Gender specific differences of the ethanol and nicotine toxicity verified by the use of mathematical models

Beside the pandemic of obesity, the binge drinking becomes a huge problem. The toxicity of consuming alcohol and smoking in the late adolescent population was examined using mathematical models. The body was divided into compartments for two different models; (i) the ethanol model (4 compartments: central compartment, muscle and fat compartment, liver compartment and gastrointestinal compartment) and (ii) the nicotine model (2 compartments: liver compartment and central compartment). Different alcohol contents simulated consumptions of 90 mL of spirits; 900 mL of beer or 600 mL of wine. Nicotine metabolism simulation was performed for three different initial doses of nicotine (light, medium and strong cigarettes). Significant differences are observed regarding the gender; where the maximum ethanol concentration is reached at 0.5 h (males: 27 mmol/dm3 and females: 33 mmol/dm3) in the gastrointestinal compartment while complete nicotine degradation in the liver takes approximately 10 h and in the central compartment 15 h, respectively. The skewness and kurtosis of the toxin concentrations showed their relation with the symmetry of the toxin retention in the body. Results show preferable positively skewed distribution which implies a shorter retention time in the organism while higher kurtosis implies higher toxin concentration

Analysis of diffusivity of the oscillating reaction components in a microreactor system

When performing oscillating reactions, periodical changes in the concentrations of reactants, intermediaries, and products take place. Due to the mentioned periodical changes of the concentrations, the information about the diffusivity of the components included into oscillating reactions is very important for the control of the oscillating reactions. Non-linear dynamics makes oscillating reactions very interesting for analysis in different reactor systems. In this paper, the analysis of diffusivity of the oscillating reaction components was performed in a microreactor, with the aim of identifying the limiting component. The geometry of the microreactor microchannel and a well defined flow profile ensure optimal conditions for the diffusion phenomena analysis, because diffusion profiles in a microreactor depend only on the residence time. In this paper, the analysis of diffusivity of the oscillating reaction components was performed in a microreactor equipped with 2 Y-shape inlets and 2 Y-shape outlets, with active volume of V = 4 μL at different residence times

Mathematical models for description of hydrodynamics, mass and heat transfer in microreactor systems

Over the last decades the increased use of microreactors in all types of industries is observed. This phenomenon is based on the advantages that the microreactor systems can achieve in term of better process control, more efficient heat transfer and handling of hazardous chemicals. During this time mathematical models that describe flow inside microchannels have emerged ranging from Navier-Stokes equations to simplified mathematical models for laminar and segmented flows. The aim of this review is to present current studies in term of mathematical models that are nowadays commonly used for the description of hydrodynamics, mass and heat transfer in microreactor systems

The Smaller, The Better - Microtechnology for a Macroresults

There is a well-known expression The Bigger, The Better, on which many would agree but when it comes to microreac- tors it is necessary to make the slight modification and say The Smaller, The Better. Reduction in reactor size emerged in many positive effects on many chemical and biochemical reactions. Faster reactions, smaller usage of reaction com- ponents, smaller amount of waste streams, safer reaction conditions, easier process manipulation etc. are just some of the advantages of microreactors. The aim of this review is to present microreactor technology in a simple way and to show its basic characteristics such as structure, advantages and disadvantages, types and general application

NEAR INFRARED SPECTROSCOPY (NIRS) AS FOOD QUALITY AND FOOD FRAUD DETECTOR – APPLIED ON FISH STICKS

The aim of this study was to present the professional application of near infrared spectroscopy (NIRs) in the detection of food quality on purchased fish sticks. The measured NIR spectra of samples prepared from fish or squid were related to nutritional labels such as the amount of certain macronutrient and the proportion of the starting material (fish/squid). In the standard procedure, NIRs coupled with chemometric tools such as principal component analysis (PCA) and partial least square regression (PLSR) was used to investigate the qualitative and/or quantitative capabilities in determining food quality. Excellent qualitative differentiation was achieved with PCA, with biplots showing how the explanation of variation increased from 80.12 % when only nutritional information was used in the observation to 96.89% when nutritional information was coupled with the corresponding NIR spectrum. Since higher levels of animal protein in food are associated with an increase in price, the detection probabilities of different protein sources (fish/meat) were tested using PLSR, with 100% of the samples successfully detected. PLSR was also used to detect the correlation of the NIR spectra to the macronutrient contents and the strongest correlation was determined for proteins (R2 = 0.99). The results confirmed the feasibility of using NIRs in the qualitative evaluation of samples where it is possible to determine the predominance of fish or squid, and also to estimate the expected protein content. The protein content is related to the price of the product, since all products containing animal proteins have higher prices that grow proportionally to their share. NIRs is not a qualitative method, but it can help in the selection of products, whose exact composition and possible adulteration can be confirmed by additional laboratory analysis

Application of NIR spectroscopy in gluten detection as a cross-contaminant in food

The determination of gluten is of critical importance when food screening is intended for special groups such as food ingredient intolerant and allergic persons. Cross-contamination of food that does not contain gluten is also possible in the sales chain. The aim of this study was to determine the applicability of Near-Infrared Spectroscopy (NIRs) for the detection of gluten traces in rice, rice flour, corn flour and corn grits. In the cross-contamination simulation, two types of wheat flour were used. They were added to rice, rice flour, corn flour and corn grits in a range from 5 % to 30 %. Apart from the spectra of pure and contaminated samples, conductivity and total dissolved solids were monitored to determine changes in the samples. NIR spectroscopy was combined with chemometric techniques to determine at which wavelengths a glutenfree fingerprint can be detected. Although experiments were carried out with a NIR instrument that monitors molecular vibrations in the range of λ= 904-1699 nm, the gluten fingerprint was successfully determined, regardless of the type of flour that was added to the rice, rice flour, corn flour and corn grits. All concentrations of the added flours were successfully determined and models were developed to detect the concentrations of the added flours. Even the conductivity showed good prediction potential in gluten determination. Regardless if the investigated samples were contaminated or not, the determination coefficient R2 was over 0.9. Developed models could be used to predict possible wheat flour contamination of any rice or corn product samples or samples prepared for cooking in water

NEAR INFRARED SPECTROSCOPY (NIRS) AS FOOD QUALITY AND FOOD FRAUD DETECTOR – APPLIED ON FISH STICKS

The aim of this study was to present the professional application of near infrared spectroscopy (NIRs) in the detection of food quality on purchased fish sticks. The measured NIR spectra of samples prepared from fish or squid were related to nutritional labels such as the amount of certain macronutrient and the proportion of the starting material (fish/squid). In the standard procedure, NIRs coupled with chemometric tools such as principal component analysis (PCA) and partial least square regression (PLSR) was used to investigate the qualitative and/or quantitative capabilities in determining food quality. Excellent qualitative differentiation was achieved with PCA, with biplots showing how the explanation of variation increased from 80.12 % when only nutritional information was used in the observation to 96.89% when nutritional information was coupled with the corresponding NIR spectrum. Since higher levels of animal protein in food are associated with an increase in price, the detection probabilities of different protein sources (fish/meat) were tested using PLSR, with 100% of the samples successfully detected. PLSR was also used to detect the correlation of the NIR spectra to the macronutrient contents and the strongest correlation was determined for proteins (R2 = 0.99). The results confirmed the feasibility of using NIRs in the qualitative evaluation of samples where it is possible to determine the predominance of fish or squid, and also to estimate the expected protein content. The protein content is related to the price of the product, since all products containing animal proteins have higher prices that grow proportionally to their share. NIRs is not a qualitative method, but it can help in the selection of products, whose exact composition and possible adulteration can be confirmed by additional laboratory analysis

NEAR INFRARED SPECTROSCOPY (NIRS) COUPLED WITH CHEMOMETRIC TOOLS USED FOR FOOD PRODUCTS ADULTERATION DETECTION

The growing problem of food products adulteration requires a rapid and simple method for adulteration detection. Adulterants, which can range from plant material to natural and synthetic colours and compounds have a severe influence on customer trust as well as public health risks. Food safety regulations are being tightened and expanded, requiring a more thorough examination of hazards and risk management solutions. Due to its advantages, near infrared spectroscopy has been recognised as an effective method for food adulteration detection. In this work, an overview of the basics of NIR spectroscopy, NIR data analysis and the use of NIR for food adulteration detection are discussed

OPTIMIZATION OF ETHANOL/WATER SOLVENT EXTRACTION OF BIOACTIVE COMPONENTS ORIGINATING FROM INDUSTRIAL HEMP (Cannabis sativa L.)

Hemp (Cannabis sativa L.) contains a wide range of biocompounds with different beneficial properties such as anti-inflammatory, antithrombotic, antiarrhythmic, hypolipidemic and antioxidative. Response Surface Methodology (RSM) coupled with Box-Behnken design (BBD) was applied to determine the influence of extraction temperature, liquid to solid ratio, extraction time, rotational speed and ethanol/water solvent ratios at three levels on the solid-liquid extraction of the bioactives from the hemp (flowers, leaves, seeds, stems). Based on the obtained results, liquid to solid ratio, temperature and ethanol/water solvent ratio had statistically significant effects on the total polyphenolic content (TPC), while extraction time and rotational speed had no influence on the TPC extraction. Regarding antioxidant activity (AOX) determined by the DPPH method, only liquid to solid ratio had a statistically significant effect. Liquid to solid ratio, ethanol/water solvent ratio, temperature and rotational speed significantly influenced AOX determined by the FRAP method. According to BBD, the optimum extraction conditions were as follows: extraction temperature 45 °C, liquid to solid ratio 30 mL/g, extraction time 25 min, rotational speed 500 rpm, ethanol/water solvent ratio 25%. RSM coupled with a BBD model was shown to be effective for optimization the solid-liquid extraction of hemp

NEAR INFRARED SPECTROSCOPY (NIRS) COUPLED WITH CHEMOMETRIC TOOLS USED FOR FOOD PRODUCTS ADULTERATION DETECTION

The growing problem of food products adulteration requires a rapid and simple method for adulteration detection. Adulterants, which can range from plant material to natural and synthetic colours and compounds have a severe influence on customer trust as well as public health risks. Food safety regulations are being tightened and expanded, requiring a more thorough examination of hazards and risk management solutions. Due to its advantages, near infrared spectroscopy has been recognised as an effective method for food adulteration detection. In this work, an overview of the basics of NIR spectroscopy, NIR data analysis and the use of NIR for food adulteration detection are discussed