PubMed Health⌕ Search

Biomedical subjects

Oscar Calvo

Publications and source records attributed to Oscar Calvo.

4 recordsLinked to original sources

Polarization model for poorly-organized interfacial water: hydration forces between silica surfaces.

The main goal of this paper is to review the theoretical models which can be used to describe the interactions between silica surfaces and to show that a model proposed earlier by the authors (the polarization model), which accounts concomitantly for double layer and hydration forces, can be adapted to explain recent experiments in this direction. When the water molecules near the interface were considered to have an ice-like structure, a strong coupling between the double layer and hydration forces (described by the correlation length between neighboring dipoles, lambda(m)) generates long range interactions, larger than the experimentally determined interactions between silica surfaces. Arguments are brought that a gel layer is likely to be formed on the surface of silica, which, by generating disorder in the interfacial water layers, can decrease strongly the value of lambda(m). Since the prediction of lambda(m) involves a choice for the microscopic structure of water, which is often unknown, the polarization model is also presented here as a phenomenological theory, in which lambda(m) is used as a fitting parameter. Two extreme cases are considered. In one of them, the water molecules near the interface are considered to have an ice-like structure, whereas in the other they are considered randomly distributed. In the first case, the dipole correlation length lambda(m)=14.9 Angstrom. In the second limiting case, lambda(m) can be of the order of 1 Angstrom. It is shown that, for lambda(m)=4 Angstrom, a more than qualitative agreement with the experiment could be obtained, for reasonable values of the parameters involved (e.g. surface dipole strength and density, dipole location, surface charge).

Journal Article↗

Spared nerve injury rats exhibit thermal hyperalgesia on an automated operant dynamic thermal escape task.

Well-established methods are available to measure thermal and mechanical sensitivity in awake behaving rats. However, they require experimenter manipulations and tend to emphasize reflexive behaviors. Here we introduce a new behavioral test, with which we examine thermal sensitivity of rats with neuropathic injury. We contrast thermal hyperalgesia between spared nerve injury and chronic constriction injury rats. This device is a fully automated thermal sensitivity assessment tool designed to emphasize integrated learned responses to thermal painful and non-painful stimuli that are applied dynamically to a surface on which the animal is standing. It documents escape behavior in awake, unrestrained animals to innocuous and noxious heating of the floor where the animal is located. Animals learn to minimize pain by escaping to the opposite non-heated side; escape latency is recorded. On this device, thermal stimulus-response curves showed > 6 degrees C leftward shift in both groups of neuropathic rats. In contrast, when these animals were tested on hotplate the stimulus-response shift was < 2 degrees C. Spared nerve injury rats showed even less evidence for thermal hyperalgesia when thermal sensitivity was tested by measuring paw withdrawal to infrared heating, plantar test. The implications of test dependent magnitude of thermal hyperalgesia are discussed from the viewpoint of the tests used, as well as the animal models studied. It is argued that the dynamic thermal operant task reveals the relevance of the neuropathic injury associated pain-like behavior in relation to the whole organism.

Animals↗

Anticipated synchronization: a metaphorical linear view.

We study the regime of anticipated synchronization recently described on a number of dynamical systems including chaotic ones. We use simple linear caricatures to show the minimal setups able to reproduce the basic facts described.

Adaptation, Physiological↗

Subharmonic stochastic synchronization and resonance in neuronal systems.

We study the response of a model neuron, driven simultaneously by noise and at least two weak periodic signals. We focus on signals with frequencies components kf(0),(k+1)f(0),...(k+n)f(0) with k>1. The neuron's output is a sequence of pulses spaced at random interpulse intervals. We find an optimum input noise intensity for which the output pulses are spaced approximately 1/f(0), i.e., there is a stochastic resonance (SR) at a frequency missing in the input. Even higher noise intensities uncover additional, but weaker, resonances at frequencies present in the input. This is a different form of SR whereby the most robust resonance is the one enhancing a frequency, which is absent in the input, and which is not possible to recover via any linear processing. This can be important in understanding sensory systems including the neuronal mechanism for perception of complex tones.

Algorithms↗