Organogenesis of the juxta-oral organ in mice.

The juxta-oral organ is a bilateral organ in the mammalian bucca. It consists of epithelial cords with surrounding mesenchyme. It develops from embryonic oral epithelium, but its macroscopic morphology in mice is less studied and seems to be very different from that of humans. The juxta-oral organ in mice extends more widely from the subcutaneous tissue of the mandible near the lateral fascia of the masseter to the submucosa of the soft palate. In this paper, we report that the mutant mouse allele Bmp7(lacZ) presented intense lacZ expression in the epithelial component of the juxta-oral organ in its homo- and heterozygous states. The main aims of this study were to show that this mutant mouse allele is suitable for observing macroscopic structure of the juxta-oral organ and to describe the development of this organ during embryonic and postnatal stages. Whole-mount beta-gal staining of this strain of mouse showed that the juxta-oral organ in mice appeared at E12.0 from oral epithelium and lost connection with it before E12.5. Then, the juxta-oral organ extended anteriorly to the lateral fascia of the masseter and posteriorly to the submucosal layer of the soft palate via the orbit. The mature juxta-oral organ had no connection to other epithelia such as those of the bucca and parotid duct. It persisted until adulthood and there seemed to be no tendency to regress. Transmission electron microscopy showed that each part of the juxta-oral organ was an epithelial cord surrounded by a basement membrane and mesenchymal tissue.

Learning of spatiotemporal patterns in Ising-spin neural networks: analysis of storage capacity by path integral methods.

We encode periodic spatiotemporal patterns in Ising-spin neural networks, using the simple learning rule inspired by the spike-timing-dependent synaptic plasticity. It is then found that periodically oscillating spin neurons successfully reproduce phase differences of the encoded periodic patterns. The storage capacity of this associative memory neural network is enhanced with an adequate level of asymmetry in synapse connections. To understand the properties of these nonequilibrium retrieval states of the neural network, we carry out an analysis based on a path integral method. The relation of a dynamic crosstalk term to time-persistent oscillation of a correlation function well explains the enhancement of the storage capacity in spite of our approximation on nonpersistent terms. We investigate the accuracy of this approximation further by detailed comparison with numerical simulations.

Culture of porcine fetal pancreatic neurons.

OBJECTIVES: Pancreatic neurons have not been cultured commonly. Cultured neurons can be continuously observed, and their external environment is easy to be controlled. We report here a simple method for separating and cultivating neuronal cells from pancreas. METHODS: Pancreata of fetal swine were digested with collagenase. Clusters were collected with a sieve and digested with trypsin. Digested clusters were collected and cultured in Dulbecco modified Eagle medium containing serum and basic fibroblast growth factor. Cultured cells were investigated morphologically. RESULTS: Cultured cells formed spiderweblike colonies. These cells were distinguished into Schwann cells and 2 types of neurons. The neurons were positive on immunocytochemical staining with antigrowth-associated protein-43 and cytochemical staining for cholinesterase. One type of neuron was located in the central cluster and had very long processes extending radially. The other type of neuron was sparsely scattered, had long processes, and was connected to other neurons. The neurotransmitter of these neurons was concluded to be acetylcholine. CONCLUSIONS: Using our method, neuronal cells were readily cultured from pancreatic tissue. These cells will be useful in elucidating the physiology and pharmacology of pancreatic neurons.

Spatiotemporal learning in analog neural networks using spike-timing-dependent synaptic plasticity.

Incorporating the spike-timing-dependent synaptic plasticity (STDP) into a learning rule, we study spatiotemporal learning in analog neural networks. First, we study learning of a finite number of periodic spatiotemporal patterns by deriving the dynamics of the order parameters. When a pattern is retrieved successfully, the order parameters exhibit periodic oscillation. Analyzing this oscillation of the order parameters, we elucidate the relation of the STDP time window to the properties of the retrieval state; the phase of the Fourier transform of the STDP time window determines the retrieval frequency and the time average of the STDP time window crucially affects the storage capacity. We also evaluate the stability of the order parameter oscillation and identify the retrieval state that is stable in single-pattern learning but unstable in multiple-pattern learning even when the retrieval state is independent of a pattern number. To examine the further applicability of the STDP-based learning rule, we also study learning of nonperiodic spatiotemporal Poisson patterns. Our numerical simulations demonstrate that the Poisson patterns are memorized successfully not only in analog neural networks but also in spiking neural networks.

A matrix metalloproteinase inhibitor, ONO-4817, suppresses the development of aortic intimal hyperplasia in experimental hyperlipidemic rabbit.

Inhibition of matrix metalloproteinases (MMPs) would be expected to suppress atherosclerotic neointimal proliferation and thus limit atheromatous plaque progression, but this has not yet been demonstrated morphologically in atherosclerotic intimal hyperplasia induced by cholesterol loading in experimental animals. We therefore investigated whether a broad-spectrum MMP inhibitor (MMPi), ONO-4817, could inhibit the development of intimal hyperplasia in male hyperlipidemic rabbits (n = 6) fed laboratory chow supplemented with 1% cholesterol for 2 months followed by a 1% cholesterol diet plus 100 mg/kg ONO-4817 for another month (Chol + ONO group). Control animals (n = 6) received no ONO-4817. When the aortas were studied both histologically and immunohistochemically, intimal hyperplasia was inhibited in Chol + ONO rabbits. The distribution of macrophages and MMP-12 in the hyperplastic tissue of the Chol + ONO rabbits was limited to the luminal side of the lesions. No such limitation in the distribution of macrophages and MMP-12 was observed in the control group. The distribution of smooth muscle cells in the hyperplastic tissue was not different between the Chol + ONO and control groups. However, the distribution of MMP-2 and MMP-12 was limited to the luminal side of lesions in the Chol + ONO group. This is the first reported evidence that an MMPi can suppress the development of intimal hyperplasia in hyperlipidemic rabbits.

Histogenesis of the intravitreal membrane and secondary vitreous in the mouse.

PURPOSE: The intravitreal membrane (IVM) is a membranous structure between the primary and secondary vitreous bodies in developing mammalian eyes. In this study, for the first time the histogenesis of the IVM and the relationship between the hyaloid vasculature and the IVM was characterized in newborn mice. METHODS: Eyes of mice less than 12 days old were fixed and embedded. From these, serial paraffin-embedded sections were made for lectin histochemistry, immunohistochemistry, and picrosirius red (PSR) staining, and ultrathin sections were made for transmission electron microscopy (TEM). Eight biotinylated lectins and antibodies for laminin and type IV collagen were used. RESULTS: Among the eight lectins tested, concanavalin A (Con A) agglutinin, Ricinus communis agglutinin I, and wheat germ agglutinin demonstrated strong positive staining in the IVM and vitreous fibrils of the primary and secondary vitreous bodies. They also bound to the internal limiting membrane (ILM) of the retina. At postgestational day 4, the secondary vitreous first appeared between the ILM and the vasa hyaloidea propria (VHP). Immunohistochemical staining revealed that the IVM consists of extracellular matrix components including laminin and type IV collagen, whereas PSR staining and TEM showed that collagen fibrils in the IVM are bundled and continuous with the basement membrane of hyaloid capillaries or the VHP. CONCLUSIONS: Lectin histochemistry and immunohistochemistry provided good methods for visualizing the structures of the IVM and vitreous fibrils. These results suggest that the IVM is separated from the basement membrane of the retinal ILM along with the vascular network of the VHP when the secondary vitreous begins to form.

Cluster synchronization in an ensemble of neurons interacting through chemical synapses.

In networks of periodically firing spiking neurons that are interconnected with chemical synapses, we analyze a cluster state, where an ensemble of neurons are subdivided into a few clusters, in each of which neurons exhibit perfect synchronization. To clarify stability of the cluster state, we decompose linear stability of the solution into two types of stabilities, stability of a mean state and stabilities of clusters. Computing Floquet matrices for these stabilities, we clarify the total stability of the cluster state for any type of neuron and any strength of interaction even if the size of networks is infinitely large. First, we apply this stability analysis to investigating synchronization in the large ensemble of integrate-and-fire (IF) neurons. In one-cluster state we find the change of stability of a cluster, which elucidates that in-phase synchronization of IF neurons occurs with only inhibitory synapses. Then, we investigate entrainment of two clusters of IF neurons with different excitability. IF neurons with fast decaying synapses show low entrainment capability, which is explained by a pitchfork bifurcation appearing in the two-cluster state with change of synapse decay time constant. Second, we analyze a one-cluster state of Hodgkin-Huxley (HH) neurons and discuss the difference in synchronization properties between IF neurons and HH neurons.

Chaos synchronization in gap-junction-coupled neurons.

Depending on temperature, the modified Hodgkin-Huxley (MHH) equations exhibit a variety of dynamical behaviors, including intrinsic chaotic firing. We analyze synchronization in a large ensemble of MHH neurons that are interconnected with gap junctions. By evaluating tangential Lyapunov exponents we clarify whether the synchronous state of neurons is chaotic or periodic. Then, we evaluate transversal Lyapunov exponents to elucidate if this synchronous state is stable against infinitesimal perturbations. Our analysis elucidates that with weak gap junctions, the stability of the synchronization of MHH neurons shows rather complicated changes with temperature. We, however, find that with strong gap junctions, the synchronous state is stable over the wide range of temperature irrespective of whether synchronous state is chaotic or periodic. It turns out that strong gap junctions realize the robust synchronization mechanism, which well explains synchronization in interneurons in the real nervous system.

Prolonged Ca2+ transients in ATP-stimulated endothelial cells exposed to 50 Hz electric fields.

Human umbilical vein endothelial cells were exposed to sinusoidal electric fields of 0.3 or 30 kV/m, 50 Hz, for 24 h. Changes in intracellular calcium concentration ([Ca(2+)](i)) induced by ATP-stimulation in the absence of extracellular Ca(2+) were observed in individual cells. No differences were observed between the exposure and sham-exposure groups in [Ca(2+)](i) resting level before ATP-stimulation, or in the [Ca(2+)](i) peak levels induced by stimulation. However, the duration of the initial transients in [Ca(2+)](i) following an ATP stimulus was significantly prolonged by exposure to a 30 kV/m field. The inositol trisphosphate receptor inhibitor, xestospongin C, inhibited the ATP-induced elevation in [Ca(2+)](i) in both the exposure and sham-exposure groups. The ATP-receptor P2Y appeared to play an important role in the increase of [Ca(2+)](i). The present results suggest that an extremely low-frequency electric field affects the function of vascular endothelial cells by a mechanism involving activation of P2Y.

[Unique structure of the esophago-gastric junction of the house musk shrew (Suncus murinus)].

The house musk shrew (Suncus murinus) belongs to the Order Insectivora, and has been used for the research in comparative anatomy as one of the most primitive placental mammals. Another feature of this shrew is its ability to easily vomit which mimics the human emesis or motion sickness response. The house musk shrew has thus been utilized as a rare small experimental animal for studies on the neurophysiological mechanism of vomiting. However, there is no report investigating the morphological background of vomiting in this species. The purpose of this study is to provide detailed morphological and histological features of the house musk shrew stomach as they possibly correlate to vomiting. The stomachs of ten female house musk shrews were used. Six of them were the wild type (Jic: SUN), two were the high-emesis strain (Jic: SUN-Her) and the rest of them were the low-emesis strain (Jic: Sun-Ler). In addition to the macroscopic anatomy, the region of esophago-gastric (EG) junction and the gastric groove were observed using the light and transmission electron microscopy. Although evident differences in structure of stomach were not found among the three strains, some interesting findings in comparative anatomy were noted. The circular valve-like thick fold was seen at the cardiac portion, which protruded into the esophageal lumen forming a deep groove between its frilled edge and the esophagus. The second frilled ridge was often found as inner ridge of this valve-like thick fold. The esophago-gastric junction between the stratified squamous and the simple columnar epithelium was found at the edge of the second frilled ridge. The lamina propria of the frilled edge was occupied by loose connective tissue and many large lumens of lymphatic vessels. The lamina muscularis mucosae, which developed in the esophageal region, was not in the main frilled edge. A well-developed inner muscle layer was found around the base of the fold, which seemed to correspond to the human lower esophageal sphincter. Cardiac glands occupied most of the thick cardiac wall, forming complicated crypts lined by simple columnar epithelium, and ducts of cardiac gland opened to these crypts. Since the house musk shrew has no esophageal gland, these cardiac glands may actively protect the lower part of the esophagus. In the cardiac wall, the inner circular and outer longitudinal muscle layer largely crossed each other obliquely as same as other reports. The transition area from the striated to the smooth muscle was observed in the sphincter surrounding the distal end of the cardiac wall. The gastric groove, lined by simple columnar epithelium in the lesser curvature, which has been reported to play a role as a shortcut from the cardia to the pylorus in other species including rodents, was also confirmed in the house musk shrew. The mucosal fold in the boundary between the esophageal and the gastric epithelium of house musk shrew may correspond to the structure called the limiting ridge (in mouse, rat and hamster), the teeth-like fimbria or Grenzfalten (in vole), and the gastric teeth (in crustacean and mollusk). The valve-like mucosal fold protruding into the esophageal cavity, the well developed huge cardiac glands, and the cardiac sphincter localized distally to the cardiac gland appear to facilitate the regurgitation of the stomach content, that is, vomiting. These findings suggest that this structure might have developed to support the feeding habit of house musk shrew, and that the differences of strains in vomiting may be determined by neurophysiological mechanisms.

Spike-timing-dependent learning rule to encode spatiotemporal patterns in a network of spiking neurons.

We study associative memory neural networks based on the Hodgkin-Huxley type of spiking neurons. We introduce the spike-timing-dependent learning rule, in which the time window with the negative part as well as the positive part is used to describe the biologically plausible synaptic plasticity. The learning rule is applied to encode a number of periodical spatiotemporal patterns, which are successfully reproduced in the periodical firing pattern of spiking neurons in the process of memory retrieval. The global inhibition is incorporated into the model so as to induce the gamma oscillation. The occurrence of gamma oscillation turns out to give appropriate spike timings for memory retrieval of discrete type of spatiotemporal pattern. The theoretical analysis to elucidate the stationary properties of perfect retrieval state is conducted in the limit of an infinite number of neurons and shows the good agreement with the result of numerical simulations. The result of this analysis indicates that the presence of the negative and positive parts in the form of the time window contributes to reduce the size of crosstalk term, implying that the time window with the negative and positive parts is suitable to encode a number of spatiotemporal patterns. We draw some phase diagrams, in which we find various types of phase transitions with change of the intensity of global inhibition.

Linear stability analysis of retrieval state in associative memory neural networks of spiking neurons.

We study associative memory neural networks of the Hodgkin-Huxley type of spiking neurons in which multiple periodic spatiotemporal patterns of spike timing are memorized as limit-cycle-type attractors. In encoding the spatiotemporal patterns, we assume the spike-timing-dependent synaptic plasticity with the asymmetric time window. Analysis for periodic solution of retrieval state reveals that if the area of the negative part of the time window is equivalent to the positive part, then crosstalk among encoded patterns vanishes. Phase transition due to the loss of the stability of periodic solution is observed when we assume fast function for direct interaction among neurons. In order to evaluate the critical point of this phase transition, we employ Floquet theory in which the stability problem of the infinite number of spiking neurons interacting with function is reduced to the eigenvalue problem with the finite size of matrix. Numerical integration of the single-body dynamics yields the explicit value of the matrix, which enables us to determine the critical point of the phase transition with a high degree of precision.