The functional structure of our new network is not preset; instead, it
comes into existence in a random, stochastic manner.
The anatomical structure of our model consists of two input “neurons”, hundreds up to five thousands of hidden-layer “neurons” and one output “neuron”.
The proper process is based on iteration, i.e., mathematical operation governed by a set of rules, in which repetition helps to approximate the desired result.
Each iteration begins with data being introduced into the input layer to be processed in accordance with a particular algorithm in the hidden layer; it then continues with the computation of certain as yet very crude configurations of images regulated by a genetic code, and ends up with the selection of 10% of the most accomplished “offspring”. The next iteration begins with the application of these new, most successful variants of the results, i.é., descendants in the continued process of image perfection. The ever new variants (descendants) of the genetic algorithm are always generated randomly. The determinist rule then only requires the choice of 10% of all the variants available (in our case 20 optimal variants out of 200).
The stochastic model is marked by a number of characteristics, e.g., the initial conditions are determined by different data dispersion variance, the evolution of the network organisation is controlled by genetic rules of a purely stochastic nature; Gaussian distribution noise proved to be the best “organiser”.
Another analogy between artificial networks and neuronal structures lies in the use of time in network algorithms.
For that reason, we gave our networks organisation a kind of temporal development, i.e., rather than being instantaneous; the connection between the artificial elements and neurons consumes certain units of time per one synapse or, better to say, per one contact between the preceding and subsequent neurons.
The latency of neurons, natural and artificial alike, is very importaiit as it
enables feedback action.
Our network becomes organised under the effect of considerable noise. Then, however, the amount of noise must subside. However, if the network evolution gets stuek in the local minimum, the amount of noise has to be inereased again. While this will make the network organisation waver, it will also inerease the likelihood that the erisis in the local minimum will abate and improve substantially the state of the network in its self-organisation.
Our system allows for constant state-of-the-network reading by ineaiis of establishing the network energy level, i.e., basically ascertaining progression of the network’s rate of success in self-organisation. This is the principal parameter for the detection of any jam in the local minimum. It is a piece of input information for the formator algorithm which regulates the level of noise in the system.
In this study, we focused on an analysis of biguanides effects on mitochondrial enzyme activities, mitochondrial membrane potential and membrane permeabili ty transition pore function. We used phenformin, which is more efficient than metformin, and evaluated its effect on rat liver mitochondria and isolated hepatocytes. In contrast to prev iously published data, we found that phenformin, after a 5 min pr e-incubation, dose-dependently inhibits not only mitochondrial complex I but also complex II and IV activity in isolated mitochondria. The enzymes complexes inhibition is paralleled by the decreased respiratory control index and mitochondrial membrane potent ial. Direct measurements of mitochondrial swelling revealed that phenformin increases the resistance of the permeability transition pore to Ca 2+ ions. Our data might be in agreement with the hypothesis of Schäfer (1976) that binding of biguanides to membrane phospholipids alters membrane properties in a non-specific manner and, subsequently, different enzyme activities are modified via lipid phase. However, our measurements of anisotropy of fluorescence of hydrophobic membrane probe diphenylhexatriene have not shown a measurable effect of membrane fluidity with the 1 mM concentration of phenformin that strongly inhibited complex I activity. Our data therefore suggest that biguanides could be considered as agents with high efficacy but low specifity., Z. Drahota ... [et al.]., and Obsahuje bibliografii a bibliografické odkazy
Many extracellular signals are at the cell surface received by specific receptors, which upon activation transduce information to the appropriate cellular effector molecules via trimeric G proteins. The G protein-mediated cascades ultimately lead to the highly refined regulation of systems such as sensory perception, cell growth, and hormonal regulation. Transmembrane signaling may be seriously deranged in various pathophysiological conditions. Over the last two decades the major experimental effort of our group has been devoted to better understanding the molecular mechanisms underlying transmembrane signaling regulated by G proteins and to the closely related process of desensitization of hormone response. This review provides general information about the basic principles of G protein-regulated transmembrane signaling as well as about our contribution to the current progress in the field.
Impaired wakefulness in machine operators poses a danger not only to themselves but often to the public at large as well. While on duty, such persons are expected to be continuously, i.e., without interruption, on the alert. For that purpose, we designed and carried out an experimental model of continuous vigilance monitoring using electroencephalography (EEG) and reaction time measured as the latency of the probanďs reaction to sound stimulus. If constructed, the set together with other logical elements and an alarm systém can be used for an autornatic detection of vigilance and, possibly, also of arousal stimuli in cases of micro-sleep.
Our data indicate the significant intrinsic efficacy of GABABreceptors in rat brain cortex already at birth (PD1, PD2). Subsequently, baclofen- and SKF97541-stimulated G-protein activity, measured by agonist-stimulated, high-affinity [35S]GTPγS binding assay, was increased; the highest level of both baclofen and SKF97541-stimulated [35S]GTPγS binding was detected between PD10 and PD15. In older rats, baclofen- and SKF97541- stimulated [35S]GTPγS binding was continuously decreased so, that the level in adult, 90-days old animals, was not different from that in newborn animals. The potency of G-protein response to baclofen (characterized by EC50 values) was also high at birth but unchanged by further postnatal development. An individual variance among different agonists was observed in this respect as the potency of SKF97541 response was decreased between the birth and adulthood. Accordingly, the highest plasma membrane density of GABAB-R, determined by saturation binding assay with antagonist [3 H]CGP54626, was measured in 1-day old animals (2.27±0.08 pmol · mg-1). The further development was reflected in a decrease of [3 H]CGP54626 binding as the Bmax values of 1.38±0.05 and 0.93±0.04 pmol · mg-1 were determined in PM isolated from 13- and 90-days old rats, respectively., D. Kagan, ... [et al.]., and Obsahuje seznam literatury
Visfatin is a multi-functional molecule that can act intracellularly and extracellularly as an adipokine, cytokine and enzyme. One of the main questions concerning visfatin is the mechanism of its secretion; whether, how and from which cells visfatin is released. The objective of this in vitro study was to observe the active secretion of visfatin from 3T3-L1 preadipocytes and adipocytes, HepG2 hepatocytes, U-937, THP-1 and HL-60 monocytes and macrophages. The amount of visfatin in media and cell lysate was always related to the intracellular enzyme, glyceraldehyde-3- phosphate dehydrogenase (GAPDH), to exclude the passive release of visfatin. Visfatin was not found in media of 3T3-L1 preadipocytes. In media of 3T3-L1 adipocytes and HepG2 hepatocytes, the ratio of visfatin to the amount of GAPDH was identical to cell lysates. Hence, it is likely that these cells do not actively secrete visfatin in a significant manner. However, we found that significant producers of visfatin are differentiated macrophages and that the amount of secreted visfatin depends on used cell line and it is affected by the mode of differentiation. Results show that 3T3-L1 adipocytes and HepG2 hepatocytes released visfatin only passively during the cell death. U-937 macrophages secrete visfatin in the greatest level from all of the tested cell lines., P. Svoboda, E. Křížová, K. Čeňková, K. Vápenková, J. Zídková, V. Zídek, V. Škop., and Obsahuje bibliografii