AVALIAÇÂO DE UMA NOVA TÉCNICA DE QUIMIOLUMINESCÊNCIA PARA DETERMINAÇÃO DE ANTICORPOS ANTI-DSDNA

Introdução A determinação dos anticorpos anti-dsDNA é um teste de grande importância para o diagnóstico e monitorização de doentes com Lúpus Eritematoso Sistémico (LES), fazendo parte dos critérios de classificação de LES do ACR. (American College of Rheumathology). Existem actualmente vários métodos laboratoriais disponíveis, que respondem de forma desigual na determinação destes anticorpos nos doentes, em diferentes fases de evolução da patologia. Objectivo Avaliar o desempenho do novo método automatizado de determinação dos anticorpos anti-dsDNA por técnica de quimioluminescência (CLIA), Zenit RA dsDNA (Menarini), comparando-o com os métodos de imunofluorescência indirecta (IFI) e fluoroimunoensaio (FEIA), utilizados na rotina assistencial no Serviço de Imunologia do CHP. Material e Métodos A população estudada incluiu 151 amostras seriadas de doentes com LES, 33 doentes com doença infecciosa, 28 doentes com outras patologias com envolvimento autoimune e 38 indivíduos saudáveis. Realizou-se a determinação dos anticorpos anti-dsDNA por técnica CLIA no equipamento ZENIT RA (Menarini), por técnica FEIA no equipamento ImmunoCAP 250 (Phadia) e por IFI em lâminas de Crithidia luciliae (BioRad) processadas no aparelho PhD (BioRad). Resultados Todos os testes apresentaram uma baixa sensibilidade nos doentes com LES (33,1% a 44,4%), traduzindo o facto de um grande número de doentes se encontrar em tratamento e com fraca actividade da doença. O teste CLIA apresentou uma especificidade semelhante à da IFI (93,9% vs. 95,6%), superior à observada no FEIA (85,9%). Conclusões O teste dsDNA ZENIT RA revelou uma sensibilidade inferior ao FEIA mas uma melhor especificidade e valor preditivo positivo, semelhantes aos observados na técnica de IFI. Sendo um teste totalmente automatizado e sem a subjectividade da IFI, será agora importante a sua avaliação numa população com critérios de actividade bem definidos

Solving a harvest scheduling optimization problem with constraints on clearcut area and clearcut proximity

This study aims at solving a harvesting scheduling optimization problem with constraints on the clearcut area with additional constraints on clearcut proximity. The objective function is defined as the net present value generated by harvesting discounted by a penalty for each clearcut. This problem arises to reduce the negative environmental impact of excessive harvesting. We propose the connected-bucket model, the so-called bucket model with additional constraints on bucket connectivity and two definitions of stand adjacency, and a Dantzig–Wolfe decomposition. The decomposed model is solved by branch-and-price and the connected-bucket model by a general-purpose mixed integer programming solver (CPLEX). We compare the quality of the solutions obtained with both approaches for real instances. The branch-and-price approach found better solutions for the majority of the instances.This research was supported by the Center of Mathematics, Fundamental Applications and Operations Research - project UIDB/04561/2020, the INESC TEC - Institute for Systems and Computer, Engineering, Technology and Science - project LA/P/0063/2020, and also by the R&D project entitled “An Optimization Framework to reduce Forest Fire” - PCIF/GRF/0141/2019, all funded by FCT - Fundação para a Ciência e Tecnologia

Desenvolvimento e otimização de um filme biodegradável à base de proteína do tremoço (Lupinus angustifolius)

Dissertação de Mestrado, Biologia Molecular e Microbiana, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015Os consumidores atuais, preocupando-se com o ambiente e a saúde humana, preferem materiais de embalagem biológicos. Estes, desenvolvidos através da investigação, devem substituir as poliolefinas na indústria de embalagens. O objetivo deste estudo foi desenvolver um filme de embalagem alimentar baseado em proteína isolada de tremoço (PIT) com propriedades antioxidantes e antimicrobianas. Para otimizar a composição do filme, usou-se a metodologia de superfície de resposta (MSR) e um design de mistura, sendo as variáveis independentes: % PIT, (x1); % glicerol, (x2) e % de água, (x3). Foram medidas 6 respostas: L (Y1), a (Y2), b (Y3); espessura (Y4); força de punção (Y5) e teor de humidade (Y6), originando 6 modelos polinomiais. Através de otimização numérica, obteve-se a melhor composição: 8,98 % PIT, 6,88 % glicerol e 84.15 % água. A validação experimental revelou que Y2 e Y4, eram significativamente diferentes dos valores previstos, sendo o filme mais fino e amarelado. As atividades antioxidantes e antimicrobiana do filme otimizado foram seguidamente avaliadas e, como o crescimento de Saccharomyces cerevisiae, Staphylococcus aureus e Pseudomonas aeruginosa não foi inibido, adicionou-se carvacrol à solução formadora do filme repetindo-se os testes de atividade antimicrobiana e antioxidante. As propriedades foram também avaliadas no filme PIT, no filme com carvacrol (FCC) e nas soluções com (SCC) e sem carvacrol (SSC). SCC inibiu todos os microrganismos, enquanto o filme com carvacrol inibiu todos menos a Pseudomonas aeruginosa. Os compostos fenólicos totais, flavonoides e capacidade antioxidante do filme foram, respetivamente, 307.41 mg EAG/100 g PIT, 20.56 mg EQ/100 g PIT e 9.38 mmol ET/100g PIT não se verificando diferenças significativas entre a SSC e o filme de PIT. Estes valores aumentaram consideravelmente na SCC e no FCC. Neste estudo foi possível desenvolver um filme de embalagem de PIT, amarelo, com atividade antioxidante relativamente baixa e sem atividade antimicrobiana, requerendo adição de um agente antimicrobiano que irá aumentar a sua atividade antioxidante

Cyclin D mediates tolerance of genome-doubling in cancers with functional p53

BACKGROUND: Aneuploidy and chromosomal instability (CIN) are common features of human malignancy that fuel genetic heterogeneity. Although tolerance to tetraploidization, an intermediate state that further exacerbates CIN, is frequently mediated by TP53 dysfunction, we find that some genome-doubled tumours retain wild-type TP53. We sought to understand how tetraploid cells with a functional p53/p21-axis tolerate genome-doubling events. METHOD: We performed quantitative proteomics in a diploid/tetraploid pair within a system of multiple independently derived TP53 wild-type tetraploid clones arising spontaneously from a diploid progenitor. We characterized adapted and acute tetraploidization in a variety of flow cytometry and biochemical assays and tested our findings against human tumours through bioinformatics analysis of the TCGA dataset. RESULTS: Cyclin D1 was found to be specifically overexpressed in early but not late passage tetraploid clones, and this overexpression was sufficient to promote tolerance to spontaneous and pharmacologically induced tetraploidy. We provide evidence that this role extends to D-type cyclins and their overexpression confers specific proliferative advantage to tetraploid cells. We demonstrate that tetraploid clones exhibit elevated levels of functional p53 and p21 but override the p53/p21 checkpoint by elevated expression of cyclin D1, via a stoichiometry-dependent and CDK activity-independent mechanism. Tetraploid cells do not exhibit increased sensitivity to abemaciclib, suggesting that cyclin D-overexpressing tumours might not be specifically amenable to treatment with CDK4/6 inhibitors. CONCLUSION: Our study suggests that D-type cyclin overexpression is an acute event, permissive for rapid adaptation to a genome-doubled state in TP53 wild-type tumours and that its overexpression is dispensable in later stages of tumour progression

A universal assay for detection of oncogenic fusion transcripts by oligo microarray analysis

<p>Abstract</p> <p>Background</p> <p>The ability to detect neoplasia-specific fusion genes is important not only in cancer research, but also increasingly in clinical settings to ensure that correct diagnosis is made and the optimal treatment is chosen. However, the available methodologies to detect such fusions all have their distinct short-comings.</p> <p>Results</p> <p>We describe a novel oligonucleotide microarray strategy whereby one can screen for all known oncogenic fusion transcripts in a single experiment. To accomplish this, we combine measurements of chimeric transcript junctions with exon-wise measurements of individual fusion partners. To demonstrate the usefulness of the approach, we designed a DNA microarray containing 68,861 oligonucleotide probes that includes oligos covering all combinations of chimeric exon-exon junctions from 275 pairs of fusion genes, as well as sets of oligos internal to all the exons of the fusion partners. Using this array, proof of principle was demonstrated by detection of known fusion genes (such as <it>TCF3:PBX1</it>, <it>ETV6:RUNX1</it>, and <it>TMPRSS2:ERG</it>) from all six positive controls consisting of leukemia cell lines and prostate cancer biopsies.</p> <p>Conclusion</p> <p>This new method bears promise of an important complement to currently used diagnostic and research tools for the detection of fusion genes in neoplastic diseases.</p

Negative MR4·0 chronic myeloid leukaemia and its possible implications for treatment-free remission

© 2019 British Society for Haematology and John Wiley & Sons Ltd.ABL1 tyrosine kinase inhibitors (TKI) have dramatically improved the outcome for chronic myeloid leukaemia (CML) patients, resulting in a life expectancy that approaches that of the general population. Nevertheless, lifelong TKI therapy may have consequences, including chronic adverse events that can substantially impact patients’ quality of life, adherence to therapy and treatment success. Recently, several clinical discontinuation trials have demonstrated that 40–60% of chronic phase CML patients (CP-CML) who have achieved a stable deep molecular response (DMR) can stop therapy without relapsing (Breccia & Foà, 2018). Laboratory recommendations for scoring DMR were previously defined as MR4·0 [either detectable disease ⩽0·01% BCR-ABLIS (MR4·0 positive) or undetectable disease in cDNA with 10 000–31 999 ABL1 transcripts or 24 000–76 999 GUSB transcripts (MR4·0 negative)], MR4·5 [either detectable disease ⩽0·0032% BCR-ABLIS (MR4·5 positive) or undetectable disease in cDNA with 32 000–99 999 ABL1 transcripts or 77 000–239 999 GUSB transcripts (MR4·5 negative)], and MR5·0 [either detectable disease ⩽0·001% BCR-ABLIS (MR5·0 positive) or undetectable disease in cDNA with ⩾100 000 ABL1 transcripts or ⩾240 000 GUSB transcripts (MR5·0 negative)] (Cross et al, 2015).info:eu-repo/semantics/publishedVersio

Both SEPT2 and MLL are down-regulated in MLL-SEPT2 therapy-related myeloid neoplasia

<p>Abstract</p> <p>Background</p> <p>A relevant role of septins in leukemogenesis has been uncovered by their involvement as fusion partners in <it>MLL</it>-related leukemia. Recently, we have established the <it>MLL-SEPT2 </it>gene fusion as the molecular abnormality subjacent to the translocation t(2;11)(q37;q23) in therapy-related acute myeloid leukemia. In this work we quantified <it>MLL </it>and <it>SEPT2 </it>gene expression in 58 acute myeloid leukemia patients selected to represent the major AML genetic subgroups, as well as in all three cases of <it>MLL-SEPT2</it>-associated myeloid neoplasms so far described in the literature.</p> <p>Methods</p> <p>Cytogenetics, fluorescence in situ hybridization (FISH) and molecular studies (RT-PCR, qRT-PCR and qMSP) were used to characterize 58 acute myeloid leukemia patients (AML) at diagnosis selected to represent the major AML genetic subgroups: <it>CBFB-MYH11 </it>(n = 13), <it>PML-RARA </it>(n = 12); <it>RUNX1-RUNX1T1 </it>(n = 12), normal karyotype (n = 11), and <it>MLL </it>gene fusions other than <it>MLL-SEPT2 </it>(n = 10). We also studied all three <it>MLL-SEPT2 </it>myeloid neoplasia cases reported in the literature, namely two AML patients and a t-MDS patient.</p> <p>Results</p> <p>When compared with normal controls, we found a 12.8-fold reduction of wild-type <it>SEPT2 </it>and <it>MLL-SEPT2 </it>combined expression in cases with the <it>MLL-SEPT2 </it>gene fusion (p = 0.007), which is accompanied by a 12.4-fold down-regulation of wild-type <it>MLL </it>and <it>MLL-SEPT2 </it>combined expression (p = 0.028). The down-regulation of <it>SEPT2 </it>in <it>MLL-SEPT2 </it>myeloid neoplasias was statistically significant when compared with all other leukemia genetic subgroups (including those with other <it>MLL </it>gene fusions). In addition, <it>MLL </it>expression was also down-regulated in the group of <it>MLL </it>fusions other than <it>MLL-SEPT2</it>, when compared with the normal control group (p = 0.023)</p> <p>Conclusion</p> <p>We found a significant down-regulation of both <it>SEPT2 </it>and <it>MLL </it>in <it>MLL-SEPT2 </it>myeloid neoplasias. In addition, we also found that <it>MLL </it>is under-expressed in AML patients with <it>MLL </it>fusions other than <it>MLL-SEPT2</it>.</p

FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods.

Comprehensive and accurate identification of structural variations (SVs) from next generation sequencing data remains a major challenge. We develop FusorSV, which uses a data mining approach to assess performance and merge callsets from an ensemble of SV-calling algorithms. It includes a fusion model built using analysis of 27 deep-coverage human genomes from the 1000 Genomes Project. We identify 843 novel SV calls that were not reported by the 1000 Genomes Project for these 27 samples. Experimental validation of a subset of these calls yields a validation rate of 86.7%. FusorSV is available at https://github.com/TheJacksonLaboratory/SVE . Genome Biol 2018 Mar 20; 19(1):38

An open-source solution for advanced imaging flow cytometry data analysis using machine learning

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performed in a highly manual and subjective manner using very limited image analysis techniques in combination with conventional flow cytometry gating strategies. This approach is not scalable to the hundreds of available image-based features per cell and thus makes use of only a fraction of the spatial and morphometric information. As a result, the quality, reproducibility and rigour of results are limited by the skill, experience and ingenuity of the data analyst. Here, we describe a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms. Compensated and corrected raw image files (.rif) data files from an imaging flow cytometer (the proprietary .cif file format) are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analysed using cutting-edge machine learning and clustering approaches using “user-friendly” platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data set. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye that include subtle measured differences in label free detection channels such as bright-field and dark-field imagery