Low-cost microscope system with fluorescence and Raman spectroscopy capabilities for phytoplankton identification

RESUMEN: El fitoplancton es el conjunto de seres vivos unicelulares de origen vegetal con capacidad de realizar la fotosíntesis que pueblan las aguas marinas y dulces de todo el planeta. Son una parte fundamental de estos ecosistemas por ser alimento primario y regular la concentración de oxígeno en el agua, fijando el CO2 atmosférico. Los sucesos en los que el fitoplancton sufre un rápido aumento en su población se conocen como floraciones de algas. Una floración de algas nocivas (harmful algal bloom, HAB) ocurre cuando causa impactos negativos al producir toxinas naturales, originando consecuencias fatales tanto a otros organismos como al medio ambiente natural y con importantes repercusiones económicas, por ejemplo, para la industria de la acuicultura. La detección de las HAB cuando los niveles de toxinas son alarmantes se produce con poca antelación, por lo que es de gran importancia el desarrollo de herramientas de detección y predicción tempranas. Las soluciones actuales que contribuyen a cubrir esta brecha suelen consistir en equipos de laboratorio costosos y de gran complejidad que requieren de profesionales altamente capacitados con una experiencia casi única en la identificación visual de especies dañinas. Por ello, es fundamental el desarrollo de métodos de identificación y cuantificación rentables, rápidos y fiables. En este trabajo se lleva a cabo la construcción de un microscopio de bajo coste imprimible en 3D, basado en el proyecto OpenFlexure, desarrollado por investigadores de la Universidad de Bath. El objetivo es la mejora del diseño para permitir un análisis in situ del fitoplancton, incorporando un sistema de microfluídica y tres modalidades de microscopía: campo claro, fluorescencia y espectroscopía Raman. Además de la construcción del microscopio OpenFlexure, se han realizado propuestas de rediseño, que se han simulado, probado experimentalmente y validado tras compararlas con equipos de referencia de laboratorio.ABSTRACT: Phytoplankton is the set of unicellular living beings of plant origin with the capacity to carry out photosynthesis that populate marine and fresh waters all over the world. They are a fundamental part of these ecosystems because they are a primary food and because they regulate the concentration of oxygen in the water, fixing the atmospheric CO2. Events in which phytoplankton rapidly increases in population are known as algal blooms. A harmful algal bloom (HAB) occurs when it causes a negative impact on the environment by producing natural toxins. This leads to fatal consequences both to other organisms and to the natural environment as well as significant economic repercussions, for example, in the field of aquaculture industry. The detection of HABs when toxin levels are alarming occurs at short notice, so the deve lopment of early detection and prediction tools is of great importance. Current solutions that help to bridge this gap often consist of expensive and highly complex laboratory equipment requiring highly trained professionals with almost unique expertise in visual identification of harmful species. Therefore, the development of cost-effective, rapid and reliable identification and quantification methods is essential. In this research work, a low-cost 3D-printed microscope is constructed based on the OpenFlexure project, developed by researchers at the University of Bath. The objective is to improve the design to allow in-situ analyses of phytoplankton, incorporating a microfluidic system and three microscopy modalities: brightfield, fluorescence and Raman spectroscopy. In addition to the construction of the OpenFlexure microscope, redesigned proposals have been made, which have been simulated, experimentally tested and validated against laboratory reference equipment.Máster en Ciencia e Ingeniería de la Lu

Simulation and light capture experiments for laser spectroscopy

RESUMEN: La espectroscopia de ruptura inducida por láser (LIBS) es un tipo de espectroscopia de emisión atómica que permite obtener información sobre la composición de materiales o la presencia de determinadas sustancias mediante el análisis de la luz del plasma generado al hacer incidir un láser multipulso de alta energía sobre la superficie de un material en cualquier estado de agregación. La captura de luz se puede realizar a través de varios métodos: fibra óptica, imagen por lente, telescopio remoto... Estas formas de captura cuentan con numerosas ventajas e inconvenientes, siendo los principales problemas la pérdida de luz y las fluctuaciones del plasma con el tiempo, lo cual genera resultados diferentes para cada medición. En este trabajo se van a intentar solventar dichos problemas buscando un sistema de lentes que forme imágenes homogéneas en el tiempo y que capte la mayor cantidad de luz posible. Para ello, se utilizará el software de diseño óptico OpticStudio de Zemax, con el que se realizarán las simulaciones del comportamiento de la emisión del plasma a su paso por los diferentes sistemas ópticos, y, posteriormente, se comprobará la eficacia de dichas simulaciones experimentalmente.ABSTRACT: Laser-Induced Breakdown Spectroscopy (LIBS) is a type of atomic emission spectroscopy that allows to obtain information on the composition of materials or the presence of certain substances by analyzing the light from the plasma generated when a high-energy multipulse laser strikes on the surface of a material in any state of aggregation. Light capture can be done through various methods: fiber optics, lens imaging, remote telescope... These forms of capture have numerous advantages and disadvantages, the main problems being the loss of light and plasma fluctuations over time, which produces different results for each measurement. The objective of this dissertation is to solve these problems by looking for a lens system that forms homogeneous images over time and captures as much light as possible. For this purpose, the OpticStudio software by Zemax will be used to simulate the behavior of the plasma emission as it passes through the different optical systems, and, subsequently, the effectiveness of these simulations will be experimentally verified.Grado en Físic

Photonic microfluidic technologies for phytoplankton research

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world’s vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.This work was supported by Ministerio de Ciencia e Innovación and Agencia Estatal de Investigación (PID2019-107270RB-C21/AIE/10.13039/501100011033. J.F.A. received funding from Ministerio de Ciencia, Innovación y Universidades of Spain under Juan de la Cierva Incorporación grant

Automatic classification of Candida species using Raman spectroscopy and machine learning

One of the problems that most affect hospitals is infections by pathogenic microorganisms. Rapid identification and adequate, timely treatment can avoid fatal consequences and the development of antibiotic resistance, so it is crucial to use fast, reliable, and not too laborious techniques to obtain quick results. Raman spectroscopy has proven to be a powerful tool for molecular analysis, meeting these requirements better than traditional techniques. In this work, we have used Raman spectroscopy combined with machine learning algorithms to explore the automatic identification of eleven species of the genus Candida, the most common cause of fungal infections worldwide. The Raman spectra were obtained from more than 220 different measurements of dried drops from pure cultures of each Candida species using a Raman Confocal Microscope with a 532 nm laser excitation source. After developing a spectral preprocessing methodology, a study of the quality and variability of the measured spectra at the isolate and species level, and the spectral features contributing to inter-class variations, showed the potential to discriminate between those pathogenic yeasts. Several machine learning and deep learning algorithms were trained using hyperparameter optimization techniques to find the best possible classifier for this spectral data, in terms of accuracy and lowest possible overfitting. We found that a one-dimensional Convolutional Neural Network (1-D CNN) could achieve above 80 % overall accuracy for the eleven classes spectral dataset, with good generalization capabilities.This work was supported by the R + D projects INNVAL19/17 (funded by Instituto de Investigación Valdecilla-IDIVAL), PID2019-107270RB-C21 (funded by MCIN/ AEI /10.13039/501100011033) and by Plan Nacional de I + D + and Instituto de Salud Carlos III (ISCIII), Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/0007), CIBERINFEC (CB21/13/00068), CIBER-BBN (BBNGC1601), cofinanced by European Development Regional Fund “A way to achieve Europe”. A. A. O.-S was financially supported by the Miguel Servet II program (ISCIII-CPII17-00011)

Comparison of light capturing approaches in Laser-Induced Breakdown Spectroscopy (LIBS) for multichannel spectrometers

LIBS technique requires the spectroscopic analysis of the light emitted by a laser-induced plasma plume. One challenge of the different approaches to capture the plasma light emission is the significant shot-to-shot variations of the plume inhomogeneities, position, and morphology. This is even more challenging when multichannel CCD spectrometers are used, because the light should be homogeneously divided among multiple capturing optical fibers (typically up to 8 fibers) with stable spectral efficiency for all channels. Otherwise, any further analysis of the atomic emission spectra involving multiple channels, such as line intensity ratios, Boltzmann plots, or calibration-free LIBS, could be compromised by the morphology-dependent spectral artifacts induced by the collection optics. In this work, we assess the performance of several collection optics in terms of overall capturing efficiency and channel-to-channel variations due to changes in plasma morphology. Results clearly show that this could be an issue even with the approaches with the best spatial homogenization, including optical fibers and Köhler optics.This work was supported by the R + D project PID2019-107270RBC21 (funded by MCIN/AEI10.13039/501100011033) and by Plan Nacional de I + D + and Instituto de Salud Carlos III (ISCIII), Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/0007), CIBERINFEC (CB21/13/00068), CIBER-BBN (BBNGC1601), cofinanced by European Development Regional Fund “A way to achieve Europe”. A. O.-S was financially supported by the Miguel Servet II program (ISCIIICPII17–00011). AGE was supported by the Catalonia Government throughout a Beatriu de Pin´os fellowship (grant number 2020 BP 00240). We thanks Dr. A. Pic´on for providing the pure iron ingot and helpful suggestions to improve the experimental setup