926 resultados para Human genome, CpG islands, Markov models, DNA walk
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Tese de Doutoramento, Ciências Económicas e Empresariais (especialidade de Economia), 18 de Junho de 2015, Universidade dos Açores
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Specimens from cervical dysplasias or carcinomas and genital condylomata acuminata were retrospectively analysed by in situ hybridization (ISH) with bioti-nylated DNA probes for human papillomavirus (HPV) types 6, 11, 16 and 18. In the control group no case was positive for HPV DNA. In mild/moderate dysplasias, 4 cases (14%) were positive for HPV 6 or 11 and 2 cases (7%), for HPV 16. In the severe dysplasia/in situ carcinoma group, 9 cases (31%) showed presence of DNA of HPV types 16 or 18. Six invasive carcinomas (20%) were positive for HPV type 16 or 18. Among condylomata acuminata, 22 cases (73%) were positive for HPV types 6 or 11. In all ISH-positive cases only one viral type was detected. No correlation between HPV DNA positivity and histological findings of HPV infection was observed. Although less sensitive than some other molecular biology techniques, in situ hybridization with biotinylated DNA probes proved to be simple and useful for detecting and typing HPV in samples routinely received for histopathological analysis.
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We describe a case of human T-lymphotropic virus type I associated myelopathy in a 50-year old woman in Nigeria. The patient presented with progressive loss of tone to the two lower limbs and later inability to walk. The HTLV-I antibody presence in the plasma collected from the patient was repeatedly detected by enzyme immunoassays (Abbott HTLV-I EIA and Coulter SELECT-HTLV I/II) and confirmed by Western blot technique. In addition, HTLV-I DNA was amplified from the genomic DNA isolated from the peripheral blood mononuclear cells of the patient by the polymerase chain reaction technique. This finding is significant being the first report of association of HTLV-I with myelopathy in Nigeria.
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Abdominal and cerebral angiostrongyliasis are two important infections produced by metastrongylid worms, the former occurring in Central and South America and the later in Asia and Pacific Islands. Drug treatment is a challenge since the worms and its evolving larvae live or migrate inside vessels and efficient killing of the parasites may produce more severe lesions. Larvicidal effect of certain drugs appears to be more easily accomplished but this outcome is not useful in abdominal angiostrongyliasis since clinical manifestations appear to result from sexual maturation of the worms. We review the drug trials in murine experimental models and conclude that most of them could not be considered good candidates for treatment of human infection, except for PF1022A, pyrantel and flubendazole.
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Toxic effects of ultraviolet (UV) radiation on skin include protein and lipid oxidation, and DNA damage. The latter is known to play a major role in photocarcinogenesis and photoaging. Many plant extracts and natural compounds are emerging as photoprotective agents. Castanea sativa leaf extract is able to scavenge several reactive species that have been associated to UV-induced oxidative stress. The aim of this work was to analyze the protective effect of C. sativa extract (ECS) at different concentrations (0.001, 0.01, 0.05 and 0.1 μg/mL) against the UV mediated-DNA damage in a human keratinocyte cell line (HaCaT). For this purpose, the cytokinesis-block micronucleus assay was used. Elucidation of the protective mechanism was undertaken regarding UV absorption, influence on 1O2 mediated effects or NRF2 activation. ECS presented a concentration-dependent protective effect against UV-mediated DNA damage in HaCaT cells. The maximum protection afforded (66.4%) was achieved with the concentration of 0.1 μg/mL. This effect was found to be related to a direct antioxidant effect (involving 1O2) rather than activation of the endogenous antioxidant response coordinated by NRF2. Electrochemical studies showed that the good antioxidant capacity of the ECS can be ascribed to the presence of a pool of different phenolic antioxidants. No genotoxic or phototoxic effects were observed after incubation of HaCaT cells with ECS (up to 0.1 μg/mL). Taken together these results reinforce the putative application of this plant extract in the prevention/minimization of UV deleterious effects on skin.
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Dissertation to obtain master degree in Genética Molecular e Biomedicina
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INTRODUCTION: Human herpesviruses are frequently associated with orofacial diseases in humans (HSV-1, EBV, CMV and HHV-8), some can also cause systemic disease (CMV and HHV-8). The transmission of these viruses occurs by contact with infected secretions, especially saliva. Human immunodeficiency virus infection is associated with an increased risk of HHVs and related diseases. METHODS: This work aimed to detect HSV-1, EBV, CMV and HHV-8 DNA in saliva of HIV-infected patients from Teresina, northeast Brazil, by PCR and compare these findings with age and sex matched HIV-seronegative individuals. RESULTS: No difference in prevalence was verified between HHV detection in the saliva of HIV-seropositive individuals and controls. The individual frequencies of these viruses in these two populations were different. HIV seropositivity correlated positively with the presence of CMV (OR: 18.2, p= 0.00032) and EBV (OR: 3.44, p= 0.0081). No association between CD4 counts and the prevalence of HHVs in the saliva was observed; however, a strong association was determined between seropositivity and the presence of multiple HHV DNAs in saliva (OR: 4.83, p = 0.0028). CONCLUSIONS: These findings suggest the asymptomatic salivary shedding of HHVs is a common event between HIV-seropositive and seronegative individuals from Teresina, Piauí, Brazil, and, especially for HIV-seropositive patients, saliva is a risk factor for the acquisition/transmission of multiple HHVs.
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INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.
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The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.
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The introduction of molecular biology techniques, especially of DNA analysis, for human identification is a recent advance in legal medicine. Substantial effort has continuously been made in an attempt to identify cadavers and human remains after wars, socio-political problems and mass disasters. In addition, because of the social dynamics of large cities, there are always cases of missing people, as well as unidentified cadavers and human remains that are found. In the last few years, there has also been an increase in requests for exhumation of human remains in order to determine genetic relationships in civil suits and court action. The authors provide an extensive review of the literature regarding the use of this new methodology for human identification of ancient or recent bones.
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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
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In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.
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High-risk human papillomavirus (hrHPV) is an essential cause of cervical carcinoma and is also strongly related to anal cancer development. The hrHPV E6 oncoprotein plays a major role in carcinogenesis. We aimed to evaluate the frequency of hrHPV DNA and E6 oncoprotein in the anuses of women with cervical carcinoma. We analyzed 117 women with cervical cancer and 103 controls for hrHPV and the E6 oncogene. Positive test results for a cervical carcinoma included 66.7 % with hrHPV-16 and 7.7 % with hrHPV-18. One case tested positive for both HPV variants (0.9 %). The samples from the anal canal were positive for HPV-16 in 59.8 % of the cases. Simultaneous presence of HPV in the cervix and anal canal was found in 53.8 % of the cases. Regarding expression of E6 RNA, positivity for HPV-16 in the anal canal was found in 21.2 % of the cases, positivity for HPV-16 in the cervix was found in 75.0 %, and positivity for HPV-18 in the cervix was found in 1.9 %. E6 expression in both the cervix and anal canal was found in 19.2 % of the cases. In the controls, 1 % tested positive for HPV-16 and 0 % for HPV-18. Anal samples from the controls showed a hrHPV frequency of 4.9 % (only HPV16). The presence of hrHPV in the anal canal of women with cervical cancer was detected at a high frequency. We also detected E6 RNA expression in the anal canal of women with cervical cancer, suggesting that these women are at risk for anal hrHPV infection.
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Invasive cervical cancer (ICC) is the third most frequent cancer among women worldwide and is associated with persistent infection by carcinogenic human papillomaviruses (HPVs). The combination of large populations of viral progeny and decades of sustained infection may allow for the generation of intra-patient diversity, in spite of the assumedly low mutation rates of PVs. While the natural history of chronic HPVs infections has been comprehensively described, within-host viral diversity remains largely unexplored. In this study we have applied next generation sequencing to the analysis of intra-host genetic diversity in ten ICC and one condyloma cases associated to single HPV16 infection. We retrieved from all cases near full-length genomic sequences. All samples analyzed contained polymorphic sites, ranging from 3 to 125 polymorphic positions per genome, and the median probability of a viral genome picked at random to be identical to the consensus sequence in the lesion was only 40%. We have also identified two independent putative duplication events in two samples, spanning the L2 and the L1 gene, respectively. Finally, we have identified with good support a chimera of human and viral DNA. We propose that viral diversity generated during HPVs chronic infection may be fueled by innate and adaptive immune pressures. Further research will be needed to understand the dynamics of viral DNA variability, differentially in benign and malignant lesions, as well as in tissues with differential intensity of immune surveillance. Finally, the impact of intralesion viral diversity on the long-term oncogenic potential may deserve closer attention.
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The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.