Ney Lemke

Recebemos com entusiasmo esse livro que registra a continuidade dos estudos propositivos do Projeto Métricas, que se desloca, agora, para a pesquisa dos saberes e das práticas das instituições de ensino e pesquisa. Estão em plena execução estudos relativos aos fatores que condicionam os resultados de projetos de pesquisas, seus impactos científicos e sociais, assim como um curso de especialização na divulgação de ciências para jornalistas profissionais. Isso exige o monitoramento permanente das metodologias de comparações globais, para entender e familiarizar-se com o uso de métricas de resultados e de impactos que permita aprimorar seu desempenho e reconhecimento no país e no exterior. A identificação, em cada universidade, dos pontos fortes e dos que exigem aprimoramento e uma política de avaliação compatível se completarão com o acesso a uma plataforma digital de acompanhamento, que registrará em tempo real informações a respeito da evolução do desempenho acadêmico. É assim que atuam as maiores e melhores instituições de ensino superior e pesquisa em todo o mundo. Temos a expectativa de que os conteúdos deste livro sejam levados à prática com êxito, consoante foram concebidos, e de que as instituições passarão a dispor de um instrumento novo e eficaz de prestação de contas à sociedade que paga impostos e mantém o sistema publico de ensino superior e pesquisa científica. Cada instituição adaptará as recomendações do Projeto à sua cultura institucional, alinhada ao monitoramento e à interpretação das metodologias adotadas em comparações internacionais.

A evasão é um tema de interesse mundial na área da educação, contudo o entendimento atual sobre o fenômeno é ainda insuficiente, sobretudo quando o objetivo é avaliar políticas efetivas de evasão. Neste artigo o percentual anual de evasão da Unesp é avaliado com base na adoção da política de reserva de vagas. Existem três possibilidades de ingresso - sistema universal (SU), quota por ter estudado em escola pública (EP) e quota por ser PPI (pretos, pardos, indígenas). Os dados foram segmentados por curso e ano de ingresso. A Unesp tem campus em 24 cidades, que reúnem 34 unidades e abrigam 136 diferentes cursos de Graduação. O ingresso para estes cursos é realizado por meio de vestibular com 186 diferentes opções em 63 carreiras. Uma comparação das taxas de evasão permite observar que elas podem depender do modo de ingresso, mas isso ocorre de forma variada ao longo do tempo e depende da área do curso, não sendo significativo. Verificou-se um decréscimo consistente da taxa de evasão global e por categoria de ingresso.

Nile tilapia is the third most cultivated fish worldwide and a novel model species for evolutionary studies. Aiming to improve productivity and contribute to the selection of traits of economic impact, biotechnological approaches have been intensively applied to species enhancement. In this sense, recent studies have focused on the multiple roles played by microRNAs (miRNAs) in the post-transcriptional regulation of protein-coding genes involved in the emergence of phenotypes with relevance for aquaculture. However, there is still a growing demand for a reference resource dedicated to integrating Nile Tilapia miRNA information, obtained from both experimental and in silico approaches, and facilitating the analysis and interpretation of RNA sequencing data. Here, we present an open repository dedicated to Nile Tilapia miRNAs: the “miRTil database”. The database stores data on 734 mature miRNAs identified in 11 distinct tissues and five key developmental stages. The database provides detailed information about miRNA structure, genomic context, predicted targets, expression profiles, and relative 5p/3p arm usage. Additionally, miRTil also includes a comprehensive pre-computed miRNA-target interaction network containing 4936 targets and 19,580 interactions.

Microbiome–host interactions play significant roles in health and in various diseases including autoimmune disorders. Uncovering these inter-kingdom cross-talks propels our understanding of disease pathogenesis and provides useful leads on potential therapeutic targets. Despite the biological significance of microbe–host interactions, there is a big gap in understanding the downstream effects of these interactions on host processes. Computational methods are expected to fill this gap by generating, integrating, and prioritizing predictions—as experimental detection remains challenging due to feasibility issues. Here, we present MicrobioLink, a computational pipeline to integrate predicted interactions between microbial and host proteins together with host molecular networks. Using the concept of network diffusion, MicrobioLink can analyse how microbial proteins in a certain context are influencing cellular processes by modulating gene or protein expression. We demonstrated the applicability of the pipeline using a case study. We used gut metaproteomic data from Crohn’s disease patients and healthy controls to uncover the mechanisms by which the microbial proteins can modulate host genes which belong to biological processes implicated in disease pathogenesis. MicrobioLink, which is agnostic of the microbial protein sources (bacterial, viral, etc.), is freely available on GitHub.

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.

Background: Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, and the number of common predicted essential proteins by different methods is very small. Results: In this paper, an ensemble framework is proposed which integrates gene expression data and protein-protein interaction networks (PINs). It aims to improve the prediction accuracy of basic centrality measures. The idea behind this ensemble framework is that different protein-protein interactions (PPIs) may show different contributions to protein essentiality. Five standard centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and subgraph centrality) are integrated into the ensemble framework respectively. We evaluated the performance of the proposed ensemble framework using yeast PINs and gene expression data. The results show that it can considerably improve the prediction accuracy of the five centrality measures individually. It can also remarkably increase the number of common predicted essential proteins among those predicted by each centrality measure individually and enable each centrality measure to find more low-degree essential proteins. Conclusions: This paper demonstrates that it is valuable to differentiate the contributions of different PPIs for identifying essential proteins based on network topological characteristics. The proposed ensemble framework is a successful paradigm to this end.

Background: The apicomplexan parasiteNeospora caninumcauses neosporosis, a disease that leads to abortion or stillbirth in cattle, generating an economic impact on the dairy and beef cattle trade. As an obligatory intracellular parasite,N. caninumneeds to invade the host cell in an active manner to survive. The increase in parasite cytosolic Ca²⁺upon contact with the host cell mediates critical events, including the exocytosis of phylum-specific secretory organelles and the activation of the parasite invasion motor. Because invasion is considered a requirement for pathogen survival and replication within the host, the identification of secreted proteins (secretome) involved in invasion may be useful to reveal interesting targets for therapeutic intervention.Methods: To chart the currently missingN. caninumsecretome, we employed mass spectrometry-based proteomics to identify proteins present in theN. caninumtachyzoite using two different approaches. The first approach was identifying the proteins present in the tachyzoite-secreted fraction (ESA). The second approach was determining the relative quantification through peptide stable isotope labelling of the tachyzoites submitted to an ethanol secretion stimulus (dischargedtachyzoite), expecting to identify the secreted proteins among the down-regulated group.Results: As a result, 615 proteins were identified at ESA and 2,011 proteins quantified at thedischargedtachyzoite. We have analysed the connection between the secreted and the down-regulated proteins and searched for putative regulators of the secretion process among the up-regulated proteins. An interaction network was built by computational prediction involving the up- and down-regulated proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000424.Conclusions: The comparison between the protein abundances in ESA and their measure in thedischargedtachyzoite allowed for a more precise identification of the most likely secreted proteins. Information from the network interaction and up-regulated proteins was important to recognise key proteins potentially involved in the metabolic regulation of secretion. Our results may be helpful to guide the selection of targets to be investigated againstNeospora caninumand other Apicomplexan organisms.

Background: Sleep spindles, as detected on scalp electroencephalography (EEG), are considered to be markers of thalamo-cortical network integrity. Since obstructive sleep apnea (OSA) is a known cause of brain dysfunction, the aim of this study was to investigate sleep spindle frequency distribution in OSA. Seven non-OSA subjects and 21 patients with OSA (11 mild and 10 moderate) were studied. A matching pursuit procedure was used for automatic detection of fast (≥13Hz) and slow (Hz) spindles obtained from 30min samples of NREM sleep stage 2 taken from initial, middle and final night thirds (sections I, II and III) of frontal, central and parietal scalp regions.Results: Compared to non-OSA subjects, Moderate OSA patients had higher central and parietal slow spindle percentage (SSP) in all night sections studied, and higher frontal SSP in sections II and III. As the night progressed, there was a reduction in central and parietal SSP, while frontal SSP remained high. Frontal slow spindle percentage in night section III predicted OSA with good accuracy, with OSA likelihood increased by 12.1%for every SSP unit increase (OR 1.121, 95% CI 1.013 - 1.239, p=0.027).Conclusions: These results are consistent with diffuse, predominantly frontal thalamo-cortical dysfunction during sleep in OSA, as more posterior brain regions appear to maintain some physiological spindle frequency modulation across the night. Displaying changes in an opposite direction to what is expected from the aging process itself, spindle frequency appears to be informative in OSA even with small sample sizes, and to represent a sensitive electrophysiological marker of brain dysfunction in OSA.

Background: The modeling of interactions among transcription factors (TFs) and their respective target genes (TGs) into transcriptional regulatory networks is important for the complete understanding of regulation of biological processes. In the case of human TF-TG interactions, there is no database at present that explicitly provides such information even though many databases containing human TF-TG interaction data have been available. In an effort to provide researchers with a repository of TF-TG interactions from which such interactions can be directly extracted, we present here the Human Transcriptional Regulation Interactions database (HTRIdb).Description: The HTRIdb is an open-access database of experimentally validated interactions among human TFs and their TGs. HTRIdb can be searched via a user-friendly web interface and the retrieved TF-TG interactions data and the associated protein-protein interactions can be downloaded or interactively visualized as a network using the Cytoscape Web software. Moreover, users can improve the database quality by uploading their own interactions and indicating inconsistencies in the data. So far, HTRIdb has been populated with 283 TFs that regulate 11886 genes, totaling 18160 TF-TG interactions. HTRIdb is freely available at http://www.lbbc.ibb.unesp.br/htri. Conclusions: HTRIdb is a powerful user-friendly tool from which human experimentally validated TF-TG interactions can be easily extracted and used to construct transcriptional regulation interaction networks enabling researchers to decipher the regulation of biological processes.