Gliadin proteins from wheat flour: the optimal determination conditions by ELISA

Introduction. The number of people with celiac disease is rapidly increasing. Gluten, is one of the most common food allergens, consists of two fractions: gliadins and glutenins. The research objective was to determine the optimal conditions for estimating gliadins by using enzyme-linked immunosorbent assay (ELISA). Study objects and methods. The experiment involved wheat flour samples (0.10; 0.20, 0.25, 0.50, and 1.0 g) suspended in different solvents (ethanol, methanol, 1-propanol, and isopropanol) of different concentrations (40, 50, 60, 70, 80, and 90% v/v). The samples were diluted with Tris buffer in ratios of 1:50, 1:100, 1:150, and 1:200. The gliadin test was performed using a Gliadin/Gluten Biotech commercial ELISA kit (Immunolab). Results and discussion. The optimal conditions for determining gliadin proteins that provided the highest gliadin concentration were: solvent – 70% v/v ethanol, extract:Tris buffer ratio – 1:50, and sample weight – 1.0 g. Conclusion. The obtained results can be of great importance to determine gliadin/gluten concentrations in food products by rapid analysis methods.

Optimization of DNA extraction and amplification of Kikuyu (Pennisetum clandestinum Hochst. ex Chiov) for molecular identification

Kikuyu (Pennisetum clandestinum Hochst. ex Chiov) is an important forage containing high crude protein for livestock. Molecular analysis of kikuyu relies on high yields of pure DNA and suitable PCR conditions. This research aimed to extract DNA from kikuyu based on weight of the sample and amplify the DNA of Burangrang accession using specific primers. 100 grams and 200 grams leaves of 3 accessions of kikuyu from Burangrang, Bukit Tunggul, and Tangkuban Perahu were extracted by Qiagen Mini Kit Plant. Concentration and purity of DNA were analyzed by NanoDrop Spectrophotometer 2000. DNA from Burangrang accession was amplified using six specific primers at different annealing temperatures. The result showed that the yield of DNA ranged 2.2 µg/µl to 21.4 µg/µl and the purity (ratio) were 1.08 to 2.01. Bukit Tunggul and Burangrang accession showed the same interaction pattern on the sample weight for concentration and purity. One hundred grams of leaves from Burangrang accession produce the highest concentration and the best purity of DNA, but no difference between other weight and accession. Reproducible amplifiable products were observed in all PCR reactions except primer K2. These results indicated that optimized protocol is suitable for further work on molecular identification of kikuyu.

Influence of jeringau (Acorus calamus Linn.) rhizome extract against dry-wood termites (Cryptotermes cynocephalus Light.)

Rubberwood (Hevea brasiliensis Muell Arg.) is classified as a hardwood, yet it is vulnerable to dry-wood termites attack, namely Cryptotermes cynocephalus Light. Hence, a preservative is necessary for prevention. The purpose of this research was to examine the effect of jeringau rhizome extract on dry-wood termites C. cynocephalus attack. The experimental design was a completely randomized factorial design with two factors include 2 levels of solvent (water and ethanol) and 4 levels of extract ratio (1:4, 1:6, 1:8, and 1:10). Parameters observed were actual retention, termites mortality, sample weight loss, and attack degree. Rubberwood was sized in 5 cm x 3 cm x 3 cm. The method used was immersing the samples in a container that contains jeringau rhizome extract in various treatments for 72 hours. The immersed samples were then fed to healthy and active C. cynocephalus for 12 weeks. The results showed that the type of solvents and extract ratio had a significant effect on termites mortality and samples weight loss, while actual retention was influenced by the extract ratio. In conclusion, the most effective formula to prevent dry-wood termites attack was jeringau rhizome extract with a weight ratio of jeringau powder and ethanol 1:6.

Anti-termite activities of Indonesia’s essential oils against invasive drywood termite for wood product protection

The Indo-Malayan drywood termite, Cryptotermes cynocephalus (Light) (Kalotermitidae), is considered one of the most invasive drywood termites in the Southeast Asian region. Once infesting a timber, the colony of a drywood termite is very difficult to be controlled. Thus, the best way to mitigate a new infestation of a drywood termite is by applying chemical protection on wood. In recent years, particular attention has been given by researchers to develop and use organic termiticides, such as essential oils extracted from plants as active ingredients. The objective of the present study is to evaluate the repellency performance of several economically important essential oils from Indonesia, such as Clove (Eugenia caryophyllata), Cubeb Pepper (Piper cubeba L), and Lemon Grass (Cymbopogon winterianus Jowitt) against a drywood termite, C. cynocephalus. The test was performed by subjecting various concentrations of essential oil toward C. cynocephalus in the force-feeding test method. Sample weight-loss was evaluated after two weeks test. The results suggested that Clove oil has the highest repellence performance against C. cynocephalus, followed by Lemon Grass and Cubeb Pepper oils. The Termite mortality rate was also recorded to understand the toxicity performance of those essential oils.

Research on Cross-Company Defect Prediction Method to Improve Software Security

As the scale and complexity of software increase, software security issues have become the focus of society. Software defect prediction (SDP) is an important means to assist developers in discovering and repairing potential defects that may endanger software security in advance and improving software security and reliability. Currently, cross-project defect prediction (CPDP) and cross-company defect prediction (CCDP) are widely studied to improve the defect prediction performance, but there are still problems such as inconsistent metrics and large differences in data distribution between source and target projects. Therefore, a new CCDP method based on metric matching and sample weight setting is proposed in this study. First, a clustering-based metric matching method is proposed. The multigranularity metric feature vector is extracted to unify the metric dimension while maximally retaining the information contained in the metrics. Then use metric clustering to eliminate metric redundancy and extract representative metrics through principal component analysis (PCA) to support one-to-one metric matching. This strategy not only solves the metric inconsistent and redundancy problem but also transforms the cross-company heterogeneous defect prediction problem into a homogeneous problem. Second, a sample weight setting method is proposed to transform the source data distribution. Wherein the statistical source sample frequency information is set as an impact factor to increase the weight of source samples that are more similar to the target samples, which improves the data distribution similarity between the source and target projects, thereby building a more accurate prediction model. Finally, after the above two-step processing, some classical machine learning methods are applied to build the prediction model, and 12 project datasets in NASA and PROMISE are used for performance comparison. Experimental results prove that the proposed method has superior prediction performance over other mainstream CCDP methods.

Alkaline pre-treatment of rice hull and coconut hull using Response Surface Methodology

In this research, the rice hull and coconut hull from agriculture waste were investigated. The lignin content within the rice and coconut hull were determined before and after pre-treatment. Response Surface Methodology (RSM) used to predict the optimal condition for the treatments and Fourier Transform Infrared (FTIR) to identify the lignin content. The interaction of NaOH concentration, contact time (CT), and sample weight was investigated to optimize the lignin removal percentage (%). The correlation coefficient, R2 for a quadratic model of rice hull lignin removal was 0.8863 while for coconut hull lignin removal in the linear model was 0.7998, as well as the 2FI model was 0.8892. The optimum condition for rice hull lignin removal predicted by RSM were10 M NaOH concentration, 1-hour CT and 0.5 g sample produced 32.45% lignin removal. While for coconut hull lignin removal were 10 M NaOH concentration, 12 hours CT, 0.5 g sample produced 59.47% removal of lignin. Results show that alkaline pre-treated rice hull and coconut hull able to be used to remove higher percentage of lignin.

Optymalizacja warunków oznaczania wody metodą miareczkowania kulometrycznego z odparowaniem dla olejów smarowych

The knowledge of the water content of various petroleum products, including lubricating oils, additives and various innovative products, is important from the point of view of manufacturing, purchasing or selling them, due to the impact on their quality and performance characteristics. In the case of lubricating oils, the presence of water can lead to premature corrosion and wear, the formation of deposits, which leads to reduced lubrication and premature clogging of filters, reduced action of additives or undesirable bacterial growth. The article presents the study on the selection of optimal conditions for the determination of water content by coulometric Karl-Fischer titration with evaporation in lubricating oils. The tests were carried out using a coulometer with a titration cell without a diaphragm by Metrohm, 917 Coulometer model with an automatic sample feeder equipped with a heating chamber 885 Compact Oven Sample Changer. Various types of lubricating oils were selected for testing, namely engine oils of different viscosity classes (5W/40, 10W/40, 15W/40, 5W/30), gear oil, hydraulic oil, turbine oil, base oil and hydraulic fluid. All selected samples of lubricating oils were tested in four different measuring conditions: 110°C and 20 ml/min; 150°C and 50 ml/min, 180°C and 50 ml/min and 150°C and 70 ml/min. It was found that for all the lubricating oils, the best results were obtained with a furnace temperature setting of 150°C and a carrier gas flow of 50 ml/min or 70 ml/min. The influence of various factors, such as the sample weight, the furnace temperature, the carrier gas flow velocity on the test course and the analysis speed, was determined. Increased carrier gas flow of up to 70 ml/min does not shorten the analysis time. In some cases, an increase in the oven temperature may speed up the analysis, but this is quite risky for some samples that decompose at given temperature. It is therefore safer to conduct the test at an oven temperature of 150°C. The speed of analysis is most influenced by an appropriate selection of the sample quantity under analysis. Depending on the water content in the tested sample, the appropriate sample weight should be selected. It should be small enough not to excessively extend the analysis, but also large enough that the amount of titrated water is at least twice as large as in the blank.

Microplastic in Several Fishes at Banyusangka Waters

The purpose of this study was to determine the shape, amount, and weight of microplastics in each sampel of Tuna fish (Euthynnus sp.), Bloated fish (Rastrelliger sp.), And Layur fish (Trichiurus sp.) which have obtained, and to know the comparison of microplastics between fish. The analysis method is random sampling with a 2x sampling period, and continued with laboratory analysis. The fish organs which analyzed were focused on the digestive system by the addition of 10% KOH by 1: 3 sample weight. The filtering results are then observed in a stereo microscope to determine the shape and amount of microplastics and weighing in an analytical balance. The results of the analysis found microplastics in the form of fiber, fragments, and films, with the dominance of the total number of microplastic findings in a row is in tuna, mackerel, and layur fish. Anova analysis was conducted which found that there was no difference of microplastic between fish.

Speciation analysis of organoarsenic species in marine samples: method optimization using fractional factorial design and method validation

Organoarsenic species in marine matrices have been studied for many years but knowledge gaps still exist. Most literature focuses on monitoring of arsenic (As) species using previously published methods based on anion- and cation-exchange high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS). These studies are often limited to few As species and/or only specific method performance characteristics are described. Most marine certified reference materials (CRMs) are only certified for arsenobetaine (AB) and dimethylarsinate (DMA), making it difficult to evaluate the accuracy of analytical methods for other organoarsenic species. To address these gaps, the main objective of this work was to develop and validate a method for speciation analysis of a broad range of organoarsenic species in marine matrices. Optimum extraction conditions were identified through a 27–3 fractional factorial design using blue mussel as test sample. The effects of sample weight, type and volume of extraction solution, addition of H2O2 to the extraction solution, extraction time and temperature, and use of ultrasonication were investigated. The highest As recoveries were obtained by using 0.2 g as sample weight, 5 mL of aqueous methanol (MeOH:H2O, 50% v/v) as extractant, extraction carried out at 90 °C for 30 min, and without ultrasonication. Anion- and cation-exchange HPLC-ICP-MS settings were subsequently optimized. The method detected a total of 33 known and unknown As species within a run time of 23 and 20 min for cation-exchange and anion-exchange, respectively. A single-laboratory validation was conducted using several marine CRMs: BCR 627 (tuna fish tissue), ERM-CE278k (mussel tissue), DORM-4 (fish protein), DOLT-5 (dogfish liver), SQID-1 (cuttlefish), TORT-3 (lobster hepatopancreas), and CRM 7405-b (hijiki seaweed). Method performance characteristics were evaluated based on selectivity, limits of detection and quantification, linearity, trueness, precision, and measurement uncertainty. This work proposes an extraction procedure which allowed satisfactory quantification of As species with low solvent and energy consumption, supporting “Green Chemistry” principles. The study also presents a new set of As speciation data, including methylated arsenic species and arsenosugars, in recently issued marine CRMs, which will be valuable for future speciation studies on As. This work is the first to report a total of 33 different As species in marine CRMs. Graphical abstract