精雕思维,提升素养——高中教材中“基因工程”复习方法的思考

复习基因工程的内容时,抓住怎样培育抗虫棉这一核心进行多方位多角度的联想,将联想到的内容编写成相应的问题,从而在引出、深入、延伸核心问题等层面上展开复习,以求达到精雕思维,提升素养的目的。     

Review of subtribe Singilina Jeannel, 1949, of the Middle East and Central Asia (Coleoptera, Carabidae, Lebiini)

Species of the genus Singilis Rambur, 1837 (Phloeozeteus Peyron, 1856, syn. n., Agatus Motschulsky, 1845, syn. n.), occurring in the Middle East and Central Asia are reviewed, with 24 species now recognized in the region, including ten species described as new: Singilis makarovi sp. n. (Tajikistan), Singilis jedlickai sp. n. (Afghanistan), Singilis kolesnichenkoi sp. n. (Iran), Singilis kabakovi sp. n. (Afghanistan, Iran), Singilis timuri sp. n. (Uzbekistan), Singilis klimenkoi sp. n. (Iran), Singilis saeedi sp. n. (Iran), Singilis felixi sp. n. (UAE), Singilis kryzhanovskii sp. n. (Iran, Turkmenistan), and Singilis timidus sp. n. (Iran); Singilis libani (Sahlberg, 1913) is recognized as a valid species; and Singilis solskyi nom. n. is proposed as a replacement name for Agatus bicolor (Solsky, 1874, not Rambur 1837), now placed in Singilis as junior homonym. New synonymies include: Singilis cingulatus (Gebler, 1843) = Singilis jakeschi Jedlička, 1967, syn. n.; Singilis mesopotamicus Pic, 1901 = Singilis apicalis Jedlička, 1956, syn. n. A key to species is provided. Habitus and aedeagal illustrations are provided for all species. Distributional data include many new country records.     

The role of mathematical models of host-pathogen interactions for livestock health and production - a review

Compared with the application of mathematical models to study human diseases, models that describe animal responses to pathogen challenges are relatively rare. The aim of this review is to explain and show the role of mathematical host-pathogen interaction models in providing underpinning knowledge for improving animal health and sustaining livestock production. Existing host-pathogen interaction models can be assigned to one of three categories: (i) models of the infection and immune system dynamics, (ii) models that describe the impact of pathogen challenge on health, survival and production and (iii) models that consider the co-evolution of host and pathogen. State-of-the-art approaches are presented and discussed for models belonging to the first two categories only, as they concentrate on the host-pathogen dynamics within individuals. Models of the third category fall more into the class of epidemiological models, which deserve a review by themselves. An extensive review of published models reveals a rich spectrum of methodologies and approaches adopted in different modelling studies, and a strong discrepancy between models concerning diseases in animals and models aimed at tackling diseases in humans (most of which belong to the first category), with the latter being generally more sophisticated. The importance of accounting for the impact of infection not only on health but also on production poses a considerable challenge to the study of host-pathogen interactions in livestock. This has led to relatively simplistic representations of host-pathogen interaction in existing models for livestock diseases. Although these have proven appropriate for investigating hypotheses concerning the relationships between health and production traits, they do not provide predictions of an animal's response to pathogen challenge of sufficient accuracy that would be required for the design of appropriate disease control strategies. A synthesis between the modelling methodologies adopted in categories 1 and 2 would therefore be desirable. The progress achieved in mathematical modelling to study immunological processes relevant to human diseases, together with the current advances in the generation and analysis of biological data related to animal diseases, offers a great opportunity to develop a new generation of host-pathogen interaction models that take on a fundamental role in the study and control of disease in livestock.     

Characteristics of papers that affect citations in the Journal of Fish Biology

Identifying the factors that influence the citation of articles helps authors improve the impact and reach of their research. Analysis of publications in the Journal of Fish Biology between 2008 and 2021 revealed that variables such as the number of keywords, abstract length, number of authors, and page length were associated with higher impact papers. These trends applied to both review and regular papers. These findings suggest that papers that are more informative, have higher numbers of authors, and have more keywords are more likely to be cited. Adoption of some simple “best-practice” behaviors can improve the likelihood that a paper is cited.     

Influence of Observer Presence on Pacific Damsel Bug Behavior: Who is Watching Whom?

When direct observations are used to study animal behavior the presence of the observer may alter the animal and hence influence the data being collected, yet few studies have quantified this effect. We conducted direct observation studies in the glasshouse to assess the relative influence of observer presence on the behavior of Pacific damsel bugs, Nabis kinbergii, a potentially important predator of crop pests. Comparisons of predator activity, predator distribution, prey (Helicoverpa armigera) mortality and prey distribution between frequently observed and minimally observed treatments, during diurnal and nocturnal observation sessions showed that the frequency of observer presence had no apparent impact on Pacific damsel bug behavior. This is the first documented test of the impact of observer presence in an insect system. To place our results in context, we reviewed 15 papers on the influence of observer presence in a range of animals. We established that just over half of these papers found evidence for an effect. Nevertheless, direct observations should be useful in further studies of Pacific damsel bug behavior, and researchers using direct observations to study the behavior of other animals should be cognizant of observer effects during design and interpretation of their study.     

Molecular tools and analytical approaches for the characterization of farm animal genetic diversity

Genetic studies of livestock populations focus on questions of domestication, within- and among-breed diversity, breed history and adaptive variation. In this review, we describe the use of different molecular markers and methods for data analysis used to address these questions. There is a clear trend towards the use of single nucleotide polymorphisms and whole-genome sequence information, the application of Bayesian or Approximate Bayesian analysis and the use of adaptive next to neutral diversity to support decisions on conservation.     

Ethics, ambiguity aversion, and the review of complex translational clinical trials

Clinical trials of novel agents often present several layers of ethical challenge. Because time and resources for ethical and safety review are limited, how investigators, IRBs, and regulators allocate attention to a trial's various safety dimensions itself represents a critical ethical question. In what follows, I use the example of a Parkinson's disease gene transfer trial to show how risks involving unknown probabilities or outcomes (ambiguity), might sometimes draw attention away from risks that involve known probabilities or outcomes. This potentially undermines the goal of 'systematic and nonarbitrary analysis of risk' during ethical review. To counteract the possible effects of such attention biases, I propose that reviewers develop 'cognitive aids' like lists and, where appropriate, set aside time to discuss non-ambiguous risks. I also propose further research for addressing and understanding how attention allocation, emotion, and ambiguity influence ethical decision-making.     

The need for systematic reviews of reasons

There are many ethical decisions in the practice of health research and care, and in the creation of policy and guidelines. We argue that those charged with making such decisions need a new genre of review. The new genre is an application of the systematic review, which was developed over decades to inform medical decision-makers about what the totality of studies that investigate links between smoking and cancer, for example, implies about whether smoking causes cancer. We argue that there is a need for similarly inclusive and rigorous reviews of reason-based bioethics, which uses reasoning to address ethical questions. After presenting a brief history of the systematic review, we reject the only existing model for writing a systematic review of reason-based bioethics, which holds that such a review should address an ethical question. We argue that such a systematic review may mislead decision-makers when a literature is incomplete, or when there are mutually incompatible but individually reasonable answers to the ethical question. Furthermore, such a review can be written without identifying all the reasons given when the ethical questions are discussed, their alleged implications for the ethical question, and the attitudes taken to the reasons. The reviews we propose address instead the empirical question of which reasons have been given when addressing a specified ethical question, and present such detailed information on the reasons. We argue that this information is likely to improve decision-making, both directly and indirectly, and also the academic literature. We explain the limitations of our alternative model for systematic reviews.     

Common misconceptions in molecular ecology: echoes of the modern synthesis

The field of molecular ecology has burgeoned into a large discipline spurred on by technical innovations that facilitate the rapid acquisition of large amounts of genotypic data, by the continuing development of theory to interpret results, and by the availability of computer programs to analyse data sets. As the discipline grows, however, misconceptions have become enshrined in the literature and are perpetuated by routine citations to other articles in molecular ecology. These misconceptions hamper a better understanding of the processes that influence genetic variation in natural populations and sometimes lead to erroneous conclusions. Here, we consider eight misconceptions commonly appearing in the literature: (i) some molecular markers are inherently better than other markers; (ii) mtDNA produces higher F(ST) values than nDNA; (iii) estimated population coalescences are real; (iv) more data are always better; (v) one needs to do a Bayesian analysis; (vi) selective sweeps influence mtDNA data; (vii) equilibrium conditions are critical for estimating population parameters; and (viii) having better technology makes us smarter than our predecessors. This is clearly not an exhaustive list and many others can be added. It is, however, sufficient to illustrate why we all need to be more critical of our own understanding of molecular ecology and to be suspicious of self-evident truths.