HIV Reverse Transcriptase Fidelity And Inhibition Are Modulated By Divalent Cations In A Concentration-Dependent Manner In Vitro

Human immunodeficiency virus (HIV) rapidly evolves through generation and selection of mutants that can escape drug therapy. This process is fueled, in part, by the presumably highly error prone polymerase reverse transcriptase (RT). Fidelity of polymerases can be influenced by cation co-factors. Physiologically, magnesium (Mg2+) is used as a co-factor by RT to perform catalysis, however, alternative cations including manganese (Mn2+), cobalt (Co2+), and zinc (Zn2+) can also be used. I demonstrate here that fidelity and inhibition of HIV RT can be influenced differently, in vitro, by divalent cations depending on their concentration. The reported mutation frequency for purified HIV RT in vitro is typically in the 10-4 range (per nucleotide addition), making the enzyme several-fold less accurate than most polymerases. Paradoxically, results examining HIV replication in cells indicate an error frequency that is ~10 times lower than the error rate obtained in the test tube. Here, I reconcile, at least in part, these discrepancies by showing that HIV RT fidelity in vitro is in the same range as cellular results, in physiological concentrations of free Mg2+ (~0.25 mM). At low Mg2+, mutation rates were 5-10 times lower compared to high Mg2+ conditions (5-10 mM). Alternative divalent cations also have a concentration-dependent effect on RT fidelity. Presumed promutagenic cations Mn2+ and Co2+ decreases the fidelity of RT only at elevated concentrations, and Zn2+, when present in low concentration, increases the fidelity of HIV-1 RT by ~2.5 fold compared to Mg2+. HIV-1 and HIV-2 RT inhibition by nucleoside (NRTIs) and non-nucleoside RT inhibitors (NNRTIs) in vitro is also affected by the Mg2+ concentration. NRTIs lacking 3'-OH group inhibited both enzymes less efficiently in low Mg2+ than in high Mg2+; whereas inhibition by the “translocation defective RT inhibitor”, which retains the 3ʹ-OH, was unaffected by Mg2+ concentration, suggesting that NRTIs with a 3ʹ-OH group may be more potent than other NRTIs. In contrast, NNRTIs were more effective in low vs. high Mg2+ conditions. Overall, the studies presented reveal strategies for designing novel RT inhibitors and strongly emphasize the need for studying HIV RT and RT inhibitors in physiologically relevant low Mg2+ conditions.

Errors in preparation and medication management in nursing professionals

The preparation and administration of medications is one of the most common and relevant functions of nurses, demanding great responsibility. Incorrect administration of medication, currently constitutes a serious problem in health services, and is considered one of the main adverse effects suffered by hospitalized patients. Objectives: Identify the major errors in the preparation and administration of medication by nurses in hospitals and know what factors lead to the error occurred in the preparation and administration of medication. Methods: A systematic review of the literature. Deined as inclusion criteria: original scientiic papers, complete, published in the period 2011 to May 2016, the SciELO and LILACS databases, performed in a hospital environment, addressing errors in preparation and administration of medication by nurses and in Portuguese language. After application of the inclusion criteria obtained a sample of 7 articles. Results: The main errors identiied in the pr eparation and administration of medication were wrong dose 71.4%, wrong time 71.4%, 57.2% dilution inadequate, incorrect selection of the patient 42.8% and 42.8% via inadequate. The factors that were most commonly reported by the nursing staff, as the cause of the error was the lack of human appeal 57.2%, inappropriate locations for the preparation of medication 57.2%, the presence of noise and low brightness in preparation location 57, 2%, professionals untrained 42.8%, fatigue and stress 42.8% and inattention 42.8%. Conclusions: The literature shows a high error rate in the preparation and administration of medication for various reasons, making it important that preventive measures of this occurrence are implemented.

A medida e as escalas de avaliação da saúde das populações neonatais e pediátricas : estudo de simulação de Monte Carlo com variáveis ordinais

A investigação na área da saúde e a utilização dos seus resultados tem funcionado como base para a melhoria da qualidade de cuidados, exigindo dos profissionais de saúde conhecimentos na área específica onde desempenham funções, conhecimentos em metodologia de investigação que incluam as técnicas de observação, técnicas de recolha e análise de dados, para mais facilmente serem leitores capacitados dos resultados da investigação. Os profissionais de saúde são observadores privilegiados das respostas humanas à saúde e à doença, podendo contribuir para o desenvolvimento e bem-estar dos indivíduos muitas vezes em situações de grande vulnerabilidade. Em saúde infantil e pediatria o enfoque está nos cuidados centrados na família privilegiando-se o desenvolvimento harmonioso da criança e jovem, valorizando os resultados mensuráveis em saúde que permitam determinar a eficácia das intervenções e a qualidade de saúde e de vida. No contexto pediátrico realçamos as práticas baseadas na evidência, a importância atribuída à pesquisa e à aplicação dos resultados da investigação nas práticas clínicas, assim como o desenvolvimento de instrumentos de mensuração padronizados, nomeadamente as escalas de avaliação, de ampla utilização clínica, que facilitam a apreciação e avaliação do desenvolvimento e da saúde das crianças e jovens e resultem em ganhos em saúde. A observação de forma sistematizada das populações neonatais e pediátricas com escalas de avaliação tem vindo a aumentar, o que tem permitido um maior equilíbrio na avaliação das crianças e também uma observação baseada na teoria e nos resultados da investigação. Alguns destes aspetos serviram de base ao desenvolvimento deste trabalho que pretende dar resposta a 3 objetivos fundamentais. Para dar resposta ao primeiro objetivo, “Identificar na literatura científica, os testes estatísticos mais frequentemente utilizados pelos investigadores da área da saúde infantil e pediatria quando usam escalas de avaliação” foi feita uma revisão sistemática da literatura, que tinha como objetivo analisar artigos científicos cujos instrumentos de recolha de dados fossem escalas de avaliação, na área da saúde da criança e jovem, desenvolvidas com variáveis ordinais, e identificar os testes estatísticos aplicados com estas variáveis. A análise exploratória dos artigos permitiu-nos verificar que os investigadores utilizam diferentes instrumentos com diferentes formatos de medida ordinal (com 3, 4, 5, 7, 10 pontos) e tanto aplicam testes paramétricos como não paramétricos, ou os dois em simultâneo, com este tipo de variáveis, seja qual for a dimensão da amostra. A descrição da metodologia nem sempre explicita se são cumpridas as assunções dos testes. Os artigos consultados nem sempre fazem referência à distribuição de frequência das variáveis (simetria/assimetria) nem à magnitude das correlações entre os itens. A leitura desta bibliografia serviu de suporte à elaboração de dois artigos, um de revisão sistemática da literatura e outro de reflexão teórica. Apesar de terem sido encontradas algumas respostas às dúvidas com que os investigadores e os profissionais, que trabalham com estes instrumentos, se deparam, verifica-se a necessidade de desenvolver estudos de simulação que confirmem algumas situações reais e alguma teoria já existente, e trabalhem outros aspetos nos quais se possam enquadrar os cenários reais de forma a facilitar a tomada de decisão dos investigadores e clínicos que utilizam escalas de avaliação. Para dar resposta ao segundo objetivo “Comparar a performance, em termos de potência e probabilidade de erro de tipo I, das 4 estatísticas da MANOVA paramétrica com 2 estatísticas da MANOVA não paramétrica quando se utilizam variáveis ordinais correlacionadas, geradas aleatoriamente”, desenvolvemos um estudo de simulação, através do Método de Monte Carlo, efetuado no Software R. O delineamento do estudo de simulação incluiu um vetor com 3 variáveis dependentes, uma variável independente (fator com três grupos), escalas de avaliação com um formato de medida com 3, 4, 5, e 7 pontos, diferentes probabilidades marginais (p1 para distribuição simétrica, p2 para distribuição assimétrica positiva, p3 para distribuição assimétrica negativa e p4 para distribuição uniforme) em cada um dos três grupos, correlações de baixa, média e elevada magnitude (r=0.10, r=0.40, r=0.70, respetivamente), e seis dimensões de amostras (n=30, 60, 90, 120, 240, 300). A análise dos resultados permitiu dizer que a maior raiz de Roy foi a estatística que apresentou estimativas de probabilidade de erro de tipo I e de potência de teste mais elevadas. A potência dos testes apresenta comportamentos diferentes, dependendo da distribuição de frequência da resposta aos itens, da magnitude das correlações entre itens, da dimensão da amostra e do formato de medida da escala. Tendo por base a distribuição de frequência, considerámos três situações distintas: a primeira (com probabilidades marginais p1,p1,p4 e p4,p4,p1) em que as estimativas da potência eram muito baixas, nos diferentes cenários; a segunda situação (com probabilidades marginais p2,p3,p4; p1,p2,p3 e p2,p2,p3) em que a magnitude das potências é elevada, nas amostras com dimensão superior ou igual a 60 observações e nas escalas com 3, 4,5 pontos e potências de magnitude menos elevada nas escalas com 7 pontos, mas com a mesma ma magnitude nas amostras com dimensão igual a 120 observações, seja qual for o cenário; a terceira situação (com probabilidades marginais p1,p1,p2; p1,p2,p4; p2,p2,p1; p4,p4,p2 e p2,p2,p4) em que quanto maiores, a intensidade das correlações entre itens e o número de pontos da escala, e menor a dimensão das amostras, menor a potência dos testes, sendo o lambda de Wilks aplicado às ordens mais potente do que todas as outra s estatísticas da MANOVA, com valores imediatamente a seguir à maior raiz de Roy. No entanto, a magnitude das potências dos testes paramétricos e não paramétricos assemelha-se nas amostras com dimensão superior a 90 observações (com correlações de baixa e média magnitude), entre as variáveis dependentes nas escalas com 3, 4 e 5 pontos; e superiores a 240 observações, para correlações de baixa intensidade, nas escalas com 7 pontos. No estudo de simulação e tendo por base a distribuição de frequência, concluímos que na primeira situação de simulação e para os diferentes cenários, as potências são de baixa magnitude devido ao facto de a MANOVA não detetar diferenças entre grupos pela sua similaridade. Na segunda situação de simulação e para os diferentes cenários, a magnitude das potências é elevada em todos os cenários cuja dimensão da amostra seja superior a 60 observações, pelo que é possível aplicar testes paramétricos. Na terceira situação de simulação, e para os diferentes cenários quanto menor a dimensão da amostra e mais elevada a intensidade das correlações e o número de pontos da escala, menor a potência dos testes, sendo a magnitude das potências mais elevadas no teste de Wilks aplicado às ordens, seguido do traço de Pillai aplicado às ordens. No entanto, a magnitude das potências dos testes paramétricos e não paramétricos assemelha-se nas amostras com maior dimensão e correlações de baixa e média magnitude. Para dar resposta ao terceiro objetivo “Enquadrar os resultados da aplicação da MANOVA paramétrica e da MANOVA não paramétrica a dados reais provenientes de escalas de avaliação com um formato de medida com 3, 4, 5 e 7 pontos, nos resultados do estudo de simulação estatística” utilizaram-se dados reais que emergiram da observação de recém-nascidos com a escala de avaliação das competências para a alimentação oral, Early Feeding Skills (EFS), o risco de lesões da pele, com a Neonatal Skin Risk Assessment Scale (NSRAS), e a avaliação da independência funcional em crianças e jovens com espinha bífida, com a Functional Independence Measure (FIM). Para fazer a análise destas escalas foram realizadas 4 aplicações práticas que se enquadrassem nos cenários do estudo de simulação. A idade, o peso, e o nível de lesão medular foram as variáveis independentes escolhidas para selecionar os grupos, sendo os recém-nascidos agrupados por “classes de idade gestacional” e por “classes de peso” as crianças e jovens com espinha bífida por “classes etárias” e “níveis de lesão medular”. Verificou-se um bom enquadramento dos resultados com dados reais no estudo de simulação.

Classificação de esquizofrenia com base em máquinas de suporte vetorial aplicadas a características de imagens de ressonância magnética

Dissertação (mestrado)—Universidade de Brasília, Faculdade Gama, Programa de Pós-Graduação em Engenharia Biomédica, 2015.

Development of a novel platform for high-throughput gene design and artificial gene synthesis to produce large libraries of recombinant venom peptides for drug discovery

Tese de Doutoramento em Ciências Veterinárias na Especialidade de Ciências Biológicas e Biomédicas

Using dysphonic voice to characterize speaker's biometry

Phonation distortion leaves relevant marks in a speaker's biometric profile. Dysphonic voice production may be used for biometrical speaker characterization. In the present paper phonation features derived from the glottal source (GS) parameterization, after vocal tract inversion, is proposed for dysphonic voice characterization in Speaker Verification tasks. The glottal source derived parameters are matched in a forensic evaluation framework defining a distance-based metric specification. The phonation segments used in the study are derived from fillers, long vowels, and other phonation segments produced in spontaneous telephone conversations. Phonated segments from a telephonic database of 100 male Spanish native speakers are combined in a 10-fold cross-validation task to produce the set of quality measurements outlined in the paper. Shimmer, mucosal wave correlate, vocal fold cover biomechanical parameter unbalance and a subset of the GS cepstral profile produce accuracy rates as high as 99.57 for a wide threshold interval (62.08-75.04%). An Equal Error Rate of 0.64 % can be granted. The proposed metric framework is shown to behave more fairly than classical likelihood ratios in supporting the hypothesis of the defense vs that of the prosecution, thus ofering a more reliable evaluation scoring. Possible applications are Speaker Verification and Dysphonic Voice Grading.

Conversação homem-máquina. Caracterização e avaliação do estado actual das soluções de speech recognition, speech synthesis e sistemas de conversação homem-máquina

A comunicação verbal humana é realizada em dois sentidos, existindo uma compreensão de ambas as partes que resulta em determinadas considerações. Este tipo de comunicação, também chamada de diálogo, para além de agentes humanos pode ser constituído por agentes humanos e máquinas. A interação entre o Homem e máquinas, através de linguagem natural, desempenha um papel importante na melhoria da comunicação entre ambos. Com o objetivo de perceber melhor a comunicação entre Homem e máquina este documento apresenta vários conhecimentos sobre sistemas de conversação Homemmáquina, entre os quais, os seus módulos e funcionamento, estratégias de diálogo e desafios a ter em conta na sua implementação. Para além disso, são ainda apresentados vários sistemas de Speech Recognition, Speech Synthesis e sistemas que usam conversação Homem-máquina. Por último são feitos testes de performance sobre alguns sistemas de Speech Recognition e de forma a colocar em prática alguns conceitos apresentados neste trabalho, é apresentado a implementação de um sistema de conversação Homem-máquina. Sobre este trabalho várias ilações foram obtidas, entre as quais, a alta complexidade dos sistemas de conversação Homem-máquina, a baixa performance no reconhecimento de voz em ambientes com ruído e as barreiras que se podem encontrar na implementação destes sistemas.

Performance of LTE-V2V for Cooperative Awareness

The large scale development of an Intelligent Transportation System is very close. The main component of such a smart environment is the network that provides connectivity for all vehicles. Public safety is the most demanding application because requires a fast, reliable and secure communication. Although IEEE 802.11p is presently the only full wireless standard for vehicular communications, recent advancements in 3GPP LTE provide support to direct communications and the ongoing activities are also addressing the vehicle to vehicle case. This thesis focuses on the resource allocation procedures and performance of LTE-V2V. To this aim, a MATLAB simulator has been implemented and results have been obtained adopting different mobility models for both in-coverage and out-of-coverage scenarios.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

Voice conversion with pre-trained representations for audio anonymization

The recording and processing of voice data raises increasing privacy concerns for users and service providers. One way to address these issues is to move processing on the edge device closer to the recording so that potentially identifiable information is not transmitted over the internet. However, this is often not possible due to hardware limitations. An interesting alternative is the development of voice anonymization techniques that remove individual speakers characteristics while preserving linguistic and acoustic information in the data. In this work, a state-of-the-art approach to sequence-to-sequence speech conversion, ini- tially based on x-vectors and bottleneck features for automatic speech recognition, is explored to disentangle the two acoustic information using different pre-trained speech and speakers representation. Furthermore, different strategies for selecting target speech representations are analyzed. Results on public datasets in terms of equal error rate and word error rate show that good privacy is achieved with limited impact on converted speech quality relative to the original method.

Logarithmical hopping encoding: a low computational complexity algorithm for image compression

LHE (logarithmical hopping encoding) is a computationally efficient image compression algorithm that exploits the Weber–Fechner law to encode the error between colour component predictions and the actual value of such components. More concretely, for each pixel, luminance and chrominance predictions are calculated as a function of the surrounding pixels and then the error between the predictions and the actual values are logarithmically quantised. The main advantage of LHE is that although it is capable of achieving a low-bit rate encoding with high quality results in terms of peak signal-to-noise ratio (PSNR) and image quality metrics with full-reference (FSIM) and non-reference (blind/referenceless image spatial quality evaluator), its time complexity is O( n) and its memory complexity is O(1). Furthermore, an enhanced version of the algorithm is proposed, where the output codes provided by the logarithmical quantiser are used in a pre-processing stage to estimate the perceptual relevance of the image blocks. This allows the algorithm to downsample the blocks with low perceptual relevance, thus improving the compression rate. The performance of LHE is especially remarkable when the bit per pixel rate is low, showing much better quality, in terms of PSNR and FSIM, than JPEG and slightly lower quality than JPEG-2000 but being more computationally efficient.

Theoretic analysis of IEEE 802.11 rate adaptation algorithm SampleRate

In this paper we investigate rate adaptation algorithm SampleRate, which spends a fixed time on bit-rates other than the currently measured best bit-rate. A simple but effective analytic model is proposed to study the steady-state behavior of the algorithm. Impacts of link condition, channel congestion and multi-rate retry on the algorithm performance are modeled. Simulations validate the model. It is also observed there is still a large performance gap between SampleRate and optimal scheme in case of high frame collision probability.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

A Study of Ordered Gene Problems Featuring DNA Error Correction and DNA Fragment Assembly with a Variety of Heuristics, Genetic Algorithm Variations, and Dynamic Representations

Ordered gene problems are a very common classification of optimization problems. Because of their popularity countless algorithms have been developed in an attempt to find high quality solutions to the problems. It is also common to see many different types of problems reduced to ordered gene style problems as there are many popular heuristics and metaheuristics for them due to their popularity. Multiple ordered gene problems are studied, namely, the travelling salesman problem, bin packing problem, and graph colouring problem. In addition, two bioinformatics problems not traditionally seen as ordered gene problems are studied: DNA error correction and DNA fragment assembly. These problems are studied with multiple variations and combinations of heuristics and metaheuristics with two distinct types or representations. The majority of the algorithms are built around the Recentering- Restarting Genetic Algorithm. The algorithm variations were successful on all problems studied, and particularly for the two bioinformatics problems. For DNA Error Correction multiple cases were found with 100% of the codes being corrected. The algorithm variations were also able to beat all other state-of-the-art DNA Fragment Assemblers on 13 out of 16 benchmark problem instances.