The new nativism: a commentary on Gary Marcus’s The birth of the mind

Gary Marcus (2004) has written a very interesting book about mental development from a nativist perspective. For the general readership at which the book is largely aimed, it will be interesting because of its many informative examples of the development of cognitive structures and because of its illuminating explanations of ways in which genes can contribute to these developmental processes. However, the book is also interesting from a theoretical point of view. Marcus tries to make nativism compatible with the central arguments that anti-nativists use to attack nativism and with many recent discoveries about genetic activity and brain development. In so doing, he reconfigures the nativist position to a considerable extent. Marcus’s theory is certainly more sophisticated than any version of nativism on the market. However, in our view Marcus ends up reconfiguring the nativist position out of existence. While many of the points that Marcus makes are both interesting and correct, we see no compelling reason to classify his considered position with traditional nativism rather than anti-nativism. More generally, we that think his book points to a general moral: the opposition between nativism and anti-nativism does not help us to understand psycho-developmental issues, and should therefore be abandoned.     

Analyzing a kinetic titration series using affinity biosensors

The classical method of measuring binding constants with affinity-based biosensors involves testing several analyte concentrations over the same ligand surface and regenerating the surface between binding cycles. Here we describe an alternative approach to collecting kinetic binding data, which we call "kinetic titration." This method involves sequentially injecting an analyte concentration series without any regeneration steps. Through a combination of simulation and experimentation, we show that this method can be as robust as the classical method of analysis. In addition, kinetic titrations can be more efficient than the conventional data collection method and allow us to fully characterize analyte binding to ligand surfaces that are difficult to regenerate.     

Dreaming of dragons: on the imagination of real life

This article draws on studies of medieval monasticism and northern indigenous ontologies to show how we might heal the rupture between the real world and our imagination of it, which underpins the official procedures of modern science. Though science is not averse to dreams of the imagination as potential sources of novel insight, they are banished from the reality it seeks to uncover. Ever since Bacon and Galileo, nature has been thought of as a book that will not willingly give up its secrets to human readers. The idea of the book of nature, however, dates from medieval times. For medieval readers as for indigenous hunters, creatures would speak and offer counsel. But in the transition to modernity the book was silenced. This article suggests that by acknowledging our imaginative participation in a more‐than‐human world, and the commitments this entails, we can reconcile scientific inquiry with religious sensibility as ways of knowing in being.     

Bodies and borders: a new cultural history of medicine

Both medicine and the history of medicine have seen many changes in the last four decades. The way we tell the story of medical developments no longer concentrates on the important doctors and their ideas. The influences of social history in the 1960s and 1970s and cultural history in the 1980s and 1990s have broadened and enriched the interpretations of our medical past. The social historians have helped us to include politics, economics, and the leading ideas of any period we wanted to study; the cultural approach has added ethnography as well as an emphasis on language or discourse.Today there is a new history of medicine, one far more willing to cross disciplinary boundaries to ask questions about how we know what we know and why we do what we do.This article highlights some of the work in the adjoining fields of medical anthropology and of literature and medicine to demonstrate new interests, new questions, and new methods of inquiry. However, although we have cast our nets far more widely in the process of professionalizing the history of medicine, there is a question about whether we have lost the appeal to one of our core constituencies: medical students and physicians. We need to welcome some of the new changes in medical history as in medicine itself; the common goal is to achieve a better understanding of what we have done and what we are doing.     

Experimental approaches for addressing fundamental biological questions in living, functioning cells with single molecule precision

In recent years, single molecule experimentation has allowed researchers to observe biological processes at the sensitivity level of single molecules in actual functioning, living cells, thereby allowing us to observe the molecular basis of the key mechanistic processes in question in a very direct way, rather than inferring these from ensemble average data gained from traditional molecular and biochemical techniques. In this short review, we demonstrate the impact that the application of single molecule bioscience experimentation has had on our understanding of various cellular systems and processes, and the potential that this approach has for the future to really address very challenging and fundamental questions in the life sciences.     

Vitalism and the Resistance to Experimentation on Life in the Eighteenth Century

There is a familiar opposition between a ‘Scientific Revolution’ ethos and practice of experimentation, including experimentation on life, and a ‘vitalist’ reaction to this outlook. The former is often allied with different forms of mechanism – if all of Nature obeys mechanical laws, including living bodies, ‘iatromechanism’ should encounter no obstructions in investigating the particularities of animal-machines – or with more chimiatric theories of life and matter, as in the ‘Oxford Physiologists’. The latter reaction also comes in different, perhaps irreducibly heterogeneous forms, ranging from metaphysical and ethical objections to the destruction of life, as in Margaret Cavendish, to more epistemological objections against the usage of instruments, the ‘anatomical’ outlook and experimentation, e.g. in Locke and Sydenham. But I will mainly focus on a third anti-interventionist argument, which I call ‘vitalist’ since it is often articulated in the writings of the so-called Montpellier Vitalists, including their medical articles for the Encyclopédie. The vitalist argument against experimentation on life is subtly different from the metaphysical, ethical and epistemological arguments, although at times it may borrow from any of them. It expresses a Hippocratic sensibility – understood as an artifact of early modernity, not as some atemporal trait of medical thought – in which Life resists the experimenter, or conversely, for the experimenter to grasp something about Life, it will have to be without torturing or radically intervening in it. I suggest that this view does not have to imply that Nature is something mysterious or sacred; nor does the vitalist have to attack experimentation on life in the name of some ‘vital force’ – which makes it less surprising to find a vivisectionist like Claude Bernard sounding so close to the vitalists.     

One danger of biomedical enhancements

In the near future, our society may develop a vast array of medical enhancements. There is a large debate about enhancements, and that debate has identified many possible harms. This paper describes a harm that has so far been overlooked. Because of some particular features of enhancements, we could come to place more value on them than we actually should. This over-valuation would lead us to devote time, energy, and resources to enhancements that could be better spent somewhere else. That mistake might not be trivial. By spending too much time, energy, and resources on enhancements, we could set back our pursuit of our deepest goals such as living happily and leading ethical lives.     

Magnetic resonance imaging findings in primary lymphoma of the liver: a case report

ABSTRACT: INTRODUCTION: Primary lymphoma of the liver is an extremely rare finding, with the few such cases reported in the literature to date describing indeterminate imaging findings, being focused more on computed tomography. To the best of our knowledge, there is no prior report describing magnetic resonance imaging scan findings with such a lesion. In the case reported here, magnetic resonance imaging gave us the opportunity to ascertain the correct diagnosis, confirmed by histopathology, thus avoiding unnecessary surgery or other treatments. Although this condition is rare, knowledge of magnetic resonance imaging findings will be invaluable for radiologists and other medical subspecialties that may face such cases in the future in helping to provide adequate management for affected patients. CASE PRESENTATION: A focal lesion was incidentally detected by ultrasound in a 75-year-old asymptomatic Albanian man being treated for benign hypertrophy of prostate. Chest and abdomen computed tomography scans did not reveal any abnormal findings besides a solid focal lesion on the right lobe of the liver and a mild homogenous enlargement of the prostate gland. Subsequently, magnetic resonance imaging of the upper abdomen was performed for better characterization of this lesion. Our patient was free of symptoms and his laboratory test results were normal. CONCLUSIONS: The magnetic resonance imaging scan results showed some distinctive features that helped us to make the correct diagnosis, and were thus very important in helping us provide the correct treatment for our patient.     

Images in the dialogue between science and society

In France, over 45 millions people watch TV every day for more than 3 hours. Science and image get well together since most TV watchers trust this media and rely on it (more than on any other source) for their scientific information. This emphasizes the power of images, which do not always deliver information, but can be naively regarded as creating communication. Image is necessary and an event which does not generate images is a non-event. Images are more than just a support for scientific messages: technologies have produced an enormous amount of images which allow us to uncover the mysteries of the world and Universe, their beauty and delicacy. We can be fascinated by the discovery of the invisible world which surrounds us, and science has truly generated artistic masterpieces even though we should remember that its primary goal is to understand the world rather than to create images.     

Steel wheels: The Age of Migration 5.0

As with all previous editions, the fifth edition offers substantial updates and developments. The addition of de Haas as a third author in this edition has had noticeable impacts on the shape and content of the book. The Age of Migration does not simply report on or contribute to the field of migration studies; it has done more than any other book to define that field.     

A probabilistic model for mining implicit 'chemical compound-gene' relations from literature

MOTIVATION: The importance of chemical compounds has been emphasized more in molecular biology, and 'chemical genomics' has attracted a great deal of attention in recent years. Thus an important issue in current molecular biology is to identify biological-related chemical compounds (more specifically, drugs) and genes. Co-occurrence of biological entities in the literature is a simple, comprehensive and popular technique to find the association of these entities. Our focus is to mine implicit 'chemical compound and gene' relations from the co-occurrence in the literature. RESULTS: We propose a probabilistic model, called the mixture aspect model (MAM), and an algorithm for estimating its parameters to efficiently handle different types of co-occurrence datasets at once. We examined the performance of our approach not only by a cross-validation using the data generated from the MEDLINE records but also by a test using an independent human-curated dataset of the relationships between chemical compounds and genes in the ChEBI database. We performed experimentation on three different types of co-occurrence datasets (i.e. compound-gene, gene-gene and compound-compound co-occurrences) in both cases. Experimental results have shown that MAM trained by all datasets outperformed any simple model trained by other combinations of datasets with the difference being statistically significant in all cases. In particular, we found that incorporating compound-compound co-occurrences is the most effective in improving the predictive performance. We finally computed the likelihoods of all unknown compound-gene (more specifically, drug-gene) pairs using our approach and selected the top 20 pairs according to the likelihoods. We validated them from biological, medical and pharmaceutical viewpoints.     

Animal experimentation: a rational approach towards drug development

Man's observation of animals as objects of study undoubtedly began in prehistoric times. The first recorded attempt involving the use of live animals for research was by Ersistratis in Alexandria in 300 B.C. Animal investigation has clearly made possible the enormous advances in drug development in this century. A cursory review of any modern text book of pharmacology or medicine will attest the many drugs currently available to benefit mankind in the struggle to eradicate and control diseases. The main purpose of this article is to describe some of the experimental work on animals which contributed to the discovery and development of drugs benefiting human beings and other animal species. Since animal experimentation has occupied a focal position in all the research leading to useful drugs, one will appreciate that it will be necessary to limit the discussion to certain aspects of this broad and interesting topic. With this in mind, an attempt is made to relate briefly the nature of animal investigations which were instrumental in the development of major classes of drugs. Some attention has also been focused on legislation's on animal experimentation of some developed countries with emphasis on India and to views on animal experimentation. We hope this article will stimulate the minds of the scientists for a rational debate on the future of animal experimentation.     

What makes us human? Answers from evolutionary anthropology

Today, scholars from numerous and highly diverse fields are not only addressing the question of what makes us human, but also seeking input from other disciplines to inform their answers to this fundamental issue. However, for the most part, evolutionary anthropologists are not particularly prominent in this discussion, or at least not acknowledged to be. Why is this the case? One reason may be that although evolutionary anthropologists are uniquely positioned to provide valuable insight on this subject, the responses from any one of us are likely to be as different as the research specializations and intellectual experiences that we bring to the table. Indeed, one would anticipate that a paleoanthropologist would not only have different views than a primatologist, geneticist, or behavioral ecologist, but from other paleoanthropologists as well. Yet if asked by a theologian, psychologist, or political scientist, and perhaps most importantly, by any curious person outside the walls of academia, do we have a response that most evolutionary anthropologists could agree on as reflecting our contributions to the understanding of being and becoming human? Our introductory textbooks usually begin with this fundamental question, yet seldom produce a concise answer. © 2012 Wiley Periodicals, Inc.     

Probabilistic classifiers with high-dimensional data

For medical classification problems, it is often desirable to have a probability associated with each class. Probabilistic classifiers have received relatively little attention for small n large p classification problems despite of their importance in medical decision making. In this paper, we introduce 2 criteria for assessment of probabilistic classifiers: well-calibratedness and refinement and develop corresponding evaluation measures. We evaluated several published high-dimensional probabilistic classifiers and developed 2 extensions of the Bayesian compound covariate classifier. Based on simulation studies and analysis of gene expression microarray data, we found that proper probabilistic classification is more difficult than deterministic classification. It is important to ensure that a probabilistic classifier is well calibrated or at least not "anticonservative" using the methods developed here. We provide this evaluation for several probabilistic classifiers and also evaluate their refinement as a function of sample size under weak and strong signal conditions. We also present a cross-validation method for evaluating the calibration and refinement of any probabilistic classifier on any data set.     

Efficient Modeling and Active Learning Discovery of Biological Responses

High throughput and high content screening involve determination of the effect of many compounds on a given target. As currently practiced, screening for each new target typically makes little use of information from screens of prior targets. Further, choices of compounds to advance to drug development are made without significant screening against off-target effects. The overall drug development process could be made more effective, as well as less expensive and time consuming, if potential effects of all compounds on all possible targets could be considered, yet the cost of such full experimentation would be prohibitive. In this paper, we describe a potential solution: probabilistic models that can be used to predict results for unmeasured combinations, and active learning algorithms for efficiently selecting which experiments to perform in order to build those models and determining when to stop. Using simulated and experimental data, we show that our approaches can produce powerful predictive models without exhaustive experimentation and can learn them much faster than by selecting experiments at random.     

New roles for model genetic organisms in understanding and treating human disease: report from the 2006 Genetics Society of America meeting

Fundamental biological knowledge and the technology to acquire it have been immeasurably advanced by past efforts to understand and manipulate the genomes of model organisms. Has the utility of bacteria, yeast, worms, flies, mice, plants, and other models now peaked and are humans poised to become the model organism of the future? The Genetics Society of America recently convened its 2006 meeting entitled "Genetic Analysis: Model Organisms to Human Biology" to examine the future role of genetic research. (Because of time limitations, the meeting was unable to cover the substantial contributions and future potential of research on model prokaryotic organisms.) In fact, the potential of model-organism-based studies has grown substantially in recent years. The genomics revolution has revealed an underlying unity between the cells and tissues of eukaryotic organisms from yeast to humans. No uniquely human biological mechanisms have yet come to light. This common evolutionary heritage makes it possible to use genetically tractable organisms to model important aspects of human medical disorders such as cancer, birth defects, neurological dysfunction, reproductive failure, malnutrition, and aging in systems amenable to rapid and powerful experimentation. Applying model systems in this way will allow us to identify common genes, proteins, and processes that underlie human medical conditions. It will allow us to systematically decipher the gene-gene and gene-environment interactions that influence complex multigenic disorders. Above all, disease models have the potential to address a growing gap between our ability to collect human genetic data and to productively interpret and apply it. If model organism research is supported with these goals in mind, we can look forward to diagnosing and treating human disease using information from multiple systems and to a medical science built on the unified history of life on earth.     

The neurobiology of attachment

It is difficult to think of any behavioural process that is more intrinsically important to us than attachment. Feeding, sleeping and locomotion are all necessary for survival, but humans are, as Baruch Spinoza famously noted, "a social animal" and it is our social attachments that we live for. Over the past decade, studies in a range of vertebrates, including humans, have begun to address the neural basis of attachment at a molecular, cellular and systems level. This review describes some of the important insights from this work.     

The human adrenergic neurovascular mechanism

The major features of adrenergic neurotransmission established in animals have been observed in one blood vessel or another from the human. However, the detailed mechanism in one particular human blood vessel or vascular sample from a particular regional bed has not yet been carefully compared with a corresponding vessel from nonhuman species. There is probably more known about cerebral blood vessels than others, and if our knowledge of this bed is at all representative of what occurs elsewhere, then any projections regarding the human from animal studies are potentially very misleading. The little evidence that is available suggests that generalization regarding human vessels is going to be difficult. Yet this very difficulty emphasizes the need for study, not only from the normal and healthy subject, but from the diseased. The human circulation represents a source of vascular tissue whose analysis will reveal much more about the circulation and its change with circumstances, including disease, of interest to the scientist and the physician than can ever be achieved by experimentation with animal tissues.     

Simple rules underlying gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients

MOTIVATIONS AND RESULTS: For classifying gene expression profiles or other types of medical data, simple rules are preferable to non-linear distance or kernel functions. This is because rules may help us understand more about the application in addition to performing an accurate classification. In this paper, we discover novel rules that describe the gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients. We also introduce a new classifier, named PCL, to make effective use of the rules. PCL is accurate and can handle multiple parallel classifications. We evaluate this method by classifying 327 heterogeneous ALL samples. Our test error rate is competitive to that of support vector machines, and it is 71% better than C4.5, 50% better than Naive Bayes, and 43% better than k-nearest neighbour. Experimental results on another independent data sets are also presented to show the strength of our method. AVAILABILITY: Under http://sdmc.lit.org.sg/GEDatasets/, click on Supplementary Information.     

Species assembly in model ecosystems, I: Analysis of the population model and the invasion dynamics

Recently we have introduced a simplified model of ecosystem assembly (Capitán et al., 2009) for which we are able to map out all assembly pathways generated by external invasions in an exact manner. In this paper we provide a deeper analysis of the model, obtaining analytical results and introducing some approximations which allow us to reconstruct the results of our previous work. In particular, we show that the population dynamics equations of a very general class of trophic-level structured food-web have an unique interior equilibrium point which is globally stable. We show analytically that communities found as end states of the assembly process are pyramidal and we find that the equilibrium abundance of any species at any trophic level is approximately inversely proportional to the number of species in that level. We also find that the per capita growth rate of a top predator invading a resident community is key to understand the appearance of complex end states reported in our previous work. The sign of these rates allows us to separate regions in the space of parameters where the end state is either a single community or a complex set containing more than one community. We have also built up analytical approximations to the time evolution of species abundances that allow us to determine, with high accuracy, the sequence of extinctions that an invasion may cause. Finally we apply this analysis to obtain the communities in the end states. To test the accuracy of the transition probability matrix generated by this analytical procedure for the end states, we have compared averages over those sets with those obtained from the graph derived by numerical integration of the Lotka-Volterra equations. The agreement is excellent.