Implementation of the e-SUS Primary Care Strategy: an analysis based on official data

OBJETIVO Analisar a implantação da estratégia e-SUS Atenção Básica (e-SUS AB) no Brasil entre os anos iniciais do sistema, de 2013 até 2019. MÉTODOS Trata-se de um estudo quantitativo, descritivo e exploratório. Foram considerados os dados oficiais do Ministério da Saúde, enviados pelos municípios brasileiros, no período de abril de 2013 a dezembro de 2019. Os municípios foram categorizados como ‘não implantado’, ‘implantação inicial’, ‘implantação parcial’ e ‘implantado’, de acordo com os critérios definidos neste estudo. Verificou-se também se o tipo de município, segundo a classificação do IBGE, influenciou no grau de implantação da estratégia e-SUS AB. Foram realizadas análises descritivas e investigada a associação entre os graus de implantação do e-SUS AB e a tipologia da classificação e caracterização dos espaços rurais e urbanos do IBGE. RESULTADOS O grau de implantação aumentou no período analisado. A situação de implantação da estratégia e-SUS AB, em 2019, foi ‘implantado’ em 20,2% (1.117) dos municípios, ‘implantação parcial’ em 32,9% (1.819), ‘implantação inicial’ 39,1% (2.159) e a situação ‘não implantado’ foi atribuída em 7,8% (432). As regiões Sul e Sudeste apresentaram a melhor situação de implantação em todos os anos e os estados do Rio Grande do Sul, São Paulo e Santa Catarina alcançaram um maior percentual de municípios com a situação ‘implantado’ em 2019. CONCLUSÕES Houve avanço na implantação da estratégia e-SUS AB ao longo dos anos. A maior parte dos municípios encontra-se entre o status ‘implantação inicial’ e ‘implantação parcial’. Com isso, conclui-se que ainda são necessários investimentos em recursos tecnológicos, treinamento de profissionais e suporte para qualificar a implantação e uso de sistemas de informação no país, especialmente para a estratégia e-SUS AB.OBJETIVE Analyze the implementation of the strategy e-SUS Atenção Básica (e-SUS AB – e-SUS Primary Care) in Brazil between the first years of the system, from 2013 to 2019. METHODS This is a quantitative, descriptive, and exploratory study. We considered official data from the Ministry of Health, submitted by Brazilian municipalities, in the period from April 2013 to December 2019. We categorized the municipalities as ‘not implemented’, ‘initial implementation’, ‘partial implementation’ and ‘implemented’ according to the criteria defined in this study. We also verified whether the type of municipality, according to the IBGE classification, influenced the degree of implementation of the e-SUS AB strategy. We performed descriptive analyses and investigated the association between the degrees of implementation of e-SUS AB and the typology of the IBGE classification and characterization of rural and urban spaces. RESULTS The implementation increased in the analyzed period. The implementation status of the e-SUS AB strategy in 2019 was ‘implemented’ in 20.2% (1,117) of the municipalities, ‘partial implementation’ in 32.9% (1,819), ‘initial implementation’ in 39.1% (2,159) and ‘not implemented’ in 7.8% (432). The South and Southeast regions presented the best implementation situation in all years, and the states of Rio Grande do Sul, São Paulo and Santa Catarina reached a higher percentage of municipalities with ‘implemented’ status in 2019. CONCLUSIONS We confirmed the progress in the implementation of the e-SUS AB strategy over the years. Most of the municipalities are between the status ‘initial implementation’ and ‘partial implementation’. Therefore, we conclude that investments in technological resources, training of professionals, and support are necessary to qualify the implementation and use of information systems in the country, especially for the e-SUS AB strategy

A support vector machine based method to distinguish long non-coding RNAs from protein coding transcripts

Background: In recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed when analyzing this data is distinguishing between long non-coding RNAs (lncRNAs) and protein coding transcripts (PCTs). Thus, we present a Support Vector Machine (SVM) based method to distinguish lncRNAs from PCTs, using features based on frequencies of nucleotide patterns and ORF lengths, in transcripts. Methods: The proposed method is based on SVM and uses the first ORF relative length and frequencies of nucleotide patterns selected by PCA as features. FASTA files were used as input to calculate all possible features. These features were divided in two sets: (i) 336 frequencies of nucleotide patterns; and (ii) 4 features derived from ORFs. PCA were applied to the first set to identify 6 groups of frequencies that could most contribute to the distinction. Twenty-four experiments using the 6 groups from the first set and the features from the second set where built to create the best model to distinguish lncRNAs from PCTs. Results: This method was trained and tested with human (Homo sapiens), mouse (Mus musculus) and zebrafish (Danio rerio) data, achieving 98.21%, 98.03% and 96.09%, accuracy, respectively. Our method was compared to other tools available in the literature (CPAT, CPC, iSeeRNA, lncRNApred, lncRScan-SVM and FEELnc), and showed an improvement in accuracy by ≈ 3.00%. In addition, to validate our model, the mouse data was classified with the human model, and vice-versa, achieving ≈ 97.80% accuracy in both cases, showing that the model is not overfit. The SVM models were validated with data from rat (Rattus norvegicus), pig (Sus scrofa) and fruit fly (Drosophila melanogaster), and obtained more than 84.00% accuracy in all these organisms. Our results also showed that 81.2% of human pseudogenes and 91.7% of mouse pseudogenes were classified as non-coding. Moreover, our method was capable of re-annotating two uncharacterized sequences of Swiss-Prot database with high probability of being lncRNAs. Finally, in order to use the method to annotate transcripts derived from RNA-seq, previously identified lncRNAs of human, gorilla (Gorilla gorilla) and rhesus macaque (Macaca mulatta) were analyzed, having successfully classified 98.62%, 80.8% and 91.9%, respectively. Conclusions: The SVM method proposed in this work presents high performance to distinguish lncRNAs from PCTs, as shown in the results. To build the model, besides using features known in the literature regarding ORFs, we used PCA to identify features among nucleotide pattern frequencies that contribute the most in distinguishing lncRNAs from PCTs, in reference data sets. Interestingly, models created with two evolutionary distant species could distinguish lncRNAs of even more distant species

Excalibur: An Autonomic Cloud Architecture for Executing Parallel Applications

International audienceIaaS providers often allow the users to specify many re-quirements for their applications. However, users without advanced technical knowledge usually do not provide a good specification of the cloud environment, leading to low per-formance and/or high monetary cost. In this context, the users face the challenges of how to scale cloud-unaware ap-plications without re-engineering them. Therefore, in this paper, we propose and evaluate a cloud architecture, namely Excalibur, to execute applications in the cloud. In our ar-chitecture, the users provide the applications and the archi-tecture sets up the whole environment and adjusts it at run-time accordingly. We executed a genomics workflow in our architecture, which was deployed in Amazon EC2. The ex-periments show that the proposed architecture dynamically scales this cloud-unaware application up to 10 instances, re-ducing the execution time by 73% and the cost by 84% when compared to the execution in the configuration specified by the user

Genótipos do vírus da hepatite C em pacientes em hemodiálise no Distrito Federal, Brasil

Hepatitis C virus (HCV) genotypes and subtypes were determined in hemodialysis patients in the Federal District, Brazil, by sequencing of the 5' noncoding (NC) and nonstructural 5B (NS5B) regions. From 761 patients, 66 anti-HCV-positive samples were tested for HCV RNA. All 51 HCV RNA-positive samples by PCR of the 5' NC region were genotyped as genotypes 1 (90.2%) and 3 (9.8%). Subtype 1a (82.3%) was the most prevalent, followed by subtypes 3a (9.8%), 1b (5.9%) and 1a/1b (2.0%). Forty-two samples could be amplified and genotyped in the NS5B region: 38 (90.5%) as genotype 1, subtypes 1a, and 8 (9.5%) as genotype 3, subtype 3a. For the 42 samples sequenced in both regions, the genotypes and subtypes determined were concordant in 100% and 95.2% of cases, respectively. Two samples presented discrepant results, with the 5' NC region not distinguishing correctly the subtypes 1a and 1b. These findings indicate that the HCV genotype 1, subtype 1a, is the most prevalent among hemodialysis patients in the Federal District, Brazil.Os genótipos e subtipos do vírus da hepatite C (HCV) foram determinados em pacientes em hemodiálise no Distrito Federal, Brasil, pelo sequenciamento das regiões 5' não codificante (NC) e não estrutural 5B (NS5B). De 761 pacientes, 66 amostras anti-HCV positivas foram testadas para RNA-HCV. Todas as 51 amostras RNA-HCV positivas por PCR para a região 5' NC foram genotipadas como dos genótipos 1 (90,2%) e 3 (9,8%). O subtipo 1a (82,3%) foi o mais prevalente, seguido pelos subtipos 3a (9,8%), 1b (5,9%) e 1a/1b (2,0%). Quarenta e duas amostras puderam ser amplificadas e genotipadas na região NS5B: 38 (90,5%) como genótipo 1, subtipo 1a, e 8 (9,5%) como genótipo 3, subtipo 3a. Para as 42 amostras sequenciadas nas duas regiões, os genótipos e subtipos determinados foram concordantes em 100% e 95,2% dos casos, respectivamente. Duas amostras apresentaram resultados discrepantes, sendo que a região 5' NC não diferenciou corretamente os subtipos 1a e 1b. Estes achados indicam que o genótipo 1, subtipo 1a, do HCV é o mais prevalente em pacientes em hemodiálise no Distrito Federal, Brasil

Clustering Rfam 10.1 : clans, families, and classes

The Rfam database contains information about non-coding RNAs emphasizing their secondary structures and organizing them into families of homologous RNA genes or functional RNA elements. Recently, a higher order organization of Rfam in terms of the so-called clans was proposed along with its “decimal release”. In this proposition, some of the families have been assigned to clans based on experimental and computational data in order to find related families. In the present work we investigate an alternative classification for the RNA families based on tree edit distance. The resulting clustering recovers some of the Rfam clans. The majority of clans, however, are not recovered by the structural clustering. Instead, they get dispersed into larger clusters, which correspond roughly to well-described RNA classes such as snoRNAs, miRNAs, and CRISPRs. In conclusion, a structure-based clustering can contribute to the elucidation of the relationships among the Rfam families beyond the realm of clans and classes

Modulation of the immune response by Fonsecaea pedrosoi morphotypes in the course of experimental chromoblastomycosis and their role on inflammatory response chronicity

A common theme across multiple fungal pathogens is their ability to impair the establishment of a protective immune response. Although early inflammation is beneficial in containing the infection, an uncontrolled inflammatory response is detrimental and may eventually oppose disease eradication. Chromoblastomycosis (CBM), a cutaneous and subcutaneous mycosis, caused by dematiaceous fungi, is capable of inducing a chronic inflammatory response. Muriform cells, the parasitic form of Fonsecaea pedrosoi, are highly prevalent in infected tissues, especially in long-standing lesions. In this study we show that hyphae and muriform cells are able to establish a murine CBM with skin lesions and histopathological aspects similar to that found in humans, with muriform cells being the most persistent fungal form, whereas mice infected with conidia do not reach the chronic phase of the disease. Moreover, in injured tissue the presence of hyphae and especially muriform cells, but not conidia, is correlated with intense production of pro-inflammatory cytokines in vivo. Highthroughput RNA sequencing analysis (RNA-Seq) performed at early time points showed a strong up-regulation of genes related to fungal recognition, cell migration, inflammation, apoptosis and phagocytosis in macrophages exposed in vitro to muriform cells, but not conidia. We also demonstrate that only muriform cells required FcγR and Dectin-1 recognition to be internalized in vitro, and this is the main fungal form responsible for the intense inflammatory pattern observed in CBM, clarifying the chronic inflammatory reaction observed in most patients. Furthermore, our findings reveal two different fungal-host interaction strategies according to fungal morphotype, highlighting fungal dimorphism as an important key in understanding the bipolar nature of inflammatory response in fungal infections

Plasmodium vivax gametocytes in the bone marrow of an acute malaria patient and changes in the erythroid miRNA profile

Plasmodium vivax is the most widely distributed human malaria parasite and responsible for large amounts of disease and burden [1]. The presence of P. vivax in the bone marrow was first noticed in the late 19th century [2], and examinations of sternal bone marrow aspirates were performed as an accessory to examinations of peripheral blood in malaria, including P. vivax [3]. Since then, little progress has been made in studying P. vivax infections in this tissue. One report explored accumulation of dyserythropoietic cells in anaemic infected patients [4]. In addition, two case studies reported P. vivax infections after autologous bone marrow transplantation [5][6], and a third one documented an accidental P. vivax infection due to bone marrow transplantation between a malaria-infected donor and a malaria-free receptor [7]. In Brazil, one patient with persistent thrombocytopaenia and an enlarged spleen was diagnosed with chronic P. vivax malaria after the finding of schizonts in the bone marrow aspirate [8]. In all these reports and case studies, however, parasite loads and life stages found in the bone marrow were not investigated, and no molecular tools were available to rule out mixed infections or to characterize specific parasite stages

Draft genome sequence of FT9, a novel Bacillus cereus strain isolated from a Brazilian Thermal Spring

O presente trabalho trata das bactérias formadoras da esporos, incluindo um patógeno presente na intoxicação alimentar e sistêmica e em infecções locais, trazendo uma sequência do genoma FT9

Morphological and Transcriptional Changes in Human Bone Marrow During Natural Plasmodium vivax Malaria Infections.

--- - Label: BACKGROUND NlmCategory: BACKGROUND content: The presence of Plasmodium vivax malaria parasites in the human bone marrow (BM) is still controversial. However, recent data from a clinical case and experimental infections in splenectomized nonhuman primates unequivocally demonstrated the presence of parasites in this tissue. - Label: METHODS NlmCategory: METHODS content: In the current study, we analyzed BM aspirates of 7 patients during the acute attack and 42 days after drug treatment. RNA extracted from CD71+ cell suspensions was used for sequencing and transcriptomic analysis. - Label: RESULTS NlmCategory: RESULTS content: We demonstrated the presence of parasites in all patients during acute infections. To provide further insights, we purified CD71+ BM cells and demonstrated dyserythropoiesis and inefficient erythropoiesis in all patients. In addition, RNA sequencing from 3 patients showed that genes related to erythroid maturation were down-regulated during acute infections, whereas immune response genes were up-regulated. - Label: CONCLUSIONS NlmCategory: CONCLUSIONS content: This study thus shows that during P. vivax infections, parasites are always present in the BM and that such infections induced dyserythropoiesis and ineffective erythropoiesis. Moreover, infections induce transcriptional changes associated with such altered erythropoietic response, thus highlighting the importance of this hidden niche during natural infections