A framework for initialising a dynamic clustering algorithm: ART2-A

Algorithms in the Adaptive Resonance Theory (ART) family adapt to structural changes in data as new information presents, making it an exciting candidate for dynamic online clustering of big health data. Its use however has largely been restricted to the signal processing field. In this paper we introduce an refinement of the ART2-A method within an adapted separation and concordance (SeCo) framework which has been shown to identify stable and reproducible solutions from repeated initialisations that also provides evidence for an appropriate number of initial clusters that best calibrates the algorithm with the data presented. The results show stable, reproducible solutions for a mix of real-world heath related datasets and well known benchmark datasets, selecting solutions which better represent the underlying structure of the data than using a single measure of separation. The scalability of the method and it's facility for dynamic online clustering makes it suitable for finding structure in big data

Teste de fungicidas em viveiros para controle do "mal das folhas" da seringueira.

bitstream/item/59887/1/PA-15840001.pd

Relating pseudospin and spin symmetries through charge conjugation and chiral transformations: the case of the relativistic harmonic oscillator

We solve the generalized relativistic harmonic oscillator in 1+1 dimensions, i.e., including a linear pseudoscalar potential and quadratic scalar and vector potentials which have equal or opposite signs. We consider positive and negative quadratic potentials and discuss in detail their bound-state solutions for fermions and antifermions. The main features of these bound states are the same as the ones of the generalized three-dimensional relativistic harmonic oscillator bound states. The solutions found for zero pseudoscalar potential are related to the spin and pseudospin symmetry of the Dirac equation in 3+1 dimensions. We show how the charge conjugation and $\gamma^5$ chiral transformations relate the several spectra obtained and find that for massless particles the spin and pseudospin symmetry related problems have the same spectrum, but different spinor solutions. Finally, we establish a relation of the solutions found with single-particle states of nuclei described by relativistic mean-field theories with scalar, vector and isoscalar tensor interactions and discuss the conditions in which one may have both nucleon and antinucleon bound states.Comment: 33 pages, 10 figures, uses revtex macro

A Voting Ensemble Method to Assist the Diagnosis of Prostate Cancer Using Multiparametric MRI

© 2020, Springer Nature Switzerland AG. Prostate cancer is the second most commonly occurring cancer in men. Diagnosis through Magnetic Resonance Imaging (MRI) is limited, yet current practice holds a relatively low specificity. This paper extends a previous SPIE ProstateX challenge study in three ways (1) to include healthy tissue analysis, creating a solution suitable for clinical practice, which has been requested and validated by collaborating clinicians; (2) by using a voting ensemble method to assist prostate cancer diagnosis through a supervised SVM approach; and (3) using the unsupervised GTM to provide interpretability to understand the supervised SVM classification results. Pairwise classifiers of clinically significant lesion, non-significant lesion, and healthy tissue, were developed. Results showed that when combining multiparametric MRI and patient level metadata, classification of significant lesions against healthy tissue attained an AUC of 0.869 (10-fold cross-validation)

Fisiopatologia da Hidradenite Supurativa: uma Revisão Sistemática da Literatura

Hidradenitis suppurative (HS) is a multifactorial, recurrent, chronic inflammatory disease with a significant impact on patient’s quality of life. The etiopathogenesis of this complex condition is not fully understood. In this systematic review, we aimed to address and clarify the role of genetics, immunity, endocrinology, and skin microbiome together with risk factors in HS etio pathogenesis. A systematic review, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed using PubMed® and Web of ScienceTM databases on December 3rd, 2021, using patient/population, intervention, comparison and outcomes (PICO) criteria, limited to the last 10 years and English. Reports were analyzed by two independent reviewers. A total of 123 reports were included and divided into five sections: genetics, immunity, endocrino logy, microbiome, and risk factors. Regarding genetics, up to 30-40% of patients have a positive family history of HS but only a small subset of these harbor genetic variants in components of the gamma-secretase complex. In fact, in more than 90% of HS patients, the genetic features contributing to disease development remain largely unknown. The immune response is also crucial for HS; it is characterized by antimicrobial peptide and proinflammatory cytokine dysregulation, namely interleukin (IL)—IL-23, IL-12, and Th17 immune response. This immune response in local and, consequently, systemic inflammation is amplified in patients with metabolic syndrome. The relationship between metabolic syndrome and HS is clear, and patients with metabolic syndrome have a higher risk of developing HS. The most recent evidence also associates skin microbiota dysbiosis with HS pathogenesis, contributing to local and systemic inflammation. Besides these intrinsic factors, the role of lifestyle in the development of HS is well accepted. Tobacco smoking and obesity are the main risk factors identified as con tributing to HS pathogenesis. Chronic inflammation characterizes HS, a debilitating condition with a complex and multifactorial etiopathogenesis. The current model integrates genetics, immunity, endocrinology, and skin microbiome. Notwithstanding, efforts should be made to improve our comprehension of HS etiopathogenesis, hopefully leading to the development of more effective treatments.A hidradenite supurativa (HS) é uma doença inflamatória, multifatorial, recorrente e crónica com um impacto significativo na qualidade de vida dos doentes. A etiologia desta condição complexa não é totalmente compreendida. Nesta revisão sistemática, pretende-se abordar e clarificar o papel da genética, imunidade, endocrinologia, microbioma cutâneo e fatores de risco que contribuem para o desenvolvimento da HS. A revisão sistemática, seguindo as orientações PRISMA, foi rea lizada através de uma pesquisa bibliográfica nas bases de dados PubMed® e da Web of ScienceTM a 3 de dezembro de 2021, utilizando critérios do PICO, e limitada aos últimos 10 anos e inglês. Os estudos a serem incluídos foram anali sados por dois revisores independentes. Um total de 123 estudos foram selecionados e divididos em cinco secções: genética, imunidade, endocrinologia, microbioma e fatores de risco. Em relação à genética, cerca de 30-40% dos doentes têm uma história familiar positiva de HS, mas as variantes genéticas das componentes do complexo da gama secretase só estão identificadas num número reduzido de doentes. De facto, em mais de 90% dos doentes com HS, a componente genética que contribui para o desenvolvimento da doença permanece desconhecida. A resposta imunitária é também crucial para a HS: caracteriza-se pela desregulação dos péptidos anti-microbianos assim como das citocinas pró-inflamatórias, nomeadamente IL-23, IL-12 e resposta Th17. Esta resposta que ocorre na inflamação local e consequentemente sistémica é exacerbada em doentes com síndrome metabólica. A relação entre a síndrome metabólica e a HS é clara, e os doentes com síndrome metabólica tem um risco elevado para o desenvolvimento de HS. As evidências mais recentes correlacionam também a disbiose do microbioma cutâneo com a patogénese da HS, contribuindo para a inflamação local e sistémica. Além destes fatores intrínsecos, o papel do estilo de vida no desenvolvimento da HS está bem estabelecido. O tabagismo e a obesidade são os principais fatores de risco identificados que contribuem para a patogénese da HS. A inflamação crónica caracteriza a HS, uma condição debilitante com uma etiologia complexa e multifatorial. O presente modelo integra a genética, a imunidade, a endocrinologia e o microbioma cutâneo, e poderá contribuir para o desenvolvimento de tratamentos mais eficazes.info:eu-repo/semantics/publishedVersio

Insetos pragas de madeiras de edificações em Belém - Pará.

bitstream/item/32005/1/CPATU-BP101.pd

Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures

Several approaches have been proposed for the analysis of DNA microarray datasets, focusing on the performance and robustness of the final feature subsets. The novelty of this paper arises in the use of q-values to pre-filter the features of a DNA microarray dataset identifying the most significant ones and including this information into a genetic algorithm for further feature selection. This method is applied to a lung cancer microarray dataset resulting in similar performance rates and greater robustness in terms of selected features (on average a 36.21% of robustness improvement) when compared to results of the standard algorithm

Automatic relevance source determination in human brain tumors using Bayesian NMF.

The clinical management of brain tumors is very sensitive; thus, their non-invasive characterization is often preferred. Non-negative Matrix Factorization techniques have been successfully applied in the context of neuro-oncology to extract the underlying source signals that explain different tissue tumor types, for which knowing the number of sources to calculate was always required. In the current study we estimate the number of relevant sources for a set of discrimination problems involving brain tumors and normal brain. For this, we propose to start by calculating a high number of sources using Bayesian NMF and automatically discarding the irrelevant ones during the iterative process of matrices decomposition, hence obtaining a reduced range of interpretable solutions. The real data used in this study come from a widely tested human brain tumor database. Simulated data that resembled the real data was also generated to validate the hypothesis against ground truth. The results obtained suggest that the proposed approach is able to provide a small range of meaningful solutions to the problem of source extraction in human brain tumors