Quantitative automated analysis of host-pathogen interactions

This work aims to broaden knowledge about neutrophil biology in their interaction with fungi species that most frequently cause invasive fungal diseases (IFD). The questions addressed include the alteration of neutrophil morphology after interaction with Candida albicans or C. glabrata, revealing factors that modulate the production and composition of neutrophil-derived extracellular vesicles (EVs) obtained in confrontation assay with conidia of Aspergillus fumigatus and analysing EVs activity against this fungus. Alongside fundamental interests, those questions have important applied aspects in the medicine of IFD. In particular, for diagnostic purposes and infection process monitoring. The results of this work include: 1 a novel segmentation and tracking algorithm which is capable of working with low-contrast cell images, producing accurate cell contours and providing data about positions of clusters, which would improve further analysis; 2 a novel workflow algorithm for analysis of neutrophil continuous morphological spectrum without consensus-based manual annotation; 3 quantitative evidence that morphodynamics of isolated neutrophils depends on the infectious agent (C. albicans or C. glabrata) used in whole blood infection assay; 4 quantitative evidence that neutrophil-derived extracellular vesicles, obtained in confrontation assays with conidia of A. fumigatus could inhibit hyphae development and damage hyphae cell wall; 5 quantitative evidence that EVs inhibition activity is strain-specific

Three-dimensional X-ray imaging and analysis of fungi on and in wood

As wood is prone to fungal degradation, fundamental research is necessary to increase our knowledge aiming at product improvement. Several imaging modalities are capable of visualizing fungi, but the X-ray equipment presented in this paper can envisage fungal mycelium in wood non-destructively in three dimensions with sub-micron resolution. Four types of wood subjected to the action of the white rot fungus Coriolus versicolor (Linnaeus) Quélet (CTB 863 A) were scanned using an X-ray based approach. Comparison of wood volumes before and after fungal exposure, segmented manually or semi-automatically, showed the presence of the fungal mass on and in the wood samples and therefore demonstrated the usefulness of computed X-ray tomography for mycological and wood research. Further improvements to the experimental set-up are necessary in order to resolve individual hyphae and enhance segmentation

Fully automated computer system for diagnosis of corneal diseases. Development of image processing technologies for the diagnosis of Acanthamoeba and Fusarium diseases in confocal microscopy images

Confocal microscopy demonstrated its value in the diagnosis of Acanthamoeba and fungal keratitis which considered sight-threatening corneal diseases. However, it can be difficult to find and train confocal microscopy graders to accurately detect Acanthamoeba cysts and fungal filaments in the images. Use of an automated system could overcome this problem and help to start the correct treatment more quickly. Also, response to treatment can be difficult to assess in infectious keratitis using clinical examination alone, but there is evidence that the morphology of filaments and cysts may change over time with the use of correct treatment. An automated system to analyse confocal microscopy images for such changes would also assist clinicians in determining whether the ulcer is improving, or whether a change of treatment is needed. This research proposes a fully automated novel system with GUI to detect cysts and hyphae (filaments) and measure useful quantitative parameters for them through many stages; Image enhancement, image segmentation, quantitative analysis for detected cysts and hyphae, and registration and tracking of ordered sequence of images. The performance of the proposed segmentation procedure is evaluated by comparing between the manual and the automated traced images of the dataset that was provided by the Manchester Royal Eye Hospital. The positive predictive values rate of cysts for Acanthamoeba images was 76%. For detected hyphae in Fusarium images, many standard measurements were computed. The accuracy of their values was quantified by calculating the percent error rate for each measurement and which ranged from 23% to 49%

Tracing biofilaments from images : analysis of existing methods to quantify the three-dimensional growth of filamentous fungi on solid substrates

Orientador: Prof. Dr. David Alexander MitchellCoorientadora: Prof. Dr. Maura Harumi Sugai-GuériosDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Química. Defesa : Curitiba, 29/05/2018Inclui referências: p.100-113Área de concentração: Engenharia QuímicaResumo: Análise de imagens de biofilamentos tem se tornado uma parte importante na pesquisa em biologia e biotecnologia, pois ela não só elucida a morfologia destas estruturas, mas também fornece ideias sobre o desenvolvimento destas estruturas. Além disso, a morfologia pode ser correlacionada com outras variáveis. Por exemplo, análise de imagem de fungos filamentosos permite correlacionar produtividade de enzimas com diferentes morfologias. Há um interesse em compreender como o micélio de um fungo filamentoso se desevolve ao crescer em substratos sólidos. Para estudar isso, foram obtidas imagens 3D do fungo em crescimento em diversos tempos, objetivando computar dados da morfologia e dinâmica de crescimento: velocidades de extensão da colônia e de pontas, número e posição de ramificações e pontas, comprimentos de segmentos, entre outros dados. Porém, antes de computar estes dados, foi feita uma análise da literatura de métodos de traçado de biofilamentos. A análise foi realizada para facilitar a compreensão do vasto número de métodos disponíveis, desde componentes individuais (e.g. técnicas de realçe de filamentos) a workflows completas de traçado de biofilamentos. Também há muitas opções de implementações de software. Na análise, foram incluídas 87 publicações envolvendo workflows de traçado de filamentos ou componentes. Para a análise, criou-se uma classificação (10 classes, que incluem interação com o usuário, abordagem teórica, técnica de imageamento, entre outras classes e 120 sub-classes) para apoiar a análise com o uso de conceitos de teoria de grafos. A metodologia proposta poderá ser utilizada no futuro com ferramentas de semântica web e uma base de dados e permitirá analisar um número maior de dados. Desta análise, identificaram-se os métodos mais comuns de melhoramento de imagem (Realçe de filamentos, 44.9%, suavização, 16.3% e Subtração de background 14.3%) e as tendências em abordagens teóricas (e.g. abordagens baseadas em grafos juntas à algoritmos de aprendizado de máquina, realçe de filamentos como o gradient vector flow seguidos de abordagem Levei-set fast-marching). Após a análise da literatura, foram selecionados os métodos de melhoramento mais comuns e avaliados segundo seu impacto na qualidade da imagem. Os testes foram realizados em duas amostras de imagem (experimentos do crescimento de Aspergillus niger de microscopia confocal de varredura a laser) através de um planejamento fatorial completo e análise do índice de similaridade estrutural, SSIM, e razão sinal-ruído, SNR. Resultados mostraram que o algoritmo rolling bali de subtração de background com raio 20 pixels teve o maior efeito positivo em SSIM e SNR no geral. Então, ao utilizar as imagens melhoradas como entrada, foram testados 5 métodos de traçado de filamentos (APP, APP2, NeuTube, NeuronStudio e NeuroGPS-Tree). Os resultados do traçado foram avaliados qualitativamente: O método NeuTube mostrou os resultados visualmente mais acurados. Definiu-se então o método e foram traçadas as imagens completas 3D e no tempo e obtivemos parâmetros morfométricos e da dinâmica do crescimento do fungo (perfis de biomassa e comprimentos totais, por exemplo). Embora se observe que o uso de traçado de filamentos é promisor para obter mais dados do crescimento de fungos filamentosos, discutiu-se a necessidade de aprimorar as técnicas de preparo de amostra e das configurações na aquisição das imagens, de maneira a aumentar a qualidade final das imagens e fornecer resultados mais confiáveis e concretos após o traçado para então tirar conclusões dos dados. Palavras-chave: fungos filamentosos, filamentos biológicos, análise de imagem, traçado de filamentos, melhoramento de imagem.Abstract: Image analysis of biofilaments is becoming an important part of research on biology and biotechnology because it does not only elucidates the morphology of such structures but also gives insights into their development. Additionally, the morphology can be correlated with other variables. For example, image analysis of filamentous fungi allows the correlation of enzyme productivity with different morphologies. We are interested in understanding how the mycelium of a filamentous fungus develops during growth on solid substrates. In order to study that, time-lapsed 3D images of the fungus during growth were obtained, with the intention of computing growth dynamics and morphometric data: colony and tip extension rates, number and positions of branches and tips, segment lengths, among others. However, prior to computing this data, we analysed the literature of biofilament tracing methods. The analysis was done to facilitate the understanding of the vast number of methods available, from single components (e.g. filament enhancement techniques, and specialized model-based approaches) to complete biofilament tracing workflows. There were also many software implementations options. The analysis comprised 87 publications proposing complete biofilament tracing workflows or workflow components. For the analysis, we created a classification methodology (10 main classes, including user interaction, theoretical approach, imaging technique, among other classes and 120 sub-classes) and analysed the publications using graph theory concepts. The proposed methodology could be used in the future with semantic web tools and crowd-sourced web-based databases, allowing the analysis of greater number of data. Out of this analysis, we identified the most common image enhancement methods (Filament enhancement 44.9%, smoothing 16.3%, background subtraction 14.3%) and the theoretical approach trends for biofilament tracing (e.g. graph-based approaches coupled with machine learning algorithms, image enhancement such as gradient vector flows followed by model-based fast marching approach). Following the literature analysis, we selected the most common image enhancement methods to be used prior to biofilament tracing and evaluated their impact on image quality. The tests were done on two sample images (experiments of the growth of Aspergillus niger on two different carbon sources obtained by confocal laser scanning microscopy) through a full factorial design of experiments and analysis of the structural similarity index, SSIM and signal-to-noise ratio, SNR. Results show that background subtraction (Rolling-ball algorithm, 20 pixels radius) had the most positive effect on SSIM and SNR. Then, using the enhanced images as input, we tested 5 different biofilament tracing methods (APP1, APP2, NeuTube, NeuronStudio and NeuroGPS-Tree). We evaluated the tracing results visually and qualitatively: NeuTube was the method with the most visually accurate results. After choosing NeuTube as the best method, we applied it to our complete 3D time-lapsed images and computed some growth dynamics and morphmetric parameters (e.g. biomass profiles, segment and total lengths). Although we indicate that biofilament tracing methods are a promising approach to obtain more data on the growth of the filamentous fungi, we discuss the need to improve the sample preparation techniques and image acquisition set-up in order to increase the quality of the images so the tracing results provide more reliable and concrete results to draw conclusions. Keywords: filamentous fungi, biological filaments, image analysis, filament tracing, image enhancement

Accessible software frameworks for reproducible image analysis of host-pathogen interactions

Um die Mechanismen hinter lebensgefährlichen Krankheiten zu verstehen, müssen die zugrundeliegenden Interaktionen zwischen den Wirtszellen und krankheitserregenden Mikroorganismen bekannt sein. Die kontinuierlichen Verbesserungen in bildgebenden Verfahren und Computertechnologien ermöglichen die Anwendung von Methoden aus der bildbasierten Systembiologie, welche moderne Computeralgorithmen benutzt um das Verhalten von Zellen, Geweben oder ganzen Organen präzise zu messen. Um den Standards des digitalen Managements von Forschungsdaten zu genügen, müssen Algorithmen den FAIR-Prinzipien (Findability, Accessibility, Interoperability, and Reusability) entsprechen und zur Verbreitung ebenjener in der wissenschaftlichen Gemeinschaft beitragen. Dies ist insbesondere wichtig für interdisziplinäre Teams bestehend aus Experimentatoren und Informatikern, in denen Computerprogramme zur Verbesserung der Kommunikation und schnellerer Adaption von neuen Technologien beitragen können. In dieser Arbeit wurden daher Software-Frameworks entwickelt, welche dazu beitragen die FAIR-Prinzipien durch die Entwicklung von standardisierten, reproduzierbaren, hochperformanten, und leicht zugänglichen Softwarepaketen zur Quantifizierung von Interaktionen in biologischen System zu verbreiten. Zusammenfassend zeigt diese Arbeit wie Software-Frameworks zu der Charakterisierung von Interaktionen zwischen Wirtszellen und Pathogenen beitragen können, indem der Entwurf und die Anwendung von quantitativen und FAIR-kompatiblen Bildanalyseprogrammen vereinfacht werden. Diese Verbesserungen erleichtern zukünftige Kollaborationen mit Lebenswissenschaftlern und Medizinern, was nach dem Prinzip der bildbasierten Systembiologie zur Entwicklung von neuen Experimenten, Bildgebungsverfahren, Algorithmen, und Computermodellen führen wird

Assessment of monthly rain fade in the equatorial region at C & KU-band using measat-3 satellite links

C & Ku-band satellite communication links are the most commonly used for equatorial satellite communication links. Severe rainfall rate in equatorial regions can cause a large rain attenuation in real compared to the prediction. ITU-R P. 618 standards are commonly used to predict satellite rain fade in designing satellite communication network. However, the prediction of ITU-R is still found to be inaccurate hence hinder a reliable operational satellite communication link in equatorial region. This paper aims to provide an accurate insight by assessment of the monthly C & Ku-band rain fade performance by collecting data from commercial earth stations using C band and Ku-band antenna with 11 m and 13 m diameter respectively. The antennas measure the C & Ku-band beacon signal from MEASAT-3 under equatorial rain conditions. The data is collected for one year in 2015. The monthly cumulative distribution function is developed based on the 1-year data. RMSE analysis is made by comparing the monthly measured data of C-band and Ku-band to the ITU-R predictions developed based on ITU-R’s P.618, P.837, P.838 and P.839 standards. The findings show that Ku-band produces an average of 25 RMSE value while the C-band rain attenuation produces an average of 2 RMSE value. Therefore, the ITU-R model still under predicts the rain attenuation in the equatorial region and this call for revisit of the fundamental quantity in determining the rain fade for rain attenuation to be re-evaluated

Modern Seed Technology

Satisfying the increasing number of consumer demands for high-quality seeds with enhanced performance is one of the most imperative challenges of modern agriculture. In this view, it is essential to remember that the seed quality of crops does not improve