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.

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

Mass spectrometry analysis of follicular fluid from patients with ovary cancer

2008 ◽  
Vol 90 ◽  
pp. S269
Author(s):  
E.G. Lo Turco ◽  
J. Stevanato ◽  
A.B. Victorino ◽  
M. Sakata ◽  
R. Fraietta ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Follicular Fluid ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Ovary Cancer

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 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.

scholarly journals N-glycan profiling of bovine follicular fluid at key dominant follicle developmental stages

Reproduction ◽  
2014 ◽  
Vol 148 (6) ◽  
pp. 569-580 ◽  
Author(s):  
T Tharmalingam-Jaikaran ◽  
S W Walsh ◽  
P A McGettigan ◽  
O Potter ◽  
W B Struwe ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Follicular Fluid ◽  
High Performance ◽  
Developmental Stages ◽  
Exchange Chromatography ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Glycan Profile ◽  
Dairy Heifers

Follicular fluid (FF), an important microenvironment for the development of oocytes, contains many proteins that are glycosylated withN-linked glycans. This study aimed i) to present an initial analysis of theN-linked glycan profile of bovine FF using hydrophilic interaction liquid chromatography, anion exchange chromatography, high performance liquid chromatography (HPLC)-based separations and subsequent liquid chromatography–mass spectrometry/mass spectrometry analysis; ii) to determine differences in theN-glycan profile between FF from dominant and subordinate follicles from dairy heifers and lactating dairy cows and iii) to identify alterations in theN-glycan profile of FF during preovulatory follicle development using newly selected, differentiated (preovulatory) and luteinised dominant follicles from dairy heifers and lactating cows. We found that the majority of glycans on bovine FF are based on biantennary hypersialylated structures, where the glycans are sialylated on both the galactose andN-acetylglucosamine terminal sugars. A comparison of FFN-glycans from cows and heifers indicated higher levels of nonsialylated glycans with a lower proportion of sialylated glycans in cows than in heifers. Overall, as the follicle develops from Selection, Differentiation and Luteinisation in both cows and heifers, there is an overall decrease in sialylated structures on FFN-glycans.

scholarly journals Understanding the Fate of Almond (Prunus dulcis (Mill.) D.A. Webb) Oleosomes during Simulated Digestion

Nutrients ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3397
Author(s):  
Domenico Trombetta ◽  
Antonella Smeriglio ◽  
Marcella Denaro ◽  
Roberto Zagami ◽  
Mara Tomassetti ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Droplet Size ◽  
Protein Profile ◽  
Imaging Mass Spectrometry ◽  
Mass Spectrometry Analysis ◽  
Gastrointestinal Digestion ◽  
Positive Health ◽  
Plant Oil ◽  
Spectrometry Analysis

Background: Almond kernels contain phytochemicals with positive health effects in relation to heart disease, diabetes and obesity. Several studies have previously highlighted that almond cell wall encapsulation during digestion and particle size are factors associated with these benefits. In the present study, we have characterized almond oleosomes, natural oil droplets abundant in plants, and we have investigated their integrity during simulated gastrointestinal digestion. Methods: Oleosomes were visualized on the almond seed surface by imaging mass spectrometry analysis, and then characterized in terms of droplet size distribution by dynamic light scattering and protein profile by liquid chromatography high-resolution tandem mass spectrometry analysis. Results: The almond oleosomes’ distribution remained monomodal after in vitro mastication, whereas gastric and duodenal digestion led to a bimodal distribution, albeit characterized mainly by a prevalent population with a droplet size decrease related to a rearrangement of the protein profile. Oleosins, structural proteins found in plant oil bodies, persisted unchanged during simulated mastication, with the appearance of new prunin isoforms after gastric and duodenal digestion. Conclusions: The rearrangement of the protein profile could limit lipid bioaccessibility. The data improve our understanding of the behavior of almond lipids during gastrointestinal digestion, and may have implications for energy intake and satiety imparted by almonds.

Mass spectrometry analysis of follicular fluid from a patient with endometriosis

2008 ◽  
Vol 90 ◽  
pp. S439
Author(s):  
E.G. Lo Turco ◽  
A.B. Victorino ◽  
J. Stevanato ◽  
J. Perez ◽  
R.P. Bertolla ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Follicular Fluid ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis

scholarly journals A dry method for preserving tear protein samples

2017 ◽  
Author(s):  
Weiwei Qin ◽  
Chan Zhao ◽  
Linpei Zhang ◽  
Ting Wang ◽  
Youhe Gao
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Low Cost ◽  
Mass Spectrometry Analysis ◽  
Protein Patterns ◽  
Spectrometry Analysis ◽  
Disease Biomarkers ◽  
Tear Protein ◽  
Significant Difference ◽  
Biomarker Research

AbstractTears covering the ocular surface is an important bio-fluid containing thousands of molecules, including proteins, lipids, metabolites, nucleic acids, and electrolytes. Tears are valuable resources for biomarker research of ocular and even systemic diseases. For application in biomarker studies, tear samples should ideally be stored using a simple, low-cost, and efficient method along with the patient’s medical records. For this purpose, we developed a novel Schirmer’s strip-based dry method that allows for storage of tear samples in vacuum bags at room temperature. Using this method, tear protein patterns can also be preserved. Liquid chromatography-mass spectrometry/mass spectrometry analysis of proteins recovered from the dry method and traditional wet method showed no significant difference. Some tissue/organ enriched proteins were identified in tear, thus tear might be a good window for monitoring the change of these tissues or organs. This dry method facilitates sample transportation and enables the storage of tear samples on a large scale, increasing the availability of samples for studying disease biomarkers in tears.

scholarly journals XFlow: An algorithm for extracting ion chromatograms

2019 ◽  
Author(s):  
Mathew Gutierrez ◽  
Rob Smith
Keyword(s):  
Mass Spectrometry ◽  
Open Source ◽  
Analytical Methods ◽  
Feature Detection ◽  
Detection Algorithm ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Target Acquisition ◽  
Spectrometry Analysis ◽  
Broad Applicability

AbstractMass spectrometry is a fundamental tool for modern proteomics. The increasing availability of mass spectrometry data paired with the increasing sensitivity and fidelity of the instruments necessitates new and more potent analytical methods. To that end, we have created and present XFlow, a feature detection algorithm for extracting ion chromatograms from MS1 LC-MS data. XFlow is a parameter-free procedurally agnostic feature detection algorithm that utilizes the latent properties of ion chromatograms to resolve them from the surrounding noise present in MS1 data. XFlow is designed to function on either profile or centroided data across different resolutions and instruments. This broad applicability lends XFlow strong utility as a one-size-fits-all method for MS1 analysis or target acquisition for MS2. XFlow is written in Java and packaged with JS-MS, an open-source mass spectrometry analysis toolkit.

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