Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Frequency-dependent conspecific attraction to food patches

In many ecological situations, resources are difficult to find but become more apparent to nearby searchers after one of their numbers discovers and begins to exploit them. If the discoverer cannot monopolize the resources, then others may benefit from joining the discoverer and sharing their discovery. Existing theories for this type of conspecific attraction have often used very simple rules for how the decision to join a discovered resource patch should be influenced by the number of individuals already exploiting that patch. We use a mechanistic, spatially explicit model to demonstrate that individuals should not necessarily simply join patches more often as the number of individuals exploiting the patch increases, because those patches are likely to be exhausted soon or joining them will intensify future local competition. Furthermore, we show that this decision should be sensitive to the nature of the resource patches, with individuals being more responsive to discoveries in general and more tolerant of larger numbers of existing exploiters on a patch when patches are resource-rich and challenging to locate alone. As such, we argue that this greater focus on underlying joining mechanisms suggests that conspecific attraction is a more sophisticated and flexible tactic than currently appreciated.     

How intraspecific variation in seed‐dispersing animals matters for plants

Seed dispersal by animals is a complex phenomenon, characterized by multiple mechanisms and variable outcomes. Most researchers approach this complexity by analysing context‐dependency in seed dispersal and investigating extrinsic factors that might influence interactions between plants and seed dispersers. Intrinsic traits of seed dispersers provide an alternative way of making sense of the enormous variation in seed fates. I review causes of intraspecific variability in frugivorous and granivorous animals, discuss their effects on seed dispersal, and outline likely consequences for plant populations and communities. Sources of individual variation in seed‐dispersing animals include sexual dimorphism, changes associated with growth and ageing, individual specialization, and animal personalities. Sexual dimorphism of seed‐dispersing animals influences seed fate through diverse mechanisms that range from effects caused by sex‐specific differences in body size, to influences of male versus female cognitive functions. These differences affect the type of seed treatment (e.g. dispersal versus predation), the number of dispersed seeds, distance of seed dispersal, and likelihood that seeds are left in favourable sites for seeds or seedlings. The best‐documented consequences of individual differences associated with growth and ageing involve quantity of dispersed seeds and the quality of seed treatment in the mouth and gut. Individual specialization on different resources affects the number of dispersed plant species, and therefore the connectivity and architecture of seed‐dispersal networks. Animal personalities might play an important role in shaping interactions between plants and dispersers of their seeds, yet their potential in this regard remains overlooked. In general, intraspecific variation in seed‐dispersing animals often influences plants through effects of these individual differences on the movement ecology of the dispersers. Two conditions are necessary for individual variation to exert a strong influence on seed dispersal. First, the individual differences in traits should translate into differences in crucial characteristics of seed dispersal. Second, individual variation is more likely to be important when the proportions of particular types of individuals fluctuate strongly in a population or vary across space; when proportions are static, it is less likely that intraspecific differences will be responsible for changes in the dynamics and outcomes of plant–animal interactions. In conclusion, focusing on variation among foraging animals rather than on species averages might bring new, mechanistic insights to the phenomenon of seed dispersal. While this shift in perspective is unlikely to replace the traditional approach (based on the assumption that all important variation occurs among species), it provides a complementary alternative to decipher the enormous variation observed in animal‐mediated seed dispersal.     

Juvenile bimodal length distribution and sea-run migration of the lower modal group in the Pacific Ocean form of three-spined stickleback

Juvenile three-spined stickleback Gasterosteus aculeatus in their nursery pond had a bimodal length distribution after October in their first year of life. A sea-run migration of all individuals belonging to the lower modal group was observed, with a peak in early November. These data suggest that partial migration based on the early status of individual juveniles occurs in the Pacific Ocean form of three-spined stickleback.     

The importance of intraspecific frequency-dependent selection in modelling competitive coevolution

Summary The coevolution of competitors has been analyzed by two different types of fitness-maximization techniques; ESS methods (Lawlor and Maynard Smith, 1976), and CSS methods (Roughgarden, 1979). This paper argues that CSS methods generally do not predict the outcome of competitive coevolution. Even when there is relatively little variability within species, fitness maximization leads to an ESS rather than a CSS. A simple model is analyzed to show that ESS and CSS predictions about character displacement can differ qualitatively. Previous results of CSS analyses are discussed.     

一种复合神经元网络结构的并行动力学及快速学习算法

提出两种功能互相不同的神经细胞组成的复合神经元网络(CNN)模型;导出一种特殊结构的CNN的并行动力学;而且证明了它的稳定性。在这些结果基础上,得到快速的假逆矩阵学习算法。计算机仿真试验证实学习算法与动力学稳定性的正确性,并表现出良好的容错性能与存储容量。     

Mobilization of cloned luciferase genes into Vibrio harveyi luminescence mutants

A recombinant plasmid which carried a 5 kb fragment of Vibrio harveyi DNA containing the luxA and luxB genes was mobilized from Escherichia coli into luminescence-deficient mutants of V. harveyi. The cloned genes complemented a temperature sensitive luciferase mutation, but failed to complement lesions in two different aldehyde deficient mutants. Expression of the cloned genes was not subject to autoinduction in either E. coli or in V. harveyi.