Role of midbrain in the control of breathing in anuran amphibians

The present study was designed to explore systematically the midbrain of unanesthetized, decerebrate anuran amphibians (bullfrogs), using chemical and electrical stimulation and midbrain transections to identify sites capable of exciting and inhibiting breathing. Ventilation was measured as fictive motor output from the mandibular branch of the trigeminal nerve and the laryngeal branch of the vagus nerve. The results of our transection studies suggest that, under resting conditions, the net effect of inputs from sites within the rostral half of the midbrain is to increase fictive breathing frequency, whereas inputs from sites within the caudal half of the midbrain have no net effect on fictive breathing frequency but appear to act on the medullary central rhythm generator to produce episodic breathing. The results of our stimulation experiments indicate that the principal sites in the midbrain that are capable of exciting or inhibiting the fictive frequency of lung ventilation, and potentially clustering breaths into episodes, appear to be those primarily involved in visual and auditory integration, motor functions, and attentional state.

Efeitos do treino em esteira na marcha com dupla tarefa de indivíduos com doença de Parkinson: ensaio clínico controlado randomizado

Background: The gait automaticity loss difficults realization of concurrent activities - Dual Task (DT). In these situations, individuals with Parkinson`s disease (PD) show a significant reduction in gait velocity and stride length, as strides variability and asymmetry increased, factors predisposing to falls. However, recent studies have shown that training involving DT may cause subsequent improvements in gait variables with DT in individuals with PD. The treadmill use was adopted by this study, by promoting greater regularity in step and enhance training. Objective:To investigate immediate effects of gait training associated with cognitive tasks on gait in individuals with PD. Methods: Twenty-two volunteers were randomly divided into two groups: control group (n = 11), who performed gait training on a treadmill for 20 minutes, and the experimental group (n = 11), who performed treadmill gait training for 20 minutes associated with cognitive tasks of verbal fluency, memory, and spatial planning. Participants were evaluated in phase on of antiparkinsonian medication as the demographic, clinical and anthropometric (identification form), cognitive status (Montreal Cognitive Assessment - MoCA), executive function (Frontal Assessment Battery), level of physical disability (Hoehn and Yahr Modified), motor and functional status (Unified Rating Scale for Parkinson`s Disease - UPDRS), and kinematics (Qualisys Motion Capture System). Results: There were not differences between groups, but both showed improvement after the intervention. The control group had an increase in velocity (p = 0.008), stride length (p = 0.04), step length (p = 0.02) and decreased double support time(p = 0.03). The experimental group showed an increase in speed (p = 0.002), stride length (p = 0.008), step length (p = 0.02) and cadence (p = 0.01), as well as a decrease in the width stride (p = 0.001) and total support time (p = 0.02). As the angular variables, the experimental group had a significant increase in the initial contact angle of ankle (p = 0.01). Conclusion: The gait training combined with cognitive activities didn`t provide significant improvements in gait variables with DT, but this study was the first to demonstrate that gait training on treadmill as simple task minimized the negative interference of DT in PD

Optical Design for Automatic Identification and Portable Systems

This thesis proposes design methods and test tools, for optical systems, which may be used in an industrial environment, where not only precision and reliability but also ease of use is important. The approach to the problem has been conceived to be as general as possible, although in the present work, the design of a portable device for automatic identification applications has been studied, because this doctorate has been funded by Datalogic Scanning Group s.r.l., a world-class producer of barcode readers. The main functional components of the complete device are: electro-optical imaging, illumination and pattern generator systems. For what concerns the electro-optical imaging system, a characterization tool and an analysis one has been developed to check if the desired performance of the system has been achieved. Moreover, two design tools for optimizing the imaging system have been implemented. The first optimizes just the core of the system, the optical part, improving its performance ignoring all other contributions and generating a good starting point for the optimization of the whole complex system. The second tool optimizes the system taking into account its behavior with a model as near as possible to reality including optics, electronics and detection. For what concerns the illumination and the pattern generator systems, two tools have been implemented. The first allows the design of free-form lenses described by an arbitrary analytical function exited by an incoherent source and is able to provide custom illumination conditions for all kind of applications. The second tool consists of a new method to design Diffractive Optical Elements excited by a coherent source for large pattern angles using the Iterative Fourier Transform Algorithm. Validation of the design tools has been obtained, whenever possible, comparing the performance of the designed systems with those of fabricated prototypes. In other cases simulations have been used.

The Effect of Metronome Pacing on Gait in Healthy Subjects

The complex process of gait is rendered partially automatic by central pattern generators (CPGs). To further our understanding of their role in gait control in healthy subjects, we applied a paradigm of anti-phase, or syncopated, movement to gait. To provide a context for our results, we reviewed the literature on in-phase, or synchronized, gait. The review results are as follows. Auditory cueing increased step/stride rate for older subjects, but not younger. Stride rate variability decreased for younger subjects, perhaps because the metronome’s cue acted as a temporal ‘anchor point’ for each step. Step width increased in half of the treadmill studies, but none of the overground ones, suggesting a cumulative effect of the attentional demands of synchronizing gait while on a treadmill. Time series analysis revealed that the α exponent was the most sensitive parameter reported, decreasing toward anti-persistence in almost all cued-gait studies. This project compares in-phase (IN) and anti-phase gait (ANTI) in young and old healthy subjects. We expected gait to be less disrupted during ANTI trials at preferred speed, when the facilitating effect of CPGs would be strongest. The measures step time variability, jerk index, and harmonic ratio quantified gait perturbation: none indicated that ANTI was easiest at preferred walking speed. Surprisingly, the gait of older subjects was no more perturbed than that of younger subjects. When they successfully matched the pace of the beat, they unwittingly synchronized to it. The temporal relationship of their steps to the beat was the same in the IN and ANTI conditions. Younger subjects, visibly struggling during ANTI trials, were able to walk in syncopation. This result suggests that cognitive resources available only to the younger group are required to resist synchronizing to the beat.

Clustering through post inhibitory rebound in synaptically coupled neurons

Post inhibitory rebound is a nonlinear phenomenon present in a variety of nerve cells. Following a period of hyper-polarization this effect allows a neuron to fire a spike or packet of spikes before returning to rest. It is an important mechanism underlying central pattern generation for heartbeat, swimming and other motor patterns in many neuronal systems. In this paper we consider how networks of neurons, which do not intrinsically oscillate, may make use of inhibitory synaptic connections to generate large scale coherent rhythms in the form of cluster states. We distinguish between two cases i) where the rebound mechanism is due to anode break excitation and ii) where rebound is due to a slow T-type calcium current. In the former case we use a geometric analysis of a McKean type model to obtain expressions for the number of clusters in terms of the speed and strength of synaptic coupling. Results are found to be in good qualitative agreement with numerical simulations of the more detailed Hodgkin-Huxley model. In the second case we consider a particular firing rate model of a neuron with a slow calcium current that admits to an exact analysis. Once again existence regions for cluster states are explicitly calculated. Both mechanisms are shown to prefer globally synchronous states for slow synapses as long as the strength of coupling is sufficiently large. With a decrease in the duration of synaptic inhibition both systems are found to break into clusters. A major difference between the two mechanisms for cluster generation is that anode break excitation can support clusters with several groups, whilst slow T-type calcium currents predominantly give rise to clusters of just two (anti-synchronous) populations.

Predicting the metabolic energy costs of bipedalism using evolutionary robotics

To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.

Geographic pattern of genetic diversity in natural populations of Rosewood (Aniba rosaeodora), in the Central Amazonia

Rosewood (Aniba rosaeodora Ducke, Lauraceae) is an Amazonian evergreen tree and a source of the purest linalool, the main component of its essential oil, which is very valuable in the international perfumery market. After decades of over-exploitation it is currently considered as threatened. We evaluated the genetic diversity and its distribution in four populations in Central Amazonia. Thirty-five reliable RAPD markers were generated, of which 32 were polymorphic (91.4%). Variation was higher within the populations (76.5%; p < 0.0001) and geographic distribution contributed to population differentiation (23.4%; p < 0.0001). The Amazon River had a small influence on gene flow (3.3%; p < 0.0001), but we identified evidence of gene flow across the river. There were significant differences in marker frequencies (p < 0.05), in agreement with the low gene flow (Nm = 2.02). The correlation between genetic distance and gene flow was - 0.95 (p = 0.06) and between geographic distance and gene flow was -0.78 (p = 0.12). There was a geographic cline of variability across an East-West axis, influenced as well by the Amazon River, suggesting the river could be a barrier to gene flow. Although threatened, these Rosewood populations retain high diversity, with the highest levels in the Manaus population, which has been protected for over 42 years in a Reserve.

Daily pattern of flight activity of Aedes albifasciatus in Central Argentina

Aedes albifasciatus is an important common mosquito in Central Argentina. Its a confirmed vector of the Western Equine Encephalitis and is responsible for loss of milk production in dairy cattle during peak populations. This paper reports the flight activity pattern of Ae. albifasciatus for different seasons, in the southern coast of the Mar Chiquita Lake (Central Argentina). Data were collected by sampling two sites between 1992 and 1993 with CDC traps and human-bait captures. Adult mosquito population density, estimated by CDC trapping and human-bait, were highly correlated. However, when compared to other species, the proportion of Ae. albifasciatus was higher in human-bait collections. Adult female populations were active only when temperature were higher than 6§C. Two daily biting peaks were observed (dusk and dawn) during the spring, summer and autumn, and only one peak during winter (around 15:00 pm). Adult abundance was significantly correlated (R²= 0.71; p<0.01) with temperature and illumination.

Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling.

Incidence, aetiology and pattern of mandibular fractures in central Switzerland

The two major causative factors for mandibular fractures, as stated in the literature, are either interpersonal violence or motor vehicle accidents. The purpose of this study was to describe epidemiological trends of mandibular fractures in Switzerland. A special emphasis was directed towards the potential impact of socio-economic standards on the mechanism and pattern of mandible fractures.

kappa-Opioid receptor in humans: cDNA and genomic cloning, chromosomal assignment, functional expression, pharmacology, and expression pattern in the central nervous system.

Using the mouse delta-opioid receptor cDNA as a probe, we have isolated genomic clones encoding the human mu- and kappa-opioid receptor genes. Their organization appears similar to that of the human delta receptor gene, with exon-intron boundaries located after putative transmembrane domains 1 and 4. The kappa gene was mapped at position q11-12 in human chromosome 8. A full-length cDNA encoding the human kappa-opioid receptor has been isolated. The cloned receptor expressed in COS cells presents a typical kappa 1 pharmacological profile and is negatively coupled to adenylate cyclase. The expression of kappa-opioid receptor mRNA in human brain, as estimated by reverse transcription-polymerase chain reaction, is consistent with the involvement of kappa-opioid receptors in pain perception, neuroendocrine physiology, affective behavior, and cognition. In situ hybridization studies performed on human fetal spinal cord demonstrate the presence of the transcript specifically in lamina II of the dorsal horn. Some divergences in structural, pharmacological, and anatomical properties are noted between the cloned human and rodent receptors.

Organizational, direct support, and general support maintenance ... for generator, test pattern SG-1223/T (NSN 6625-01-127-6846).

"20 August 1984."

Present-day Pattern Variations in the Central and Eastern Pacific El Nino

El Niño and the Southern Oscillation (ENSO) is a cycle that is initiated in the equatorial Pacific Ocean and is recognized on interannual timescales by oscillating patterns in tropical Pacific sea surface temperatures (SST) and atmospheric circulations. Using correlation and regression analysis of datasets that include SST’s and other interdependent variables including precipitation, surface winds, sea level pressure, this research seeks to quantify recent changes in ENSO behavior. Specifically, the amplitude, frequency of occurrence, and spatial characteristics (i.e. events with maximum amplitude in the Central Pacific versus the Eastern Pacific) are investigated. The research is based on the question; “Are the statistics of ENSO changing due to increasing greenhouse gas concentrations?” Our hypothesis is that the present-day changes in amplitude, frequency, and spatial characteristics of ENSO are determined by the natural variability of the ocean-atmosphere climate system, not the observed changes in the radiative forcing due to change in the concentrations of greenhouse gases. Statistical analysis, including correlation and regression analysis, is performed on observational ocean and atmospheric datasets available from the National Oceanographic and Atmospheric Administration (NOAA), National Center for Atmospheric Research (NCAR) and coupled model simulations from the Coupled Model Inter-comparison Project (phase 5, CMIP5). Datasets are analyzed with a particular focus on ENSO over the last thirty years. Understanding the observed changes in the ENSO phenomenon over recent decades has a worldwide significance. ENSO is the largest climate signal on timescales of 2 - 7 years and affects billions of people via atmospheric teleconnections that originate in the tropical Pacific. These teleconnections explain why changes in ENSO can lead to climate variations in areas including North and South America, Asia, and Australia. For the United States, El Niño events are linked to decreased number of hurricanes in the Atlantic basin, reduction in precipitation in the Pacific Northwest, and increased precipitation throughout the southern United Stated during winter months. Understanding variability in the amplitude, frequency, and spatial characteristics of ENSO is crucial for decision makers who must adapt where regional ecology and agriculture are affected by ENSO.

Present-day Pattern Variations in the Central and Eastern Pacific El Nino

El Niño and the Southern Oscillation (ENSO) is a cycle that is initiated in the equatorial Pacific Ocean and is recognized on interannual timescales by oscillating patterns in tropical Pacific sea surface temperatures (SST) and atmospheric circulations. Using correlation and regression analysis of datasets that include SST’s and other interdependent variables including precipitation, surface winds, sea level pressure, this research seeks to quantify recent changes in ENSO behavior. Specifically, the amplitude, frequency of occurrence, and spatial characteristics (i.e. events with maximum amplitude in the Central Pacific versus the Eastern Pacific) are investigated. The research is based on the question; “Are the statistics of ENSO changing due to increasing greenhouse gas concentrations?” Our hypothesis is that the present-day changes in amplitude, frequency, and spatial characteristics of ENSO are determined by the natural variability of the ocean-atmosphere climate system, not the observed changes in the radiative forcing due to change in the concentrations of greenhouse gases. Statistical analysis, including correlation and regression analysis, is performed on observational ocean and atmospheric datasets available from the National Oceanographic and Atmospheric Administration (NOAA), National Center for Atmospheric Research (NCAR) and coupled model simulations from the Coupled Model Inter-comparison Project (phase 5, CMIP5). Datasets are analyzed with a particular focus on ENSO over the last thirty years. Understanding the observed changes in the ENSO phenomenon over recent decades has a worldwide significance. ENSO is the largest climate signal on timescales of 2 - 7 years and affects billions of people via atmospheric teleconnections that originate in the tropical Pacific. These teleconnections explain why changes in ENSO can lead to climate variations in areas including North and South America, Asia, and Australia. For the United States, El Niño events are linked to decreased number of hurricanes in the Atlantic basin, reduction in precipitation in the Pacific Northwest, and increased precipitation throughout the southern United Stated during winter months. Understanding variability in the amplitude, frequency, and spatial characteristics of ENSO is crucial for decision makers who must adapt where regional ecology and agriculture are affected by ENSO.