Characterizing aeroallergens by infrared spectroscopy of fungal spores and pollen

Background Fungal spores and plant pollen cause respiratory diseases in susceptible individuals, such as asthma, allergic rhinitis and hypersensitivity pneumonitis. Aeroallergen monitoring networks are an important part of treatment strategies, but unfortunately traditional analysis is time consuming and expensive. We have explored the use of infrared spectroscopy of pollen and spores for an inexpensive and rapid characterization of aeroallergens. Methodology The study is based on measurement of spore and pollen samples by single reflectance attenuated total reflectance Fourier transform infrared spectroscopy (SR-ATR FTIR). The experimental set includes 71 spore (Basidiomycota) and 121 pollen (Pinales, Fagales and Poales) samples. Along with fresh basidiospores, the study has been conducted on the archived samples collected within the last 50 years. Results The spectroscopic-based methodology enables clear spectral differentiation between pollen and spores, as well as the separation of confamiliar and congeneric species. In addition, the analysis of the scattering signals inherent in the infrared spectra indicates that the FTIR methodology offers indirect estimation of morphology of pollen and spores. The analysis of fresh and archived spores shows that chemical composition of spores is well preserved even after decades of storage, including the characteristic taxonomy-related signals. Therefore, biochemical analysis of fungal spores by FTIR could provide economical, reliable and timely methodologies for improving fungal taxonomy, as well as for fungal identification and monitoring. This proof of principle study shows the potential for using FTIR as a rapid tool in aeroallergen studies. In addition, the presented method is ready to be immediately implemented in biological and ecological studies for direct measurement of pollen and spores from flowers and sporocarps

The CFA Franc: French monetary imperialism in Africa

Ndongo Samba Sylla argues that the CFA franc - officially created on 26 December 1945 by a decree of General de Gaulle - used across much of Africa today is a colonial relic. For those hoping to export competitive products, obtain affordable credit, work for the integration of continental trade, or fight for an Africa free from imperialist control, the CFA franc is an anachronism demanding orderly and methodical eliminatio

A Fully Automated Robot for the Preparation of Fungal Samples for FTIR Spectroscopy Using Deep Learning

Manual preparation of fungal samples for Fourier Transform Infrared (FTIR) spectroscopy involves sample washing, homogenization, concentration and spotting, which requires time-consuming and repetitive operations, making it unsuitable for screening studies. This paper presents the design and development of a fully automated robot for the preparation of fungal samples for FTIR spectroscopy. The whole system was constructed based on a previously-developed ultrasonication robot module, by adding a newly-designed centrifuge module and a newly-developed liquid handling module. The liquid handling module consists of a high accuracy electric pipette for spotting and a low accuracy syringe pump for sample washing and concentration. A dual robotic arm system with a gripper connects all of the hardware components. Furthermore, a camera on the liquid handling module uses deep learning to identify the labware settings, which includes the number and positions of well plates and pipette tips. Machine vision on the ultrasonication robot module can detect the sample wells and return the locations to the liquid handling module, which makes the system hand-free for users. Tight integration of all the modules enables the robot to process up to two 96-well microtiter (MTP) plates of samples simultaneously. Performance evaluation shows the deep learning based approach can detect four classes of labware with high average precision, from 0.93 to 1.0. In addition, tests of all procedures show that the robot is able to provide homogeneous sample spots for FTIR spectroscopy with high positional accuracy and spot coverage rate

Two-resonator circuit QED: Dissipative Theory

We present a theoretical treatment for the dissipative two-resonator circuit quantum electrodynamics setup referred to as quantum switch. There, switchable coupling between two superconducting resonators is mediated by a superconducting qubit operating in the dispersive regime, where the qubit transition frequency is far detuned from those of the resonators. We derive an effective Hamiltonian for the quantum switch beyond the rotating wave approximation and study the dissipative dynamics within a Bloch-Redfield quantum master equation approach. We derive analytically how the qubit affects the quantum switch even if the qubit has no dynamics, and we estimate the strength of this influence. The analytical results are corroborated by numerical calculations, where coherent oscillations between the resonators, the decay of coherent and Fock states, and the decay of resonator-resonator entanglement are studied. Finally, we suggest an experimental protocol for extracting the damping constants of qubit and resonators by measuring the quadratures of the resonator fields.Comment: 17 pages, 9 figure

Oleaginous yeasts respond differently to carbon sources present in lignocellulose hydrolysate

Background Microbial oils, generated from lignocellulosic material, have great potential as renewable and sustainable alternatives to fossil-based fuels and chemicals. By unravelling the diversity of lipid accumulation physiology in different oleaginous yeasts grown on the various carbon sources present in lignocellulose hydrolysate (LH), new targets for optimisation of lipid accumulation can be identified. Monitoring lipid formation over time is essential for understanding lipid accumulation physiology. This study investigated lipid accumulation in a variety of oleaginous ascomycetous and basidiomycetous strains grown in glucose and xylose and followed lipid formation kinetics of selected strains in wheat straw hydrolysate (WSH). Results Twenty-nine oleaginous yeast strains were tested for their ability to utilise glucose and xylose, the main sugars present in WSH. Evaluation of sugar consumption and lipid accumulation revealed marked differences in xylose utilisation capacity between the yeast strains, even between those belonging to the same species. Five different promising strains, belonging to the species Lipomyces starkeyi, Rhodotorula glutinis, Rhodotorula babjevae and Rhodotorula toruloides, were grown on undiluted wheat straw hydrolysate and lipid accumulation was followed over time, using Fourier transform-infrared (FTIR) spectroscopy. All five strains were able to grow on undiluted WSH and to accumulate lipids, but to different extents and with different productivities. R. babjevae DVBPG 8058 was the best-performing strain, accumulating 64.8% of cell dry weight (CDW) as lipids. It reached a culture density of 28 g/L CDW in batch cultivation, resulting in a lipid content of 18.1 g/L and yield of 0.24 g lipids per g carbon source. This strain formed lipids from the major carbon sources in hydrolysate, glucose, acetate and xylose. R. glutinis CBS 2367 also consumed these carbon sources, but when assimilating xylose it consumed intracellular lipids simultaneously. Rhodotorula strains contained a higher proportion of polyunsaturated fatty acids than the two tested Lipomyces starkeyi strains. Conclusions There is considerable metabolic diversity among oleaginous yeasts, even between closely related species and strains, especially when converting xylose to biomass and lipids. Monitoring the kinetics of lipid accumulation and identifying the molecular basis of this diversity are keys to selecting suitable strains for high lipid production from lignocellulose

Grayscale representation of infrared microscopy images by Extended Multiplicative Signal Correction for registration with histological images

Fourier-transform infrared (FTIR) microspectroscopy is rounding the corner to become a label-free routine method for cancer diagnosis. In order to build infrared-spectral based classifiers, infrared images need to be registered with Hematoxylin and Eosin (H&E) stained histological images. While FTIR images have a deep spectral domain with thousands of channels carrying chemical and scatter information, the H&E images have only three color channels for each pixel and carry mainly morphological information. Therefore, image representations of infrared images are needed that match the morphological information in H&E images. In this paper, we propose a novel approach for representation of FTIR images based on extended multiplicative signal correction highlighting morphological features that showed to correlate well with morphological information in H&E images. Based on the obtained representations, we developed a strategy for global-to-local image registration for FTIR images and H&E stained histological images of parallel tissue sections.publishedVersio

Investigation of resonance structures in optically thin solar cells

publishedVersio

Montana Kaimin, January 30, 2008

Student newspaper of the University of Montana, Missoula.https://scholarworks.umt.edu/studentnewspaper/6138/thumbnail.jp