Coconut oil as a rehydrant in air dried oral buccal smears: An alternative to routine wet fixation

The routine procedure to prepare a Pap smear is done by fixing the slides with 95% ethanol immediately after the sample is taken. This study was performed to determine the alternative method of air-drying and rehydration prior to alcohol fixation instead of conventional method. Paired buccal smears were collected from 50 patients who participated in the study. One set was labeled as (Wet fixed in 95% ethanol) WF and the other one Air-dried fixed (ARF) rehydrated and fixed with coconut oil. The staining quality of the slides was assessed with respect to nuclear details and cytoplasmic details, cytoplasmic staining and background staining. Single blinded study was done. The results were analyzed by Chi square test to compare the defined parameters between the two groups. Air-dried fixed (ARF) slides with coconut oil was significantly better with regard to clearance of background. There was statistically significant difference between the air dried smear rehydrated with coconut oil and normal wet fixed smear. So air dried smear rehydrated with coconut oil can be used as an alternative to wet fixed smear.

Effects of thermal treatment on the characteristics quality of some Ghanaian vegetable oils (palm, coconut and groundnut)

Introduction: Vegetable oils contain natural antioxidants and other properties reported to impart anti-diabetic properties when consumed, in animal study. In humans however, these oils are subjected to high temperatures during cooking before consumption. High temperature tends to affect the characteristic quality and potential to impart on health benefits such as antidiabetic properties. The objective of this work was to determine the characteristics quality of vegetable oils after thermal treatment that equates to temperatures oils are subjected to during food processing/cooking.Methodology: Three portions of 200g of each fresh unrefined red palm oil, coconut oil and groundnut oils in three conical flasks T1, T2 and T3 were heated to room temperature 28oC (T1) to 100o C in boiling water (T2) and to 200o C in electric cooker oven (T3) for 10 minutes. Acid, iodine, peroxide, saponification, unsaponification values of the oils, Phytoconstituents (Flavanoids, polyphenols saponins etc) and antioxidant (Vitamin A&C) and DPPH (1,1-Diphenyl-2-Picrylhydrazyl) Radical Scavenging Activity were then determined after cooling to room temperature. Results: Coconut oil heated to 200˚C had the least Acid value of 2.89±0.135 whiles Palm oil heated to 100 ˚C had the highest value of 19.57±0.165. There were no peroxides formed in Coconut and Palm oils at 28 ˚C as well as Palm oil at 100 ˚C. However, peroxides were highest in Coconut oil at 200˚C with value of 15.28±2.315. Saponification value of groundnut oil at 28 ˚C was the least at 89.52 ± 2.18 and 296.57±1.045 the highest in coconut oil at 200 ˚C. Heating however increased the unsaponifiable matter in all the vegetable oils used. Total antioxidant capacity was not significantly changed across the temperature treatment. Total phenolic content was not significantly changed for palm oil but was significantly increased at 100C for coconut and groundnut oilsConclusion: The quality of the oils in terms of acid value, iodine vale, peroxide value and saponification value, total antioxidant and phenolic content were retained after one heat treatment. This implies the quality of the oils are maintained after a single heating. The oils may still retain antidiabetic property when consumed after processing.

Preparation, Properties and Application of Gel Materials for Coal Gangue Control

In order to solve the problem of the spontaneous combustion of coal gangue, a coal gangue fire-extinguishing material of gel–foam was developed. The foaming agent was screened by the Waring blender method with varying foam amounts, and the superabsorbent foam stabilizer was synthesized by free radical polymerization. Moreover, the gel–foam was used in a spontaneous combustion of coal gangue mountain field practice. The results showed that when the mass fraction of sodium dodecyl sulfonate and coconut oil amide propyl betaine was 0.6% and 4:6, the foaming amount was as high as 1500 mL. When the mass ratio of chitosan to acrylic acid was 1:6, the neutralization degree was 80%, the cross-linking agent was 0.8%, and the initiator was 0.01%, the water absorption of the synthesized superabsorbent foam stabilizer reached 476 mL/g. The synthesized gel–foam was tested in a spontaneous combustion coal gangue hill in a certain area, and no reburning sign was found within one month.

A Decision Support System for Sustainable Agriculture: The Case Study of Coconut Oil Extraction Process

The high demand of information and communication technology (ICT) in agriculture applications has led to the introduction of the concept of smart farming. In this respect, moving from the main features of the Fourth Industrial Revolution (Industry 4.0) promoted by the European Community, new approaches have been suggested and adopted in agriculture, giving rise to the so-called Agriculture 4.0. Improvements in automation, advanced information systems and Internet technologies allow for farmers to increase the productivity and to allocate the resources reasonably. For these reasons, agricultural decision support systems (DSS) for Agriculture 4.0 have become a very interesting research topic. DSS are interactive tools that enable users to make informed decisions about unstructured problems, and can be either fully computerized, human or a combination of both. In general, a DSS analyzes and synthesizes large amounts of data to assist in decision making. This paper presents an innovative decision support system solution to address the issues faced by coconut oil producers in making strategic decisions, particularly in the comparison of different methods of oil extraction. In more detail, the adopted methodology describes how to address the problems of coconut oil extraction in order to minimize the processing time and processing cost and to obtain energy savings. To this end, the coconut oil extraction process of the Leão São Tomé and Principe Company is presented as a case study: a DSS instance that analyzes the problem of the optimal selection between two different oil coconut extraction methods (fermentation-based and standard extraction processes) is developed as a meta-heuristics with a mixed integer linear programming problem. The obtained results show that there is clearly a trade-off between the increase in cost and reliability that the decision-maker may be willing to evaluate. In this respect, the proposed model provides a tool to support the decision-maker in choosing the best combination between the two different coconut oil extraction methods. The proposed DSS has been tested in a real application context through an experimental campaign.

UJI STANDAR MUTU SIFAT FISIK SABUN PADAT TRANSPARAN MINYAK SEREH WANGI (Cymbopogon nardus L.) DARI VCO (Virgin Coconut Oil)

Sabun merupakan sediaan yang paling banyak digunakan yang bersifat sebagai pembersih dan anti bakteri bagi tubuh. Penggunaan VCO sebagai basis sabun padat transparan karena VCO karena kandungan asam lemak yang menguntungkan kulit Proses pembuatan sabun dengan metode panas, dengan basis VCO yang dibuat metode penggaraman. Evalusi standar mutu meliputi uji organoleptis, uji tinggi busa dan stabilitas busa Hasil uji standar mutu sifat fisik yaitu uji organoleptik, uji tinggi busa dan stabilitas busa memenuhi standar mutu sediaan sabun yang beredar dipasaran, tidak terjadi perbedaan mutu fisik yang bermakna antara sabun padat transparan minyak sereh wangi yang diformulasi dengan sabun padat transparan yang beredar.

Partial Replacement of Dietary Fat with Krill Oil or Coconut Oil Alleviates Dyslipidemia by Partly Modulating Lipid Metabolism in Lipopolysaccharide-Injected Rats on a High-Fat Diet

This study investigated the effects of partial replacement of dietary fat with krill oil (KO) or coconut oil (CO) on dyslipidemia and lipid metabolism in rats fed with a high-fat diet (HFD). Sprague Dawley rats were divided into three groups as follows: HFD, HFD + KO, and HFD + CO. The rats were fed each diet for 10 weeks and then intraperitoneally injected with phosphate-buffered saline (PBS) or lipopolysaccharide (LPS) (1 mg/kg). The KO- and CO-fed rats exhibited lower levels of serum lipids and aspartate aminotransferases than those of the HFD-fed rats. Rats fed with HFD + KO displayed significantly lower hepatic histological scores and hepatic triglyceride (TG) content than rats fed with HFD. The KO supplementation also downregulated the adipogenic gene expression in the liver. When treated with LPS, the HFD + KO and HFD + CO groups reduced the adipocyte size in the epididymal white adipose tissues (EAT) relative to the HFD group. These results suggest that KO and CO could improve lipid metabolism dysfunction.

Classification of Adulterated Particle Images in Coconut Oil Using Deep Learning Approaches

In the production of coconut oil for consumption, cleanliness and safety are the first priorities for meeting the standard in Thailand. The presence of color, sediment, or impurities is an important element that affects consumers’ or buyers’ decision to buy coconut oil. Coconut oil contains impurities that are revealed during the process of compressing the coconut pulp to extract the oil. Therefore, the oil must be filtered by centrifugation and passed through a fine filter. When the oil filtration process is finished, staff inspect the turbidity of coconut oil by examining the color with the naked eye and should detect only the color of the coconut oil. However, this method cannot detect small impurities, suspended particles that take time to settle and become sediment. Studies have shown that the turbidity of coconut oil can be measured by passing light through the oil and applying image processing techniques. This method makes it possible to detect impurities using a microscopic camera that photographs the coconut oil. This study proposes a method for detecting impurities that cause the turbidity in coconut oil using a deep learning approach called a convolutional neural network (CNN) to solve the problem of impurity identification and image analysis. In the experiments, this paper used two coconut oil impurity datasets, PiCO_V1 and PiCO_V2, containing 1000 and 6861 images, respectively. A total of 10 CNN architectures were tested on these two datasets to determine the accuracy of the best architecture. The experimental results indicated that the MobileNetV2 architecture had the best performance, with the highest training accuracy rate, 94.05%, and testing accuracy rate, 80.20%.

Changes in Metabolic Regulation and the Microbiota Composition after Supplementation with Different Fatty Acids in db/db Mice

Introduction. The effects of fatty acids on health vary and depend on the type, amount, and route of consumption. EPA and DHA have a defined role in health, unlike coconut oil. Objective. The aim was to investigate the changes in metabolic regulation and the composition of the culture-dependent microbiota after supplementation with different fatty acids in db/db mice. Material and Methods. We were using 32 8-week-old db/db mice, supplemented for eight weeks with EPA/DHA derived from microalgae as well as coconut oil. The lipid, hormonal profiles, and composition of the culture-dependent microbiota and the phylogenetic analysis based on the 16S rRNA gene sequencing were determined for identification of the intestinal microbiota. Results. Enriched diet with EPA/DHA reduced TNF-α, C-peptide, insulin resistance, resistin, and the plasma atherogenic index, but increased TC, LDL-c, VLDL-c, and TG without changes in HDL-c. Coconut oil raised the HDL-c, GIP, and TNF-α, with TG, insulin resistance, adiponectin, and C-peptide reduced. Conclusion. The most abundant microbial populations were Firmicutes and the least Proteobacteria. EPA/DHA derived from microalgae contributes to improving the systemic inflammatory status, but depressed the diversity of the small intestine microbiota. Coconut oil only decreased the C-peptide, raising TNF-α, with an unfavorable hormonal and lipid profile.