BackgroundFemale breast cancer is the major cause of death by cancer in western countries. Efforts in Computer Vision have been made in order to improve the diagnostic accuracy by radiologists. Some methods of lesion diagnosis in mammogram images were developed based in the technique of principal component analysis which has been used in efficient coding of signals and 2D Gabor wavelets used for computer vision applications and modeling biological vision.MethodsIn this work, we present a methodology that uses efficient coding along with linear discriminant analysis to distinguish between mass and non-mass from 5090 region of interest from mammograms.ResultsThe results show that the best rates of success reached with Gabor wavelets and principal component analysis were 85.28% and 87.28%, respectively. In comparison, the model of efficient coding presented here reached up to 90.07%.ConclusionsAltogether, the results presented demonstrate that independent component analysis performed successfully the efficient coding in order to discriminate mass from non-mass tissues. In addition, we have observed that LDA with ICA bases showed high predictive performance for some datasets and thus provide significant support for a more detailed clinical investigation.

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Objetivo: investigar as causas de óbitos maternos em uma Regional de Saúde do Maranhão. Método: estudo retrospectivo, exploratório dos óbitos maternos ocorridos entre 2007 e 2011. Foram analisados os óbitos de mulheres na faixa etária entre 10 a 49 anos durante o ciclo gravídico-puerperal. Resultados: Dentre as causas mais frequentes, a síndrome hipertensiva gestacional (SHG) apresentou-se como a principal (37,9%), seguida da síndrome hemorrágica (31,1%) e outras causas (31%). Conclusão: a RMM na regional de saúde estudada ainda é elevada, e, independentemente de ter sido subestimada, é urgente a adoção de medidas para a sua redução, sobretudo no que concerne a prevenção e controle da SHG, principal causa de mortalidade materna nesta regional.

We evaluate the genetic characterization of 132 HIV‐1 pol sequences from children and adolescents undergoing antiretroviral therapy in Northeast Brazil. Phylogenetic and recombination analyses were performed using the maximum likelihood method using SeaView version 4 and SIMPLOT software. Most individuals harbored HIV‐1 B (84.8%) and BF recombinants (9.8%), although other non‐B subtypes were detected: HIV‐1 C (1.5%), HIV‐1 F (2.4%), and BC recombinants (1.5%). Antiretroviral resistance was 47% (95% confidence interval [CI]: 38.7%–55.4%). Non‐nucleoside reverse transcriptase inhibitors (NNRTIs) showed higher frequencies of primary mutations, with 40.9% (95% CI: 32.9%–49.4%), followed by nucleoside reverse transcriptase inhibitors (NRTI) and protease inhibitors (PIs) with 34.8% (95% CI: 27.3–43.3) and 6.1% (95% CI: 3.1%–11.5%), respectively. Among NRTIs, higher resistance levels were observed for abacavir, emtricitabine, and lamivudine; for NNRTI, nevirapine and efavirenz. The most common primary mutations found were M184V (29.5%), K103N (25%), M41L (9.8%), T215Y (8.3%), and G190A (8.3%). Our findings highlight the importance of surveillance of resistance mutations, which contributes to the continuous updating and implementation of preventive measures to decrease mother‐to‐child‐transmission and transmitted drug resistance.

The HIV-1 epidemic in Brazil has been growing in northeast and north regions, particularly an increase in AIDS cases among the younger male population has been observed. This study aims to characterize the HIV-1 genetic diversity and to evaluate its antiretroviral resistance profile among individuals presenting virological failure in the state of Maranhão-Brazil. HIV-1 pol gene sequences from 633 patients on antiretroviral therapy were obtained from the Department of Surveillance, Prevention and Control of Sexually Transmitted Infections, HIV/AIDS and Viral Hepatitis of the Brazilian Ministry of Health. Phylogenetic and recombination analyses were performed to characterize viral genetic diversity. The presence of antiretroviral resistance mutations was assessed using the HIV Drug Resistance Database online platform of Stanford University. A predominance of subtype B (84.5%) was observed, followed by recombinant BF (9.5%), where more than half of the sequences were dispersed in 3 clusters. Antiretroviral resistance was detected in 74.1% of the sequences, and it was significantly higher for nucleoside analogue reverse-transcriptase inhibitors (NRTIs) than for non-nucleoside analogue reverse-transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs). Inference of putative transmissions clusters identified 11 clusters with 22 query sequences (22/633, 3.5%). Thus, we conclude that continuous monitoring of the molecular epidemiology of HIV-1 is essential for prevention strategies, epidemic control, and treatment adequacy.