Scoring predictive models using a reduced representation of proteins: model and energy definition

Background  

Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment.     

On the structure and stability of mutualistic systems: Analysis of predator-prey and competition models as modified by the action of a slow-growing mutualist

Two basic models of mutualism are presented in which interactions among three species lead to mutualism between two of them. The models represent 2-species predator-prey or competition systems in which a third species acts as a mutualist with either the predator, the prey, or one of the competitors. The models include the assumptions that there is a cost of associating with the mutualist and that the mutualist population grows much more slowly than the other two populations. Special cases of these two models correspond to six qualitatively different types of mutualistic benefit, all of which are known to occur in nature: deterring predation, increasing prey availability, feeding on (or competing with) a predator, increasing competitive interactions, decreasing competitive interactions, and feeding on (or competing with) a competitor. These models and their special cases are subjected to a local stability analysis. The results show that mutualism based upon deterring predation, competing with a predator, or decreasing competitive interactions enhances local stability, while mutualism based upon increasing prey availability or increasing competitive interactions reduces local stability. These results clearly reject the idea that mutualism is an inherently unstable process, and reinforces the idea that each different kind of mutualism will have to be considered separately. Compared to 2-species models of mutualism, the 3-species models provide a more realistic representation of the structure of many mutualistic systems, the mechanisms by which one species benefits another, and the regulation of the interaction.     

Human liver model systems in a dish

The human adult liver has a multi‐cellular structure consisting of large lobes subdivided into lobules containing portal triads and hepatic cords lined by specialized blood vessels. Vital hepatic functions include filtering blood, metabolizing drugs, and production of bile and blood plasma proteins like albumin, among many other functions, which are generally dependent on the location or zone in which the hepatocyte resides in the liver. Due to the liver's intricate structure, there are many challenges to design differentiation protocols to generate more mature functional hepatocytes from human stem cells and maintain the long‐term viability and functionality of primary hepatocytes. To this end, recent advancements in three‐dimensional (3D) stem cell culture have accelerated the generation of a human miniature liver system, also known as liver organoids, with polarized epithelial cells, supportive cell types and extra‐cellular matrix deposition by translating knowledge gained in studies of animal organogenesis and regeneration. To facilitate the efforts to study human development and disease using in vitro hepatic models, a thorough understanding of state‐of‐art protocols and underlying rationales is essential. Here, we review rapidly evolving 3D liver models, mainly focusing on organoid models differentiated from human cells.     

Species Associations in a Species-Rich Subtropical Forest Were Not Well-Explained by Stochastic Geometry of Biodiversity

The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure.     

Olfactory ecology and the processing of complex mixtures

Natural olfactory stimuli typically are mixtures of which the identities, concentrations, and ratios of chemical constituents are important for many odor-mediated behaviors. Despite abundant behavioral examples, links between odor-evoked behavior and the processing and discrimination of complex olfactory stimuli remains an area of active study. Coupling electrophysiological and behavioral experiments, recent studies in a variety of different insect models have provided new insights into the perceptual and neural mechanisms about how natural olfactory stimuli are processed, and how plasticity and internal state of the insect may influence the odor representation. These studies show that complex stimuli are represented in unique percepts that are different from their individual constituents, and that the representation may be modulated by experience and influenced by other sensory modalities.     

Modelling geographical patterns in species richness using eigenvector-based spatial filters

Aim To test the mechanisms driving bird species richness at broad spatial scales using eigenvector‐based spatial filtering. Location South America. Methods An eigenvector‐based spatial filtering was applied to evaluate spatial patterns in South American bird species richness, taking into account spatial autocorrelation in the data. The method consists of using the geographical coordinates of a region, based on eigenanalyses of geographical distances, to establish a set of spatial filters (eigenvectors) expressing the spatial structure of the region at different spatial scales. These filters can then be used as predictors in multiple and partial regression analyses, taking into account spatial autocorrelation. Autocorrelation in filters and in the regression residuals can be used as stopping rules to define which filters will be used in the analyses. Results Environmental component alone explained 8% of variation in richness, whereas 77% of the variation could be attributed to an interaction between environment and geography expressed by the filters (which include mainly broad‐scale climatic factors). Regression coefficients of environmental component were highest for AET. These results were unbiased by short‐scale spatial autocorrelation. Also, there was a significant interaction between topographic heterogeneity and minimum temperature. Conclusion Eigenvector‐based spatial filtering is a simple and suitable statistical protocol that can be used to analyse patterns in species richness taking into account spatial autocorrelation at different spatial scales. The results for South American birds are consistent with the climatic hypothesis, in general, and energy hypothesis, in particular. Habitat heterogeneity also has a significant effect on variation in species richness in warm tropical regions.     

长江中游干流鱼类群落构建机制分析

研究选取长江中游5个采样点(宜昌、枝江、荆州、汉南、湖口)为代表, 采用系统发育群落结构方法分析了不同空间尺度下长江中游鱼类群落的构建机制。结果表明: (1)空间聚类分析显示, 在65%的相似性水平上, 所有样点可以划分为3个Group: GroupⅠ(宜昌)、GroupⅡ(枝江+荆州)和Group Ⅲ(汉南+湖口);在55%的相似性水平上, 所有样点可以划分为2个Group: Group A(宜昌)和Group B(枝江+荆州+汉南+湖口), 且聚类分析结果与采样点的空间分布相符合。(2)在不同空间尺度下, 鱼类群落构建机制存在差异: 从地区采样点尺度来看, 荆州江段鱼类群落表现为竞争作用主导群落构建, 其余采样点鱼类群落均为环境过滤作用;从区域尺度来看, 宜昌江段鱼类群落表现为环境过滤作用的建群机制, 其余4个采样点在扩大空间尺度后, 即分为Group A和Group B的情况下, 其鱼类群落构建机制转变为物种间竞争作用。因此, 长江中游干流鱼类群落构建机制表现了地区环境和空间尺度的共同作用。由于水流湍急, 宜昌始终表现为环境过滤作用。其他江段在采样点尺度多数表现了环境过滤作用, 但是在宏观的空间尺度上, 却由于空间异质性的增加, 容纳了远缘的物种, 群落构建机制转换为竞争作用。这样的转变有别于陆生植物中由小尺度竞争作用转为大尺度环境过滤作用的情况。     

Complex adaptation and system structure

The structural organization of biological systems is one of nature’s most fascinating aspects, but its origin and functional role is not yet fully understood. For instance, basic adaptational mechanisms like genetic mutation and Hebbian adaptation seem to be generic and invariant across many species and are, on their own, fairly well investigated and understood. However, it is the organism’s structure – the representations these mechanisms act upon – that bears the complex functional effects of these mechanisms. While typical technical approaches to system design require detailed problem models and suffer from the need to explicitly take care of all possible cases, the organization of biological systems seems to induce inherent adaptability, flexibility and robustness. In this discussion paper we address the concept of structured variability, particularly the role of system structure as implementing a certain representation on which basic variational mechanisms act on. The functional adaptability (or search distribution) depends crucially on this representation.     

Complex adaptation and system structure

The structural organization of biological systems is one of nature’s most fascinating aspects, but its origin and functional role is not yet fully understood. For instance, basic adaptational mechanisms like genetic mutation and Hebbian adaptation seem to be generic and invariant across many species and are, on their own, fairly well investigated and understood. However, it is the organism’s structure – the representations these mechanisms act upon – that bears the complex functional effects of these mechanisms. While typical technical approaches to system design require detailed problem models and suffer from the need to explicitly take care of all possible cases, the organization of biological systems seems to induce inherent adaptability, flexibility and robustness. In this discussion paper we address the concept of structured variability, particularly the role of system structure as implementing a certain representation on which basic variational mechanisms act on. The functional adaptability (or search distribution) depends crucially on this representation.     

The Preferred Directions of Conjunctive Grid X Head Direction Cells in the Medial Entorhinal Cortex Are Periodically Organized

The discovery of speed-modulated grid, head direction, and conjunctive grid x head direction cells in the medial entorhinal cortex has led to the hypothesis that path integration, the updating of one’s spatial representation based on movement, may be carried out within this region. This hypothesis has been formalized by many computational models, including a class known as attractor network models. While many of these models propose specific mechanisms by which path integration might occur, predictions of these specific mechanisms have not been tested. Here I derive and test a key prediction of one attractor network path integration mechanism. Specifically, I first demonstrate that this mechanism predicts a periodic distribution of conjunctive cell preferred directions in order to minimize drift. Next, I test whether conjunctive cell preferred directions are in fact periodically organized. Results indicate that conjunctive cells are preferentially tuned to increments of 36°, consistent with drift minimization in this path integration mechanism. By contrast, no periodicity was observed in the preferred directions of either pure grid or pure head direction cells. These results provide the first neural evidence of a nonuniform structure in the directional preferences of any head direction representation found in the brain.     

Animal models for the study of liver fibrosis: new insights from knockout mouse models

Fibrosis arises as part of a would-healing response that maintains organ structure and integrity following tissue damage but also contributes to a variety of human pathologies such as liver fibrosis. Liver fibrosis is an abnormal response of the liver to persistent injury with the excessive accumulation of collagenous extracellular matrices. Currently there is no effective treatment, and many patients end up with a progressive form of the disease, eventually requiring a liver transplant. The clarification of mechanisms underlying pathogenesis of liver fibrosis and the development of effective therapy are of clinical importance. Experimental animal models, in particular targeted gene knockouts (loss of function) in mice, have become a powerful resource to address the molecular mechanisms or significance of the targeted gene in hepatic functions and diseases. This review will focus on the recent advances in knowledge obtained from genetically engineered mice that provide novel insights into the pathophysiology of liver fibrosis.     

Coarse-grained models for protein aggregation

The aggregation of soluble proteins into fibrillar species is a complex process that spans many lengths and time scales, and that involves the formation of numerous on-pathway and off-pathway intermediate species. Despite this complexity, several elements underlying the aggregation process appear to be universal. The kinetics typically follows a nucleation-growth process, and proteins with very different sequences aggregate to form similar fibril structures, populating intermediates with sufficient structural similarity to bind to a common antibody. This review focuses on a computational approach that exploits the common features of aggregation to simplify or 'coarse-grain' the representation of the protein. We highlight recent developments in coarse-grained modeling and illustrate how these models have been able to shed new light into the mechanisms of protein aggregation and the nature of aggregation intermediates. The roles of aggregation prone conformations in the monomeric state and the influence of inherent β-sheet and aggregation propensities in modulating aggregation pathways are discussed.     

Point process models,the dimensions of biodiversity and the importance of small-scale biotic interactions

Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersal-based stochastic models. This body of work has emphasized the importance of both habitat filtering and dispersal limitation, and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering. One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species, phylogenetic and functional diversity. Here, we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect, the heterogeneous Poisson process for the effect of habitat heterogeneity, the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species, phylogenetic and functional structures of communities.Important findings Our evidence from species, phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales (50×50 m). Conversely, at local scales (10×10 and 20×20 m), the models often fail to predict the species, phylogenetic and functional diversity, suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.     

Molecular genetic analysis of Down syndrome

Down syndrome (DS) is caused by trisomy of all or part of human chromosome 21 (HSA21) and is the most common genetic cause of significant intellectual disability. In addition to intellectual disability, many other health problems, such as congenital heart disease, Alzheimer’s disease, leukemia, hypotonia, motor disorders, and various physical anomalies occur at an elevated frequency in people with DS. On the other hand, people with DS seem to be at a decreased risk of certain cancers and perhaps of atherosclerosis. There is wide variability in the phenotypes associated with DS. Although ultimately the phenotypes of DS must be due to trisomy of HSA21, the genetic mechanisms by which the phenotypes arise are not understood. The recent recognition that there are many genetically active elements that do not encode proteins makes the situation more complex. Additional complexity may exist due to possible epigenetic changes that may act differently in DS. Numerous mouse models with features reminiscent of those seen in individuals with DS have been produced and studied in some depth, and these have added considerable insight into possible genetic mechanisms behind some of the phenotypes. These mouse models allow experimental approaches, including attempts at therapy, that are not possible in humans. Progress in understanding the genetic mechanisms by which trisomy of HSA21 leads to DS is the subject of this review.     

An Overview of Microwave Resonance Therapy and EEG Correlates of Microwave Resonance Relaxation and Other Consciousness Altering Techniques

Microwave Resonance Therapy (MRT) is a novel medical treatment representing a synthesis of the ancient Chinese traditional knowledge in medicine (acupuncture) and recent breakthroughs in biophysics. MRT affects the appropriate acupuncture points by the generation of high-frequency microwaves (52–78 GHz); remarkable clinical results are being achieved. In this paper, the quantum-like macroscopic biophysical bases of MRT are elaborated, offering new insights into the mechanisms of the assembling gap junction hemichannels on the internal microwave (MW) electromagnetic field spatiotemporal maxima at the temporary position of the acupuncture system, and hence insights into the biophysical nature of temporary psychosomatic health or disease. Such a picture also supports an electromagnetic/ionic “optical” ultra-low-frequency modulated MW quantum holographic neural network-like function of the acupuncture system (similar to complex-valued oscillatory holographic, Hopfield-like neural networks), and its essential relation to consciousness, as strongly suggested from biophysical modeling of altered states of consciousness. Finally, our electroencephalographic (EEG) investigations showed more or less characteristic EEG features in many subjects when relaxation was induced by MRT applied to corresponding acupuncture points, as well as by some other activities that may alter consciousness (transcendental meditation, musicogenic states, healer/healee noncontact interaction, drowsiness), demonstrating that EEG may permit rapid and reproducible identification of different states of consciousness, which could be useful in evaluating the effectiveness of consciousness altering techniques and related stress reduction.     

种子的长距离风传播模型研究进展

 植物种子的长距离传播在物种迁移、生物入侵、保护生物学等领域有重要的生态和进化意义。种子传播有很多方式,开阔草原等地区的草本植物和许多热带和温带的树木都是通过风传播种子的。风传播的方式最适合进行种子长距离传播现象的模拟研究。种子的风传播模型是传播生态研究的一个重要领域,尤其是种子的长距离风传播模型,对于外来入侵植物的扩散和破碎化景观中植物种群的基因交流等生态过程研究举足轻重,然而国内鲜见这方面的研究成果。本文综述了种子长距离风传播现象研究的背景和意义,分析了风传播种子模型的基本形式和构成原理,并分别就现象模型和机理模型的相关研究进展进行了总结,同时指出了未来发展的几个重要方向。种子的风传播模型可以分为现象模型和机理模型两类,现象模型按种子传播核心的形式包括短尾模型、偏峰长尾模型和混合传播核心模型,后两者对于长距离传播数据的模拟可以取得很好的效果。机理模型按照模拟机制可分为欧拉对流扩散模型和拉格郎日随机模型两类。本文重点介绍了种子的长距离风传播现象的形成机理和两类机理模型的参数构成和处理方式。适合种子脱落的天气和适合传播的天气的同步性可能是形成种子长距离风传播的一个重要前提,林缘和地表存在的上升气流及大风和暴风中形成的速度梯度都可能对于种子的长距离传播有重要的作用。机理模型的操作因子主要包括生物方面的因子、气象方面的因子和地形方面的因子。同时对目前几个应用比较成功的机理模型进行了简要的介绍和评价,包括倾斜羽毛模型、对流-扩散-下降模型、无掩蔽模型、背景模型、WINDISPER及其改进模型和PAPPUS模型。最后指出,目前在风传播种子的长距离模型研究中,对草本植物种子的传播模拟的投入明显不如树木种子的长距离传播模拟,对于破碎化景观中种子长距离的风传播的研究还存在很大的差距,而对提高机理模型预测能力的高分辨率物理环境数据输入技术的需求则为多学科交叉提供了很好的机会。     

Practical applications of the microphotometric quantification of histoenzyme reactions

Summary There are many histochemical reactions which can be used for the accurate topographic detection of enzymes in tissues. There are also many reports of applications of these techniques in which the results have been evaluated subjectively. However, only a few of these methods have been the subject of quantification, using different methodologies, most of them based on microphotometry. A critical analysis of these procedures has generally shown that they are valid either relatively or at an absolute level. Nevertheless, the routine application of these methods is not as widespread as one might expect.In this paper, the methodological developments that have taken place in the histochemical assay of some enzymes by microspectrophotometry are reviewed briefly. The enzymes include acid phosphatase, non-specific esterase, succinate dehydrogenase and cytochrome oxidase. These methods have given consistent and useful results when applied to our experimental models of irradiated skin, and thus seem useful for various other applications.The reasons why there have been so few applications of quantitative histochemistry are also discussed together with possible ways of making its use more general.     

Selective disruption of one Cartesian axis of cortical maps and receptive fields by deficiency in ephrin-As and structured activity

The topographic representation of visual space is preserved from retina to thalamus to cortex. We have previously shown that precise mapping of thalamocortical projections requires both molecular cues and structured retinal activity. To probe the interaction between these two mechanisms, we studied mice deficient in both ephrin-As and retinal waves. Functional and anatomical cortical maps in these mice were nearly abolished along the nasotemporal (azimuth) axis of the visual space. Both the structure of single-cell receptive fields and large-scale topography were severely distorted. These results demonstrate that ephrin-As and structured neuronal activity are two distinct pathways that mediate map formation in the visual cortex and together account almost completely for the formation of the azimuth map. Despite the dramatic disruption of azimuthal topography, the dorsoventral (elevation) map was relatively normal, indicating that the two axes of the cortical map are organized by separate mechanisms.     

Effects of species diversity on disease risk

The transmission of infectious diseases is an inherently ecological process involving interactions among at least two, and often many, species. Not surprisingly, then, the species diversity of ecological communities can potentially affect the prevalence of infectious diseases. Although a number of studies have now identified effects of diversity on disease prevalence, the mechanisms underlying these effects remain unclear in many cases. Starting with simple epidemiological models, we describe a suite of mechanisms through which diversity could increase or decrease disease risk, and illustrate the potential applicability of these mechanisms for both vector-borne and non-vector-borne diseases, and for both specialist and generalist pathogens. We review examples of how these mechanisms may operate in specific disease systems. Because the effects of diversity on multi-host disease systems have been the subject of much recent research and controversy, we describe several recent efforts to delineate under what general conditions host diversity should increase or decrease disease prevalence, and illustrate these with examples. Both models and literature reviews suggest that high host diversity is more likely to decrease than increase disease risk. Reduced disease risk with increasing host diversity is especially likely when pathogen transmission is frequency-dependent, and when pathogen transmission is greater within species than between species, particularly when the most competent hosts are also relatively abundant and widespread. We conclude by identifying focal areas for future research, including (1) describing patterns of change in disease risk with changing diversity; (2) identifying the mechanisms responsible for observed changes in risk; (3) clarifying additional mechanisms in a wider range of epidemiological models; and (4) experimentally manipulating disease systems to assess the impact of proposed mechanisms.     

Learning cortical topography from spatiotemporal stimuli

Stimulus representation is a functional interpretation of early sensory cortices. Early sensory cortices are subject to stimulus-induced modifications. Common models for stimulus-induced learning within topographic representations are based on the stimuli's spatial structure and probability distribution. Furthermore, we argue that average temporal stimulus distances reflect the stimuli's relatedness. As topographic representations reflect the stimuli's relatedness, the temporal structure of incoming stimuli is important for the learning in cortical maps. Motivated by recent neurobiological findings, we present an approach of cortical self-organization that additionally takes temporal stimulus aspects into account. The proposed model transforms average interstimulus intervals into representational distances. Thereby, neural topography is related to stimulus dynamics. This offers a new time-based interpretation of cortical maps. Our approach is based on a wave-like spread of cortical activity. Interactions between dynamics and feedforward activations lead to shifts of neural activity. The psychophysical saltation phenomenon may represent an analogue to the shifts proposed here. With regard to cortical plasticity, we offer an explanation for neurobiological findings that other models cannot explain. Moreover, we predict cortical reorganizations under new experimental, spatiotemporal conditions. With regard to psychophysics, we relate the saltation phenomenon to dynamics and interaction in early sensory cortices and predict further effects in the perception of spatiotemporal stimuli. Received: 17 March 1999 / Accepted in revised form: 10 August 1999