A neural network based pattern recognition system for somatic embryos of Douglas fir

A pattern recognition system was developed to classify Douglas fir somatic embryos by employing an image analysis system and two neural network based classifiers. The contour of embryo images was segmented, digitalized and converted to numerical values after the discrete and fast Fourier transformation. These values, or Fourier features, along with some other shape factors, were used for embryo classification. The pattern recognition system used a hierarchical decision tree to classify Douglas fir embryos into three normal and one abnormal embryo classes. An accuracy of greater than 80% was achieved for normal embryos. This system provides an objective and efficient method of classifying embryos of Douglas fir. It will be a useful tool for kinetic studies and process optimization of conifer somatic embryogenesis.     

Glucose-induced period-doubling cascade in the electrical activity of pancreatic β-cells

 In the presence of stimulatory concentrations of glucose, the membrane potential of pancreatic β-cells may experience a transition from periods of rapid spike-like oscillations alternating with a pseudo-steady state to spike-only oscillations. Insulin secretion from β-cells closely correlates the periods of spike-like oscillations. The purpose of this paper is to study the mathematical structure which underlines this transitional stage in a pancreatic β-cell model. It is demonstrated that the transition can be chaotic but becomes more and more regular with increase in glucose. In particular, the system undergoes a reversed period-doubling cascade leading to the spike-only oscillations as the glucose concentration crosses a threshold. The transition interval in glucose concentration is estimated to be extremely small in terms of the rate of change for the calcium dynamics in the β-cells. The methods are based on the theory of unimodal maps and the geometric and asymptotic theories of singular perturbations. Received: 25 October 1996/Revised version: 18 August 1997     

ER stress is implicated in mitochondrial dysfunction-induced apoptosis of pancreatic beta cells

Mitochondrial dysfunction induces apoptosis of pancreatic β-cells and leads to type 2 diabetes, but the mechanism involved in this process remains unclear. Chronic endoplasmic reticulum (ER) stress plays a role in the apoptosis of pancreatic β-cells; therefore, in current study, we investigated the implication of ER stress in mitochondrial dysfunction-induced β-cells apoptosis. Metabolic stress induced by antimycin or oligomycin was used to impair mitochondrial function in MIN6N8 cells, which are mouse pancreatic β-cells. Impaired mitochondria dysfunction increased ER stress proteins such as p-eIF2α, GRP78 and GRP 94, as well as ER stress-associated apoptotic factor, CHOP, and activated JNK. AMP-activated protein kinase (AMPK) was also activated under mitochondria dysfunction by metabolic stress. However, the inhibition of AMPK by treatment with compound C, inhibitor of AMPK, and overexpression of mutant dominant negative AMPK (AMPKK45R) blocked the induction of ER stress, which was consist-ent with the decreased β-cell apoptosis and increase of insulin content. Furthermore, mitochondrial dysfunction increased the expression of the inducible nitric oxide synthase (iNOS) gene and the production of nitric oxide (NO), but NO production was prevented by compound C and mutant dominant negative AMPK (AMPK-K45R). Moreover, treatment with 1400W, which is an inhibitor of iNOS, prevented ER stress and apoptosis induced by mitochondrial dysfunction. Treatment of MIN6N8 cells with lipid mixture, physiological conditions of impaired mitochondria function, activated AMPK, increased NO production and induced ER stress. Collectively, these data demonstrate that mitochondrial dysfunction activates AMPK, which induces ER stress via NO production, resulting in pancreatic β-cells apoptosis.     

基于多尺度曲率植物叶片特征提取

基于B-样条小波计算边缘曲线多尺度曲率函数,根据多尺度信息筛选和定位超过一定曲率闲值的精角点,这样的点代表了边缘曲线的主要信息．文中使用了Canny边缘检测算子和数学形态学方法进行图像预处理,B-样条小波降低对噪声及扰动的灵敏性,以提高真实精角点定位水平．综合[1,2]给出新的角特征矢量,并生成角点特征序列CS和弧段特征序列SS．特征序列可作为自适应-时滞单元混合神经网络的输入,通过学习完成图像分类与识别,对基于植物叶片形状识别种类提供辅助。     

Application of competitive Hopfield neural network to brain-computer interface systems

We propose an unsupervised recognition system for single-trial classification of motor imagery (MI) electroencephalogram (EEG) data in this study. Competitive Hopfield neural network (CHNN) clustering is used for the discrimination of left and right MI EEG data posterior to selecting active segment and extracting fractal features in multi-scale. First, we use continuous wavelet transform (CWT) and Student's two-sample t-statistics to select the active segment in the time-frequency domain. The multiresolution fractal features are then extracted from wavelet data by means of modified fractal dimension. At last, CHNN clustering is adopted to recognize extracted features. Due to the characteristic of non-supervision, it is proper for CHNN to classify non-stationary EEG signals. The results indicate that CHNN achieves 81.9% in average classification accuracy in comparison with self-organizing map (SOM) and several popular supervised classifiers on six subjects from two data sets.     

Fast subsystem bifurcations in strongly coupled heterogeneous collections of excitable cells

A continuum model for a heterogeneous collection of excitable cells electrically coupled through gap junctions is introduced and analysed using spatial averaging, asymptotic and numerical techniques. Heterogeneity is modelled by imposing a spatial dependence on parameters which define the single cell model and a diffusion term is used to model the gap junction coupling. For different parameter values, single cell models can exhibit bursting, beating and a myriad of other complex oscillations. A procedure for finding asymptotic estimates of the thresholds between these (synchronous) behaviors in the cellular aggregates is described for the heterogeneous case where the coupling strength is strong. This procedure is tested on a model of a strongly coupled heterogeneous collection of bursting and beating cells. Since isolated pancreatic β-cells have been observed to both burst and beat, this test of the spatial averaging techniques provides a possible explanation to measured discrepancies between the electrical activities of isolated β-cells and coupled collections (islets) of β-cells. This work was supported by the National Science Foundation Grant DMS-97-04-966.     

A new approach for determination of Na,K-ATPase activity: application to intact pancreatic β-cells

It has been postulated that a decrease in Na,K-ATPase-mediated ion gradients may be a contributing mechanism to insulin secretion. However, the precise role of the Na,K-ATPase in pancreatic β-cell membrane depolarization and insulin secretion signalling have been difficult to evaluate, mostly because data reporting changes in enzymatic activity have been obtained in cell homogenates or membrane preparations, lacking intact intracellular signalling pathways. The aim of this work was to develop a method to characterize Na,K-ATPase activity in intact pancreatic β-cells that will allow the investigation of putative Na,K-ATPase activity regulation by glucose and its possible role in insulin secretion signalling. This work demonstrates for the first time that it is possible to determine Na,K-ATPase activity in intact pancreatic β-cells and that this is a suitable method for the study of the mechanisms involved in the Na,K-ATPase regulation and eventually its relevance for insulin secretion signalling.     

Visual shape representation with geometrically characterized contour partitions

This paper proposes a biologically plausible matching method to recognize general shapes based on contour curvature information. The human visual system recognizes general shapes flexibly in real-world scenes through the ventral pathway. The pathway is typically modeled using artificial neural networks. These network models, however, do not construct a shape representation that satisfies the following required constraints: (1) The original shape should be represented by a group of partitioned contours in order to retrieve the whole shape (global information) from the partial contours (local information). (2) Coarse and fine structures of the original shapes should be individually represented in order for the visual system to respond to shapes as quickly as possible based on the least number of their features, and to discriminate between shapes based on detailed information. (3) The shape recognition realized with an artificial visual system should be invariant to geometric transformation such as expansion, rotation, or shear. In this paper, we propose a visual shape representation with geometrically characterized contour partitions described on multiple spatial scales.     

Extracellular ATP and zinc are co-secreted with insulin and activate multiple P2X purinergic receptor channels expressed by islet beta-cells to potentiate insulin secretion

It is well established that ATP is co-secreted with insulin and zinc from pancreatic beta-cells (β-cells) in response to elevations in extracellular glucose concentration. Despite this knowledge, the physiological roles of extracellular secreted ATP and zinc are ill-defined. We hypothesized that secreted ATP and zinc are autocrine purinergic signaling molecules that activate P2X purinergic receptor (P2XR) channels expressed by β-cells to enhance glucose-stimulated insulin secretion (GSIS). To test this postulate, we performed ELISA assays for secreted insulin at fixed time points within a “real-time” assay and confirmed that the physiological insulin secretagogue glucose stimulates secretion of ATP and zinc into the extracellular milieu along with insulin from primary rat islets. Exogenous ATP and zinc alone or together also induced insulin secretion in this model system. Most importantly, the presence of an extracellular ATP scavenger, a zinc chelator, and P2 receptor antagonists attenuated GSIS. Furthermore, mRNA and protein were expressed in immortalized β-cells and primary islets for a unique subset of P2XR channel subtypes, P2X₂, P2X₃, P2X₄, and P2X₆, which are each gated by extracellular ATP and modulated positively by extracellular zinc. On the basis of these results, we propose that, within endocrine pancreatic islets, secreted ATP and zinc have profound autocrine regulatory influence on insulin secretion via ATP-gated and zinc-modulated P2XR channels.     

Electrical bursting and luminal calcium oscillation in excitable cell models

 It is shown in this paper that electrical bursting and the oscillations in the intracellular calcium concentration, [Ca²⁺]_i, observed in excitable cells such as pancreatic β-cells and R-15 cells of the mollusk Aplysia may be driven by a slow oscillation of the calcium concentration in the lumen of the endoplasmic reticulum, [Ca²⁺]_lum. This hypothesis follows from the inclusion of the dynamic changes of [Ca²⁺]_lum in the Chay bursting model. This extended model provides answers to some puzzling phenomena, such as why isolated single pancreatic β-cells burst with a low frequency while intact β-cells in an islet burst with a much higher frequency. Verification of the model prediction that [Ca²⁺]_lum is a primary oscillator which drives electrical bursting and [Ca²⁺]_i oscillations in these cells awaits experimental testing. Experiments using fluorescent dyes such as mag-fura-2-AM or aequorin could provide relevant information. Received: 17 August 1995/Accepted in revised form: 10 July 1996     

Effects of ethanol on pancreatic beta-cell death: interaction with glucose and fatty acids

Western lifestyle plays an important role in the prevalence of type 2 diabetes by causing insulin resistance and pancreatic β-cell dysfunction, a prerequisite for the development of diabetes. High fat diet and alcohol are major components of the western diet. The aim of the present study was to investigate the effects of ethanol and fatty acids on β-cell survival and metabolism. We treated the rat β-cell line RINm5F with ethanol, a mixture of palmitic and oleic acids, or both. Reactive oxygen species (ROS) were determined by (5-(and-6)-chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate) (CM-H2DCFDA) fluorescence assay, and mitochondrial activity was assessed by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide (MTT) reduction assay and by determining ATP production. Cell viability was assessed with a cell counter and trypan blue exclusion, and the mode of cell death by Hoechst33342 and propidium iodide staining. With both ethanol and fatty acid treatments, MTT reduction and ATP production decreased, whereas ROS production increased. Ethanol treatment had no effect on cell number, whereas fatty acid treatment reduced the cell number. Cell incubation with ethanol, fatty acids, or both increased the number of Hoechst 33342-positive nuclei. However, the majority of nuclei from fatty acid-treated cells were stained with propidium iodide, indicating a loss of plasma membrane integrity. We conclude that both ethanol and fatty acids generate cellular oxidative stress, and affect mitochondrial function in RINm5F β-cells. However, ethanol causes β-cell death by apoptosis, whereas fatty acids cause cell death predominantly by necrosis. It is not known whether these results are applicable to human β-cells.     

100% Classification Accuracy Considered Harmful: The Normalized Information Transfer Factor Explains the Accuracy Paradox

The most widely spread measure of performance, accuracy, suffers from a paradox: predictive models with a given level of accuracy may have greater predictive power than models with higher accuracy. Despite optimizing classification error rate, high accuracy models may fail to capture crucial information transfer in the classification task. We present evidence of this behavior by means of a combinatorial analysis where every possible contingency matrix of 2, 3 and 4 classes classifiers are depicted on the entropy triangle, a more reliable information-theoretic tool for classification assessment.Motivated by this, we develop from first principles a measure of classification performance that takes into consideration the information learned by classifiers. We are then able to obtain the entropy-modulated accuracy (EMA), a pessimistic estimate of the expected accuracy with the influence of the input distribution factored out, and the normalized information transfer factor (NIT), a measure of how efficient is the transmission of information from the input to the output set of classes.The EMA is a more natural measure of classification performance than accuracy when the heuristic to maximize is the transfer of information through the classifier instead of classification error count. The NIT factor measures the effectiveness of the learning process in classifiers and also makes it harder for them to “cheat” using techniques like specialization, while also promoting the interpretability of results. Their use is demonstrated in a mind reading task competition that aims at decoding the identity of a video stimulus based on magnetoencephalography recordings. We show how the EMA and the NIT factor reject rankings based in accuracy, choosing more meaningful and interpretable classifiers.     

Regulation of cAMP dynamics by Ca2+ and G protein-coupled receptors in the pancreatic -cell: a computational approach

In this report we describe a mathematical model for the regulation of cAMP dynamics in pancreatic β-cells. Incretin hormones such as glucagon-like peptide 1 (GLP-1) increase cAMP and augment insulin secretion in pancreatic β-cells. Imaging experiments performed in MIN6 insulinoma cells expressing a genetically encoded cAMP biosensor and loaded with fura-2, a calcium indicator, showed that cAMP oscillations are differentially regulated by periodic changes in membrane potential and GLP-1. We modeled the interplay of intracellular calcium (Ca²⁺) and its interaction with calmodulin, G protein-coupled receptor activation, adenylyl cyclases (AC), and phosphodiesterases (PDE). Simulations with the model demonstrate that cAMP oscillations are coupled to cytoplasmic Ca²⁺ oscillations in the β-cell. Slow Ca²⁺ oscillations (<1 min^–1) produce low-frequency cAMP oscillations, and faster Ca²⁺ oscillations (>3–4 min^–1) entrain high-frequency, low-amplitude cAMP oscillations. The model predicts that GLP-1 receptor agonists induce cAMP oscillations in phase with cytoplasmic Ca²⁺ oscillations. In contrast, observed antiphasic Ca²⁺ and cAMP oscillations can be simulated following combined glucose and tetraethylammonium-induced changes in membrane potential. The model provides additional evidence for a pivotal role for Ca²⁺-dependent AC and PDE activation in coupling of Ca²⁺ and cAMP signals. Our results reveal important differences in the effects of glucose/TEA and GLP-1 on cAMP dynamics in MIN6 β-cells. adenylyl cyclase; calcium ion; glucagon-like peptide 1; modeling; oscillations     

Selective Inhibition of Glucose-Stimulated β-Cell Activity by an Anion Channel Inhibitor

4,4′-dithiocyanatostilbene-2,2′-disulfonic acid (DIDS), an inhibitor of the volume-sensitive anion channel, was used to investigate the role of this channel in the stimulation of rat pancreatic β-cells by glucose and by tolbutamide. Glucose-stimulated electrical activity in β-cells was markedly and reversibly inhibited by DIDS. The increase in cytosolic [Ca²⁺] and stimulated insulin release evoked by glucose were also inhibited by DIDS. In contrast to its inhibitory effect on glucose-induced β-cell activity, DIDS had no effect on electrical activity, the rise in [Ca²⁺] _i or insulin release induced by tolbutamide. DIDS failed to increase β-cell input conductance, an index of whole-cell K _ATP channel activity, or the rate of efflux of ⁸⁶Rb⁺ from perifused islets, a measure of net K⁺ permeability. Furthermore, DIDS had no effect on intracellular pH or on regulatory volume increase following exposure of cells to hypertonic solutions, indicating that the effects of DIDS were not the result of inhibition of Cl⁻ transport systems. It is suggested that the DIDS-induced repolarization is caused by inactivation of the volume-sensitive anion channel. The stimulation of β-cell electrical and secretory activity by glucose, but not tolbutamide, may therefore involve activation of the anion channel. Received: 30 November 1999/Revised: 23 June 2000     

Visual shape recognition with contour propagation

A neural architecture is presented that encodes the visual space inside and outside of a shape. The contours of a shape are propagated across an excitable neuronal map and fed through a set of orientation columns, thus creating a pattern which can be viewed as a vector field. This vector field is then burned as synaptic, directional connections into a propagation map, which will serve as a “shape map”. The shape map identifies its own, preferred input when it is translated, deformed, scaled and fragmented, and discriminates other shapes very distinctively. Encoding visual space is much more efficient for shape recognition than determining contour geometry only.     

Expression of βA3/A1-crystallin in the developing and adult rat eye

Crystallins are very abundant structural proteins of the lens and are also expressed in other tissues. We have previously reported a spontaneous mutation in the rat βA3/A1-crystallin gene, termed Nuc1, which has a novel, complex, ocular phenotype. The current study was undertaken to compare the expression pattern of this gene during eye development in wild type and Nuc1 rats by in situ hybridization (ISH) and immunohistochemistry (IHC). βA3/A1-crystallin expression was first detected in the eyes of both wild type and Nuc1 rats at embryonic (E) day 12.5 in the posterior portion of the lens vesicle, and remained limited to the lens fibers throughout fetal life. After birth, βA3/A1-crystallin expression was also detected in the neural retina (specifically in the astrocytes and ganglion cells) and in the retinal pigmented epithelium (RPE). This suggested that βA3/A1-crystallin is not only a structural protein of the lens, but has cellular function(s) in other ocular tissues. In summary, expression of βA3/A1-crystallin is controlled differentially in various eye tissues with lens being the site of greatest expression. Similar staining patterns, detected by ISH and IHC, in wild type and Nuc1 animals suggest that functional differences in the protein, rather than changes in mRNA/protein level of expression, likely account for developmental abnormalities in Nuc1.     

Endoplasmic reticulum stress response in an INS-1 pancreatic β-cell line with inducible expression of a folding-deficient proinsulin

Background  

Cells respond to endoplasmic reticulum stress (ER) stress by activating the unfolded protein response. To study the ER stress response in pancreatic β-cells we developed a model system that allows for pathophysiological ER stress based on the Akita mouse. This mouse strain expresses a mutant insulin 2 gene (C96Y), which prevents normal proinsulin folding causing ER stress and eventual β-cell apoptosis. A double-stable pancreatic β-cell line (pTet-ON INS-1) with inducible expression of insulin 2 (C96Y) fused to EGFP was generated to study the ER stress response.     

Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures

 In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of the new measures. The accuracy of the classification was significantly worse, however, when supplied with these variables alone. In view of results demonstrating the efficiency of nonconventional measures in EEG analysis, the benefit appears to depend on the nature of the problem. Received: 10 October 2000 / Accepted in revised form: 26 April 2001