Condition-dependence, pleiotropy and the handicap principle of sexual selection in melanin-based colouration.

The signalling function of melanin-based colouration is debated. Sexual selection theory states that ornaments should be costly to produce, maintain, wear or display to signal quality honestly to potential mates or competitors. An increasing number of studies supports the hypothesis that the degree of melanism covaries with aspects of body condition (e.g. body mass or immunity), which has contributed to change the initial perception that melanin-based colour ornaments entail no costs. Indeed, the expression of many (but not all) melanin-based colour traits is weakly sensitive to the environment but strongly heritable suggesting that these colour traits are relatively cheap to produce and maintain, thus raising the question of how such colour traits could signal quality honestly. Here I review the production, maintenance and wearing/displaying costs that can generate a correlation between melanin-based colouration and body condition, and consider other evolutionary mechanisms that can also lead to covariation between colour and body condition. Because genes controlling melanic traits can affect numerous phenotypic traits, pleiotropy could also explain a linkage between body condition and colouration. Pleiotropy may result in differently coloured individuals signalling different aspects of quality that are maintained by frequency-dependent selection or local adaptation. Colouration may therefore not signal absolute quality to potential mates or competitors (e.g. dark males may not achieve a higher fitness than pale males); otherwise genetic variation would be rapidly depleted by directional selection. As a consequence, selection on heritable melanin-based colouration may not always be directional, but mate choice may be conditional to environmental conditions (i.e. context-dependent sexual selection). Despite the interest of evolutionary biologists in the adaptive value of melanin-based colouration, its actual role in sexual selection is still poorly understood.

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

Efficient Peer Selection in P2P JXTA-Based Platforms

Peer-reviewed

An Experimental Study on Peer Selection in a P2P Network over PlanetLab

Peer-reviewed

Type II aromatic polyketide biosynthetic tailoring enzymes: diversity and adaptation in Streptomyces secondary metabolism.

Members of the bacterial genus Streptomyces are well known for their ability to produce an exceptionally wide selection of diverse secondary metabolites. These include natural bioactive chemical compounds which have potential applications in medicine, agriculture and other fields of commerce. The outstanding biosynthetic capacity derives from the characteristic genetic flexibility of Streptomyces secondary metabolism pathways: i) Clustering of the biosynthetic genes in chromosome regions redundant for vital primary functions, and ii) the presence of numerous genetic elements within these regions which facilitate DNA rearrangement and transfer between non-progeny species. Decades of intensive genetic research on the organization and function of the biosynthetic routes has led to a variety of molecular biology applications, which can be used to expand the diversity of compounds synthesized. These include techniques which, for example, allow modification and artificial construction of novel pathways, and enable gene-level detection of silent secondary metabolite clusters. Over the years the research has expanded to cover molecular-level analysis of the enzymes responsible for the individual catalytic reactions. In vitro studies of the enzymes provide a detailed insight into their catalytic functions, mechanisms, substrate specificities, interactions and stereochemical determinants. These are factors that are essential for the thorough understanding and rational design of novel biosynthetic routes. The current study is a part of a more extensive research project (Antibiotic Biosynthetic Enzymes; www.sci.utu.fi/projects/biokemia/abe), which focuses on the post-PKS tailoring enzymes involved in various type II aromatic polyketide biosynthetic pathways in Streptomyces bacteria. The initiative here was to investigate specific catalytic steps in anthracycline and angucycline biosynthesis through in vitro biochemical enzyme characterization and structural enzymology. The objectives were to elucidate detailed mechanisms and enzyme-level interactions which cannot be resolved by in vivo genetic studies alone. The first part of the experimental work concerns the homologous polyketide cyclases SnoaL and AknH. These catalyze the closure of the last carbon ring of the tetracyclic carbon frame common to all anthracycline-type compounds. The second part of the study primarily deals with tailoring enzymes PgaE (and its homolog CabE) and PgaM, which are responsible for a cascade of sequential modification reactions in angucycline biosynthesis. The results complemented earlier in vivo findings and confirmed the enzyme functions in vitro. Importantly, we were able to identify the amino acid -level determinants that influence AknH and SnoaL stereoselectivity and to determine the complex biosynthetic steps of the angucycline oxygenation cascade of PgaE and PgaM. In addition, the findings revealed interesting cases of enzyme-level adaptation, as some of the catalytic mechanisms did not coincide with those described for characterised homologs or enzymes of known function. Specifically, SnoaL and AknH were shown to employ a novel acid-base mechanism for aldol condenzation, whereas the hydroxylation reaction catalysed by PgaM involved unexpected oxygen chemistry. Owing to a gene-level fusion of two ancestral reading frames, PgaM was also shown to adopt an unusual quaternary sturucture, a non-covalent fusion complex of two alternative forms of the protein. Furthermore, the work highlighted some common themes encountered in polyketide biosynthetic pathways such as enzyme substrate specificity and intermediate reactivity. These are discussed in the final chapters of the work.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Determinação de baixas concentrações de cobre em águas naturais por espectrofotometria de absorção atômica em chama usando um sistema SIA com uma coluna de poli(etilenimina)

This paper describes a sequential injection analysis (SIA) set-up coupled to a flame atomic absorption spectrometer (FAAS) to accomplish the determination of low concentrations of copper in drinking waters. Copper is first retained under neutral media in an on-line 29x1.6 mm column filled with poly(ethylenimine) immobilised on silica gel. The retained analyte is then eluted by flowing through the column 250 mL of a nitric acid solution. The selection of 3.85 ml of sample enabled to obtain a detection limit of 0.27 mug/L and a sampling rate of about 24 samples/h. There was a good agrement between the results of 12 samples furnished by the proposed procedure and by electrothermal atomic absorption spectrometry. Repeatability assessment gave a relative standard deviation of 1.3 % after ten replicate analysis of a sample containing about 70 mug/L in copper..

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Modelagem de proteínas por homologia

Modeling methods to derive 3D-structure of proteins have been recently developed. Protein homology-modeling, also known as comparative protein modeling, is nowadays the most accurate protein modeling method. This technique can produce useful models for about an order of magnitude more protein sequences than there have been structures determined by experiment in the same amount of time. All current protein homology-modeling methods consist of four sequential steps: fold assignment and template selection, template-target alignment, model building, and model evaluation. In this paper we discuss in some detail the protein-homology paradigm, its predictive power and its limitations.

Acoplamento de cela de difusão gasosa a sistema de análise por injeção seqüencial visando a determinação espectrofotométrica de sulfeto

A new configuration for coupling a gas diffusion cell to a sequential injection system is presented. The matrix exchange is made without the need for additional rotary injection valves or peristaltic pumps, keeping the original mechanical components of the sequential injection apparatus: one syringe pump (or peristaltic pump) and one selection valve. The system was tested constructing analytical curves for sulfide exploring the formation of the methylene blue dye. The proposed method has a detection limit of 60 µg L-1 S2-, with a linear dynamic range between 0.10 and 4.0 mg L-1 S2- concentrations, with a sampling frequency of 20 h-1.

Threshold Selection Criteria for Quantification of Lumbosacral Cerebrospinal Fluid and Root Volumes from MRI

BACKGROUND AND PURPOSE: The high variability of CSF volumes partly explains the inconsistency of anesthetic effects, but may also be due to image analysis itself. In this study, criteria for threshold selection are anatomically defined. METHODS: T2 MR images (n = 7 cases) were analyzed using 3-dimentional software. Maximal-minimal thresholds were selected in standardized blocks of 50 slices of the dural sac ending caudally at the L5-S1 intervertebral space (caudal blocks) and middle L3 (rostral blocks). Maximal CSF thresholds: threshold value was increased until at least one voxel in a CSF area appeared unlabeled and decreased until that voxel was labeled again: this final threshold was selected. Minimal root thresholds: thresholds values that selected cauda equina root area but not adjacent gray voxels in the CSF-root interface were chosen. RESULTS: Significant differences were found between caudal and rostral thresholds. No significant differences were found between expert and nonexpert observers. Average max/min thresholds were around 1.30 but max/min CSF volumes were around 1.15. Great interindividual CSF volume variability was detected (max/min volumes 1.6-2.7). CONCLUSIONS: The estimation of a close range of CSF volumes which probably contains the real CSF volume value can be standardized and calculated prior to certain intrathecal procedures

Learning and selection processes

In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism (or device) is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections

Construction and validation of a scoring system for the selection of high-quality data in a Spanish population primary care database (SIDIAP)

Background Computerised databases of primary care clinical records are widely used for epidemiological research. In Catalonia, the InformationSystem for the Development of Research in Primary Care (SIDIAP) aims to promote the development of research based on high-quality validated data from primary care electronic medical records. Objective The purpose of this study is to create and validate a scoring system (Registry Quality Score, RQS) that will enable all primary care practices (PCPs) to be selected as providers of researchusable data based on the completeness of their registers. Methods Diseases that were likely to be representative of common diagnoses seen in primary care were selected for RQS calculations. The observed/ expected cases ratio was calculated for each disease. Once we had obtained an estimated value for this ratio for each of the selected conditions we added up the ratios calculated for each condition to obtain a final RQS. Rate comparisons between observed and published prevalences of diseases not included in the RQS calculations (atrial fibrillation, diabetes, obesity, schizophrenia, stroke, urinary incontinenceand Crohn’s disease) were used to set the RQS cutoff which will enable researchers to select PCPs with research-usable data. Results Apart from Crohn’s disease, all prevalences were the same as those published from the RQS fourth quintile (60th percentile) onwards. This RQS cut-off provided a total population of 1 936 443 (39.6% of the total SIDIAP population). Conclusions SIDIAP is highly representative of the population of Catalonia in terms of geographical, age and sex distributions. We report the usefulness of rate comparison as a valid method to establish research-usable data within primary care electronic medical records

Citation auctions as a method to improve selection of scientific papers

This paper describes the basis of citation auctions as a new approach to selecting scientific papers for publication. Our main idea is to use an auction for selecting papers for publication through - differently from the state of the art - bids that consist of the number of citations that a scientist expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper's content to judge the quality of its contribution. Additionally, the method will not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives. Sample analyses of the number of citations collected in papers published in years 1999-2004 for one journal, and in years 2003-2005 for a series of conferences (in a totally different discipline), via Google scholar, are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications