997 resultados para spatial encoding
Resumo:
The PyAG1 gene, identified by the screening of a Plasmodium yoelii genomic DNA library with a rhoptry-specific Mab, encodes a protein with a zinc finger structure immediately followed by the consensus sequence of the Arf GAP catalytic site. The serum of mice immunized with the recombinant protein recognized specifically the rhoptries of the late infected erythrocytic stages. Blast analysis using the Genbank database gave the highest scores with four proteins presenting an Arf1 GAP activity. If presenting also this activity, the PyAG1 protein could be involved in the regulation of the secreted protein vesicular transport and, consequently, in the rhoptry biogenesis.
Performance on a Virtual Reality Angled Laparoscope Task Correlates with Spatial Ability of Trainees
Resumo:
The aim of the present study was to investigate whether trainees' performance on a virtual reality angled laparoscope navigation task correlates with scores obtained on a validated conventional test of spatial ability. 56 participants of a surgery workshop performed an angled laparoscope navigation task on the Xitact LS 500 virtual reality Simulator. Performance parameters were correlated with the score of a validated paper-and-pencil test of spatial ability. Performance at the conventional spatial ability test significantly correlated with performance at the virtual reality task for overall task score (p < 0.001), task completion time (p < 0.001) and economy of movement (p = 0.035), not for endoscope travel speed (p = 0.947). In conclusion, trainees' performance in a standardized virtual reality camera navigation task correlates with their innate spatial ability. This VR session holds potential to serve as an assessment tool for trainees.
Resumo:
The molecular karyotype of nine Trypanosoma rangeli strains was analyzed by contour-clamped homogeneous electric field electrophoresis, followed by the chromosomal localization of ß-tubulin, cysteine proteinase, 70 kDa heat shock protein (hsp 70) and actin genes. The T. rangeli strains were isolated from either insects or mammals from El Salvador, Honduras, Venezuela, Colombia, Panama and southern Brazil. Also, T. cruzi CL-Brener clone was included for comparison. Despite the great similarity observed among strains from Brazil, the molecular karyotype of all T. rangeli strains analyzed revealed extensive chromosome polymorphism. In addition, it was possible to distinguish T. rangeli from T. cruzi by the chromosomal DNA electrophoresis pattern. The localization of ß-tubulin genes revealed differences among T. rangeli strains and confirmed the similarity between the isolates from Brazil. Hybridization assays using probes directed to the cysteine proteinase, hsp 70 and actin genes discriminated T. rangeli from T. cruzi, proving that these genes are useful molecular markers for the differential diagnosis between these two species. Numerical analysis based on the molecular karyotype data revealed a high degree of polymorphism among T. rangeli strains isolated from southern Brazil and strains isolated from Central and the northern South America. The T. cruzi reference strain was not clustered with any T. rangeli strain.
Resumo:
This study analyzed the spatial memory capacities of rats in darkness with visual and/or olfactory cues through ontogeny. Tests were conducted with the homing board, where rats had to find the correct escape hole. Four age groups (24 days, 48 days, 3-6 months, and 12 months) were trained in 3 conditions: (a) 3 identical light cues; (b) 5 different olfactory cues; and (c) both types of cues, followed by removal of the olfactory cues. Results indicate that immature rats first take into account olfactory information but are unable to orient with only the help of discrete visual cues. Olfaction enables the use of visual information by 48-day-old rats. Visual information predominantly supports spatial cognition in adult and 12-month-old rats. Results point out cooperation between vision and olfaction for place navigation during ontogeny in rats.
Resumo:
The zinc finger motifs (Cys2His2) are found in several proteins playing a role in the regulation of transcripton. SmZF1, a Schistosoma mansoni gene encoding a zinc finger protein was initially isolated from an adult worm cDNA library, as a partial cDNA. The full sequence of the gene was obtained by subcloning and sequencing cDNA and genomic fragments. The collated gene sequence is 2181 nt and the complete cDNA sequence is 705 bp containing the full open reading frame of the gene. Analysis of the genome sequence revealed the presence of three introns interrupting the coding region. The open reading frame theoretically encodes a protein of 164 amino acids, with a calculated molecular mass of 18,667Da. The predicted protein contains three zinc finger motifs, usually present in transcription regulatory proteins. PCR amplification with specific primers for the gene allowed for the detection of the target in egg, cercariae, schistosomulum and adult worm cDNA libraries indicating the expression of the mRNA in these life cycle stages of S. mansoni. This pattern of expression suggests the gene plays a role in vital functions of different life cycle stages of the parasite. Future research will be directed to elucidate the functional role of SmZF1.
Resumo:
Humoral and cellular immune responses are currently induced against hepatitis C virus (HCV) core following vaccination with core-encoding plasmids. However, the anti-core antibody response is frequently weak or transient. In this paper, we evaluated the effect of different additives and DNA-protein combinations on the anti-core antibody response. BALB/c mice were intramuscularly injected with an expression plasmid (pIDKCo), encoding a C-terminal truncated variant of the HCV core protein, alone or combined with CaCl2, PEG 6000, Freund's adjuvant, sonicated calf thymus DNA and a recombinant core protein (Co.120). Mixture of pIDKCo with PEG 6000 and Freund's adjuvant accelerated the development of the anti-core Ab response. Combination with PEG 6000 also induced a bias to IgG2a subclass predominance among anti-core antibodies. The kinetics, IgG2a/IgG1 ratio and epitope specificity of the anti-core antibody response elicited by Co.120 alone or combined with pIDKCo was different regarding that induced by the pIDKCo alone. Our data indicate that the antibody response induced following DNA immunization can be modified by formulation strategies.
Resumo:
Impaired visual search is a hallmark of spatial neglect. When searching for an unique feature (e.g., color) neglect patients often show only slight visual field asymmetries. In contrast, when the target is defined by a combination of features (e.g., color and form) they exhibit a severe deficit of contralesional search. This finding suggests a selective impairment of the serial deployment of spatial attention. Here, we examined this deficit with a preview paradigm. Neglect patients searched for a target defined by the conjunction of shape and color, presented together with varying numbers of distracters. The presentation time was varied such that on some trials participants previewed the target together with same-shape/different-color distracters, for 300 or 600 ms prior to the appearance of additional different-shape/same-color distracters. On the remaining trials the target and all distracters were shown simultaneously. Healthy participants exhibited a serial search strategy only when all items were presented simultaneously, whereas in both preview conditions a pop-out effect was observed. Neglect patients showed a similar pattern when the target was presented in the right hemifield. In contrast, when searching for a target in the left hemifield they showed serial search in the no-preview condition, as well as with a preview of 300 ms, and partly even at 600 ms. A control experiment suggested that the failure to fully benefit from item preview was probably independent of accurate perception of time. Our results, when viewed in the context of existing literature, lead us to conclude that the visual search deficit in neglect reflects two additive factors: a biased representation of attentional priority in favor of ipsilesional information and exaggerated capture of attention by ipsilesional abrupt onsets.
Resumo:
RATIONALE AND OBJECTIVES: To determine optimum spatial resolution when imaging peripheral arteries with magnetic resonance angiography (MRA). MATERIALS AND METHODS: Eight vessel diameters ranging from 1.0 to 8.0 mm were simulated in a vascular phantom. A total of 40 three-dimensional flash MRA sequences were acquired with incremental variations of fields of view, matrix size, and slice thickness. The accurately known eight diameters were combined pairwise to generate 22 "exact" degrees of stenosis ranging from 42% to 87%. Then, the diameters were measured in the MRA images by three independent observers and with quantitative angiography (QA) software and used to compute the degrees of stenosis corresponding to the 22 "exact" ones. The accuracy and reproducibility of vessel diameter measurements and stenosis calculations were assessed for vessel size ranging from 6 to 8 mm (iliac artery), 4 to 5 mm (femoro-popliteal arteries), and 1 to 3 mm (infrapopliteal arteries). Maximum pixel dimension and slice thickness to obtain a mean error in stenosis evaluation of less than 10% were determined by linear regression analysis. RESULTS: Mean errors on stenosis quantification were 8.8% +/- 6.3% for 6- to 8-mm vessels, 15.5% +/- 8.2% for 4- to 5-mm vessels, and 18.9% +/- 7.5% for 1- to 3-mm vessels. Mean errors on stenosis calculation were 12.3% +/- 8.2% for observers and 11.4% +/- 15.1% for QA software (P = .0342). To evaluate stenosis with a mean error of less than 10%, maximum pixel surface, the pixel size in the phase direction, and the slice thickness should be less than 1.56 mm2, 1.34 mm, 1.70 mm, respectively (voxel size 2.65 mm3) for 6- to 8-mm vessels; 1.31 mm2, 1.10 mm, 1.34 mm (voxel size 1.76 mm3), for 4- to 5-mm vessels; and 1.17 mm2, 0.90 mm, 0.9 mm (voxel size 1.05 mm3) for 1- to 3-mm vessels. CONCLUSION: Higher spatial resolution than currently used should be selected for imaging peripheral vessels.
Resumo:
A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.
Resumo:
This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.