Autoimmune regulator (AIRE) contributes to Dectin-1-induced TNF-alpha production and complexes with caspase recruitment domain-containing protein 9 (CARD9), spleen tyrosine kinase (Syk), and Dectin-1

Background: Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) syndrome is a complex immunologic disease caused by mutation of the autoimmune regulator (AIRE) gene. Autoimmunity in patients with APECED syndrome has been shown to result from deficiency of AIRE function in transcriptional regulation of thymic peripheral tissue antigens, which leads to defective T-cell negative selection. Candidal susceptibility in patients with APECED syndrome is thought to result from aberrant adaptive immunity. Objective: To determine whether AIRE could function in anticandidal innate immune signaling, we investigated an extrathymic role for AIRE in the immune recognition of beta-glucan through the Dectin-1 pathway, which is required for defense against Candida species. Methods: Innate immune signaling through the Dectin-1 pathway was assessed in both PBMCs from patients with APECED syndrome and a monocytic cell line. Subcellular localization of AIRE was assessed by using confocal microscopy. Results: PBMCs from patients with APECED syndrome had reduced TNF-alpha responses after Dectin-1 ligation but in part used a Raf-1-mediated pathway to preserve function. In the THP-1 human monocytic cell line, reducing AIRE expression resulted in significantly decreased TNF-a release after Dectin-1 ligation. AIRE formed a transient complex with the known Dectin-1 pathway components phosphorylated spleen tyrosine kinase and caspase recruitment domain-containing protein 9 after receptor ligation and localized with Dectin-1 at the cell membrane. Conclusion: AIRE can participate in the Dectin-1 signaling pathway, indicating a novel extrathymic role for AIRE and a defect that likely contributes to fungal susceptibility in patients with APECED syndrome. (J Allergy Clin Immunol 2012;129:464-72.)

BF Integrase Genes of HIV-1 Circulating in Sao Paulo, Brazil, with a Recurrent Recombination Region

Although some studies have shown diversity in HIV integrase (IN) genes, none has focused particularly on the gene evolving in epidemics in the context of recombination. The IN gene in 157 HIV-1 integrase inhibitor-naive patients from the Sao Paulo State, Brazil, were sequenced tallying 128 of subtype B (23 of which were found in non-B genomes), 17 of subtype F (8 of which were found in recombinant genomes), 11 integrases were BF recombinants, and 1 from subtype C. Crucially, we found that 4 BF recombinant viruses shared a recurrent recombination breakpoint region between positions 4900 and 4924 (relative to the HXB2) that includes 2 gRNA loops, where the RT may stutter. Since these recombinants had independent phylogenetic origin, we argue that these results suggest a possible recombination hotspot not observed so far in BF CRF in particular, or in any other HIV-1 CRF in general. Additionally, 40% of the drug-naive and 45% of the drug-treated patients had at least 1 raltegravir (RAL) or elvitegravir (EVG) resistance-associated amino acid change, but no major resistance mutations were found, in line with other studies. Importantly, V151I was the most common minor resistance mutation among B, F and BF IN genes. Most codon sites of the IN genes had higher rates of synonymous substitutions (dS) indicative of a strong negative selection. Nevertheless, several codon sites mainly in the subtype B were found under positive selection. Consequently, we observed a higher genetic diversity in the B portions of the mosaics, possibly due to the more recent introduction of subtype F on top of an ongoing subtype B epidemics and a fast spread of subtype F alleles among the B population.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

The gene transformer-2 of Anastrepha fruit flies (Diptera, Tephritidae) and its evolution in insects

Abstract Background In the tephritids Ceratitis, Bactrocera and Anastrepha, the gene transformer provides the memory device for sex determination via its auto-regulation; only in females is functional Tra protein produced. To date, the isolation and characterisation of the gene transformer-2 in the tephritids has only been undertaken in Ceratitis, and it has been shown that its function is required for the female-specific splicing of doublesex and transformer pre-mRNA. It therefore participates in transformer auto-regulatory function. In this work, the characterisation of this gene in eleven tephritid species belonging to the less extensively analysed genus Anastrepha was undertaken in order to throw light on the evolution of transformer-2. Results The gene transformer-2 produces a protein of 249 amino acids in both sexes, which shows the features of the SR protein family. No significant partially spliced mRNA isoform specific to the male germ line was detected, unlike in Drosophila. It is transcribed in both sexes during development and in adult life, in both the soma and germ line. The injection of Anastrepha transformer-2 dsRNA into Anastrepha embryos caused a change in the splicing pattern of the endogenous transformer and doublesex pre-mRNA of XX females from the female to the male mode. Consequently, these XX females were transformed into pseudomales. The comparison of the eleven Anastrepha Transformer-2 proteins among themselves, and with the Transformer-2 proteins of other insects, suggests the existence of negative selection acting at the protein level to maintain Transformer-2 structural features. Conclusions These results indicate that transformer-2 is required for sex determination in Anastrepha through its participation in the female-specific splicing of transformer and doublesex pre-mRNAs. It is therefore needed for the auto-regulation of the gene transformer. Thus, the transformer/transfomer-2 > doublesex elements at the bottom of the cascade, and their relationships, probably represent the ancestral state (which still exists in the Tephritidae, Calliphoridae and Muscidae lineages) of the extant cascade found in the Drosophilidae lineage (in which tra is just another component of the sex determination gene cascade regulated by Sex-lethal). In the phylogenetic lineage that gave rise to the drosophilids, evolution co-opted for Sex-lethal, modified it, and converted it into the key gene controlling sex determination.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

Optimal Code Set Selection and Security Issues in Spectral Phase-Encoded Time Spreading (SPECTS) OCDMA Systems

In this paper, we perform a thorough analysis of a spectral phase-encoded time spreading optical code division multiple access (SPECTS-OCDMA) system based on Walsh-Hadamard (W-H) codes aiming not only at finding optimal code-set selections but also at assessing its loss of security due to crosstalk. We prove that an inadequate choice of codes can make the crosstalk between active users to become large enough so as to cause the data from the user of interest to be detected by other user. The proposed algorithm for code optimization targets code sets that produce minimum bit error rate (BER) among all codes for a specific number of simultaneous users. This methodology allows us to find optimal code sets for any OCDMA system, regardless the code family used and the number of active users. This procedure is crucial for circumventing the unexpected lack of security due to crosstalk. We also show that a SPECTS-OCDMA system based on W-H 32(64) fundamentally limits the number of simultaneous users to 4(8) with no security violation due to crosstalk. More importantly, we prove that only a small fraction of the available code sets is actually immune to crosstalk with acceptable BER (<10(-9)) i.e., approximately 0.5% for W-H 32 with four simultaneous users, and about 1 x 10(-4)% for W-H 64 with eight simultaneous users.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

Although nontechnical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy and to characterize possible illegal consumers has not attracted much attention in this context. In this paper, we focus on this problem by reviewing three evolutionary-based techniques for feature selection, and we also introduce one of them in this context. The results demonstrated that selecting the most representative features can improve a lot of the classification accuracy of possible frauds in datasets composed by industrial and commercial profiles.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.