Unmasking the functions of the chromaffin cell α7 nicotinic receptor by using short pulses of acetylcholine and selective blockers

Methyllycaconitine (MLA), α-conotoxin ImI, and α-bungarotoxin inhibited the release of catecholamines triggered by brief pulses of acetylcholine (ACh) (100 μM, 5 s) applied to fast-superfused bovine adrenal chromaffin cells, with IC50s of 100 nM for MLA and 300 nM for α-conotoxin ImI and α-bungarotoxin. MLA (100 nM), α-conotoxin ImI (1 μM), and α-bungarotoxin (1 μM) halved the entry of 45Ca2+ stimulated by 5-s pulses of 300 μM ACh applied to incubated cells. These supramaximal concentrations of α7 nicotinic receptor blockers depressed by 30% (MLA), 25% (α-bungarotoxin), and 50% (α-conotoxin ImI) the inward current generated by 1-s pulses of 100 μM ACh, applied to voltage-clamped chromaffin cells. In Xenopus oocytes expressing rat brain α7 neuronal nicotinic receptor for acetylcholine nAChR, the current generated by 1-s pulses of ACh was blocked by MLA, α-conotoxin ImI, and α-bungarotoxin with IC50s of 0.1 nM, 100 nM, and 1.6 nM, respectively; the current through α3β4 nAChR was unaffected by α-conotoxin ImI and α-bungarotoxin, and weakly blocked by MLA (IC50 = 1 μM). The functions of controlling the electrical activity, the entry of Ca2+, and the ensuing exocytotic response of chromaffin cells were until now exclusively attributed to α3β4 nAChR; the present results constitute the first evidence to support a prominent role of α7 nAChR in controlling such functions, specially under the more physiological conditions used here to stimulate chromaffin cells with brief pulses of ACh.

Importance of newly generated neurons in the adult olfactory bulb for odor discrimination

In adult rodents, neurons are continually generated in the subventricular zone of the forebrain, from where they migrate tangentially toward the olfactory bulb, the only known target for these neuronal precursors. Within the main olfactory bulb, they ascend radially into the granule and periglomerular cell layers, where they differentiate mainly into local interneurons. The functional consequences of this permanent generation and integration of new neurons into existing circuits are unknown. To address this question, we used neural cell adhesion molecule-deficient mice that have documented deficits in the migration of olfactory-bulb neuron precursors, leading to about 40% size reduction of this structure. Our anatomical study reveals that this reduction is restricted to the granule cell layer, a structure that contains exclusively γ-aminobutyric acid (GABA)ergic interneurons. Furthermore, mutant mice were subjected to experiments designed to examine the behavioral consequences of such anatomical alteration. We found that the specific reduction in the newly generated interneuron population resulted in an impairment of discrimination between odors. In contrast, both the detection thresholds for odors and short-term olfactory memory were unaltered, demonstrating that a critical number of bulbar granule cells is crucial only for odor discrimination but not for general olfactory functions.

Epistatic and independent functions of Caspase-3 and Bcl-XL in developmental programmed cell death

The number of neurons in the mammalian brain is determined by a balance between cell proliferation and programmed cell death. Recent studies indicated that Bcl-XL prevents, whereas Caspase-3 mediates, cell death in the developing nervous system, but whether Bcl-XL directly blocks the apoptotic function of Caspase-3 in vivo is not known. To examine this question, we generated bcl-x/caspase-3 double mutants and found that caspase-3 deficiency abrogated the increased apoptosis of postmitotic neurons but not the increased hematopoietic cell death and embryonic lethality caused by the bcl-x mutation. In contrast, caspase-3, but not bcl-x, deficiency changed the normal incidence of neuronal progenitor cell apoptosis, consistent with the lack of expression of Bcl-XL in the proliferative population of the embryonic cortex. Thus, although Caspase-3 is epistatically downstream to Bcl-XL in postmitotic neurons, it independently regulates apoptosis of neuronal founder cells. Taken together, these results establish a role of programmed cell death in regulating the size of progenitor population in the central nervous system, a function that is distinct from the classic role of cell death in matching postmitotic neuronal population with postsynaptic targets.

Nutritional regulation of the fatty acid synthase promoter in vivo: Sterol regulatory element binding protein functions through an upstream region containing a sterol regulatory element

The transcription of fatty acid synthase (FAS), a central enzyme in de novo lipogenesis, is dramatically induced by fasting/refeeding and insulin. We reported that upstream stimulatory factor binding to the −65 E-box is required for induction of the FAS transcription by insulin in 3T3-L1 adipocytes. On the other hand, we recently found that two upstream 5′ regions are required for induction in vivo by fasting/refeeding and insulin; one at −278 to −131 albeit at a low level, and the other at −444 to −278 with an E-box at −332 where upstream stimulatory factor functions for maximal induction. Here, we generated double transgenic mice carrying the chloramphenicol acetyltransferase reporter driven by the various 5′ deletions of the FAS promoter region and a truncated active form of the sterol regulatory element (SRE) binding protein (SREBP)-1a. We found that SREBP participates in the nutritional regulation of the FAS promoter and that the region between −278 and −131 bp is required for SREBP function. We demonstrate that SREBP binds the −150 canonical SRE present between −278 and −131, and SREBP can function through the −150 SRE in cultured cells. These in vivo and in vitro results indicate that SREBP is involved in the nutritional induction of the FAS promoter via the −278/−131 region and that the −150 SRE is the target sequence.

A chemical genomics approach toward understanding the global functions of the target of rapamycin protein (TOR)

The target of rapamycin protein (TOR) is a highly conserved ataxia telangiectasia-related protein kinase essential for cell growth. Emerging evidence indicates that TOR signaling is highly complex and is involved in a variety of cellular processes. To understand its general functions, we took a chemical genomics approach to explore the genetic interaction between TOR and other yeast genes on a genomic scale. In this study, the rapamycin sensitivity of individual deletion mutants generated by the Saccharomyces Genome Deletion Project was systematically measured. Our results provide a global view of the rapamycin-sensitive functions of TOR. In contrast to conventional genetic analysis, this approach offers a simple and thorough analysis of genetic interaction on a genomic scale and measures genetic interaction at different possible levels. It can be used to study the functions of other drug targets and to identify novel protein components of a conserved core biological process such as DNA damage checkpoint/repair that is interfered with by a cell-permeable chemical compound.

Functions of interleukin 1 receptor antagonist in gene knockout and overproducing mice.

Interleukin 1 receptor antagonist (IL-1ra) is a cytokine whose only known action is competitive inhibition of the binding of interleukin 1 (IL-1) to its receptor. To investigate the physiological roles of endogenously produced IL-1ra, we generated mice that either lack IL-1ra or overproduce it under control of the endogenous promoter. Mice lacking IL-1ra have decreased body mass compared with wild-type controls. They are more susceptible than controls to lethal endotoxemia but are less susceptible to infection with Listeria monocytogenes. Conversely, IL-1ra overproducers are protected from the lethal effects of endotoxin but are more susceptible to listeriosis. Serum levels of IL-1 following an endotoxin challenge are decreased in IL-1ra nulls and increased in IL-1ra overproducers in comparison to controls. These data demonstrate critical roles for endogenously produced IL-1ra in growth, responses to infection and inflammation, and regulation of cytokine expression.

Selective inhibition of Alzheimer disease-like tau aggregation by phenothiazines.

In Alzheimer disease (AD) the microtubule-associated protein tau is redistributed exponentially into paired helical filaments (PHFs) forming neurofibrillary tangles, which correlate with pyramidal cell destruction and dementia. Amorphous neuronal deposits and PHFs in AD are characterized by aggregation through the repeat domain and C-terminal truncation at Glu-391 by endogenous proteases. We show that a similar proteolytically stable complex can be generated in vitro following the self-aggregation of tau protein through a high-affinity binding site in the repeat domain. Once started, tau capture can be propagated by seeding the further accumulation of truncated tau in the presence of proteases. We have identified a nonneuroleptic phenothiazine previously used in man (methylene blue, MB), which reverses the proteolytic stability of protease-resistant PHFs by blocking the tau-tau binding interaction through the repeat domain. Although MB is inhibitory at a higher concentration than may be achieved clinically, the tau-tau binding assay was used to identify desmethyl derivatives of MB that have Ki values in the nanomolar range. Neuroleptic phenothiazines are inactive. Tau aggregation inhibitors do not affect the tau-tubulin interaction, which also occurs through the repeat domain. Our findings demonstrate that biologically selective pharmaceutical agents could be developed to facilitate the proteolytic degradation of tau aggregates and prevent the further propagation of tau capture in AD.

Evaluating approximations generated by the GNG3D method for mesh simplification

In this paper we present different error measurements with the aim to evaluate the quality of the approximations generated by the GNG3D method for mesh simplification. The first phase of this method consists on the execution of the GNG3D algorithm, described in the paper. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The implementation of three error functions, named Eavg, Emax, Esur, permitts us to control the error of the simplified model, as it is shown in the examples studied.

The renin-angiotensin system and male reproduction: new functions for old hormones

The blood-borne renin-angiotensin system (RAS) is known best for its role in the maintenance of blood pressure and electrolyte and fluid homeostasis. However, numerous tissues show intrinsic angiotensin-generating systems that cater for specific local needs through actions that add to, or differ from, the circulating RAS. The male reproductive system has several sites of intrinsic RAS activity. Recent focus on the epididymis, by our laboratories and by others, has contributed important details about the local RAS in this tissue. The RAS components have been localized morphologically and topographically; they have been shown to be responsive to androgens and to hypoxia; and angiotensin has been shown to influence tubular, and consequently, fluid secretion. Components of the RAS have also been found in the testis, vas deferens, prostate and semen. Angiotensin II receptors, type 1 and, to a lesser extent, type 2 are widespread, and angiotensin IV receptors have been localized in the prostate. The roles of the RAS in local processes at these sites are still uncertain and have yet to be fully elucidated, although there is evidence for involvement in tubular contractility, spermatogenesis, sperm maturation, capacitation, acrosomal exocytosis and fertilization. Notwithstanding this evidence for the involvement of the RAS in various important aspects of male reproduction, there has so far been a lack of clinical evidence, demonstrable by changes in fertility, for a crucial role of the RAS in male reproduction. However, it is clear that there are several potential targets for manipulating the activity of the male reproductive system by interfering with the locally generated angiotensin systems.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

Almost Separable Data Aggregation by Layers of Formal Neurons

Information extraction or knowledge discovery from large data sets should be linked to data aggregation process. Data aggregation process can result in a new data representation with decreased number of objects of a given set. A deterministic approach to separable data aggregation means a lesser number of objects without mixing of objects from different categories. A statistical approach is less restrictive and allows for almost separable data aggregation with a low level of mixing of objects from different categories. Layers of formal neurons can be designed for the purpose of data aggregation both in the case of deterministic and statistical approach. The proposed designing method is based on minimization of the of the convex and piecewise linear (CPL) criterion functions.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

Seizure detection in subdural recordings using nonlinear decision functions

This dissertation proposed a new approach to seizure detection in intracranial EEG recordings using nonlinear decision functions. It implemented well-established features that were designed to deal with complex signals such as brain recordings, and proposed a 2-D domain of analysis. Since the features considered assume both the time and frequency domains, the analysis was carried out both temporally and as a function of different frequency ranges in order to ascertain those measures that were most suitable for seizure detection. In retrospect, this study established a generalized approach to seizure detection that works across several features and across patients. ^ Clinical experiments involved 8 patients with intractable seizures that were evaluated for potential surgical interventions. A total of 35 iEEG data files collected were used in a training phase to ascertain the reliability of the formulated features. The remaining 69 iEEG data files were then used in the testing phase. ^ The testing phase revealed that the correlation sum is the feature that performed best across all patients with a sensitivity of 92% and an accuracy of 99%. The second best feature was the gamma power with a sensitivity of 92% and an accuracy of 96%. In the frequency domain, all of the 5 other spectral bands considered, revealed mixed results in terms of low sensitivity in some frequency bands and low accuracy in other frequency bands, which is expected given that the dominant frequencies in iEEG are those of the gamma band. In the time domain, other features which included mobility, complexity, and activity, all performed very well with an average a sensitivity of 80.3% and an accuracy of 95%. ^ The computational requirement needed for these nonlinear decision functions to be generated in the training phase was extremely long. It was determined that when the duration dimension was rescaled, the results improved and the convergence rates of the nonlinear decision functions were reduced dramatically by more than a 100 fold. Through this rescaling, the sensitivity of the correlation sum improved to 100% and the sensitivity of the gamma power to 97%, which meant that there were even less false negatives and false positives detected. ^

Parametric CAD model based shape optimization using adjoint functions

Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.

Functions of the SLC36 transporter Pathetic in growth control of Drosophila sensory neurons

Thesis (Ph.D.)--University of Washington, 2016-08