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Oils

Oils are a diverse class of lipid compounds that play vital roles in biological systems.
They can be derived from plants, animals, or minerals, and are characterized by their hydrophobic nature and ability to dissolve other lipophilic substances.
Oils serve numerous functions, including energy storage, insulation, and signaling.
They can be found in a variety of natural and synthetic forms, each with unique chemical properties and applications.
Researchers studying the effects and uses of oils can utilize AI-driven platforms like PubCompare.ai to streamline their literature searches, optimize experimental protocols, and uncover the most effective oil-based products.
This tool enhances reproducibility and accuracy by facilitating comparisons across published studies, preprints, and patents.
Exploring the diverse world of oils can lead to advancements in fields like nutrition, medicine, and industrial chemistry.

Most cited protocols related to «Oils»

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Publication 2010
Child Childbirth Diet Dietary Modification Food Head Households Index, Body Mass Mental Recall Obesity Oils Staple, Surgical Woman
The three methods that we compare are:
The names given to methods (b) and (c) follow those of Krebs-Smith et al [5 (link)].
It is not immediately clear which method would be least biased, and one can construct different numerical examples where each one of the three is the superior method. The methods must therefore be tested with data that (a) are realistic and conform to typically reported values, and (b) come from a population with known population mean usual HEI-2005 component scores. Unfortunately, available real datasets do not satisfy condition (b), so we employ instead computer simulations of data generated from a statistical model that is based on real data.
The dataset we used as a basis for our statistical model is drawn from the Eating at America’s Table Study (EATS) [6 (link)]. The study was approved by the National Cancer Institute Special Studies Institutional Review Board. The 738 women we studied were part of a nationally representative sample. Participants were asked to complete four 24HRs via telephone over a period of one year (1997–98), with one recall per season. Six hundred and fifty (88%) of these women completed all four recalls. Foods reported on the 24-hour recalls were coded using the Food Intake Analysis System, version 2., which calculated total daily intakes for energy, saturated fat and sodium. The food codes, in turn, were linked to the MyPyramid Equivalents Database, version 1.0, in order to calculate total daily intakes of the food groups of interest.
Summary statistics on the first day’s reported intake of the 12 HEI-2005 components (and energy) were computed (Table 1). Note that the mean ratio is different from the population ratio (final two columns of Table 1). In most cases, the mean ratio has the larger value; but for Oils, Saturated Fat, and Solid Fats, Alcoholic beverages, and Added Sugars (SoFAAS), it has the smaller value.
The statistical model forming the basis of our computer simulations was constructed under a set of assumptions and calculations. All of the model parameters were estimated from the data on the women participating in EATS. The details of the estimation procedures are contained in on-line Appendix A. A brief description of how the model was formed is given below.
Some food groups are not consumed every day by all individuals. We refer to days on which a given food group is consumed by a given individual as that individual’s “consumption days,” the remaining days being the individual’s “non-consumption days.”
First we made an assumption about the intake distributions. Distributions of intake on consumption days, both between individuals and within individuals, were assumed to be normal after a suitable power transformation. The power transformation for each food/nutrient was individually chosen after inspection of the deciles of the distribution (see second column of on-line Supplemental Table 1).
For food groups (but not for nutrients), there is a probability of non-consumption on a single day. We examined three assumptions regarding this probability, each of increasing complexity.
Publication 2008
Alcoholic Beverages Ethics Committees, Research Fats Food Interest Groups LINE-1 Elements Mental Recall Nutrients Oils Saturated Fatty Acid Sodium Sugars Woman

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Publication 2010
Antibodies, Anti-Idiotypic Biological Assay Buffers derivatives Enzyme-Linked Immunosorbent Assay Fats Food Healthy Volunteers Hypersensitivity Oils Phosphates Saline Solution Urban Population
We used three measures including dietary diversity [20] –[21] (link), food variety [23] (link)–[24] (link) and consumption of animal source foods [25] –[27] (link) to gauge their dietary practices. Dietary diversity [DD] was assessed using a food frequency questionnaire containing 30 food items that are commonly consumed in the study area. The list of food items was developed based on an extensive interview of the data collectors who are from the study area and who knew the culture and language and key informants in the study area on the types of foods commonly consumed. The food frequency questionnaire was pre-tested on 200 adolescents and the food items commonly consumed in the area and the patterns over the week days observed during the pretest were used to refine the food frequency questionnaire. Participants were asked to report the frequency of consumption of each food per day, per week or per month using the past 3 months as a reference [33] (link). Given the large variation of dietary habits in the local community over the days of the week, the consumption of each food item per day [34] (link) was not taken as a cut-off point to define consumers. Rather, adolescents were coded as a “consumer” of a food item if they had consumed the food item at least once per week [35] . As there is no Ethiopian classification of food groups, the 30 food items [Table 1] of the food frequency questionnaire were grouped into seven groups [gains/vegetables/fruits/dairy/protein foods/oils/Discretionary calories] [Table 2] according to the MyPyramid classification for healthy eating [36] . A Dietary Diversity Score (DDS) was constructed by counting the intake of the food groups over a period of one week [37] (link) based on the definition that it is the sum of food groups consumed over the reference period. For example, an adolescent who consumed one item from each of the food groups at least once during the week would have the maximum DDS of 7. The DDS was converted into tertiles and the highest tertile was used to define “high” dietary diversity score, while the two lower tertiles combined were labeled as “low” dietary diversity score. Food Variety Score [FVS] is the frequency of individual food items consumed in the reference period. It was calculated by counting the consumption of each of the 30 individual food items over the reference period of one week [28] (link), [37] (link) with the maximum FVS to be thirty. The mean FVS were compared by background characteristics and food security status.
Animal Source Food [ASF] intake was assessed by summing the number of times each animal source food was consumed over the days of the week. Frequency of ASF consumption was divided into tertiles and the highest tertile was used to define “high” frequency of consumption of ASF, while the two lower tertiles were labeled as “low” frequency of ASF consumption.
We adjusted our analysis for household dependency ratio calculated as the ratio of people who are not expected to be productive [age groups greater than 64 and less than 15 years] to the number of people who are expected to be potentially productive [age 15–64 years]. The dependency ratio was divided in to tertiles. We also adjusted for adolescent educational status categorized based on the current classification the Ministry of Education as “primary” [grade 8 and below] and secondary and above [Grade 9 and above].
Adolescent food insecurity was measured using items adapted from household food insecurity scales that were previously validated for use in developing countries [38] (link)–[40] (link), the details of the methods are described elsewhere[41] (link). Four items that amply to individual experiences adolescents were used to assess food insecurity. Briefly, adolescents were asked whether in the last three months they (1) had ever worried about having enough food; (2) had to reduce food intake because of shortages of food or money to buy food; (3) had to go without having eaten because of shortage of food or money to buy food and (4) had to ask outside the home for food because of shortage of food or money to buy food. All “Yes” responses were coded “1” and “No” responses were coded “0” and the scores were summed. Adolescents who had food insecurity score of 1 and above were labeled as food insecure. The index has high internal consistency (Cronbach’s Alpha = 0.81).
The study was approved by the Ethical Review Boards of both Brown University (USA) and Jimma University (Ethiopia). Informed verbal consent was obtained both from the parents and each respondent before the interview or measurement as approved by the ethical review committees which followed and documented the study process through supervisory visits.
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Publication 2013
Adolescent Age Groups Animals Diet Eating Ethical Review Feeds, Animal Food Fruit Fruit Proteins Households Oils Parent Plant Proteins, Dietary Supervision Vegetables
The following bacterial species were used: Bacillus subtilis (ATCC 10707), Enterobacter cloacae (human isolate), Escherichia coli (ATCC 0157:H7), Micrococcus flavus (ATCC 9341),Proteus mirabilis (human isolate), Pseudomonas aeruginosa (ATCC 27853), Salmonella enteritidis (ATCC 13076), S. epidermidis (ATCC 12228) S. typhimurium (ATCC 13311) Staphylococcus aureus (ATCC 25923). The antibacterial assays were carried out by the disc-diffusion [25 (link)] and microdilution method [26 ,27 (link),28 (link)] in order to determine the antibacterial activity of oils and their components against the human pathogenic bacteria. The bacterial suspensions were adjusted with sterile saline to a concentration of 1.0 × 105 CFU/mL. The inocula were prepared daily and stored at +4 °C until use. Dilutions of the inocula were cultured on solid medium to verify the absence of contamination and to check the validity of the inoculum.
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Publication 2010
Anti-Bacterial Agents Bacillus subtilis Bacteria Biological Assay Culture Media Diffusion Enterobacter cloacae Escherichia coli Homo sapiens Micrococcus flavus Oils Pathogenicity Proteus mirabilis Pseudomonas aeruginosa Saline Solution Salmonella enteritidis Staphylococcus aureus Staphylococcus epidermidis Sterility, Reproductive Technique, Dilution

Most recents protocols related to «Oils»

Example 1

10 g (33.09 mmol) of 1-(2-fluoro-6-trifluoromethyl-benzyl)-6-methyl-1H-pyrimidine-2,4-dione (III), 6.8 g (49.62 mmol) of K2CO3 and 2.4 g (6.6 mmol) of tetrabutylammonium iodide were mixed with 50 mL of acetone at the temperature of about 20° C. Subsequently, 13.6 g (43.12 mmol) of (R)-2-((tert-butoxycarbonyl)amino)-2-phenylethyl methanesulfonate (IVa) were added and the obtained mixture was heated at the temperature of about 55° C. and maintained under stirring for about 16 hours at said temperature.

Once this maintenance was finished, the solvent was vacuum distilled and 50 mL of ethyl acetate and 50 mL of water were added to the residue thus obtained. A 1 M aqueous solution of HCl was slowly added, maintaining the temperature between 20 and 25° C. until achieving a pH of between 7 and 8. The aqueous phase was separated and treated with 3 fractions of 30 mL each of ethyl acetate. All the organic extracts were pooled and the solvent was removed by means of vacuum to obtain a slightly yellowish oily residue to which 45 mL of methanol were added, obtaining complete dissolution of the residue.

Example 2

16.1 g (99.24 mmol) of iodine monochloride (ICI) were dissolved in 40 mL of methanol at the temperature of about 10° C. The methanol solution previously obtained according to the methodology described in Example 1 comprising 3-((R)-2-(tert-butoxycarbonyl)amino-2-phenylethyl)-1-(2-fluoro-6-trifluoromethylbenzyl)-6-methyl-1H-pyrimidine-2,4-dione (II) was added to the iodine monochloride solution, maintaining the temperature between 20 and 25° C. Once the addition was finished, the obtained solution was heated to about 50° C. and was maintained under stirring for 2 hours at the mentioned temperature.

Once the maintenance was finished, the solvent was vacuum distilled and 50 mL of acetone were slowly added to the obtained oily residue at the temperature of between and 25° C. The addition of acetone caused a solid precipitate to appear almost immediately. The obtained mixture was maintained for 1 hour under stirring at the mentioned temperature. The resulting solid was isolated by filtration, washed with two fractions of 25 mL of acetone, and finally dried at the temperature of 50° C. to obtain 15.6 g (80.8% yield) of a white solid corresponding to the 3-((R)-2-(amino-2-phenylethyl)-1-(2-fluoro-6-trifluoromethylbenzyl)-5-iodo-6-methyl-1H-pyrimidine-2,4-dione hydrochloride salt (Ia) (UHPLC purity: 98.9%).

1H-NMR (d6-DMSO, 400 MHz) δ (ppm): 8.70 (2H, s broad), 7.65-7.48 (3H, m), 7.40-7.32 (5H, m), 5.40-5.29 (2H, dd), 4.47 (1H, t), 4.25 (2H, dd), 2.65 (3H, s).

13C-NMR (d6-DMSO, 100 MHz) δ (ppm): 161.87, 159.47, 159.41, 154.19, 150.98, 134.70, 129.93, 129.84, 129.01, 128.58, 127.38, 122.61, 122.34, 122.22, 121.34, 121.10, 74.80, 52.26, 45.45, 44.60, 25.66.

The DSC of this compound is shown in FIG. 1 and the XRPD is shown in FIG. 2.

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Patent 2024
1H NMR Acetone Anabolism Carbon-13 Magnetic Resonance Spectroscopy elagolix ethyl acetate Filtration Iodine iodine monochloride methanesulfonate Methanol Oils potassium carbonate Pyrimidines Sodium Chloride Solvents Sulfoxide, Dimethyl TERT protein, human tetrabutylammonium iodide Vacuum

Example 11

0.18 of 1-benzoyl-3-(5′-azido-1′-pentyl)pyrrolidine (14) was dissolved in 5 ml of tetrahydrofuran, and then 0.15 g of triphenylphosphine and 2 drops of water were added and refluxed overnight. After concentration under reduced pressure, 10 ml of dichloromethane was added, and washed sequentially with water and a saturated sodium chloride solution. The reaction solution was concentrated under reduced pressure, and separated by column chromatography (dichloromethane/methanol/aqueous ammonia=10:1:0.1 vol/vol/vol), to obtain 0.16 g of an oily product 1-benzoyl-3-(5′-amino-1′-pentyl)pyrrolidine (15). LCMS: 261[M+H].

The following compounds can be prepared according to the above method of preparing the compound 15 starting from the compound 12:

PreparationMS
numberName of CompoundStructure(m/z)
161-(2,6-dimethoxybenzoyl)- 3-(5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
321 (M + 1)
171-(2,6-dimethoxybenzoyl)- 3-(6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
335 (M + 1)
181-benzoyl-3-(6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
275 (M + 1)
191-furoyl-3-(5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
251 (M + 1)
19-11-furoyl-3-(6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
265 (M + 1)
201-(2-thienylformyl)-3-(5′- amino-1′-pentyl)pyrrolidine[Figure (not displayed)]
267 (M + 1)
20-11-(2-thienylformyl)-3-(6′- amino-1′-hexyl)pyrrolidine[Figure (not displayed)]
281 (M + 1)
211-(2-pyrrolylformyl)-3-(5′- amino-1′-pentyl)pyrrolidine[Figure (not displayed)]
250 (M + 1)
221-(2-pyrrolylformyl)-3-(6′- amino-1′-hexyl)pyrrolidine[Figure (not displayed)]
264 (M + 1)
231-(2-pyrrolidinylformyl)-3- (5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
254 (M + 1)
23-11-(2-pyrrolidinylformyl)-3- (6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
268 (M + 1)
241-(2-tetrahydrofurylfuryl)-3- (5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
255 (M + 1)
251-(2- tetrahydrothienylformyl)-3- (5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
271 (M + 1)
25-11-(2- tetrahydrothienylformyl)-3- (6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
285 (M + 1)
25-21-(3-fluoro-2-thienylformyl)- 3-(5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
285 (M + 1)
25-31-(3-fluoro-2- pyrrolylformyl)-3-(5′-amino- 1′-pentyl)pyrrolidine[Figure (not displayed)]
268 (M + 1)
25-41-(3-fluoro-2-furylformyl)-3- (5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
269 (M + 1)
261-(2-indolylformyl)-3-(5′- amino-1′-pentyl)pyrrolidine[Figure (not displayed)]
300 (M + 1)
26-11-(2-indolylformyl)-3-(6′- amino-1′-hexyl)pyrrolidine[Figure (not displayed)]
314 (M + 1)
271-(2-benzofurylformyl)-3- (5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
301 (M + 1)
27-11-(2-benzofurylformyl)-3- (6′-amino-1′- hexyl)pyrrolidine[Figure (not displayed)]
315 (M + 1)
27-21-(2- benzyltetrahydrofurylfuryl)- 3-(5′-amino-1′- pentyl)pyrrolidine[Figure (not displayed)]
303 (M + 1)

[Figure (not displayed)]

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Patent 2024
Ammonia Chromatography Lincomycin Methanol Methylene Chloride Oils Pressure pyrrolidine Saline Solution tetrahydrofuran triphenylphosphine
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

Example 20

[Figure (not displayed)]

Following step 1 in the preparation of I-49, tert-butyl 3-(7-bromo-4-chloro-8-methoxyquinolin-2-yl) benzoate was prepared from Intermediate 17.

Step 1: tert-Butyl 3-(7-bromo-4-(1H-imidazol-1-yl)-8-methoxyquinolin-2-yl)benzoate. To a mixture of tert-butyl 3-(7-bromo-4-chloro-8-methoxyquinolin-2-yl) benzoate (125 mg) and Cs2CO3 (136.8 mg) in DMF (2 mL) was added imidazole (96 mg). The suspended solution was stirred and heated at 130° C. over 2 h. Aqueous work-up with EtOAc and a column chromatography eluting with EtOAc/Hexane afforded the desired product tert-butyl 3-(7-bromo-4-(1H-imidazol-1-yl)-8-methoxyquinolin-2-yl) benzoate (120 mg) (MS: [M+1]+ 480).

Step 2: 3-(7-Bromo-4-(1H-imidazol-1-yl)-8-methoxyquinolin-2-yl)benzoic acid. To a solution of tert-butyl 3-(7-bromo-4-(1H-imidazol-1-yl)-8-methoxyquinolin-2-yl)benzoate (65 mg) in DCM (0.2 mL) and MeOH (0.2 mL) was added TFA (0.4 mL). The resultant solution was stirred over 5 h and concentrated to dryness. The resultant oily residue was suspended in water (0.5 mL) and lyophilized to afford the title compound 3-(7-bromo-4-(1H-imidazol-1-yl)-8-methoxyquinolin-2-yl) benzoic acid (60 mg) as light brown powder (MS: [M+1]+ 424).

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Patent 2024
Anabolism Benzoate Benzoic Acid Chromatography Hexanes imidazole Light Oils Powder TERT protein, human
Not available on PMC !

Example 4

A composition comprising Tretinoin as active ingredient:

IngredientConcentration (w/w %)
Oleic acid5.00
Isopropanol10.00
BHT (Butylated Hydroxytoluene)0.02
Sorbic acid0.10
Tretinoin0.10
Silica microspheres0.70
CMC Na (carboxymethyl cellulose sodium)2.40
Natrosol (HBC)0.50
Glycerin5.00
Benzyl alcohol0.80
Poloxamer 4070.20
P. Waterq.s. 100%

The process for the preparation of the composition was as follows:

    • 1. CMC Na (carboxymethyl cellulose sodium) and Natrosol (HEC) were dispersed in water until a clear gel was formed
    • 2. Glycerin and benzyl alcohol were added to stage 1 and mixed;
    • 3. Oleic acid, isopropanol, BHT, sorbic acid, Poloxamer 407 and tretinoin were heated to 50° C. while stirring until clear solution was obtained. Then the solution was cooled to the room temperature;
    • 4. Silica Microspheres were added to the cooled oily phase and resultant mixture was stirred for at least one hour;
    • 5. Stage 4 was added to the stage 2 and stirred for one hour under vacuum.

An opaque yellowish gel was obtained.

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Patent 2024
Benzyl Alcohol Ethanol Glycerin Isopropyl Alcohol Microspheres Oils Oleic Acid Pharmaceutical Preparations Poloxamer 407 Silicon Dioxide Sodium Carboxymethylcellulose Sorbic Acid Tretinoin Vacuum

Top products related to «Oils»

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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
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The DB-5 capillary column is a widely used gas chromatography (GC) column designed for the separation and analysis of a wide range of organic compounds. It features a nonpolar stationary phase, making it suitable for the separation of a variety of analytes. The column is constructed with a fused silica capillary and a bonded phenyl-methyl siloxane stationary phase. This combination provides efficient separation and reliable performance for a diverse range of applications.
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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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The UV-1800 is a UV-Visible spectrophotometer manufactured by Shimadzu. It is designed to measure the absorbance or transmittance of light in the ultraviolet and visible wavelength regions. The UV-1800 can be used to analyze the concentration and purity of various samples, such as organic compounds, proteins, and DNA.

More about "Oils"

Oils are a diverse class of lipid compounds that play vital roles in biological systems.
They can be derived from plant, animal, or mineral sources, and are characterized by their hydrophobic nature and ability to dissolve other lipophilic substances.
Lipids, fats, triglycerides, fatty acids, and hydrophobic compounds are all related terms.
Oils serve numerous functions, including energy storage, insulation, and signaling.
They can be found in a variety of natural and synthetic forms, each with unique chemical properties and applications.
Researchers studying the effects and uses of oils can utilize AI-driven platforms like PubCompare.ai to streamline their literature searches, optimize experimental protocols, and uncover the most effective oil-based products.
This tool enhances reproducibility and accuracy by facilitating comparisons across published studies, preprints, and patents.
Exploring the diverse world of oils can lead to advancements in fields like nutrition, medicine, and industrial chemistry.
Researchers can utilize solvents like DMSO, Tween 80, Methanol, and Toluene, as well as analytical techniques like GC-2010 and UV-1800 to study the chemical composition and properties of oils.
Optimizing oil-based research with PubCompare.ai can involve comparing protocols using Whatman No. 1 filter paper or DB-5 capillary columns, and identifying the most effective oil-based formulations through AI-driven comparisons.
By streamlining their research process and enhancing reproducibility, researchers can unlock the full potential of oils and drive breakthroughs in various industries.