The investigation of the sensitivity gradient of the visual field, as a function of stimulus dynamic range, in the normal and abnormal eye

The study utilized the advanced technology provided by automated perimeters to investigate the hypothesis that patients with retinitis pigmentosa behave atypically over the dynamic range and to concurrently determine the influence of extraneous factors on the format of the normal perimetric sensitivity profile. The perimetric processing of some patients with retinitis pigmentosa was considered to be abnormal in either the temporal and/or the spatial domain. The standard size III stimulus saturated the central regions and was thus ineffective in detecting early depressions in sensitivity in these areas. When stimulus size was scaled in inverse proportion to the square root of ganglion cell receptive field density (M-scaled), isosensitive profiles did not result, although cortical representation was theoretically equivalent across the visual field. It was conjectured that this was due to variations in the ganglion cell characteristics with increasing peripheral angle, most notably spatial summation. It was concluded that the development of perimetric routines incorporating stimulus sizes adjusted in proportion to the coverage factor of retinal ganglion cells would enhance the diagnostic capacity of perimetry. Good general and local correspondence was found between perimetric sensitivity and the available retinal cell counts. Intraocular light scatter arising both from simulations and media opacities depressed perimetric sensitivity. Attenuation was greater centrally for the smaller LED stimuli, whereas the reverse was true for the larger projected stimuli. Prior perimetric experience and pupil size also demonstrated eccentricity-dependent effect on sensitivity. Practice improved perimetric sensitivity for projected stimuli at eccentricities greater than or equal to 30o; particularly in the superior region. Increase in pupil size for LED stimuli enhanced sensitivity at eccentricities greater than 10o. Conversely, microfluctuation in the accommodative response during perimetric examination and the correction of peripheral refractive error had no significant influence on perimetric sensitivity.

Parallel strategy for optimal learning in perceptrons

We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha–Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.

The development and stability analysis of a nonlinear growth model for microorganisms

A nonlinear dynamic model of microbial growth is established based on the theories of the diffusion response of thermodynamics and the chemotactic response of biology. Except for the two traditional variables, i.e. the density of bacteria and the concentration of attractant, the pH value, a crucial influencing factor to the microbial growth, is also considered in this model. The pH effect on the microbial growth is taken as a Gaussian function G0e-(f- fc)2/G1, where G0, G1 and fc are constants, f represents the pH value and fc represents the critical pH value that best fits for microbial growth. To study the effects of the reproduction rate of the bacteria and the pH value on the stability of the system, three parameters a, G0 and G1 are studied in detail, where a denotes the reproduction rate of the bacteria, G0 denotes the impacting intensity of the pH value to microbial growth and G1 denotes the bacterial adaptability to the pH value. When the effect of the pH value of the solution which microorganisms live in is ignored in the governing equations of the model, the microbial system is more stable with larger a. When the effect of the bacterial chemotaxis is ignored, the microbial system is more stable with the larger G1 and more unstable with the larger G0 for f0 > fc. However, the stability of the microbial system is almost unaffected by the variation G0 and G1 and it is always stable for f0 < fc under the assumed conditions in this paper. In the whole system model, it is more unstable with larger G1 and more stable with larger G0 for f0 < fc. The system is more stable with larger G1 and more unstable with larger G0 for f0 > fc. However, the system is more unstable with larger a for f0 < fc and the stability of the system is almost unaffected by a for f0 > fc. The results obtained in this study provide a biophysical insight into the understanding of the growth and stability behavior of microorganisms.

The slope of the psychometric function and non-stationarity of thresholds in spatiotemporal contrast vision

The slope of the two-interval, forced-choice psychometric function (e.g. the Weibull parameter, ß) provides valuable information about the relationship between contrast sensitivity and signal strength. However, little is known about how or whether ß varies with stimulus parameters such as spatiotemporal frequency and stimulus size and shape. A second unresolved issue concerns the best way to estimate the slope of the psychometric function. For example, if an observer is non-stationary (e.g. their threshold drifts between experimental sessions), ß will be underestimated if curve fitting is performed after collapsing the data across experimental sessions. We measured psychometric functions for 2 experienced observers for 14 different spatiotemporal configurations of pulsed or flickering grating patches and bars on each of 8 days. We found ß ˜ 3 to be fairly constant across almost all conditions, consistent with a fixed nonlinear contrast transducer and/or a constant level of intrinsic stimulus uncertainty (e.g. a square law transducer and a low level of intrinsic uncertainty). Our analysis showed that estimating a single ß from results averaged over several experimental sessions was slightly more accurate than averaging multiple estimates from several experimental sessions. However, the small levels of non-stationarity (SD ˜ 0.8 dB) meant that the difference between the estimates was, in practice, negligible.

Improving the repeatability of heterochromatic flicker photometry for measurement of macular pigment optical density

Background: Heterochromatic flicker photometry (HFP) is a psychophysical technique used to measure macular pigment optical density (MPOD). We used the MPS 9000 (MPS) HFP device. Our aim was to determine if the repeatability of the MPS could be improved to make it more suitable for monitoring MPOD over time. Methods: Intra-session repeatability was assessed in 25 participants (aged 20-50 years). The resulting data was explored in detail, e.g., by examining the effect of removal and adjustment of data with less than optimal quality parameters. A protocol was developed for improved overall reliability, which was then tested in terms of inter-session repeatability in a separate group of 27 participants (aged 19-52 years). Results: Removal and adjustment of data reduced the intra-session coefficient of repeatability (CR) by 0.04, on average, and the mean individual standard deviation by 0.004. Raw data observation offered further insight into ways of improving repeatability. The proposed protocol resulted in an inter-session CR of 0.08. Conclusions: Removal and adjustment of less than optimal data improved repeatability, and is therefore recommended. To further improve repeatability, in brief we propose that each patient perform each part of the test twice, and a third time where necessary (described in detail by the protocol). Doing so will make the MPS more useful in research and clinical settings. © 2012 Springer-Verlag.

Phenotypic effect of mutations in evolving populations of RNA molecules

Background. The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. Results. We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). Conclusions. The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate µ at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of µ, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks. © 2010 Stich et al; licensee BioMed Central Ltd.

Shared action spaces:a basis function framework for social re-calibration of sensorimotor representations supporting joint action

The article explores the possibilities of formalizing and explaining the mechanisms that support spatial and social perspective alignment sustained over the duration of a social interaction. The basic proposed principle is that in social contexts the mechanisms for sensorimotor transformations and multisensory integration (learn to) incorporate information relative to the other actor(s), similar to the "re-calibration" of visual receptive fields in response to repeated tool use. This process aligns or merges the co-actors' spatial representations and creates a "Shared Action Space" (SAS) supporting key computations of social interactions and joint actions; for example, the remapping between the coordinate systems and frames of reference of the co-actors, including perspective taking, the sensorimotor transformations required for lifting jointly an object, and the predictions of the sensory effects of such joint action. The social re-calibration is proposed to be based on common basis function maps (BFMs) and could constitute an optimal solution to sensorimotor transformation and multisensory integration in joint action or more in general social interaction contexts. However, certain situations such as discrepant postural and viewpoint alignment and associated differences in perspectives between the co-actors could constrain the process quite differently. We discuss how alignment is achieved in the first place, and how it is maintained over time, providing a taxonomy of various forms and mechanisms of space alignment and overlap based, for instance, on automaticity vs. control of the transformations between the two agents. Finally, we discuss the link between low-level mechanisms for the sharing of space and high-level mechanisms for the sharing of cognitive representations. © 2013 Pezzulo, Iodice, Ferraina and Kessler.

3D reconstruction of the complex dielectric function of glass during femtosecond laser micro-fabrication

We report on a new technique to reconstruct the 3D dielectric function change in transparent dielectric materials and the application of the technique for on-line monitoring of refractive index modification in BK7 glass during direct femtosecond laser microfabrication. The complex optical field scattered from the modified region is measured using two-beam, single-shot interferogram and the distribution of the modified refractive index is reconstructed by numerically solving the inverse scattering problem in Born approximation. The optical configuration suggested is further development of digital holographic microscopy. It takes advantage of high spatial resolution and almost the same optical paths for both interfering beams, and allows ultrafast time resolution. © Springer Science+Business Media, LLC. 2011.

Injectable hydrogels with high fixed charge density and swelling pressure for nucleus pulposus repair:biomimetic glycosaminoglycan analogues

The load-bearing biomechanical role of the intervertebral disc is governed by the composition and organization of its major macromolecular components, collagen and aggrecan. The major function of aggrecan is to maintain tissue hydration, and hence disc height, under the high loads imposed by muscle activity and body weight. Key to this role is the high negative fixed charge of its glycosaminoglycan side chains, which impart a high osmotic pressure to the tissue, thus regulating and maintaining tissue hydration and hence disc height under load. In degenerate discs, aggrecan degrades and is lost from the disc, particularly centrally from the nucleus pulposus. This loss of fixed charge results in reduced hydration and loss of disc height; such changes are closely associated with low back pain. The present authors developed biomimetic glycosaminoglycan analogues based on sulphonate-containing polymers. These biomimetics are deliverable via injection into the disc where they polymerize in situ, forming a non-degradable, nuclear "implant" aimed at restoring disc height to degenerate discs, thereby relieving back pain. In vitro, these glycosaminoglycan analogues possess appropriate fixed charge density, hydration and osmotic responsiveness, thereby displaying the capacity to restore disc height and function. Preliminary biomechanical tests using a degenerate explant model showed that the implant adapts to the space into which it is injected and restores stiffness. These hydrogels mimic the role taken by glycosaminoglycans in vivo and, unlike other hydrogels, provide an intrinsic swelling pressure, which can maintain disc hydration and height under the high and variable compressive loads encountered in vivo. © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Antiproliferative effects of carbon monoxide on pancreatic cancer

Background - Carbon monoxide, the gaseous product of heme oxygenase, is a signalling molecule with a broad spectrum of biological activities. The aim of this study was to investigate the effects of carbon monoxide on proliferation of human pancreatic cancer. Methods - In vitro studies were performed on human pancreatic cancer cells (CAPAN-2, BxPc3, and PaTu-8902) treated with a carbon monoxide-releasing molecule or its inactive counterpart, or exposed to carbon monoxide gas (500 ppm/24 h). For in vivo studies, pancreatic cancer cells (CAPAN-2/PaTu-8902) were xenotransplanted subcutaneously into athymic mice, subsequently treated with carbon monoxide-releasing molecule (35 mg/kg b.w. i.p./day), or exposed to safe doses of carbon monoxide (500 ppm 1 h/day; n = 6 in each group). Results - Both carbon monoxide-releasing molecule and carbon monoxide exposure significantly inhibited proliferation of human pancreatic cancer cells (p < 0.05). A substantial decrease in Akt phosphorylation was observed in carbon monoxide-releasing molecule compared with inactive carbon monoxide-releasing molecule treated cancer cells (by 30–50%, p < 0.05). Simultaneously, carbon monoxide-releasing molecule and carbon monoxide exposure inhibited tumour proliferation and microvascular density of xenotransplanted tumours (p < 0.01), and doubled the survival rates (p < 0.005). Exposure of mice to carbon monoxide led to an almost 3-fold increase in carbon monoxide content in tumour tissues (p = 0.006). Conclusion - These data suggest a new biological function for carbon monoxide in carcinogenesis, and point to the potential chemotherapeutic/chemoadjuvant use of carbon monoxide in pancreatic cancer.

Tunnelling density of states at Coulomb-blockade peaks

We calculate the tunnelling density of states (TDoS) for a quantum dot in the Coulomb-blockade regime, using a functional integral representation with allowing correctly for the charge quantisation. We show that in addition to the well-known gap in the TDoS in the Coulomb-blockade valleys, there is a suppression of the TDoS at the peaks. We show that such a suppression is necessary in order to get the correct result for the peak of the differential conductance through an almost close quantum dot.

Network density and R&D spillovers

This paper models how the structure and function of a network of firms affects their aggregate innovativeness. Each firm has the potential to innovate, either from in-house R&D or from innovation spillovers from neighboring firms. The nature of innovation spillovers depends upon network density, the commonality of knowledge between firms, and the learning capability of firms. Innovation spillovers are modelled in detail using ideas from organizational theory. Two main results emerge: (i) the marginal effect on innovativeness of spillover intensity is non-monotonic, and (ii) network density can affect innovativeness but only when there are heterogeneous firms.

Antiproliferative effects of carbon monoxide on pancreatic cancer

Background: Carbon monoxide, the gaseous product of heme oxygenase, is a signalling molecule with a broad spectrum of biological activities. The aim of this study was to investigate the effects of carbon monoxide on proliferation of human pancreatic cancer. Methods: In vitro studies were performed on human pancreatic cancer cells (CAPAN-2, BxPc3, and PaTu-8902) treated with a carbon monoxide-releasing molecule or its inactive counterpart, or exposed to carbon monoxide gas (500. ppm/24. h). For in vivo studies, pancreatic cancer cells (CAPAN-2/PaTu-8902) were xenotransplanted subcutaneously into athymic mice, subsequently treated with carbon monoxide-releasing molecule (35. mg/kg b.w. i.p./day), or exposed to safe doses of carbon monoxide (500. ppm 1. h/day; n=. 6 in each group). Results: Both carbon monoxide-releasing molecule and carbon monoxide exposure significantly inhibited proliferation of human pancreatic cancer cells (p<0.05). A substantial decrease in Akt phosphorylation was observed in carbon monoxide-releasing molecule compared with inactive carbon monoxide-releasing molecule treated cancer cells (by 30-50%, p<. 0.05). Simultaneously, carbon monoxide-releasing molecule and carbon monoxide exposure inhibited tumour proliferation and microvascular density of xenotransplanted tumours (p<0.01), and doubled the survival rates (p<0.005). Exposure of mice to carbon monoxide led to an almost 3-fold increase in carbon monoxide content in tumour tissues (p=0.006). Conclusion: These data suggest a new biological function for carbon monoxide in carcinogenesis, and point to the potential chemotherapeutic/chemoadjuvant use of carbon monoxide in pancreatic cancer. © 2013 Editrice Gastroenterologica Italiana S.r.l.

Effects of short-term detraining on postprandial metabolism, endothelial function, and inflammation in endurance-trained men:dissociation between changes in triglyceride metabolism and endothelial function

Endurance-trained athletes experience a low level of postprandial lipaemia, but this rapidly increases with detraining. We sought to determine whether detraining-induced changes to postprandial metabolism influenced endothelial function and inflammation. Eight endurance-trained men each undertook two oral fat tolerance tests [blood taken fasted and for 6 h following a high-fat test meal (80 g fat, 80 g carbohydrate)]: one during a period of their normal training (trained) and one after 1 wk of no exercise (detrained). Endothelial function in the cutaneous microcirculation was assessed using laser Doppler imaging with iontophoresis in the fasted state and 4 h postprandially during each test. Fasting plasma triglyceride (TG) concentrations increased by 35% with detraining (P = 0.002), as did postprandial plasma (by 53%, P = 0.002), chylomicron (by 68%, P = 0.02) and very low-density lipoprotein (by 51%, P = 0.005) TG concentrations. Endothelial function decreased postprandially in both the trained (by 17%, P = 0.03) and detrained (by 22%, P = 0.03) conditions but did not differ significantly between the trained and detrained conditions in either the fasted or the postprandial states. These results suggest that, although fat ingestion induces endothelial dysfunction, interventions that alter postprandial TG metabolism will not necessarily concomitantly influence endothelial function.

Neural Network Based Optimal Control with Constraints

In the present paper the problems of the optimal control of systems when constraints are imposed on the control is considered. The optimality conditions are given in the form of Pontryagin’s maximum principle. The obtained piecewise linear function is approximated by using feedforward neural network. A numerical example is given.