Inhibition of potassium (KATP) channels reduces the short-circuit current response of rat colonic mucosa to acetylcholine

Intestinal secretion depends upon electrogenic chloride transport into the gut lumen, which requires maintenance of an electrically negative cell-membrane voltage. We have investigated whether secretory responses of rat colonic mucosa to acetylcholine were sensitive to inhibition of potassium channels and whether selective inhibition could indicate the nature of the channel involved. Rat colonic mucosa was set up in Ussing chambers, short-circuit current responses obtained to acetylcholine, and the sensitivity of such responses to inhibition of potassium channels was investigated. Non-selective potassium-channel blockade by barium induced concentration-dependent inhibition of responses to acetylcholine. Similar inhibitory effects were obtained using 4-aminopyridine and glibenclamide. 5-Hydroxydecanoate and phentolamine also inhibited the increase in short-circuit current. However, a combination of charybdotoxin plus apamin was without effect. We conclude that a basolateral outward movement of potassium ions is required for the secretory action of acetylcholine on rat colonic mucosa. The potassium channel involved seems to be ATP-dependent and calcium-insensitive.     

On the spuriousness of the symbolic/subsymbolic distinction

The article criticises the attempt to establish connectionism as an alternative theory of human cognitive architecture through the introduction of thesymbolic/subsymbolic distinction (Smolensky, 1988). The reasons for the introduction of this distinction are discussed and found to be unconvincing. It is shown that thebrittleness problem has been solved for a large class ofsymbolic learning systems, e.g. the class oftop-down induction of decision-trees (TDIDT) learning systems. Also, the process of articulating expert knowledge in rules seems quite practical for many important domains, including common sense knowledge.The article discusses several experimental comparisons betweenTDIDT systems and artificial neural networks using the error backpropagation algorithm (ANNs usingBP). The properties of one of theTDIDT systemsID3 (Quinlan, 1986a) are examined in detail. It is argued that the differences in performance betweenANNs usingBP andTDIDT systems reflect slightly different inductive biases but are not systematic; these differences do not support the view that symbolic and subsymbolic systems are fundamentally incompatible. It is concluded, that thesymbolic/subsymbolic distinction is spurious. It cannot establish connectionism as an alternative cognitive architecture.     

A new family of tellurife glasses

Glass formation in three-component tellurite-phosphate and tellurite-borate vitreous systems has been determined, with the latter including metal oxides or metal halides (chloride, fluoride or bromide), respectively. The results obtained have served as a base for the determination of the glass forming tendency in a number of telluritemetaphosphate and tellurite-metaborate triple combinations. Hence a new family of tellurite glasses has been obtained. It has been established that the glass formation is most observed in alkaline, earth alkaline oxide and halide metaphosphate systems. The three-component tellurite-metaphosphate and metaborate systems investigated have been treated as partial three-component sections of the main four-component telluritephosphate and tellurite-borate systems also.     

A protocol for evaluation of similarity measures for rigid registration

The accuracy and robustness of a registration method depend on a number of factors, such as imaging modality, image content and image degrading effects, the class of spatial transformation used for registration, similarity measure, optimization, and numerous implementation details. The complex interdependence of these factors makes the assessment of the influence of a particular factor on registration difficult, although it is often desirable to have some estimate of such influences prior to registration. The similarity measure used to create the cost function is one of the factors that most influences the quality of registration. Traditionally, limited information on the behavior of a similarity measure is obtained either by studying the quality of the final registration or by drawing plots of similarity measure values obtained by translating or rotating one image relative to the "gold standard." In this paper, we present a protocol for a more thorough, optimization-independent, and systematic statistical evaluation of similarity measures. This protocol estimates a similarity measure's capture range, the number, location and extent of local optima, and the accuracy and distinctiveness of the global optimum. To show that the proposed evaluation protocol is viable, we have conducted several experiments with nine similarity measures and real computed tomography and magnetic resonance (MR) images of a spine phantom, MR brain images, and MR and positron emission tomography brain images, for which "gold standard" registrations were available. We have also studied the impact of histogram bin size on the behavior of nine similarity measures. The proposed evaluation protocol is useful for selecting the best similarity measure and corresponding optimization method for a particular application, as well as for studying the influence of sampling, interpolation, histogram bin size, partial image overlap, and image degradation, such as noise, intensity inhomogeneity, and geometrical distortions on the behavior of a similarity measure.     

Structure and enhanced antimicrobial activity of mechanically activated nano TiO2

Titanium dioxide is a photocatalyst, known not only for its ability to oxidize organic contaminants, but also for its antimicrobial properties. In this article, significant enhancement of the antimicrobial activity of TiO₂ (up to 32 times) was demonstrated after its activation by ball milling. The antimicrobial activity was analyzed for one fungal and 13 bacterial ATCC strains using the microdilution method and recording the minimum inhibitory concentration (MIC) values. In order to further investigate the correlation between the mechanical activation of TiO₂ and its antimicrobial activity, the structure, morphology and phase composition of the material were studied by means of Electron Microscopy, X-ray diffraction and nitrogen adsorption-desorption measurements. UV-Vis diffuse reflectance spectra were recorded and the Kubelka-Munk function was applied to convert reflectance into the equivalent band gap energy (E_g) and, consequently, to investigate changes in the E_g value. X-ray photoelectron spectroscopy was used to analyze the influence of mechanical activation on the Ti 2p and O 1s spectra. The presented results are expected to enable the development of more sustainable and effective advanced TiO₂-based materials with antimicrobial properties that could be used in numerous green technology applications.     

Modeling the impacts of climate change on the thermal and oxygen dynamics of Lake Volta

Climatic changes influence the thermal and oxygen dynamics of a lake and thus its ecological functioning. The impacts of climatic changes on tropical lakes are so far poorly studied and the extent of the effects is therefore uncertain, most investigations describing only potential effects. In this study, we applied the one-dimensional lake ecosystem model GOTM-ERGOM to quantify the effects of climate change on thermal stratification, oxygen dynamics, and primary production in meso-oligotrophic Lake Volta. GOTM-ERGOM was calibrated and validated using two years of observed data. The validated model was used to evaluate a series of future climate change scenarios. The model simulations showed good agreement with observed water temperature, dissolved oxygen and chlorophyll-a and indicated intensified stratification and reduced oxygen levels in the productive water layers of the lake. However, the longer-lasting stratification (prolonged stability) did not translate into permanent stratification. A relatively small (1?m) upward shift of thermocline depth resulted in an 8%–12% volume loss of the oxygen-rich upper mixed layer, which may be significant for the fisheries of the lake as it diminishes the size of suitable fish habitats. Light limitation of primary production renders the lake somewhat resilient to intensive algae blooms, as traceable in both the present and in the future climate scenarios. In the long term, the ongoing climate change may affect riparian communities that depend on the lake's fisheries for their livelihood. In consequence, future lake management strategies for implementation need to account for the impacts of future climate change.     

The linear assignment method for multicriteria group decision making based on interval‐valued Pythagorean fuzzy Bonferroni mean

The interval‐valued Pythagorean fuzzy sets can easily handle uncertain information more flexibly in the process of decision making. Considering the interrelationship among the input arguments, we extend the Bonferroni mean and the geometric Bonferroni mean to the interval‐valued Pythagorean fuzzy environment and solve its practical application problems. First, we develop the interval‐valued Pythagorean fuzzy Bonferroni mean and the weighted interval‐valued Pythagorean fuzzy Bonferroni mean (WIVPFBM) operators. The properties of these aggregation operators are investigated. Then, we also develop the interval‐valued Pythagorean fuzzy geometric Bonferroni mean and the weighted interval‐valued Pythagorean fuzzy geometric Bonferroni mean (WIVPFGBM) operators and analyze their properties. Third, we utilize the WIVPFBM and WIVPFGBM operators to fuse the information in the interval‐valued Pythagorean fuzzy multicriteria group decision making (IVPFMCGDM) problem, which can obtain much more information in the process of group decision making. With the aid of the linear assignment method, we present its extension and further design a new algorithm for the application of IVPFMCGDM. Finally, an example is given to elaborate our proposed algorithm and validate its excellent performance.     

Training a molecular automaton to play a game

Research at the interface between chemistry and cybernetics has led to reports of 'programmable molecules', but what does it mean to say 'we programmed a set of solution-phase molecules to do X'? A survey of recently implemented solution-phase circuitry indicates that this statement could be replaced with 'we pre-mixed a set of molecules to do X and functional subsets of X'. These hard-wired mixtures are then exposed to a set of molecular inputs, which can be interpreted as being keyed to human moves in a game, or as assertions of logical propositions. In nucleic acids-based systems, stemming from DNA computation, these inputs can be seen as generic oligonucleotides. Here, we report using reconfigurable nucleic acid catalyst-based units to build a multipurpose reprogrammable molecular automaton that goes beyond single-purpose 'hard-wired' molecular automata. The automaton covers all possible responses to two consecutive sets of four inputs (such as four first and four second moves for a generic set of trivial two-player two-move games). This is a model system for more general molecular field programmable gate array (FPGA)-like devices that can be programmed by example, which means that the operator need not have any knowledge of molecular computing methods.