Unsupervised methods in LC-MS data treatment: application for potential chemotaxonomic markers search

2021 ◽  
pp. 114382
Author(s):  
Polina Turova ◽  
Iain Styles ◽  
Vladimir Timashev ◽  
Konstantin Kravets ◽  
Alexander Grechnikov ◽  
...  
Keyword(s):  
Data Treatment ◽  
Chemotaxonomic Markers ◽  
Unsupervised Methods ◽  
Treatment Application

Reply to Comment on Grahl-Nielsen et al. (2003): sampling, data treatment and predictions in investigations on fatty acids in marine mammals

2004 ◽  
Vol 281 ◽  
pp. 303-306 ◽  
Author(s):  
O Grahl-Nielsen ◽  
M Andersen ◽  
AE Derocher ◽  
C Lydersen ◽  
Ø Wiig ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Marine Mammals ◽  
Data Treatment

Comparison of copper sulphate pentahydrate growth rates determined by different methods

1990 ◽  
Vol 55 (7) ◽  
pp. 1691-1707 ◽  
Author(s):  
Miloslav Karel ◽  
Jiří Hostomský ◽  
Jaroslav Nývlt ◽  
Axel König
Keyword(s):  
Growth Rate ◽  
Crystal Growth ◽  
Fluidized Bed ◽  
Growth Rates ◽  
Copper Sulphate ◽  
Crystal Growth Rate ◽  
Effect Of Temperature ◽  
Rotating Disc ◽  
Shape Factors ◽  
Data Treatment

Crystal growth rates of copper sulphate pentahydrate (CuSO4.5 H2O) determined by different authors and methods are compared. The methods included in this comparison are: (i) Measurement on a fixed crystal suspended in a streaming solution, (ii) measurement on a rotating disc, (iii) measurement in a fluidized bed, (iv) measurement in an agitated suspension. The comparison involves critical estimation of the supersaturation used in measurements, of shape factors used for data treatment and a correction for the effect of temperature. Conclusions are drawn for the choice of values to be specified when data of crystal growth rate measurements are published.

scholarly journals Comparison of Missing Rainfall Data Treatment Analysis at Kenyir Lake

2021 ◽  
Vol 1144 (1) ◽  
pp. 012046
Author(s):  
Azreen Harina Azman ◽  
Nurul Nadrah Aqilah Tukimat ◽  
M A Malek
Keyword(s):  
Rainfall Data ◽  
Data Treatment ◽  
Treatment Analysis

scholarly journals Emerging biogenesis technologies of extracellular vesicles for tissue regenerative therapeutics

2021 ◽  
Vol 12 ◽  
pp. 204173142110190
Author(s):  
Jung-Hwan Lee ◽  
Ji-Young Yoon ◽  
Jun Hee Lee ◽  
Hae-Hyoung Lee ◽  
Jonathan C Knowles ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Chemical Treatment ◽  
Mass Production ◽  
Disease Status ◽  
Clinical Translation ◽  
Technological Advances ◽  
Tissue Healing ◽  
Bio Imaging ◽  
Key Issues ◽  
Treatment Application

Extracellular vesicles (EVs), including exosomes, carry the genetic packages of RNA, DNA, and proteins and are heavily involved in cell-cell communications and intracellular signalings. Therefore, EVs are spotlighted as therapeutic mediators for the treatment of injured and dysfunctional tissues as well as biomarkers for the detection of disease status and progress. Several key issues in EVs, including payload content and bioactivity, targeting and bio-imaging ability, and mass-production, need to be improved to enable effective therapeutics and clinical translation. For this, significant efforts have been made recently, including genetic modification, biomolecular and chemical treatment, application of physical/mechanical cues, and 3D cultures. Here we communicate those recent technological advances made mainly in the biogenesis process of EVs or at post-collection stages, which ultimately aimed to improve the therapeutic efficacy in tissue healing and disease curing and the possibility of clinical translation. This communication will help tissue engineers and biomaterial scientists design and produce EVs optimally for tissue regenerative therapeutics.

Recent development in modification of polysulfone membrane for water treatment application

2020 ◽  
pp. 101835
Author(s):  
Stanley Chinedu Mamah ◽  
Pei Sean Goh ◽  
Ahmad Fauzi Ismail ◽  
Nor Diyana Suzaimi ◽  
Lukka Thuyavan Yogarathinam ◽  
...  
Keyword(s):  
Water Treatment ◽  
Polysulfone Membrane ◽  
Treatment Application

scholarly journals Nuclear Magnetic Resonance Metabolomics Approach for the Analysis of Major Legume Sprouts Coupled to Chemometrics

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 761
Author(s):  
Mohamed A. Farag ◽  
Mohamed G. Sharaf El-Din ◽  
Mohamed A. Selim ◽  
Asmaa I. Owis ◽  
Sameh F. Abouzid ◽  
...  
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Multivariate Data Analysis ◽  
Potential Role ◽  
Full Range ◽  
Legume Seeds ◽  
Region Data ◽  
Chemotaxonomic Markers ◽  
Seeds Germination ◽  
Nuclear Magnetic

Legume sprouts are a fresh nutritive source of phytochemicals of increasing attention worldwide owing to their many health benefits. Nuclear magnetic resonance (NMR) was utilized for the metabolite fingerprinting of 4 major legume sprouts, belonging to family Fabaceae, to be exploited for quality control purposes. Thirty-two metabolites were identified belonging to different classes, i.e., fatty acids, sugars, amino acids, nucleobases, organic acids, sterols, alkaloids, and isoflavonoids. Quantitative NMR was employed for assessing the major identified metabolite levels and multivariate data analysis was utilized to assess metabolome heterogeneity among sprout samples. Isoflavones were detected exclusively in Cicer sprouts, whereas Trigonella was characterized by 4-hydroxyisoleucine. Vicia sprouts were distinguished from other legume sprouts by the presence of L-Dopa versus acetate abundance in Lens. A common alkaloid in all sprouts was trigonelline, detected at 8–25 µg/mg, suggesting its potential role in legume seeds’ germination. Trigonelline was found at highest levels in Trigonella sprouts. The aromatic NMR region data (δ 11.0–5.0 ppm) provided a better classification power than the full range (δ 11.0–0.0 ppm) as sprout variations mostly originated from secondary metabolites, which can serve as chemotaxonomic markers.

An Approach for Data Treatment of Solar Photovoltaic Generation

2020 ◽  
Vol 18 (09) ◽  
pp. 1563-1571
Author(s):  
Jose Pessanha ◽  
Albert Melo ◽  
Roberto Caldas ◽  
Djalma Falcao
Keyword(s):  
Solar Photovoltaic ◽  
Photovoltaic Generation ◽  
Data Treatment

scholarly journals Quality Control in Fiore Sardo PDO Cheese: Detection of Heat Treatment Application and Production Chain by MRI Relaxometry and Image Analysis

Dairy ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 270-287
Author(s):  
Roberto Anedda ◽  
Riccardo Melis ◽  
Elena Curti
Keyword(s):  
Image Analysis ◽  
Raw Milk ◽  
Characteristic Relaxation Time ◽  
Resonance Imaging ◽  
Production Chain ◽  
Visual Appearance ◽  
Heat Treated ◽  
Heat Application ◽  
Magnetic Resonance Imaging Mri ◽  
Treatment Application

Fiore Sardo (FS), a traditional Italian cheese, is present in the market as a heterogeneous variety of products. The use of heat-treated (HT) milk is forbidden by the official production protocol, but no official analytical method able to detect heat application is yet available. Here, a combined magnetic resonance imaging (MRI) relaxometry and image analysis approach to recognize FS made from raw milk is presented. Artisanal FS cheeses were produced from raw milk (RC) by five shepherds in accordance with the official protocol. They were compared to HT-milk counterparts (HTC). Additionally, industrially manufactured commercial FS cheeses (I) were also purchased and compared to RC and HTC. Relaxometry data of FS indicated the presence of two water populations; the ratio of characteristic relaxation time constant T2 and area fraction (Score, Ṩ) of the fastest relaxing population was used to compare RC, HTC and I samples. RC from HTC were successfully discriminated, the latter exhibiting lower Ṩ (enhanced protein hydration). I cheeses exhibited the lowest Ṩ values, sometimes comparable to HTC. Since visual appearance of RC and HTC is appreciably different, an image analysis deep learning approach using MRI and photographic pictures was adopted to discriminate the two productions, with promising percentages (>93%).

Sign in / Sign up

Export Citation Format

Share Document