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Publications

Publications by LIAAD

2018

Inferences on specificity recognition at the Malusxdomestica gametophytic self-incompatibility system

Authors
Pratas, MI; Aguiar, B; Vieira, J; Nunes, V; Teixeira, V; Fonseca, NA; Iezzoni, A; van Nocker, S; Vieira, CP;

Publication
SCIENTIFIC REPORTS

Abstract
In Malus x domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.

2018

Gramene 2018: Unifying comparative genomics and pathway resources for plant research

Authors
Tello Ruiz, MK; Naithani, S; Stein, JC; Gupta, P; Campbell, M; Olson, A; Wei, S; Preece, J; Geniza, MJ; Jiao, Y; Lee, YK; Wang, B; Mulvaney, J; Chougule, K; Elser, J; Al Bader, N; Kumari, S; Thomason, J; Kumar, V; Bolser, DM; Naamati, G; Tapanari, E; Fonseca, N; Huerta, L; Iqbal, H; Keays, M; Munoz Pomer Fuentes, A; Tang, A; Fabregat, A; D'Eustachio, P; Weiser, J; Stein, LD; Petryszak, R; Papatheodorou, I; Kersey, PJ; Lockhart, P; Taylor, C; Jaiswal, P; Ware, D;

Publication
Nucleic Acids Research

Abstract
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces. © Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

2018

Tumors induce de novo steroid biosynthesis in T cells to evade immunity

Authors
Mahata, B; Pramanik, J; van der Weyden, L; Polanski, K; Kar, G; Riedel, A; Chen, X; Fonseca, NA; Kundu, K; Campos, LS; Ryder, E; Duddy, G; Walczak, I; Okkenhaug, K; Adams, DJ; Shields, JD; Teichmann, SA;

Publication

Abstract
ABSTRACTTumors subvert immune cell function to evade immune responses, yet the complex mechanisms driving immune evasion remain poorly understood. Here we show that tumors induce de novo steroidogenesis in T lymphocytes to evade anti-tumor immunity. Using a novel transgenic steroidogenesis-reporter mouse line we identify and characterize de novo steroidogenic immune cells. Genetic ablation of T cell steroidogenesis restricts primary tumor growth and metastatic dissemination in mouse models. Steroidogenic T cells dysregulate anti-tumor immunity, and inhibition of the steroidogenesis pathway was sufficient to restore anti-tumor immunity. This study demonstrates T cell de novo steroidogenesis as a mechanism of anti-tumor immunosuppression and a potential druggable target.

2018

Systematic overview of neuroanatomical differences in ADHD: Definitive evidence

Authors
Vieira de Melo, BBV; Trigueiro, MJ; Rodrigues, PP;

Publication
DEVELOPMENTAL NEUROPSYCHOLOGY

Abstract
Objectives: This article seeks to identify neuroanatomical differences in ADHD through an overview of systematic reviews that report encephalic differences compared to a control group in volume, area, activation likelihood or chemical composition.Methods: We conducted a systematic search using Cochrane guidelines and PRISMA criteria in PubMed, Scopus, Web of Science, Cochrane Database of Systematic Reviews and Database of Abstracts of Reviews of Effects.Results: Results revealed broad encephalic involvement that includes a functional frontal and cingulate hypoactivation and structural differences in corpus callosum, cerebellum and basal nuclei.Conclusions: ADHD symptoms might be due to a multi-network unbalanced functioning hypothesis.

2018

Impact of Imputing Missing Data in Bayesian Network Structure Learning for Obstructive Sleep Apnea Diagnosis

Authors
Santos, DF; Soares, MM; Rodrigues, PP;

Publication
Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018, Medical Informatics Europe, Gothenburg, Sweden, April 24-26, 2018

Abstract
Numerous diagnostic decisions are made every day by healthcare professionals. Bayesian networks can provide a useful aid to the process, but learning their structure from data generally requires the absence of missing data, a common problem in medical data. We have studied missing data imputation using a step-wise nearest neighbors' algorithm, which we recommended given its limited impact on the assessed validity of structure learning Bayesian network classifiers for Obstructive Sleep Apnea diagnosis. © 2018 European Federation for Medical Informatics (EFMI) and IOS Press.

2018

Sifting Through Chaos: Extracting Information from Unstructured Legal Opinions

Authors
Oliveira, BM; Guimaraes, RV; Antunes, L; Rodrigues, PP;

Publication
BUILDING CONTINENTS OF KNOWLEDGE IN OCEANS OF DATA: THE FUTURE OF CO-CREATED EHEALTH

Abstract
Abiding to the law is, in some cases, a delicate balance between the rights of different players. Re-using health records is such a case. While the law grants reuse rights to public administration documents, in which health records produced in public health institutions are included, it also grants privacy to personal records. To safeguard a correct usage of data, public hospitals in Portugal employ jurists that are responsible for allowing or withholding access rights to health records. To help decision making, these jurists can consult the legal opinions issued by the national committee on public administration documents usage. While these legal opinions are of undeniable value, due to their doctrine contribution, they are only available in a format best suited from printing, forcing individual consultation of each document, with no option, whatsoever of clustered search, filtering or indexing, which are standard operations nowadays in a document management system. When having to decide on tens of data requests a day, it becomes unfeasible to consult the hundreds of legal opinions already available. With the objective to create a modern document management system, we devised an open, platform agnostic system that extracts and compiles the legal opinions, ex-tracts its contents and produces metadata, allowing for a fast searching and filtering of said legal opinions.

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