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Fatty Acids

Fatty acids are a class of carboxylic acids that are the building blocks of lipids, playing crucial roles in various biological processes.
They can be saturated or unsaturated, and have a wide range of chain lengths.
Fatty acids are essential nutrients, serving as energy sources and structural components of cell membranes.
Imbalances in fatty acid profiles have been linked to numerous health conditions, including cardiovascular disease, diabetes, and inflammation.
Optimization of fatty acid research is key to advancing our understanding and therapeutic applications in this dynamic field of study.

Most cited protocols related to «Fatty Acids»

All metabolite reference standards underwent a two-step derivatization procedure. Therefore 1 mg of each standard was dissolved in a solution of 1 ml methanol:water:isopropanol (2.5:1:1 v/v). Then 10 μl of each standard solution were taken out and evaporated to dryness. First, methoximation was performed to inhibit the ring formation of reducing sugars, protecting also all other aldehydes and ketones. A solution of 40 mg/ml O-methylhydroxylamine hydrochloride, (CAS: [593-56-6]; Formula CH5NO.HCl; Sigma-Aldrich No. 226904 (98%)) in pyridine (99.99%) was prepared. The dried standards and 10 μl of the O-methylhydroxylamine reagent solution were mixed for 30 s in a vortex mixer and subsequently shaken for 90 minutes at 30°C. Afterwards, 90μl of N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA) with 1% trimethylchlorosilane (TMCS) (1 ml bottles, Pierce, Rockford IL) was added and shaken at 37°C for 30 min for trimethylsilylation of acidic protons to increase volatility of metabolites. A mixture of internal retention index (RI) markers was prepared using fatty acid methyl esters (FAME markers) of C8, C9, C10, C12, C14, C16, C18, C20, C22, C24, C26, C28 and C30 linear chain length, dissolved in chloroform at a concentration of 0.8 mg/ml (C8-C16) and 0.4 mg/ml (C18-C30). 2 μl of this RI mixture were added to the reagent solutions, transferred to 2 mL glass crimp amber autosampler vials. Data acquisition parameters are given in table 1. Subsequent to data processing using the instrument manufacturer’s software programs, spectra and retention indices were manually curated into the new Leco FiehnLib (359-008-100) or automatically transferred by Agilent to the new Agilent FiehnLib (G1676AA).
Publication 2009
Acids Aldehydes Amber Cardiac Arrest Chloroform Esters Fatty Acids Isopropyl Alcohol Ketones Methanol methoxyamine Protons pyridine Retention (Psychology) Sugars trimethylchlorosilane Volatility
The long-FFQ consisted of 172 food and beverage items and nine frequency categories, ranging from almost never to seven or more times per day (or to 10 or more glasses per day, for beverages). It asked about the usual consumption of listed foods during the previous year. The food list was initially developed according to percentage contributions based on absolute values of energy and intake of 14 target nutrients from weighed food records in 1989–19918 (link) and used for the Japan Public Health Center-based prospective Study,8 (link)12 (link) for which it was modified for middle-aged and elderly residents in a wide variety of areas of Japan. With regard to this modification, the following criteria were considered: calculation for an additional 17 nutrient items, such as fiber and folate, change of foods contributing to the absolute nutrient intake according to the updated Standard Tables of Food Composition in Japan,13 ,14 and dietary regionality and change in generation for the present cohort (data not shown). As a result, 33 foods were added, and 5 foods and beverages were excluded.15 (link) Moreover, six foods were also added to account for potential inter-individual variation in specific nutrients, such as isothiocyanate and isoflavone. With regard to alcoholic beverages, choices of intake amount were changed from the initial JPHC-FFQ.
To develop the food list for the short-FFQ, we selected and combined items and supporting questions from the original long-FFQ. We selected the three major foods and beverages that contributed to inter-individual variation for each of 40 nutrients according to a cumulative R2 for the 40 nutrients,16 based on the multiple regression coefficient with total intake of a specific nutrient as the dependent variable and its intake from each food as the explanatory variable. Inter-individual variation was calculated by gender among 45 869 men and 52 989 women who responded to the JPHC Study 10-year follow-up survey. Consequently, cumulative R2 for the nutrients ranged from 0.4 to 1.0. For potential inter-individual variation in intake of specific food groups, some foods, such as coffee, were added. Ultimately, 66 food and beverage items were selected for the short-FFQ. In this validation study, information on alcoholic beverages was substituted with those from the long-FFQ (united with overall information of lifestyle), because these questions were not included in the short-FFQ. This was because information on alcoholic beverage intake was structured in pages for lifestyle other than diet, such as smoking status and physical activity, and the reproducibility of alcoholic beverage intake was relatively high even if questionnaires were administered at a 1-year interval.17 (link),18 (link)Intakes of energy, 53 nutrients, and 29 food groups were calculated using the Standard Tables of Food Composition in Japan 2010,19 Standard Tables of Food Composition in Japan Fifth Revised and Enlarged Edition 2005 For Fatty Acids,20 and a specifically developed food composition table for isoflavones in Japanese foods.21 (link)
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Publication 2016
Aged Alcoholic Beverages Beverages Coffee Diet Eating Eyeglasses Fatty Acids Fibrosis Folate Food Isoflavones isothiocyanate Japanese Nutrient Intake Nutrients Woman
We created an overall plant-based diet index (PDI), a healthful plant-based diet index (hPDI), and an unhealthful plant-based diet index (uPDI). The procedure we used to create these indices is similar to the one used by Martínez-González et al. [13 (link)]; their “provegetarian food pattern” is similar in composition to our PDI. Frequencies of consumption of each food were converted into servings consumed per day. Then the number of servings of foods that belonged to each of 18 food groups were added up. The 18 food groups were created on the basis of nutrient and culinary similarities, within larger categories of animal foods and healthy and less healthy plant foods. We distinguished between healthy and less healthy plant foods using existing knowledge of associations of the foods with T2D, other outcomes (CVD, certain cancers), and intermediate conditions (obesity, hypertension, lipids, inflammation). Plant foods not clearly associated in one direction with several health outcomes, specifically alcoholic beverages, were not included in the indices. We also excluded margarine from the indices, as its fatty acid composition has changed over time from high trans fat to high unsaturated fat. We controlled for alcoholic beverages and margarine consumption in the analysis.
Healthy plant food groups included whole grains, fruits, vegetables, nuts, legumes, vegetable oils, and tea/coffee, whereas less healthy plant food groups included fruit juices, sugar-sweetened beverages, refined grains, potatoes, and sweets/desserts. Animal food groups included animal fats, dairy, eggs, fish/seafood, meat (poultry and red meat), and miscellaneous animal-based foods.
S1 Table details examples of foods constituting the food groups. The 18 food groups were divided into quintiles of consumption, and each quintile was assigned a score between 1 and 5. For PDI, participants received a score of 5 for each plant food group for which they were above the highest quintile of consumption, a score of 4 for each plant food group for which they were above the second highest quintile but below the highest quintile, and so on, with a score of 1 for consumption below the lowest quintile (positive scores). On the other hand, participants received a score of 1 for each animal food group for which they were above the highest quintile of consumption, a score of 2 for each animal food group for which they were between the highest and second highest quintiles, and so on, with a score of 5 for consumption below the lowest quintile (reverse scores). For hPDI, positive scores were given to healthy plant food groups, and reverse scores to less healthy plant food groups and animal food groups. Finally, for uPDI, positive scores were given to less healthy plant food groups, and reverse scores to healthy plant food groups and animal food groups. The 18 food group scores for an individual were summed to obtain the indices, with a theoretical range of 18 (lowest possible score) to 90 (highest possible score). The observed ranges at baseline were 24–85 (PDI), 28–86 (hPDI), and 27–90 (uPDI) across the cohorts. The indices were analyzed as deciles, with energy intake adjusted at the analysis stage.
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Publication 2016
Alcoholic Beverages Animals Cereals Coffee Diet Eggs Fabaceae Fats Fats, Unsaturated Fatty Acids Feeds, Animal Fishes Food Fowls, Domestic Fruit Fruit Juices High Blood Pressures Inflammation Lipids Malignant Neoplasms Margarine Meat Nutrients Nuts Obesity Plants Plants, Edible Red Meat Seafood Solanum tuberosum Sugar-Sweetened Beverages Vegetable Oils Vegetables Whole Grains
Eight acquisitions containing complete sets of MS and MS/MS spectra were independently submitted as *.raw files. The output was aligned by reported lipid species. Individual lipid species were considered as positively identified if they were recognized in four or more replicated analyses. In all tests the programs were prompted to identify species of PE, PI, PS, PG and PA classes. Mass tolerance was set at 0.3 Da in MS and MS/MS modes; fatty acid moieties were assumed to comprise 12 to 22 carbon atoms and 0 to 6 double bonds.
Settings specific for each tested program were as follows.
LipidXplorer: 'MS threshold' was set to 100 and 'MS/MS threshold' to 5 counts per peak area; 'Resolution gradient' was set to 1; other common spectra import settings were as in Additional file 13 (setting: 'FAS_LTQ').
LipidQA (spectra were imported as *.raw files): 'MS error' and the 'MS/MS error' were both set to 0.3 Da; 'Finnigan Filter', on; 'Quantification', off; 'Mode selection', Neg. Mode; 'If MS2 spectra were centroided', checked. Only species with a score above 0.5 were accepted. The current version of LipidQA is available at [51 ].
Lipid Search version 2.0 beta: 'SearchType' was set to 'MS2,MS3'; 'ExpType' to 'Infusion'; 'Precursor tol' to '0.3 Da'; 'Product peak tol' to 0.3 Da; 'Intensity threshold' to 0.01; 'Threshold type' to Relative; 'M-score Threshold' to 10.0. The current version of LipidSearch is available at [52 ].
LipidProfiler v.1.0.97: the software was used for creating a reference list of lipids in the E. coli extract and utilized a separate dataset acquired on a QSTAR Pulsar i mass spectrometer by the MPIS method. Intensity threshold was set to 0.2%; all lipid species reported as 'confirmed results' in at least four independent acquisitions.
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Publication 2011
Carbon-22 Escherichia coli Fatty Acids Immune Tolerance Lipid A Lipids Pulsar SLPI protein, human Tandem Mass Spectrometry

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Publication 2017
A-130A Alcoholic Beverages Diet Fatty Acids Feeds, Animal Food Margarine Nutrients Plants Plants, Edible Trans Fatty Acids

Most recents protocols related to «Fatty Acids»

Example 5

The content of free fatty acids in the oils and products was determined by neutralization titrimetry. The free fatty acids, about 0.2 g of the sample, were titrated with 0.04 mol·L−1 NaOH solution in a Mettler model DG20 automatic titrator up to a pH of 11.0 and the acidity of the sample was determined from Equation 3.

Alternatively, for samples with a larger volume, the free fatty acids, from about 0.5 to 1 g of the sample, were titrated with 0.25 mol·L−1 NaOH solution using phenolphthalein as indicator and the acidity of the sample was determined from Equation 3.

Acidity ( % w / w ) = V × M × AG 10 × m ( Equation 3 ) where:

    • V=volume of sodium hydroxide used in titration of the sample (mL);
    • M=molarity of the NaOH solution (mol·L−1);
    • AG=molecular weight of the fatty acid present in highest concentration in the oil* (g);
    • m=sample weight (g).
    • *Soya oil=linoleic acid (280 g); castor oil=ricinoleic acid (298 g).

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Patent 2024
Castor oil Fatty Acids Heartburn Linoleic Acid Nonesterified Fatty Acids Phenolphthalein ricinoleic acid Sodium Hydroxide Soybean oil Titrimetry
Not available on PMC !

Example 8

65% coconut oil, 20% rice bran oil, 10% palm oil, 5% castor oil.

100% KOH, 25% KCl, 25% NaCl (salts based on oils weight)

A hard bar 3.5 kg/cm2 a week after unmolding. 1.5:1 water to soap dilution easily dispersed to a very thick pearlescent liquid soap. Good lather and skin feel.

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Patent 2024
Castor oil Fatty Acids Feelings Oil, Coconut Oils Palm Oil potassium soap Rice Bran Oil Salts Skin Sodium Chloride Technique, Dilution
Not available on PMC !

Example 10

The linear peptide was prepared by solid phase method as per the analogous process given for Example 2, Part A starting with Fmoc protected Isoleucine was first coupled with Wang resin and then sequentially other amino acids were coupled. The grafting of activated fatty acid chain, Moiety C-OSu over the linear peptide by following analogous process of Example 2, Part B afforded the Compound 15.

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Patent 2024
Amino Acids Fatty Acids Isoleucine Peptides polypeptide C Wang resin
Not available on PMC !

Example 6

Strain 5 was subjected to another round of mutagenesis with increasing concentrations and exposure time to 4-NQO (37 μM for 30 minutes at 28° C.). This population of cells was subsequently subdivided and grown in standard lipid production medium supplemented with a range of cerulenin concentrations (7-50 μM). Cells from all concentrations were pooled and fractionated over a 60% Percoll/0.15 M NaCl density gradient. Oil laden cells recovered from a density zone of 1.02 g/mL were plated and assessed for glucose consumption and fatty acid profile. One of these clones was subsequently stabilized and given the strain designation “Strain 6”.

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Patent 2024
Cells Cerulenin Clone Cells Fatty Acids Glucose Lipids Microalgae Mutagenesis Oleic Acid Percoll Sodium Chloride Strains Triglycerides

Example 10

The linear peptide was prepared by solid phase method as per the analogous process given for Example 2, Part A starting with Fmoc protected Isoleucine was first coupled with Wang resin and then sequentially other amino acids were coupled. The grafting of activated fatty acid chain, Moiety C-OSu over the linear peptide by following analogous process of Example 2, Part B afforded the Compound 15.

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Patent 2024
Amino Acids Fatty Acids Isoleucine Peptides polypeptide C Wang resin

Top products related to «Fatty Acids»

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Bovine serum albumin (BSA) is a common laboratory reagent derived from bovine blood plasma. It is a protein that serves as a stabilizer and blocking agent in various biochemical and immunological applications. BSA is widely used to maintain the activity and solubility of enzymes, proteins, and other biomolecules in experimental settings.
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Fatty acid-free bovine serum albumin (BSA) is a purified, sterile-filtered protein preparation derived from bovine serum. It is commonly used as a stabilizing agent and carrier protein in various biochemical and cell culture applications.
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The Supelco 37 Component FAME Mix is a laboratory standard containing a mixture of 37 fatty acid methyl esters (FAMEs) in known proportions. It is designed for the identification and quantification of fatty acids in various sample types through gas chromatographic analysis.
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Palmitic acid is a saturated fatty acid with the chemical formula CH3(CH2)14COOH. It is a colorless, odorless solid at room temperature. Palmitic acid is a common constituent of animal and vegetable fats and oils.
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Oleic acid is a long-chain monounsaturated fatty acid commonly used in various laboratory applications. It is a colorless to light-yellow liquid with a characteristic odor. Oleic acid is widely utilized as a component in various laboratory reagents and formulations, often serving as a surfactant or emulsifier.
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The GC-2010 is a gas chromatograph manufactured by Shimadzu. It is a analytical instrument used for the separation, identification, and quantification of chemical compounds in a complex mixture. The GC-2010 utilizes a heated column filled with a stationary phase to separate the components of a sample based on their boiling points and interactions with the stationary phase.
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Fatty acid-free bovine serum albumin is a purified protein derived from bovine blood. It is commonly used as a component in cell culture media and other laboratory applications that require a protein source free of fatty acids.
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Methanol is a clear, colorless, and flammable liquid that is widely used in various industrial and laboratory applications. It serves as a solvent, fuel, and chemical intermediate. Methanol has a simple chemical formula of CH3OH and a boiling point of 64.7°C. It is a versatile compound that is widely used in the production of other chemicals, as well as in the fuel industry.
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
Sourced in Japan, Germany, United States, United Kingdom, Poland, Italy
The GC-2010 Plus is a gas chromatograph manufactured by Shimadzu. It is designed to analyze and separate complex mixtures of volatile and semi-volatile organic compounds. The GC-2010 Plus utilizes a capillary column and a thermal conductivity detector to provide accurate and reliable results for a wide range of applications.

More about "Fatty Acids"

Fatty acids are a crucial class of carboxylic acids that serve as the fundamental building blocks of lipids, playing pivotal roles in various biological processes.
These versatile molecules can be classified as saturated or unsaturated, and exhibit a wide range of chain lengths.
Fatty acids are essential nutrients, functioning as energy sources and structural components of cell membranes.
Imbalances in fatty acid profiles have been linked to numerous health conditions, including cardiovascular disease, diabetes, and inflammation.
Optimization of fatty acid research is key to advancing our understanding and therapeutic applications in this dynamic field of study.
Bovine serum albumin (BSA) and fatty acid-free BSA are commonly used in fatty acid research to provide a carrier for these hydrophobic molecules.
The Supelco 37 Component FAME Mix is a reference standard that contains a variety of fatty acid methyl esters, allowing for the identification and quantification of fatty acids in samples.
Palmitic acid and oleic acid are two of the most abundant and well-studied fatty acids, playing crucial roles in energy metabolism and cell signaling.
The GC-2010 and GC-2010 Plus gas chromatography systems are powerful analytical tools used to separate, identify, and quantify fatty acids in complex samples.
Methanol and fetal bovine serum (FBS) are also important components in fatty acid research, as they are used in the extraction and analysis of these lipid molecules.
By leveraging the insights gained from these related topics, researchers can optimize their fatty acid studies and uncover new discoveries that will drive progress in this dynamic field.