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.     

Reinforcement and learning

Evidence has been accumulating to support the process of reinforcement as a potential mechanism in speciation. In many species, mate choice decisions are influenced by cultural factors, including learned mating preferences (sexual imprinting) or learned mate attraction signals (e.g., bird song). It has been postulated that learning can have a strong impact on the likelihood of speciation and perhaps on the process of reinforcement, but no models have explicitly considered learning in a reinforcement context. We review the evidence that suggests that learning may be involved in speciation and reinforcement, and present a model of reinforcement via learned preferences. We show that not only can reinforcement occur when preferences are learned by imprinting, but that such preferences can maintain species differences easily in comparison with both autosomal and sex-linked genetically inherited preferences. We highlight the need for more explicit study of the connection between the behavioral process of learning and the evolutionary process of reinforcement in natural systems.     

Autism-Misregulated eIF4G Microexons Control Synaptic Translation and Higher Order Cognitive Functions

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Seasonal variation of serotonin content and nonassociative learning of swim induction in the leech Hirudo medicinalis

Summary It is possible to obtain habituation of swim induction by stimulating the leech with repetitive light electrical trains. After obtaining this simple form of nonassociative learning, it is also possible to potentiate its response by a series of nociceptive skin brushings (dishabituation). Serotonin applied to the animal is the only neurotransmitter found to mimick dishabituation. We have observed that in the period April–June most animals did not exhibit potentiation of the swimming response after nociceptive stimulation while injection of serotonin mimicked dishabituation as in the animals treated in the period October–March. We have seen correlation between the changes in nonassociative learning and the seasonal variation of serotonin levels in segmental ganglia. This finding strengthens the hypothesis of serotonin as the neurotransmitter mediating dishabituation in swim induction of the leech.Abbreviations AHP afterhyperpolarization - HPLC high pressure liquid chromatography     

Asymmetric incorporation of [14C]cyanate and of fluorescein isothiocyanate in mamillary body of conditioned rats

A marked decrease in overall learning capacity has been observed in rats injected with cyanate. Therefore it was of interest to test whether learning influenced carbamylation of brain proteins. Incorporation of [¹⁴C]cyanate into proteins of the mamillary body was selectively modified following operant conditioning of the rat, so that trained rats showed an asymmetric image with higher levels of incorporation in the right side than in the left side, as compared to control rats. These results were confirmed using fluorescein isothiocyanate. The asymmetry persisted once the learning had been well established.     

Effects of lesion of the inferior olivary complex by 3-acetylpyridine on learning and memory in the rat

Summary DA/HAN-strained male rats (pigmented rats) were submitted to two experimental tasks consisting of spatial learning (water-escape) and a passive avoidance conditioning. Both these tasks were performed by different animals. In order to destroy the inferior olivary complex, the animals were injected with 3-acetylpyridine either 9 days prior to the initial learning session or 24 h after completion of the learning task. They were retested (retrieval test) 10 days after the initial learning was achieved. Learning and retention were compared to those noted in control rats. Administration of 3-acetylpyridine before the initial learning did not prevent the spatial learning but the scores were greatly altered and the number of trials needed to reach the fixed learning criterion was much greater than in controls. However, 10 days later the animals had memorized their initial experience. Injection of 3-acetylpyridine after the initial learning session impaired memory: the animals had completely forgotten their initial learning. It can therefore be concluded that lesion of the afferent climbing fibres to the cerebellar cortex alters learning and retention of a spatial task. Such a lesion does not interfere with learning and retention of a passive avoidance conditioning, since in this condition the experimental animals injected with 3-acetylpyridine either before or after the initial learning behave similarly to controls. The effects of the inferior olivary complex lesion are obviously different according to the task to be learnt, suggesting that these two tasks do not require the integrity of the same nervous structures.Abbreviations 3-AP 3-acetylpyridine - C control - ILR initial learning-lesion-retrieval - IOC inferior olivary complex - LIR lesion-initial learning-retrieval     

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。