전체 | 과거현황 (2017년 이전) | 논문

383

Theoretical model for neurovascular coupling via interactions of NO, EET, and 20-HETE

Hyuk Kang (Jung-Min Lee, Misun Kim, Dong-Uk Hwang) | BMC Neuroscience 14 (2013)

초록

All neurons in the brain need the energy sources such as glucose and oxygen for their functions such as recognition, decision, and behavior regulation. Those energy sources are supplied directly from the capillary around the neuron, or are transported indirectly via the astrocyte. Especially, since more activated neuron consumes more energy sources, the neuron elevates intakes of glucose and oxygen via increasing the blood flow of vessels around itself. Therefore, the blood flow in the brain is important medically, and is one of major parameters in measurement of the brain activity such as functional magnetic resonance image (fMRI) and Near-infrared Spectroscopy (NIRS).

In many experiments, it has been discovered that neuron and astrocyte regulates the brain blood flow via the generated vasoactive agents from them [1]. Usually, vasoactive agents are directly generated from the activating neuron, or are produced indirectly from the stimulated astrocyte by the released neurotransmitter from the neuron. Those vasoactive agents dilate or contract the blood vessel via action on its smooth muscle cells, and there are several kinds of them: NO, EET, prostaglandin, 20-HETE, and so on. But vasoactive agents have no additive effect [2]. For example, although NO inhibitor is added to the blood with EET inhibitor, the inhibition effect shows no increase [3]. In addition, NO sometimes inhibits the effects of EET or 20-HETE [1, 4]. Therefore, the temporal or spatial roles for functional hyperemia by vasoactive agents, neuron and astrocyte become an object of attention, and, if interactions and equivalence between dilation and contraction materials are known in their system, it provides the information about the detailed neurovascular modulation.

As previously described, although the mathematical model should importantly consider the coupled effect of vasoactive agents, present modeling studies have been represented via independent interaction between vasoactive agent and vessel. Therefore, we propose the multi-compartment mathematical model, which consists of postsynaptic neuron, astrocyte, and smooth muscle cell of vessel. It is described by the following sequence: 1) the activated presynaptic neuron triggers glutamate release, 2) the glutamate binds to the metabotropic receptor of astrocyte or NMDA receptor of postsynaptic neuron, 3) the bounded glutamate increases the calcium concentration in both astrocyte and neuron, 4) the calcium concentration increase creates arachidonic acid in astrocyte and NO in neuron, 5) the arachidonic acid is metabolized to transform EET or 20-HETE, which are inhibited partly by NO, 6) EET increase the K+ channel conductance of smooth muscle cell (SMC), 7) 20-HETE decreases the K+ channel conductance of SMC, 8) SMC is hyperpolarized via the outward K+ influx, 9) voltage-dependent Ca2+ channel of SMC is d, and Ca2+ concentration decreases, 10) the contraction force of SMC decreases, so that vessel dilates. From the mathematical model, we obtain the simulation results for the direct effect of neuronal derived NO, the inhibition of 20-HETE (vasoconstriction agent) by NO, the interaction of EET (astrocyte derived vasodilation agent), and their corresponding vessel response, as an expansion of the EET generation model in Bennet's study [5].

초록

All neurons in the brain need the energy sources such as glucose and oxygen for their functions such as recognition, decision, and behavior regulation. Those energy sources are supplied directly from the capillary around the neuron, or are transported indirectly via the astrocyte. Especially, since more activated neuron consumes more energy sources, the neuron elevates intakes of glucose and oxygen via increasing the blood flow of vessels around itself. Therefore, the blood flow in the brain is important medically, and is one of major parameters in measurement of the brain activity such as functional magnetic resonance image (fMRI) and Near-infrared Spectroscopy (NIRS).

In many experiments, it has been discovered that neuron and astrocyte regulates the brain blood flow via the generated vasoactive agents from them [1]. Usually, vasoactive agents are directly generated from the activating neuron, or are produced indirectly from the stimulated astrocyte by the released neurotransmitter from the neuron. Those vasoactive agents dilate or contract the blood vessel via action on its smooth muscle cells, and there are several kinds of them: NO, EET, prostaglandin, 20-HETE, and so on. But vasoactive agents have no additive effect [2]. For example, although NO inhibitor is added to the blood with EET inhibitor, the inhibition effect shows no increase [3]. In addition, NO sometimes inhibits the effects of EET or 20-HETE [1, 4]. Therefore, the temporal or spatial roles for functional hyperemia by vasoactive agents, neuron and astrocyte become an object of attention, and, if interactions and equivalence between dilation and contraction materials are known in their system, it provides the information about the detailed neurovascular modulation.

As previously described, although the mathematical model should importantly consider the coupled effect of vasoactive agents, present modeling studies have been represented via independent interaction between vasoactive agent and vessel. Therefore, we propose the multi-compartment mathematical model, which consists of postsynaptic neuron, astrocyte, and smooth muscle cell of vessel. It is described by the following sequence: 1) the activated presynaptic neuron triggers glutamate release, 2) the glutamate binds to the metabotropic receptor of astrocyte or NMDA receptor of postsynaptic neuron, 3) the bounded glutamate increases the calcium concentration in both astrocyte and neuron, 4) the calcium concentration increase creates arachidonic acid in astrocyte and NO in neuron, 5) the arachidonic acid is metabolized to transform EET or 20-HETE, which are inhibited partly by NO, 6) EET increase the K+ channel conductance of smooth muscle cell (SMC), 7) 20-HETE decreases the K+ channel conductance of SMC, 8) SMC is hyperpolarized via the outward K+ influx, 9) voltage-dependent Ca2+ channel of SMC is d, and Ca2+ concentration decreases, 10) the contraction force of SMC decreases, so that vessel dilates. From the mathematical model, we obtain the simulation results for the direct effect of neuronal derived NO, the inhibition of 20-HETE (vasoconstriction agent) by NO, the interaction of EET (astrocyte derived vasodilation agent), and their corresponding vessel response, as an expansion of the EET generation model in Bennet's study [5].

382

Effects of environmental features on flocking behavior

Sang-Hee Lee | Journal of Asia-Pacific Entomology 16 (2013)

381

Measurement of the time required for termites to pass each other in tunnels of different curvatures

Seungwoo Sim , SangHee Lee | Insect Science 20 (2013)

초록

Subterranean termites construct complex tunnel networks for foraging. During travel in the tunnels, termites often encounter one another when passing in opposite directions. Such encounters are likely to affect the “ment efficiency,” which is the time required for a termite to travel a certain distance in a tunnel. In this study, we explored how individual–individual encounters affect ment efficiency in tunnels by measuring the time (τ) taken by two termites to pass one another in tunnels of different curvatures. Artificial tunnels of 5 cm in length and variable widths (W) of 2, 3, or 4 mm were made. Tunnel distance (D) was 2, 3, 4, or 5 cm. When D had a higher value, curvature was lower. When W = 2, τ was significantly shorter in the tunnel with D = 5 than in tunnels of D = 2, 3, or 4, whereas τ was statistically the same for D = 2, 3 and 4. When W = 3, τ was shorter in the tunnel with D = 5 than for D = 3 and 4, while τ was longer in the tunnel with D = 2 than for D = 3 and 4. When W = 4, τ was longer in the tunnels with D = 2 and 3 than for D = 4 and 5. Based on these observations, 3 types of termite behavior were identified: biased walking, backward walking, and zigzag walking. We considered these results in relation to foraging efficiency.

초록

Subterranean termites construct complex tunnel networks for foraging. During travel in the tunnels, termites often encounter one another when passing in opposite directions. Such encounters are likely to affect the “ment efficiency,” which is the time required for a termite to travel a certain distance in a tunnel. In this study, we explored how individual–individual encounters affect ment efficiency in tunnels by measuring the time (τ) taken by two termites to pass one another in tunnels of different curvatures. Artificial tunnels of 5 cm in length and variable widths (W) of 2, 3, or 4 mm were made. Tunnel distance (D) was 2, 3, 4, or 5 cm. When D had a higher value, curvature was lower. When W = 2, τ was significantly shorter in the tunnel with D = 5 than in tunnels of D = 2, 3, or 4, whereas τ was statistically the same for D = 2, 3 and 4. When W = 3, τ was shorter in the tunnel with D = 5 than for D = 3 and 4, while τ was longer in the tunnel with D = 2 than for D = 3 and 4. When W = 4, τ was longer in the tunnels with D = 2 and 3 than for D = 4 and 5. Based on these observations, 3 types of termite behavior were identified: biased walking, backward walking, and zigzag walking. We considered these results in relation to foraging efficiency.

380

Movement efficiency and behavior of termites in tunnels with varying pore sizes

Sook Junk Ku (Nan-Yao Su and Sang-Hee Lee) | Florida Entomologist 96 (2013)

초록

Subterranean termites (Isoptera) build tunnel networks to obtain food resources and nesting space. When tunneling, termites encounter spatial heterogeneity, such as differing soil pore space and moisture levels. This heterogeneity creates 2 types of irregularities in the tunnel surface: (1) a bumpy tunnel-wall structure caused by variable soil texture; and (2) hollow space within the tunnel, where tunnels pass through soil pores. We previously explored the response of termites to bumpy tunnel structure. In the present study, we investigated termite behavior in response to differing volumes of soil pore space. This response behavior is closely related to ment efficiency. We designed 8-cm-long artificial tunnels with hollow spaces in a 2-dimensional arena. The hollow spaces were represented as circular holes with varying diameters D (2, 3, 4, 6, 8, or 10 mm), positioned at the center of the tunnel. Tunnel widths, W, were 2 and 3 mm. We systematically observed the ment of termites (Reticulitermes speratus kyushuensis Morimoto) at the hole, and measured the time required (τ) for termites to pass through the tunnels. Time τ was shorter for tunnels with holes between 2 and 6 mm diameter than for those with holes of 8 or 10 mm diameter, for tunnels of both widths. Time τ was significantly different between (W, D) = (2, 10) and (3, 10). These results were explained by 3 types of behaviors. The implications of these findings are briefly discussed in relation to termite foraging efficiency. Las termitas subterráneas construyen redes de túneles para obtener recursos alimentarios y espacio para sus nidos. Cuando hacen los túneles, las termitas se encuentran con la heterogeneidad espacial, como diferentes espacios de poros en el suelo y el nivel de humedad. Esta heterogeneidad crea 2 tipos de irregularidades en la superficie del túnel: (1) una estructura del túnel con baches en los paredes causada por la textura del suelo variable y (2) espacios huecos dentro del túnel, donde los túneles pasan a través de los poros del suelo. Anteriormente, se estudió la respuesta de las termitas a las estructuras de túneles llenos de baches. En el presente estudio, se investigó el comportamiento de las termitas en respuesta a diferentes volúmenes de espacio de los poros del suelo. Este comportamiento de respuesta está estrechamente relacionado con la eficiencia del movimiento. Hemos diseñado túneles artificiales de 8 cm de largo con espacios huecos en una arena de 2 dimensiones. Los espacios huecos se representan como agujeros circulares con el diámetro D (2, 3, 4, 6, 8, o 10 mm), puestos en el centro del túnel. La anchura de túnel, W, fue de 2 y 3 mm. Se observó sistemáticamente el movimiento de las termitas (Reticulitermes speratus kyushuensis Morimoto; Rhinotermitidae) en las aperaturas, y se midió el tiempo requerido (τ) para que las termitas pasaran a través de los túneles. El tiempo, τ, fue más corto en los túneles con aperaturas entre 2 y 6 mm de diámetro que para los que tienen aperaturas de 8 o 10 mm de diámetro, para los túneles de ambos anchos. El tiempo, τ, fue significativamente diferente entre (W, D) = (2, 10) y (3, 10). Estos resultados son explicados por 3 clases de comportamiento. Se discuten brevemente las implicaciones de estos hallazgos en relación con la eficiencia de forrajeo de las termitas.

초록

Subterranean termites (Isoptera) build tunnel networks to obtain food resources and nesting space. When tunneling, termites encounter spatial heterogeneity, such as differing soil pore space and moisture levels. This heterogeneity creates 2 types of irregularities in the tunnel surface: (1) a bumpy tunnel-wall structure caused by variable soil texture; and (2) hollow space within the tunnel, where tunnels pass through soil pores. We previously explored the response of termites to bumpy tunnel structure. In the present study, we investigated termite behavior in response to differing volumes of soil pore space. This response behavior is closely related to ment efficiency. We designed 8-cm-long artificial tunnels with hollow spaces in a 2-dimensional arena. The hollow spaces were represented as circular holes with varying diameters D (2, 3, 4, 6, 8, or 10 mm), positioned at the center of the tunnel. Tunnel widths, W, were 2 and 3 mm. We systematically observed the ment of termites (Reticulitermes speratus kyushuensis Morimoto) at the hole, and measured the time required (τ) for termites to pass through the tunnels. Time τ was shorter for tunnels with holes between 2 and 6 mm diameter than for those with holes of 8 or 10 mm diameter, for tunnels of both widths. Time τ was significantly different between (W, D) = (2, 10) and (3, 10). These results were explained by 3 types of behaviors. The implications of these findings are briefly discussed in relation to termite foraging efficiency. Las termitas subterráneas construyen redes de túneles para obtener recursos alimentarios y espacio para sus nidos. Cuando hacen los túneles, las termitas se encuentran con la heterogeneidad espacial, como diferentes espacios de poros en el suelo y el nivel de humedad. Esta heterogeneidad crea 2 tipos de irregularidades en la superficie del túnel: (1) una estructura del túnel con baches en los paredes causada por la textura del suelo variable y (2) espacios huecos dentro del túnel, donde los túneles pasan a través de los poros del suelo. Anteriormente, se estudió la respuesta de las termitas a las estructuras de túneles llenos de baches. En el presente estudio, se investigó el comportamiento de las termitas en respuesta a diferentes volúmenes de espacio de los poros del suelo. Este comportamiento de respuesta está estrechamente relacionado con la eficiencia del movimiento. Hemos diseñado túneles artificiales de 8 cm de largo con espacios huecos en una arena de 2 dimensiones. Los espacios huecos se representan como agujeros circulares con el diámetro D (2, 3, 4, 6, 8, o 10 mm), puestos en el centro del túnel. La anchura de túnel, W, fue de 2 y 3 mm. Se observó sistemáticamente el movimiento de las termitas (Reticulitermes speratus kyushuensis Morimoto; Rhinotermitidae) en las aperaturas, y se midió el tiempo requerido (τ) para que las termitas pasaran a través de los túneles. El tiempo, τ, fue más corto en los túneles con aperaturas entre 2 y 6 mm de diámetro que para los que tienen aperaturas de 8 o 10 mm de diámetro, para los túneles de ambos anchos. El tiempo, τ, fue significativamente diferente entre (W, D) = (2, 10) y (3, 10). Estos resultados son explicados por 3 clases de comportamiento. Se discuten brevemente las implicaciones de estos hallazgos en relación con la eficiencia de forrajeo de las termitas.

379

Flock foraging efficiency in relation to food sensing ability and distribution: A simulation study

SANG-HEE LEE | International Journal of Modern Physics B 27 (2013)

초록

Flocking may be an advantageous strategy for acquiring food resources. The degree of advantage is related to two factors: the ability of flock members to detect food resources and patterns of food distribution in the environment. To understand foraging efficiency as a function of these factors, I constructed a two-dimensional (2D) flocking model incorporating the two factors. At the start of the simulation, food particles were heterogeneously distributed. The heterogeneity, H, was characterized as a value ranging from 0.0 to 1.0. For each flock member, food sensing ability was defined by two variables: sensing distance, R and sensing angle, θ. Foraging efficiency of a flock was defined as the time, τ, required for a flock to consume all the available food resources. Simulation results showed that flock foraging is most efficient when individuals had an intermediate sensing ability (R = 60), but decreased for low (R < 60) and high (R > 60) sensing ability. When R > 60, patterns in foraging efficiency with increasing sensing distance and food resource aggregation were less consistent. This inconsistency was due to instability of the flock and a higher rate of individuals failing to capture target food resources. In addition, I briefly discuss the benefits obtained by foraging in flocks from an evolutionary perspective.

초록

Flocking may be an advantageous strategy for acquiring food resources. The degree of advantage is related to two factors: the ability of flock members to detect food resources and patterns of food distribution in the environment. To understand foraging efficiency as a function of these factors, I constructed a two-dimensional (2D) flocking model incorporating the two factors. At the start of the simulation, food particles were heterogeneously distributed. The heterogeneity, H, was characterized as a value ranging from 0.0 to 1.0. For each flock member, food sensing ability was defined by two variables: sensing distance, R and sensing angle, θ. Foraging efficiency of a flock was defined as the time, τ, required for a flock to consume all the available food resources. Simulation results showed that flock foraging is most efficient when individuals had an intermediate sensing ability (R = 60), but decreased for low (R < 60) and high (R > 60) sensing ability. When R > 60, patterns in foraging efficiency with increasing sensing distance and food resource aggregation were less consistent. This inconsistency was due to instability of the flock and a higher rate of individuals failing to capture target food resources. In addition, I briefly discuss the benefits obtained by foraging in flocks from an evolutionary perspective.

378

Characterization of Fish Schooling Behavior with Different Numbers of Medaka (Oryzias latipes) and Goldfish (Carassius auratus) Using a Hidden Markov Model

Wonju Jeon (Seung-Ho Kang, Joo-Baek Leem, Sang-Hee Lee) | PHYSICA A 392 (2013)

초록

Fish that swim in schools benefit from increased vigilance, and improved predator recognition and assessment. Fish school size varies according to species and environmental conditions. In this study, we present a Hidden Markov Model (HMM) that we use to characterize fish schooling behavior in different sized schools, and explore how school size affects schooling behavior. We recorded the schooling behavior of Medaka (Oryzias latipes) and goldfish (Carassius auratus) using different numbers of individual fish (10–40), in a circular aquarium. Eight to ten 3 s video clips were extracted from the recordings for each group size. Schooling behavior was characterized by three variables: linear speed, angular speed, and Pearson coefficient. The values of the variables were categorized into two events each for linear and angular speed (high and low), and three events for the Pearson coefficient (high, medium, and low). Schooling behavior was then described as a sequence of 12 events ( $2 \times 2 \times 3$ ), which was input to an HMM as data for training the model. Comparisons of model output with observations of actual schooling behavior demonstrated that the HMM was successful in characterizing fish schooling behavior. We briefly discuss possible applications of the HMM for recognition of fish species in a school, and for developing bio-monitoring systems to determine water quality.

Highlights

？ We used a Hidden Markov Model to describe schooling behavior in common fish species. ？ Model output was consistent with observations of actual fish schooling behavior. ？ HMMs may have applications in field monitoring of fish species and water quality.

초록

Fish that swim in schools benefit from increased vigilance, and improved predator recognition and assessment. Fish school size varies according to species and environmental conditions. In this study, we present a Hidden Markov Model (HMM) that we use to characterize fish schooling behavior in different sized schools, and explore how school size affects schooling behavior. We recorded the schooling behavior of Medaka (Oryzias latipes) and goldfish (Carassius auratus) using different numbers of individual fish (10–40), in a circular aquarium. Eight to ten 3 s video clips were extracted from the recordings for each group size. Schooling behavior was characterized by three variables: linear speed, angular speed, and Pearson coefficient. The values of the variables were categorized into two events each for linear and angular speed (high and low), and three events for the Pearson coefficient (high, medium, and low). Schooling behavior was then described as a sequence of 12 events ( $2 \times 2 \times 3$ ), which was input to an HMM as data for training the model. Comparisons of model output with observations of actual schooling behavior demonstrated that the HMM was successful in characterizing fish schooling behavior. We briefly discuss possible applications of the HMM for recognition of fish species in a school, and for developing bio-monitoring systems to determine water quality.

Highlights

？ We used a Hidden Markov Model to describe schooling behavior in common fish species. ？ Model output was consistent with observations of actual fish schooling behavior. ？ HMMs may have applications in field monitoring of fish species and water quality.

377

Some Identities on the Generalized q-Bernoulli, q-Euler and q-Genocchi Polynomials

Daeyeoul Kim (Burak Kurt, Veli Kurt) | Abstract and Applied Analysis 2013 (2013)

초록

Mahmudov (2012, 2013) introduced and investigated some $q$ -extensions of the $q$ -Bernoulli polynomials ${\scr B}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ , the $q$ -Euler polynomials ${\scr E}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ , and the $q$ -Genocchi polynomials ${\mathrm{\scr G}}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ . In this paper, we give some identities for ${\scr B}_{n,q}^{(\alpha )}(x,y)$ , ${\mathrm{\scr G}}_{n,q}^{(\alpha )}(x,y)$ , and ${\scr E}_{n,q}^{(\alpha )}(x,y)$ and the recurrence relations between these polynomials. This is an analogous result to the $q$ -extension of the Srivastava-Pintér addition theorem in Mahmudov (2013).

초록

Mahmudov (2012, 2013) introduced and investigated some $q$ -extensions of the $q$ -Bernoulli polynomials ${\scr B}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ , the $q$ -Euler polynomials ${\scr E}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ , and the $q$ -Genocchi polynomials ${\mathrm{\scr G}}_{n,q}^{(\alpha )}(x,y)$ of order $\alpha$ . In this paper, we give some identities for ${\scr B}_{n,q}^{(\alpha )}(x,y)$ , ${\mathrm{\scr G}}_{n,q}^{(\alpha )}(x,y)$ , and ${\scr E}_{n,q}^{(\alpha )}(x,y)$ and the recurrence relations between these polynomials. This is an analogous result to the $q$ -extension of the Srivastava-Pintér addition theorem in Mahmudov (2013).

376

A Diophantine problem concerning polygonal numbers

Daeyeoul Kim (Akos Pinter,Yoon Kyung Park) | Bulletin of the Australian Mathematical Society 88 (2013)

375

Competitively Tight Graphs

Suh-Ryung Kim (Yoshio Sano, Boram Park, Jung Yeun Lee) | Annals of Combinatorics 17 (2013)

초록

The competition graph of a digraph D is a (simple undirected) graph which has the same vertex set as D and has an edge between two distinct vertices x and y if and only if there exists a vertex v in D such that (x, v) and (y, v) are arcs of D. For any graph G, G together with sufficiently many isolated vertices is the competition graph of some acyclic digraph. The competition number k(G) of a graph G is the smallest number of such isolated vertices. Computing the competition number of a graph is an NP-hard problem in general and has been one of the important research problems in the study of competition graphs. Opsut [1982] showed that the competition number of a graph G is related to the edge clique cover number θ _E(G) of the graph G via θ _E(G) − |V(G)| + 2 ≤ k(G) ≤ θ _E(G). We first show that for any positive integer m satisfying 2 ≤ m ≤ |V(G)|, there exists a graph G with k(G) = θ _E(G) − |V(G)| + m and characterize a graph G satisfying k(G) = θ _E(G). We then focus on what we call competitively tight graphs G which satisfy the lower bound, i.e., k(G) = θ _E(G) − |V(G)| + 2. We completely characterize the competitively tight graphs having at most two triangles. In addition, we provide a new upper bound for the competition number of a graph from which we derive a sufficient condition and a necessary condition for a graph to be competitively tight.

초록

The competition graph of a digraph D is a (simple undirected) graph which has the same vertex set as D and has an edge between two distinct vertices x and y if and only if there exists a vertex v in D such that (x, v) and (y, v) are arcs of D. For any graph G, G together with sufficiently many isolated vertices is the competition graph of some acyclic digraph. The competition number k(G) of a graph G is the smallest number of such isolated vertices. Computing the competition number of a graph is an NP-hard problem in general and has been one of the important research problems in the study of competition graphs. Opsut [1982] showed that the competition number of a graph G is related to the edge clique cover number θ _E(G) of the graph G via θ _E(G) − |V(G)| + 2 ≤ k(G) ≤ θ _E(G). We first show that for any positive integer m satisfying 2 ≤ m ≤ |V(G)|, there exists a graph G with k(G) = θ _E(G) − |V(G)| + m and characterize a graph G satisfying k(G) = θ _E(G). We then focus on what we call competitively tight graphs G which satisfy the lower bound, i.e., k(G) = θ _E(G) − |V(G)| + 2. We completely characterize the competitively tight graphs having at most two triangles. In addition, we provide a new upper bound for the competition number of a graph from which we derive a sufficient condition and a necessary condition for a graph to be competitively tight.

374

New approach to twisted q-Bernoulli polynomials

Daeyeoul Kim (Yoon Kyung Park, JaKyeong Koo) | Advances in Difference Equations 298 (2013)

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