Color tunable electroluminescence and resistance switching from a ZnO-nanorod-TaOx-p-GaN heterojunction.

Well-aligned ZnO nanorods have been prepared on p-GaN-sapphire using a vapor phase transport (VPT) technique. A thin sputtered layer of TaOx is employed as the intermediate layer and an n-ZnO-TaOx-p-GaN heterojunction device has been achieved. The current transport of the heterojunction exhibited a typical resistance switching behavior, which originated from the filament forming and breaking in the TaOx layer. Color controllable electroluminescence (EL) was observed from the biased heterojunction at room temperature. Bluish-white wide band emission is achieved from the forward biased device in both the high resistance and low resistance states, while red emission can only be observed for the reverse biased device in the low resistance state. The correlation between the EL and resistance switching has been analyzed in-depth based on the interface band diagram of the heterojunction.

Fentanyl stimulates prolactin release through mu-opiate receptors, but not the serotonergic system.

Both serotonin (5-HT) and opiates exert a stimulatory effect on PRL secretion. Some evidence suggests that the action of opiates may be elicited through serotonergic neurons. We tested this hypothesis in the present study by evaluating the effect of perturbation of the serotonergic system on PRL secretion induced by fentanyl, a potent morphine-like analgesic. Female Sprague-Dawley rats ovariectomized for 3 weeks and given polyestradiol phosphate (0.1 mg/rat) for 1 week were used in the study. Fentanyl, at a dose of 20 micrograms/rat, induced significant PRL secretion that peaked at 10 min and lasted for more than 30 min. Pretreatment with naloxone (0.5 mg/kg BW, ip) did not block the acute phase of PRL secretion, but significantly lowered the PRL level at 30 min. Fentanyl at a smaller dose (5 micrograms/rat, iv) still induced significant PRL release 10, but not 30, min after injection. This effect was significantly blocked by pretreatment with the same dose of naloxone. On the other hand, whereas animals pretreated with ketanserin or LY53857 (both at a dose of 5 mg/kg BW, ip), two specific 5-HT2 receptor antagonists, had no effect on fentanyl-induced PRL secretion, the same treatment significantly blocked 5-HT-induced PRL secretion. Likewise, pretreatment with p-chlorophenylalanine (250 mg/kg BW, ip), a 5-HT synthesis inhibitor, for 2 days had no effect on the action of fentanyl, while 5-HT-induced PRL secretion was significantly augmented. We conclude that fentanyl acts through mu-opiate receptors to stimulate PRL secretion in a process that does not involve the serotonergic system.

Optimal insulin infusion resulting from a mathematical model of blood glucose dynamics.

Mathematical optimization techniques are applied to a simplified mathematical model of blood glucose dynamics to derive insulin infusion programs for the control of blood glucose levels in diabetic individuals. Two particular cases are discussed. First, the insulin infusion program which results in an initially high blood glucose level being reduced to acceptable levels. Second, the control of blood glucose levels following a meal, prior to which blood glucose and net blood-glycemic hormone were at their fasting levels.

A worst-case optimal parameter selection model of cancer chemotherapy.

An optimal parameter selection model of cancer chemotherapy in which two system parameters are unknown is formulated as a worst-case optimal parameter selection model. The model assumes that the unknown parameters lie within a known set. The system constraints must be satisfied over this entire set, and the objective function minimized in the worst case. The continuous dependence of the objective function and the system constraints upon the unknown parameters can be removed, making a numerical solution tractable. For the data considered it is proven that a cure is impossible no matter what the values of the unknown parameters in the parameter set. The optimal policy is shown to be relatively low dose intensity for the majority of the treatment, with the remaining drug delivered towards the end of the treatment interval.

Species preservations in an optimal harvest model with random prices.

In this paper, we consider an optimal harvest model in which the objective is to maximize the expected return. The unit price of biomass is assumed constant until a random time when the price increases by a given amount. Furthermore, due to obvious environmental protection requirements, it is assumed that the fishery population is bounded from below for all time so as to reduce the danger of species extinction. Clearly, this problem is an optimal control problem in which a random parameter is involved. However, due to its special structure, it is shown that the problem is convertible into a deterministic optimal control problem and hence is solvable by an existing optimal control software package, MISER. The practical implication of several computed results obtained by this approach is discussed. They are also compared with other related results in the literature.

Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy.

The high failure rates encountered in the chemotherapy of some cancers suggest that drug resistance is a common phenomenon. In the current study, the tumor burden during therapy is used to slow the growth of the drug-resistant cells, thereby maximizing the survival time of the host. Three types of tumor growth model are investigated--Gompertz, logistic, and exponential. For each model, feedback controls are constructed that specify the optimal tumor mass as a function of the size of the resistant subpopulation. For exponential and logistic tumor growth, the tumor burden during therapy is shown to have little impact upon survival time. When the tumor is in Gompertz growth, therapies maintaining a large tumor burden double and sometimes triple the survival time under aggressive therapies. Aggressive therapies aim for a rapid reduction in the sensitive cell subpopulation. These conclusions are not dependent upon the values of the model constants that determine the mass of resistant cells. Since treatments maintaining a high tumor burden are optimal for Gompertz tumor growth and close to optimal for exponential and logistic tumor growth, it may no longer be necessary to know the growth characteristics of a tumor to schedule anticancer drugs.

Low-intensity combination chemotherapy maximizes host survival time for tumors containing drug-resistant cells.

Recent clinical trials have shown that for some cancers, high-intensity alternating chemotherapy does not significantly improve either survival times or response rates compared with nonalternating therapy. The current study uses optimal control to determine the best way to treat a tumor that contains drug-resistant cells that cannot be destroyed. The delivery of two non-cross-resistant chemotherapeutic agents is limited by bounds on the drug concentration and the dose intensity. This ensures that the drug toxicity stays within a tolerable range. The aim of the therapy is to maximize the host survival time, defined as the time over which the tumor burden can be kept below a fixed bound. The model is posed as a free terminal time, optimal parameter selection problem in which the constraints are continuously parametrized by time and the number of courses of therapy is free to vary. New theory is developed so that the optimal parameter selection problem can be solved as a sequence of fixed terminal time problems using existing optimal control software. Numerical simulations of Gompertz tumor growth showed that a treatment maintaining a high tumor burden doubled and sometimes tripled with survival time under aggressive therapy. When these simulations were repeated using exponential and logistic tumor growth models, the tumor burden during treatment had little influence upon survival time. In all simulations, survival time was not extended by delivering the anticancer drugs concurrently instead of staggering the treatment arms.

A mathematical model of cancer chemotherapy with an optimal selection of parameters.

An optimal parameter selection model of cancer chemotherapy is presented which describes the treatment of a tumor over a fixed period of time by the repeated administration of a single drug. The drug is delivered at evenly spaced intervals over the treatment period at doses to be selected by the model. The model constructs a regimen that both minimizes the tumor population at the end of the treatment and satisfies constraints on the drug toxicity and intermediate tumor size. Numerical solutions show that an optimal regimen withholds the bulk of the doses until the end of the treatment period. When a drug used is of either moderate or low effectiveness, an optimal regimen is superior to a schedule that delivers all of the drug at the beginning of the treatment. This study questions whether the current method for the administration of chemotherapy is optimal and suggests that alternative regimens should be considered.

Nonlinear system modeling via knot-optimizing B-spline networks.

In using the B-spline network for nonlinear system modeling, owing to a lack of suitable theoretical results, it is quite difficult to choose an appropriate set of knot points to achieve a good network structure for minimizing, say, a minimum error criterion. In this paper, a novel knot-optimizing B-spline network is proposed to approximate the general nonlinear system behavior. The knot points are considered to be independent variables in the B-spline network and are optimized together with the B-spline expansion coefficients. The simulated annealing algorithm with an appropriate search strategy is used as an optimization algorithm for the training process in order to avoid any possible local minima. Examples involving dynamic systems up to six dimensions in the input space to the network are solved by the proposed method to illustrate the effectiveness of this approach.

Serotonin-stimulated prolactin secretion may not involve the dopaminergic system.

The possible involvement of the dopaminergic system in the serotonin (5-HT)-stimulated prolactin (PRL) secretion was tested in this study. Adult female rats were ovariectomized for two weeks and treated with estrogen (polyestradiol phosphate, 0.1 mg/rat, sc) for 6 days before use. They either received pretreatment with alpha-methyl-p-tyrosine (250 mg/kg BW, ip), a dopamine (DA) synthesis inhibitor, or two DA antagonists, domperidone and haloperidol (0.1 mg/kg BW, iv) before receiving 5-HT (1 mg/kg BW, iv) or quipazine (1 mg/kg BW, iv), a 5-HT agonist. Blockade of DA synthesis or antagonism of DA action invariably induced elevated plasma PRL levels. 5-HT or quipazine, however, could still induce significant PRL secretion on top of the increased PRL levels. Minor difference was found between the action of domperidone and that of haloperidol. In conclusion, the dopaminergic system may not be involved in the action of 5-HT to stimulate PRL secretion.

Small dose of domperidone potentiated the effects of TRH and serotonin on prolactin release in ovariectomized, estrogen-treated rats.

A transient antagonism of the dopaminergic action by using a dopamine antagonist, domperidone, plus a dopamine agonist, CB154, has been shown to potentiate the effect of thyrotropin-releasing hormone (TRH) on prolactin (PRL) secretion. In order to test whether the serotonin (5-HT)-induced PRL secretion can also be enhanced in a similar way, we used 5-HT instead of TRH in our first experiment. We found that the dose of domperidone used (10 micrograms/rat) seems to be excessive since it induced a marked and substantial increase in PRL release and the use of CB154 further masked the action of 5-HT. We used a smaller dose of domperidone (1 microgram/rat) without the CB154 and found that it induced a moderate amount of PRL release which lasted for over 1 h. Given TRH (1 microgram/rat) or 5-HT (0.3 mg/rat) 1 h later resulted in a significant increase in plasma PRL which was much higher than that induced by TRH or 5-HT alone. The potentiating effect of domperidone was even more significant for the 5-HT- than the TRH-stimulated PRL secretion. Pretreatment with 5-HT or vasoactive intestinal polypeptide (10 micrograms/rat) were without any effect in potentiating the action of TRH. In conclusion, antagonizing the dopamine action appears to enhance the stimulatory effect of TRH and 5-HT on PRL secretion.