抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

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Feeling and thinking : Preferences need no inferences

A category of stimuli of great importance for primates, humans in particular, is that formed by actions done by other individuals. If we want to survive, we must understand the actions of others. Furthermore, without action understanding, social organization is impossible. In the case of humans, there is another faculty that depends on the observation of others' actions: imitation learning. Unlike most species, we are able to learn by imitation, and this faculty is at the basis of human culture. In this review we present data on a neurophysiological mechanism--the mirror-neuron mechanism--that appears to play a fundamental role in both action understanding and imitation. We describe first the functional properties of mirror neurons in monkeys. We review next the characteristics of the mirror-neuron system in humans. We stress, in particular, those properties specific to the human mirror-neuron system that might explain the human capacity to learn by imitation. We conclude by discussing the relationship between the mirror-neuron system and language.

The mirror-neuron system.

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

Acknowledgments: This work was supported by a grant from the National Science Foundation (NSF#0354453). Any opinions, findings and conclusions expressed in the paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors wish to thank the following individuals for their contributions to the chapter: Leah Bricker, Hank Clark, Barbara Conboy, Joan Davis, Katie Hardin, Beth Koemans, Tiffany Lee, Laurie McCarthy, Maisy McGaughey, Raj Raizada, Suzanne Reeve, Maritza Rivera-Gaxiola, Tom Satwicz, Yang Zhang, and Heather Toomey Zimmmerman.

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Learning Theories and Education: Toward a Decade of Synergy

The Scientist in the Crib: What Early Learning Tells Us About the Mind

What infant memory tells us about infantile amnesia: long-term recall and deferred imitation.

Three experiments examined peer imitation with 14- to 18-month-old infants. In Experiment 1, infants saw a trained 14-month-old (“expert peer”) perform specific actions on 5 objects. Imitation from memory was tested after a 5-min delay. In Experiment 2, the infants observed an expert peer in the laboratory, and retention and imitation were tested in the home (change of context) after a 2-day delay. In Experiment 3, a peer demonstrated target acts at a day care, and after a 2-day delay infants were tested in their homes. Results from all 3 experiments showed significant imitation compared with controls. The experiments demonstrate social learning from peers during infancy and also provide the first evidence for infant imitation from memory across a change in context.

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Peer Imitation by Toddlers in Laboratory, Home, and Day-Care Contexts: Implications for Social Learning and Memory.

Facial imitation was investigated in infants 6 weeks and 2 to 3 months of age. Three findings emerged: (a) early imitation did not vary as a function of familiarity with the model—infants imitated a stranger as well as their own mothers; (b) infants imitated both static facial postures and dynamic facial gestures; and (c) there was no disappearance of facial imitation in the 2- to 3-month age range, contrary to previous reports. Two broad theoretical points are developed. First, a proposal is made about the social and psychological functions that early imitation serves in infants' encounters with people. It is argued that infants deploy imitation to enrich their understanding of persons and actions and that early imitation is used for communicative purposes. Second, a theoretical bridge is formed between early imitation and the “object concept.” The bridge is formed by considering the fundamental role that identity plays in infants' understanding of people and things. One of the psychological functions that early imitation subserves is to identify people. Infants use the nonverbal behavior of people as an identifier of who they are and use imitation as a means of verifying this identity. Data and theory are adduced in favor of viewing early imitation as an act of social cognition.

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Andrew N. Meltzoff

Papers

Learning Theories and Education: Toward a Decade of Synergy

The Scientist in the Crib: What Early Learning Tells Us About the Mind

What infant memory tells us about infantile amnesia: long-term recall and deferred imitation.

Peer Imitation by Toddlers in Laboratory, Home, and Day-Care Contexts: Implications for Social Learning and Memory.

Early imitation within a functional framework : the importance of person identity, movement, and development