Understanding the responses of Saccharomyces cerevisiae yeast strain during dehydration processes using synchrotron infrared spectroscopy

The Analyst ◽  
2017 ◽  
Vol 142 (19) ◽  
pp. 3620-3628 ◽  
Author(s):  
T. D. Nguyen ◽  
S. Guyot ◽  
C. Pénicaud ◽  
S. Passot ◽  
C. Sandt ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Infrared Spectroscopy ◽  
Relative Humidity ◽  
Real Time ◽  
Yeast Strain ◽  
Dehydration Processes ◽  
First Time

For the first time, synchrotron infrared spectroscopy was performed on yeast during dehydration processes in real time with simultaneously controlled relative humidity and temperature.

scholarly journals Dynamic surface properties of PEG-coated CuS nanoparticles alter their interaction with cells as revealed by surface-enhanced infrared spectroscopy

2019 ◽  
Vol 1 (11) ◽  
pp. 4268-4276
Author(s):  
Fengjuan Cao ◽  
Lie Wu ◽  
Xiaofei Zhang ◽  
Shanshan Li ◽  
Chao Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Real Time ◽  
Surface Properties ◽  
Cell Interaction ◽  
Label Free ◽  
Dynamic Changes ◽  
Dynamic Surface ◽  
Surface Enhanced ◽  
First Time

How the dynamic changes of the surface properties of nanoparticles affect the nano-cell interaction was revealed for the first time, by in situ real-time label-free SEIRA spectroscopy at the nanoscale.

Probing the Dynamic Self-Assembly Behaviour of Photoswitchable Wormlike Micelles in Real Time

2018 ◽  
Author(s):  
Elaine A. Kelly ◽  
Judith E. Houston ◽  
Rachel Evans
Keyword(s):  
Real Time ◽  
Absorption Spectroscopy ◽  
Self Assembly ◽  
Uv Light ◽  
Wormlike Micelles ◽  
Tetraethylene Glycol ◽  
Light Illumination ◽  
First Time ◽  
Dependent Processes

Understanding the dynamic self-assembly behaviour of azobenzene photosurfactants (AzoPS) is crucial to advance their use in controlled release applications such as<i></i>drug delivery and micellar catalysis. Currently, their behaviour in the equilibrium <i>cis-</i>and <i>trans</i>-photostationary states is more widely understood than during the photoisomerisation process itself. Here, we investigate the time-dependent self-assembly of the different photoisomers of a model neutral AzoPS, <a>tetraethylene glycol mono(4′,4-octyloxy,octyl-azobenzene) </a>(C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>) using small-angle neutron scattering (SANS). We show that the incorporation of <i>in-situ</i>UV-Vis absorption spectroscopy with SANS allows the scattering profile, and hence micelle shape, to be correlated with the extent of photoisomerisation in real-time. It was observed that C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>could switch between wormlike micelles (<i>trans</i>native state) and fractal aggregates (under UV light), with changes in the self-assembled structure arising concurrently with changes in the absorption spectrum. Wormlike micelles could be recovered within 60 seconds of blue light illumination. To the best of our knowledge, this is the first time the degree of AzoPS photoisomerisation has been tracked <i>in</i><i>-situ</i>through combined UV-Vis absorption spectroscopy-SANS measurements. This technique could be widely used to gain mechanistic and kinetic insights into light-dependent processes that are reliant on self-assembly.

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

scholarly journals Temperature and Relative Humidity Profile Retrieval from Fengyun-3D/HIRAS in the Arctic Region

2021 ◽  
Vol 13 (10) ◽  
pp. 1884
Author(s):  
Jingjing Hu ◽  
Yansong Bao ◽  
Jian Liu ◽  
Hui Liu ◽  
George P. Petropoulos ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Wide Spectrum ◽  
Warm Season ◽  
Arctic Region ◽  
Cold Season ◽  
The Arctic ◽  
Practical Applications ◽  
A New Technique ◽  
The Arctic Region

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

scholarly journals Transcriptome Analysis Reveals a Promotion of Carotenoid Production by Copper Ions in Recombinant Saccharomyces cerevisiae

2021 ◽  
Vol 9 (2) ◽  
pp. 233
Author(s):  
Buli Su ◽  
Anzhang Li ◽  
Ming-Rong Deng ◽  
Honghui Zhu
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Transcriptome Analysis ◽  
Gene Expression Analysis ◽  
Target Genes ◽  
Copper Ions ◽  
Carotenoid Production ◽  
Carotenoid Accumulation ◽  
Nutritional Components ◽  
Differential Gene ◽  
First Time

We previously constructed a Saccharomyces cerevisiae carotenoid producer BL03-D-4 which produced much more carotenoid in YPM (modified YPD) media than YPD media. In this study, the impacts of nutritional components on carotenoid accumulation of BL03-D-4 were investigated. When using YPM media, the carotenoid yield was increased 10-fold compared to using the YPD media. To elucidate the hidden mechanism, a transcriptome analysis was performed and showed that 464 genes changed significantly in YPM media. Furthermore, inspired by the differential gene expression analysis which indicated that ADY2, HES1, and CUP1 showed the most remarkable changes, we found that the improvement of carotenoid accumulation in YPM media was mainly due to the copper ions, since supplementation of 0.08 mM CuSO4 in YPD media could increase carotenoid yield 9.2-fold. Reverse engineering of target genes was performed and carotenoid yield could be increased 6.4-fold in YPD media through overexpression of ACE1. The present study revealed for the first time the prominent promotion of carotenoid yield by copper ions in engineered S. cerevisiae and provided a new target ACE1 for genetic engineering of S. cerevisiae for the bioproduction of carotenoids.

scholarly journals Molecular Survey of Vector-Borne Pathogens of Dogs and Cats in Two Regions of Saudi Arabia

Pathogens ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Abdullah D. Alanazi ◽  
Abdulaziz S. Alouffi ◽  
Mohamed S. Alyousif ◽  
Mohammad Y. Alshahrani ◽  
Hend H. A. M. Abdullah ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Real Time ◽  
Real Time Pcr ◽  
Bartonella Henselae ◽  
Public Awareness ◽  
Effective Control ◽  
Vector Borne Diseases ◽  
Babesia Vogeli ◽  
Vector Borne ◽  
First Time

Dogs and cats play an important role as reservoirs of vector-borne pathogens, yet reports of canine and feline vector-borne diseases in Saudi Arabia are scarce. Blood samples were collected from 188 free-roaming dogs and cats in Asir (70 dogs and 44 cats) and Riyadh (74 dogs), Saudi Arabia. The presence of Anaplasma spp., Bartonella spp., hemotropic Mycoplasma spp., Babesia spp., and Hepatozoon spp. was detected using a multiplex tandem real-time PCR. PCR-positive samples were further examined with specific conventional and real-time PCR followed by sequencing. Dogs from Riyadh tested negative for all pathogens, while 46 out of 70 dogs (65.7%) and 17 out of 44 cats (38.6%) from Asir were positive for at least one pathogen. Positive dogs were infected with Anaplasma platys (57.1%), Babesia vogeli (30%), Mycoplasma haemocanis (15.7%), and Bartonella henselae (1.4%), and cats were infected with Mycoplasma haemofelis (13.6%), Candidatus Mycoplasma haemominutum (13.6%), B. henselae (9.2%), and A. platys (2.27%), all of which are reported for the first time in Saudi Arabia. Co-infection with A. platys and B. vogeli was detected in 17 dogs (24.28%), while coinfections were not detected in cats. These results suggest that effective control and public awareness strategies for minimizing infection in animals are necessary.

Kinetic and mechanistic studies on the Heck reaction using real-time near infrared spectroscopy

2003 ◽  
Vol 5 (20) ◽  
pp. 4455-4460 ◽  
Author(s):  
Susana C. Cruz ◽  
Petra J. Aarnoutse ◽  
Gadi Rothenberg ◽  
Johan A. Westerhuis ◽  
Age K. Smilde ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Real Time ◽  
Near Infrared Spectroscopy ◽  
Heck Reaction ◽  
Near Infrared ◽  
Mechanistic Studies

scholarly journals Mating of 2 Laboratory Saccharomyces cerevisiae Strains Resulted in Enhanced Production of 2-Phenylethanol by Biotransformation of L-Phenylalanine

2017 ◽  
Vol 27 (2) ◽  
pp. 81-90 ◽  
Author(s):  
Jolanta Mierzejewska ◽  
Aleksandra Tymoszewska ◽  
Karolina Chreptowicz ◽  
Kamil Krol
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Batch Culture ◽  
Fold Increase ◽  
Biotechnological Production ◽  
Aromatic Alcohol ◽  
Enhanced Production ◽  
Yeast Strains ◽  
First Time

2-Phenylethanol (2-PE) is an aromatic alcohol with a rosy scent which is widely used in the food, fragrance, and cosmetic industries. Promising sources of natural 2-PE are microorganisms, especially yeasts, which can produce 2-PE by biosynthesis and biotransformation. Thus, the first challenging goal in the development of biotechnological production of 2-PE is searching for highly productive yeast strains. In the present work, 5 laboratory <i>Saccharomyces cerevisiae</i> strains were tested for the production of 2-PE. Thereafter, 2 of them were hybridized by a mating procedure and, as a result, a new diploid, <i>S. cerevisiae</i> AM1-d, was selected. Within the 72-h batch culture in a medium containing 5 g/L of <smlcap>L</smlcap>-phenylalanine, AM1-d produced 3.83 g/L of 2-PE in a shaking flask. In this way, we managed to select the diploid <i>S. cerevisiae</i> AM1-d strain, showing a 3- and 5-fold increase in 2-PE production in comparison to parental strains. Remarkably, the enhanced production of 2-PE by the hybrid of 2 yeast laboratory strains is demonstrated here for the first time.

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