Interaction between natural and sexual selection during the evolution of mate recognition

The interaction between natural and sexual selection is central to many theories of how mate choice and reproductive isolation evolve, but their joint effect on the evolution of mate recognition has not, to my knowledge, been investigated in an evolutionary experiment. Natural and sexual selection were manipulated in interspecific hybrid populations of Drosophila to determine their effects on the evolution of a mate recognition system comprised of cuticular hydrocarbons (CHCs). The effect of natural selection in isolation indicated that CHCs were costly for males and females to produce. The effect of sexual selection in isolation indicated that females preferred males with a particular CHC composition. However, the interaction between natural and sexual selection had a greater effect on the evolution of the mate recognition system than either process in isolation. When natural and sexual selection were permitted to operate in combination, male CHCs became exaggerated to a greater extent than in the presence of sexual selection alone, and female CHCs evolved against the direction of natural selection. This experiment demonstrated that the interaction between natural and sexual selection is critical in determining the direction and magnitude of the evolutionary response of the mate recognition system.

Evolutionary experiments on mate recognition in the Drosophila serrata species complex

It is becoming increasingly apparent that at least some aspects of the evolution of mate recognition may be amenable to manipulation in evolutionary experiments. Quantitative genetic analyses that focus on the genetic consequences of evolutionary processes that result in mate recognition evolution may eventually provide an understanding of the genetic basis of the process of speciation. We review a series of experiments that have attempted to determine the genetic basis of the response to natural and sexual selection on mate recognition in the Drosophila serrata species complex. The genetic basis of mate recognition has been investigated at three levels: (1) between the species of D. serrata and D. birchii using interspecific hybrids, (2) between populations of D. serrata that are sympatric and allopatric with respect to D. birchii, and (3) within populations of D. serrata. These experiments suggest that it may be possible to use evolutionary experiments to observe important events such as the reinforcement of mate recognition, or the generation of the genetic associations that are central to many sexual selection models.

Interspecific variation in plumage colour among birds: species recognition or light environment?

The traditional explanation for interspecific plumage colour variation in birds is that colour differences between species are adaptations to minimize the risk of hybridization. Under this explanation, colour differences between closely related species of birds represent reproductive character displacement. An alternative explanation is that interspecific variation in plumage colour is an adaptive response to variation in light environments across habitats. Under this explanation, differences in colour between closely related species are a product of selection on signal efficiency. We use a comparative approach to examine these two hypotheses, testing the effects of sympatry and habitat use, respectively, on divergence in male plumage colour. Contrary to the prediction of the Species Isolation Hypothesis, we find no evidence that sympatric pairs of species are consistently more divergent in coloration than are allopatric pairs of species. However, in agreement with the Light Environment Hypothesis, we find significant associations between plumage coloration and habitat use. All of these results remain qualitatively unchanged irrespective of the statistical methodology used to compare reflectance spectra, the body regions used in the analyses, or the exclusion of areas of plumage not used in sexual displays. Our results suggest that, in general, interspecific variation in plumage colour among birds is more strongly influenced by the signalling environment than by the risk of hybridization.

Enhancing the immunogenicity and modulating the fine epitope recognition of antisera to a helical group A streptococcal peptide vaccine candidate from the M protein using lipid-core peptide technology

A conserved helical peptide vaccine candidate from the M protein of group A streptococci, p145, has been described. Minimal epitopes within p145 have been defined and an epitope recognized by protective antibodies, but not by autoreactive T cells, has been identified. When administered to mice, p145 has low immunogenicity. Many boosts of peptide are required to achieve a high antibody titre (> 12 800). To attempt to overcome this low immunogenicity, lipid-core peptide technology was employed. Lipid-core peptides (LCP) consist of an oligomeric polylysine core, with multiple copies of the peptide of choice, conjugated to a series of lipoamino acids, which acts as an anchor for the antigen. Seven different LCP constructs based on the p145 peptide sequence were synthesized (LCP1-->LCP7) and the immunogenicity of the compounds examined. The most immunogenic constructs contained the longest alkyl side-chains. The number of lipoamino acids in the constructs affected the immunogenicity and spacing between the alkyl side-chains increased immunogenicity. An increase in immunogenicity (enzyme-linked immunosorbent assay (ELISA) titres) of up to 100-fold was demonstrated using this technology and some constructs without adjuvant were more immunogenic than p145 administered with complete Freund's adjuvant (CFA). The fine specificity of the induced antibody response differed for the different constructs but one construct, LCP4, induced antibodies of identical fine specificity to those found in endemic human serum. Opsonic activity of LCP4 antisera was more than double that of p145 antisera. These data show the potential for LCP technology to both enhance immunogenicity of complex peptides and to focus the immune response towards or away from critical epitopes.

Genetic constraints on the evolution of mate recognition under natural selection

Field populations of Drosophila serrata display reproductive character displacement in cuticular hydrocarbons (CHCs) when sympatric with Drosophila birchii. We have previously shown that the naturally occurring pattern of reproductive character displacement can be experimentally replicated by exposing field allopatric populations of D. serrata to experimental sympatry with D. birchii. Here, we tested whether the repeated evolution of reproductive character displacement in natural and experimental populations was a consequence of genetic constraints on the evolution of CHCs. The genetic variance-covariance (G) matrices for CHCs were determined for populations of D. serrata that had evolved in either the presence or absence of D. birchii under field and experimental conditions. Natural selection on mate recognition under both field and experimental sympatric conditions increased the genetic variance in CHCs consistent with a response to selection based on rare alleles. A close association between G eigenstructure and the eigenstructure of the phenotypic divergence (D) matrix in natural and experimental populations suggested that G matrix eigenstructure may have determined the direction in which reproductive character displacement evolved during the reinforcement of mate recognition.

A naturally selected dimorphism within the HLA-B44 supertype alters class I structure, peptide repertoire, and T cell recognition

HLA-B*4402 and B*4403 are naturally occurring MHC class I alleles that are both found at a hi,,h frequency in all human populations, and vet they only differ by one residue on the alpha2 helix (B*4402 Aspl56-->B*4403 Leu156) CTLs discriminate between HLA-B*4402 and B*4403, and these allotypes stimulate strong mutual allogeneic responses reflecting their known barrier to hemopoeitic stem cell transplantation. Although HLA-B*4402 and B*4403 share >95% of their peptide repertoire, B*4403 presents more unique peptides than B*4402, consistent with the stronger T cell alloreactivity observed toward B*4403 compared with B*4402. Crystal structures of B*4402 and B*4403 show how the polymorphisin at position 156 is completely buried and yet alters both the peptide and the heavy chain conformation, relaxing ligand selection by B*4403 compared with B*4402. Thus, the polymorphism between HLA-B*4402 and B 4403 modifies both peptide repertoire and T cell recognition, and is reflected lit the paradoxically powerful alloreactivity that occurs across this minimal mismatch. The findings suggest that these closely related class I genes are maintained lit diverse human populations through their differential impact on the selection of peptide ligands and the T cell repertoire.

Promiscuous CTL recognition of viral epitopes on multiple human leukocyte antigens: Biological validation of the proposed HLA A24 supertype

Multiple HLA class I alleles can bind peptides with common sequence motifs due to structural similarities in the peptide binding cleft, and these groups of alleles have been classified into supertypes. Nine major HLA supertypes have been proposed, including an A24 supertype that includes A*2301, A*2402, and A*3001. Evidence for this A24 supertype is limited to HLA sequence homology and/or similarity in peptide binding motifs for the alleles. To investigate the immunological relevance of this proposed supertype, we have examined two viral epitopes (from EBV and CMV) initially defined as HLA-A*2301-binding peptides. The data clearly demonstrate that each peptide could be recognized by CTL clones in the context of A*2301 or A*2402; thus validating the inclusion of these three alleles within an A24 supertype. Furthermore, CTL responses to the EBV epitope were detectable in both A*2301(+) and A*2402(+) individuals who had been previously exposed to this virus. These data substantiate the biological relevance of the A24 supertype, and the identification of viral epitopes with the capacity to bind promiscuously across this supertype could aid efforts to develop CTL-based vaccines or immunotherapy. The degeneracy in HLA restriction displayed by some T cells in this study also suggests that the dogma of self-MHC restriction needs some refinement to accommodate foreign peptide recognition in the context of multiple supertype alleles.

Brazil's rise on the international scene: Brazil and the World

Since Cardoso and during Lula's Administration, the international order has undergone significant changes. These changes have allowed the Brazilian foreign policy to mitigate internal effects of an order established by others and, at the same time, to become an active participant in the formulation of the new order. To democratize globalization became the mainspring of Brazilian foreign policy. In the scope, President Lula has maintained the tradition of formulating and programming foreign policy as a State policy, and also has fostered the logistic strategy of incorporation of Brazil into the international scene.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

Maternal Recognition of Pregnancy in the Mare : a mini review

Nos equinos, um grande número de eventos das fases iniciais do desenvolvimento embrionário são únicos e distintos daqueles que se verificam em outras espécies, incluindo os críticos mas pouco esclarecidos mecanismos de reconhecimento materno da gestação. Este processo fisiológico, através do qual o concepto sinaliza a sua presença ao organismo materno assegurando a manutenção do corpo lúteo (CL) primário e, consequentemente, dos níveis de progesterona necessários à sobrevivência e desenvolvimento do embrião, está pouco esclarecido. De facto, ainda não é claro qual o sinal embrionário primário que assegura a manutenção do CL nos equinos e, apesar do número de potenciais factores que contribuem para o reconhecimento e manutenção da gestação não parar de crescer, nenhum é capaz por si só de satisfazer todos os critérios que caracterizam um factor anti-luteolítico ou luteostático. Por outro lado, é geralmente aceite o conceito de que o reconhecimento materno da gestação é um fenómeno fisiológico de extrema importância e que qualquer falha, quer no envio quer na recepção do sinal apropriado, pode levar a morte embrionária. De facto, a perda de gestações durante ou à volta do espaço de tempo em que ocorre o reconhecimento materno da gestação (i.e dias 10-16 após a ovulação) é comum mas imprevisível (e, portanto, difícil de controlar e prevenir) na prática clínica, sendo uma causa de grandes perdas económicas.

Tuning Iris Recognition for Noisy Images

The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

Image and color recognition using amorphous silicon p-i-n photodiodes

Large area hydrogenated amorphous silicon single and stacked p-i-n structures with low conductivity doped layers are proposed as monochrome and color image sensors. The layers of the structures are based on amorphous silicon alloys (a-Si(x)C(1-x):H). The current-voltage characteristics and the spectral sensitivity under different bias conditions are analyzed. The output characteristics are evaluated under different read-out voltages and scanner wavelengths. To extract information on image shape, intensity and color, a modulated light beam scans the sensor active area at three appropriate bias voltages and the photoresponse in each scanning position ("sub-pixel") is recorded. The investigation of the sensor output under different scanner wavelengths and varying electrical bias reveals that the response can be tuned, thus enabling color separation. The operation of the sensor is exemplified and supported by a numerical simulation.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.