scholarly journals Mass Spectrometry Analysis of NMC622/Graphite Li-Ion Cells Electrolyte Degradation Products after Storage and Cycling

2021 ◽  
Author(s):  
Rigaud Sébastien ◽  
Ana Cristina Martinez Maciel ◽  
Tristan Lombard ◽  
Sylvie Grugeon ◽  
Pierre Tran-Van ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Degradation Products ◽  
Principal Component ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Statistical Tool ◽  
Decomposition Products ◽  
Spectrometry Analysis ◽  
Li Ion ◽  
Triton X

Abstract With the aim of establishing a data simultaneous comparison, the Principal Component Analysis (PCA) statistical tool was applied to LiNi0.6Mn0.2Co0.2O2/graphite Li-ion cells electrolyte’s decomposition products detected by UHPLC-ESI-HRMS. Herein, we illustrate how the chemometric tool associated with mass spectrometry data can be relevant to provide information about the presence of unusual molecules. Indeed, pristine Triton X-100 surfactant molecules used in electrode elaboration process were detected after impregnation stage. However, as they chemically react and oxidize at a potential lower than 4.5V vs. Li/Li+, only surfactant derivatives and classical ageing molecules were observed, respectively, after storage and cycling stages at 55°C, leading to a triangle-type correlation circle. On the other hand, global schemes of LiPF6-based electrolyte degradation pathways were elaborated from a comparative study with literature to help interpret results in future electrolyte ageing studies.

Quantitative In Situ Mass Spectrometry Analysis of Mannitol Decomposition Products under Hydrothermal Conditions

2017 ◽  
Vol 31 (10) ◽  
pp. 10866-10873
Author(s):  
Pattasuda Duangkaew ◽  
Shuhei Inoue ◽  
Tsunehiro Aki ◽  
Yutaka Nakashimada ◽  
Yoshiko Okamura ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Analysis ◽  
Hydrothermal Conditions ◽  
Decomposition Products ◽  
Spectrometry Analysis

Utilities for Mass Spectrometry Analysis of Proteins (UMSAP): Fast post-processing of mass spectrometry data

2018 ◽  
Vol 32 (19) ◽  
pp. 1659-1667 ◽  
Author(s):  
Kenny Bravo-Rodriguez ◽  
Birte Hagemeier ◽  
Lea Drescher ◽  
Marian Lorenz ◽  
Juliana Rey ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Post Processing ◽  
Spectrometry Analysis

Protein profile of the ovarian follicular fluid of brown brocket deer (Mazama gouazoubira; Fisher, 1814)

Zygote ◽  
2019 ◽  
Vol 28 (2) ◽  
pp. 170-173
Author(s):  
Thaís T.S. Souza ◽  
Maria J.B. Bezerra ◽  
Maurício F. van Tilburg ◽  
Celso S. Nagano ◽  
Luciana D. Rola ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Follicular Fluid ◽  
Protein Profile ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Significant Difference ◽  
Mazama Gouazoubira ◽  
Ovarian Follicular Fluid ◽  
Brocket Deer

SummaryThe aim of this study was to characterize the protein profile of ovarian follicular fluid (FF) of brown brocket deer (Mazama gouazoubira). Five adult females received an ovarian stimulation treatment and the FF was collected by laparoscopy from small/medium (≤3.5 mm) and large (>3.5 mm) follicles. Concentrations of soluble proteins in FF samples were measured and proteins were analyzed by 1-D SDS-PAGE followed by tryptic digestion and tandem mass spectrometry. Data from protein list defined after a Mascot database search were analyzed using the STRAP software tool. For the protein concentration, no significant difference (P > 0.05) was observed between small/medium and large follicles: 49.2 ± 22.8 and 56.7 ± 27.4 μg/μl, respectively. Mass spectrometry analysis identified 13 major proteins, but with no significant difference (P > 0.05) between follicle size class. This study provides insight into elucidating folliculogenesis in brown brocket deer.

scholarly journals A validated method for the analysis and profiling of ‘nyaope’ using gas chromatography – mass spectrometry

2021 ◽  
Vol 117 (11/12) ◽  
Author(s):  
Pabalala M. Mthembi ◽  
Ellen M. Mwenesongole ◽  
Michael D. Cole
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Principal Component ◽  
Mass Spectrometry Analysis ◽  
Gas Chromatography Mass Spectrometry ◽  
Drug Cocktail ◽  
Spectrometry Analysis ◽  
Chromatography Mass Spectrometry ◽  
First Time ◽  
Problem Drug

Nyaope, a Tswana word for a mixture or ‘mish-mash’, describes a drug cocktail consisting of heroin, cannabis, and on occasion other controlled substances and warfarin. It is highly addictive with extremely unpleasant side effects caused by withdrawal from the drug. It is a problem drug especially in townships in South Africa. However, its prevalence in neighbouring southern African states and further afield is not yet known. There is currently no validated method for the analysis and comparison of nyaope. We describe a validated method for the gas chromatography – mass spectrometry analysis of nyaope so that within-batch and between-batch comparisons of nyaope can successfully be made for the first time. The validated method managed an accuracy within the range 80–120%, the precision was less than 20% for all analytes and managed linearity with R2≥0.99. The detection limits for diamorphine, efavirenz, nevirapine and Δ9-tetrahydrocannabinol were 14.2, 18.6, 18.7 and 9.94 pg on column, respectively, and the limits of quantitation were 43.1, 56.3, 56.6 and 30.1 pg on column, respectively. The simulated and casework samples were successfully discriminated into original batches using the identified nyaope components, the unsupervised chemometric methods principal component analysis and hierarchical clustering, as well as chromatographic profiles.

Bio-Inspired Metaheuristic Optimization Algorithms for Biomarker Identification in Mass Spectrometry Analysis

2012 ◽  
Vol 3 (2) ◽  
pp. 64-85 ◽  
Author(s):  
Syarifah Adilah Mohamed Yusoff ◽  
Ibrahim Venkat ◽  
Umi Kalsom Yusof ◽  
Rosni Abdullah
Keyword(s):  
Mass Spectrometry ◽  
Chemical Properties ◽  
Feature Subset Selection ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Computational Techniques ◽  
Feature Subset ◽  
Protein Patterns ◽  
Spectrometry Analysis ◽  
Biomarker Analysis

Mass spectrometry is an emerging technique that is continuously gaining momentum among bioinformatics researchers who intend to study biological or chemical properties of complex structures such as protein sequences. This advancement also embarks in the discovery of proteomic biomarkers through accessible body fluids such as serum, saliva, and urine. Recently, literature reveals that sophisticated computational techniques mimetic survival and natural processes adapted from biological life for reasoning voluminous mass spectrometry data yields promising results. Such advanced approaches can provide efficient ways to mine mass spectrometry data in order to extract parsimonious features that represent vital information, specifically in discovering disease-related protein patterns in complex proteins sequences. This article intends to provide a systematic survey on bio-inspired approaches for feature subset selection via mass spectrometry data for biomarker analysis.

scholarly journals Online capillary electrophoresis – mass spectrometry analysis of histatin-5 and its degradation products

The Analyst ◽  
2020 ◽  
Vol 145 (14) ◽  
pp. 4787-4794
Author(s):  
Jared Lamp ◽  
Svetlana P. Ikonomova ◽  
Amy J. Karlsson ◽  
Qiangwei Xia ◽  
Yan Wang
Keyword(s):  
Mass Spectrometry ◽  
Capillary Electrophoresis ◽  
Degradation Products ◽  
Mass Spectrometry Analysis ◽  
Histatin 5 ◽  
Spectrometry Analysis ◽  
Salivary Peptide ◽  
Antibacterial And Antifungal Activities ◽  
Antibacterial And Antifungal ◽  
Capillary Electrophoresis Mass Spectrometry

Histatin-5 (Hst-5) is a human salivary peptide with antibacterial and antifungal activities. A novel capillary electrophoresis – mass spectrometry (CE-MS) method is developed to address issues related to highly basic and cationic nature of Hst-5.

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