体现出对照原则的价值;有根据地给出每个小组合适的样本含量,是试验结果具有重现性的基本保证;严格遵循随机、对照和重复原则,最终才能实现对比组之间达到极好的均衡效果,这说明均衡原则是一个把关的原则。结论：在生理学科研中,严格遵循四原则对保证生理学研究结果准确可靠至关重要。     

我与《生理学报》--写在《生理学报》70诞辰之际

<生理学报>迎来她的70周年诞辰.作为<生理学报>的一位年轻编委,我谨向她表示衷心的祝贺.70年的历程中,<生理学报>为我国生理科学的发展作出了不可磨灭的贡献,为我国生理学家、尤其是年轻生理学工作者的成长与发展提供了重要的舞台.     

中国生理学会第八届全国青年生理学工作者学术会议征文通知（再次刊登）

为更广泛地组织青年科学工作者交流学术心得,促进我国生理学的发展,促进生理学科科研和教学队伍的成长,推动青年科学工作者了解世界科技发展动向,拓宽视野、增长知识和才干,营造良好的学术论坛环境和学术交流氛围,搭建高层次的学术交流平台,培养优秀的科技人才和各个学科的学术和技术带头人。中国生理学会决定在2009年5月中旬在江西南昌大学召开中国生理学会第八届全国青年生理学工作者学术会议,与张锡钧基金会第十届全国青年优秀生理学学术论文交流会同期举行（报到通知将另发）。     

《植物生理学通讯》办得好

时值《植物生理学通讯》创刊40周年之际,作为从事高等学校植物生理学教学和科学研究40多年的老读者,谨向编委会致以热烈的祝贺,并感谢编委们为办好刊物付出的辛勤劳动。     

科学本质中“主观因素影响”对科学教学的建议与启示

作为科学本质观的组成要素,使学生明确"科学工作中高度关注主观因素的影响",是《高中生物学课程标准(2017版)》提出的建议之一。在科学教学中,学生应能认识到主观因素的"客观存在性",并在此基础上尽量减少其中消极部分的影响。教师可把握这一概念从认可、消除,再到利用之间的渐进关系,发展学生的科学本质观,帮助学生进行更有效的科学学习,最终提升学生的科学素养。     

遗传科学信息来源

在当今这个被称为信息爆炸的时代,不论是从事遗传学理论研究还是从事遗传学实验研究的科学家,不论是遗传学研究工作者还是教育工作者,都不可能用有限的时间去总揽全部研究文献。了解遗传科学信息来源,不仅有助于获取信息、把握研究领域的前沿,而且有助于扩大交流。我国遗传学工作者编著的《遗     

《生理科学进展》征稿简则

一、《生理科学进展》是综合报道国内外生理科学新进展的高级学术期刊,读者对象主要为生理科学工作者以及有关的研究、教学、医药卫生工作者和相关的管理工作者。本刊的方针任务是:贯彻理论与实践相结合、普及与提高相结合的原则,交流推广有关生理学、生物化学与分子生物学、药     

《生理科学进展》征稿简则

一、《生理科学进展》是综合报道国内外生理科学新进展的高级学术期刊,读者对象主要为生理科学工作者以及有关的研究、教学、医药卫生工作者和相关的管理工作者。本刊的方针任务是:贯彻理论与实践相结合、普及与提高相结合的原则,交流推广有关生理学、生物化学与分子生物学、药理学、病理生理学、生物物     

十年来巴甫洛夫学说在我国的成就

伟大的依凡彼德洛维奇·巴甫洛夫和他的不朽的生理学学说早为世界生理学界所熟知并受到广泛的贊扬。世界各国的生理学教学与教科书一般都涉及巴甫洛夫在消化生理学和条件反射学说方面的一些科学事实,在解放前的旧中国也是如此。中国生理学会于1934年曾选举巴甫洛夫为名誉会员。1935年少数中国生理科学工作者曾     

全球长期城市生态研究中的社会经济要素:指标、数据与应用前景

社会经济要素作为城市生态系统的重要组成部分,能够反映居民特征、衡量居民福祉,是城市生态研究中不可或缺的内容。然而,在城市生态研究中合理、有效利用社会经济要素的规范和框架尚未得到充分研究。城市生态研究中常用的社会经济指标包括哪些？社会经济指标的常见数据源有哪些？社会经济要素可协助回答哪些方面的科学问题？为回答上述问题,本文综述了全球范围内11个长期城市生态研究站点开展的系统性调查和案例研究,总结社会经济指标的内容、数据来源,以及这些研究的议题。结果表明：常用社会经济指标可分为人口基本信息、认知和意愿、行为三类,前两者在城市生态研究中的应用已较为普遍。数据的主要来源包括政府部门提供的统计资料或普查数据、商业数据,以及研究人员开展的独立调查。在城市生态研究中纳入社会经济要素有助于分析社会与环境的相互关系,进而揭示城市系统中人与自然的耦合效应。近年来,我国城市生态研究快速发展,但研究中欠缺对社会经济要素的考虑与利用,可能会逐渐偏离国际上城市生态学的主流研究方向。社会经济数据获取困难是当前研究者面临的重大挑战,同时也存在一些机遇能够促进我国城市生态研究纳入社会经济要素,例如利用新兴数据和大数据手段、构建统一的指标框架和数据共享机制,以及充分了解和利用政府公开的统计数据。     

Interspecific competition in plants: how well do current methods answer fundamental questions?

Accurately quantifying and interpreting the processes and outcomes of competition among plants is essential for evaluating theories of plant community organization and evolution. We argue that many current experimental approaches to quantifying competitive interactions introduce size bias, which may significantly impact the quantitative and qualitative conclusions drawn from studies. Size bias generally arises when estimates of competitive ability are erroneously influenced by the initial size of competing individuals. We employ a series of quantitative thought experiments to demonstrate the potential for size bias in analysis of four traditional experimental designs (pairwise, replacement series, additive series, and response surfaces) either when only final measurements are available or when both initial and final measurements are collected. We distinguish three questions relevant to describing competitive interactions: Which species dominates? Which species gains? and How do species affect each other? The choice of experimental design and measurements greatly influences the scope of inference permitted. Conditions under which the latter two questions can give biased information are tabulated. We outline a new approach to characterizing competition that avoids size bias and that improves the concordance between research question and experimental design. The implications of the choice of size metrics used to quantify both the initial state and the responses of elements in interspecific mixtures are discussed. The relevance of size bias in competition studies with organisms other than plants is also discussed.     

Freshwater ecosystem structure–function relationships: from theory to application

1. In this issue we aimed to answer the questions: (i) under what circumstances are functional variables better than structural ones for assessing ecosystem health? and (ii) are there good indicators of change in ecological functioning along perturbation gradients?
2. Of the numerous functional indicators tested in this issue, several show a response to anthropogenic stress and could be included in assessments of ecosystem health and integrity in running waters.
3. In three of eight studies, function showed a stronger response to anthropogenic stress than structure, whereas one study showed a response in structure and not function, and four studies showed responses in both structure and function. Thus structure alone could not detect all types of impairment and functional aspects should also be included and further developed for assessing running-water ecosystem health and integrity. Functional variables may be especially useful in situations where there is a stronger response among organisms not usually included in stream assessment (e.g. fungi and bacteria) than the commonly used invertebrate, macrophytes and fish indicators.
4. Leading research questions related to the use of functional indicators in running waters include: (i) how large is natural and operator-induced variation for functional indicators? (ii) how small of an effect size (delta) can be detected using structural versus functional indicators? and (iii) how do we efficiently improve theories as well as predictive ability for functional measures to assess the effects of anthropogenic stressors?
5. To advance the use of functional indicators in applied running-water studies, we need to supplement the approach of using large-scale datasets and correlation with ecosystem manipulations.     

The experimental paradigm and long-term population studies

Most ecologists recognize the value of long-term studies to population and community ecology, and many also subscribe to the experimental approach as the most effective way of obtaining ecological knowledge. But if we are experimentalists, do we need long-term studies? I argue that the answer to this question is yes, that we must combine these two approaches to solve the major ecological questions of the next century. Most of the challenging questions facing ecologists involve systems subject to long-term time trends or high environmental variability.
Because of the statistical power of many ecological methods, long-term studies are essential to measure time trends in ecosystems. Ignoring statistical power has been a major problem with short-term studies, which have predominated in the ecological literature.
Some examples of long-term studies on larch bud-moth Zeiraphera diniana , winter moth Operophthera brumata and snowshoe hares are discussed briefly to illustrate the four major desiderata of long-term projects: spatial scale, sampling design, hypothesis testing and timeframe.
Two reasons for not doing long-term studies are to assess density-dependence and to monitor ecosystem health. The density-dependent paradigm is bankrupt and has produced much argument and little understanding of population processes. Monitoring of populations is politically attractive but ecologically banal unless it is coupled with experimental work to understand the mechanisms behind system changes.     

Fertility effects of family planning programs: a methodological review.

This paper reviews and compares the methodologies of some 70 investigations of the effect of family planning programs on fertility levels. Differences among the studies include variations in questions asked, research methods used, program type investigated, and made of program action assumed. Programs can affect fertility by providing means of fertility control, education, legitimation, incentives/disincentives or any combination of these but the actual effect of these modes is unclear. Comparison is usually made between the effects on fertility of a program as a whole and a hypothetical estimate of what fertility rates would have been without the program. This hypothetical estimate is in fact not subject to empirical measurement, and a variety of methods have been developed largely to attack this methodological problem. The article compares the characteristics of several methods and provides a matrix comparing their strength, limitations and applications. The methods discussed include: 1) decomposition of change which identifies several factors affecting changes in crude birth rate; 2) correspondence between program activity and fertility trends over time to across areas or groups, which often takes close statistical association as evidence of causality; 3) matching studies, which try to remove the influence of nonprogram factors by controlling the characteristics of the subject; 4) experimental and control areas, comparing presumably similar groups with and without family planning programs; 5) multiple regression across areal units which provides some information on areal trends but requires extensive data for many statistical areas; 6) calculation of national effects of births averted among acceptors; and 7) simulation, which compares data to mathematical projection models, such as the TABRAP/CONVERSE and POPSIM models. No one method is best but certain methods are best to answer certain questions. All of the methods have difficulty establishing actual causality between the program studied and fertility trends and ruling out alternative explanations. Recent studies encouraged by the U.N. Population Division are seeking cross-method and cross-program evaluation.     

Neural population codes

In many regions of the brain, information is represented by patterns of activity occurring over populations of neurons. Understanding the encoding of information in neural population activity is important both for grasping the fundamental computations underlying brain function, and for interpreting signals that may be useful for the control of prosthetic devices. We concentrate on the representation of information in neurons with Poisson spike statistics, in which information is contained in the average spike firing rate. We analyze the properties of population codes in terms of the tuning functions that describe individual neuron behavior. The discussion centers on three computational questions: first, what information is encoded in a population; second, how does the brain compute using populations; and third, when is a population optimal? To answer these questions, we discuss several methods for decoding population activity in an experimental setting. We also discuss how computation can be performed within the brain in networks of interconnected populations. Finally, we examine questions of optimal design of population codes that may help to explain their particular form and the set of variables that are best represented. We show that for population codes based on neurons that have a Poisson distribution of spike probabilities, the behavior and computational properties of the code can be understood in terms of the tuning properties of individual cells.     

Understanding development and prevention of chronic physical aggression: towards experimental epigenetic studies

The aim of this paper was to highlight how developmental psychopathology, epigenetics and prevention experiments are starting to blend together to explain the developmental causes of chronic physical aggression (CPA) and, more importantly, to help prevent CPA and its associated physical, mental and social problems. After defining the keywords (prevention, chronic and physical aggression), a selected review of published studies is used to answer the following four questions: when should we attempt to prevent onset of CPA? What are the risk factors for CPA? Have early childhood interventions been shown to prevent CPA? Can early preventive interventions benefit from epigenetic studies? The last section of this paper gives two examples of experimental prevention designs that integrate present knowledge of CPA development, risk factors, early childhood preventive interventions and epigenetic programming of brain development during pregnancy and early childhood. I conclude that randomized control trials of preventive interventions during pregnancy and early childhood with a specific focus on epigenetic effects are the research design most likely to advance our understanding of the biopsychosocial mechanisms that lead to CPA, and the only research design that can identify effective interventions for preventing the development of CPA.     

Early childhood development project in Uganda as a strategy for reducing children's poor growth indicators: an explanatory study

This study shall explore the activities of the Uganda nutrition and early childhood development project using explanatory program effects, qualitative research methods to determine the role/interplay of project factors and community dynamics in relation to poor growth and social indicators in Ugandan children. This project aimed to improve the quality of life for children age less than 6 years by improving their nutrition, health, cognitive and psychosocial development. The key concern remains how successful and sustainable are the outcomes? Data shall be collected using interviews, focus groups and document reviews. Data analysis shall employ the thematic networks analytical tool, which is aided by the ATLAS.ti software. The key hypotheses and recommendations from the analysis shall then be tested in a suitable community location and period in line with the research questions.     

Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding

Spider: SPecies IDentity and Evolution in R is a new R package implementing a number of useful analyses for DNA barcoding studies and associated research into species delimitation and speciation. Included are functions essential for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, and for testing and optimizing divergence threshold limits. In terms of investigating evolutionary and taxonomic questions, techniques for assessing diagnostic nucleotides and probability of reciprocal monophyly are also provided. Additionally, a sliding window function offers opportunities to analyse information across a gene, essential for marker design in degraded DNA studies. Spider capitalizes on R's extensible ethos and offers an integrated platform ideal for the analysis of both nucleotide and morphological data. The program can be obtained from the comprehensive R archive network (CRAN, http://cran.r-project.org) and from the R-Forge package development site (http://spider.r-forge.r-project.org/).