Research Watch: Bioconcentration potential

Modeling.     

Physicochemical properties of sweeteners in artificial saliva and determination of a hydrophobicity scale for some sweeteners

Saliva, the first physiological secretion induced by ingestion of food or beverages, plays an extensive role in the oral cavity and in taste perception. The influence of salts and proteins (the major constituents of saliva) on physicochemical properties of sweeteners is studied. Previous findings on the effects of KCl, NaCl and MgCl₂ on sweetener properties are now completed with the study of CaCl₂. Ca²⁺ modifies the type of hydration of sugars and polyols and has a detergent effect on sweet solutions. As water structure is sensitive to the presence of salts, physico-chemical properties of sugars, polyols and intense sweeteners are determined in artificial saliva. Proteins also play a major part in hydration and surface properties of stimuli in saliva. All physicochemical properties determined in this work help in the mechanistic elucidation of sweet taste chemoreception. A scale of hydrophobicity is established for some sweeteners using partition coefficient and contact angle measurements.     

Hydrophobic properties of textile materials: robustness of hydrophobicity

Extremely hydrophobic surfaces have been receiving considerable interest, such as in the contexts of self-cleaning glass or clothes, antifouling paintings, and the reduction of friction drag. A large variety of treatments permits the obtainment of (super)hydrophobic textile surfaces. The point here is to investigate the role of different geometrical textile parameters on the hydrophobicity, and more particularly, on the robustness of this property. The influences of solid surface roughness on the wetting behavior are commonly studied for model solid textures while textile roughness is largely deformable. A laboratory test method is suggested to evaluate this robustness. Some hydrophobic fibrous structures were prepared (using classical woven fabrics and pile fabrics) to investigate the influence of textile structures on their static and forced wetting properties. Static contact angles, contact angle hysteresis, and the contact angle after compression were measured. The meso- and micro-structures appeared to influence either the static wetting or the robustness of the hydrophobicity after compression.     

Technical note: A simplified procedure for myofibril hydrophobicity determination

A simple and reliable method for the determination of surface hydrophobicity of nonsolubilized myofibrils (from pig M. longissimus dorsi) was developed and validated. This method is based on the interaction of the hydrophobic chromophore bromophenol blue (BPB) with myofibrillar proteins and the separation of free and bound BPB by centrifugation. The titration of bound BPB is performed by absorption spectroscopy, and the amount of bound BPB is considered as an index of protein hydrophobicity. Heating, which is known to increase protein hydrophobicity, was performed in order to validate this method. Fixation of BPB to myofibrils increased with heating time and temperature, strongly suggesting that it may be closely related to protein hydrophobicity.     

Technical note: A simplified procedure for myofibril hydrophobicity determination

A simple and reliable method for the determination of surface hydrophobicity of nonsolubilized myofibrils (from pig M. longissimus dorsi) was developed and validated. This method is based on the interaction of the hydrophobic chromophore bromophenol blue (BPB) with myofibrillar proteins and the separation of free and bound BPB by centrifugation. The titration of bound BPB is performed by absorption spectroscopy, and the amount of bound BPB is considered as an index of protein hydrophobicity. Heating, which is known to increase protein hydrophobicity, was performed in order to validate this method. Fixation of BPB to myofibrils increased with heating time and temperature, strongly suggesting that it may be closely related to protein hydrophobicity.     

Ultrasound and effect on the surface hydrophobicity of proteins: a meta-analysis

This review aims to investigate and evaluate the effect of ultrasound process parameters on the interfacial properties (surface hydrophobicity) of food proteins. The data obtained from English published papers accessed on Web of Science, PubMed and Wiley published from 2013 to 2021 allowed a table overview construction and a meta-analysis. Study selection was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. A total of 40 relevant reports and 185 data used for meta-analysis were considered. In general, the results revealed that the use of the ultrasound process increased the surface hydrophobicity of proteins. Processing time, power, amplitude and ultrasound frequency were significant in protein modification. The findings showed that the ultrasound process parameters should be considered to assess the effect on the modification and improvement of the interfacial properties of proteins.     

A computerized mastitis decision aid using farm-based records: an artificial neural network approach

A computer module was developed and tested that used field survey and Dairy Herd Improvement Association (DHIA) data to broadly classify bacterial causes of mastitis in dairy herds. Further development of the computer model could aid interpretation of DHIA data by dairy record processing centers and herd consultants. This diagnostic module was developed with an artificial neural network, a technology that processes complex data in a manner similar to human brain function. Information describing herd management practices, quarter milk samples, and monthly DHIA data was collected from Pennsylvania dairy herds with moderate to high somatic cell counts. This information was used to develop or train an artificial neural network model that discriminated among four categories of bacterial organisms (contagious, environmental, no significant growth, and other) associated with clinical and subclinical mastitis. After training the model, new DHIA and management data were presented to the model to assess its ability to classify bacteriological etiology. When the artificial neural network was used, the probabilities of diagnosing the bacteriologic status from three randomly selected cow groups and from new untested herds ranged from 57 to 71%. Performance of the artificial neural network model was best in herds with higher frequency of minor and contagious pathogens. Prediction results for the same test data with linear discriminant analysis were less successful, ranging from 42 to 57%.     

Use of an artificial mouth to study bread aroma

This work aimed to select artificial mouth extraction conditions to obtain an aroma extract of bread close to that perceived in the human mouth in terms of similarity and intensity. Once the representative extraction conditions were determined, they were used to show the influence of mastication and the effect of saliva on bread aroma release. The significance of mastication was shown by comparing headspace aromatic extracts with artificial mouth extracts. The results showed that headspace extraction, associated with a previous crushing of bread, did not provide an extract similar to that obtained after mastication. The determination of the influence of saliva on bread aroma was done respecting the ratio between saliva and bread in the human oral cavity. The results revealed that bread was crushed differently in the presence of saliva than in the presence of water. In addition, saliva had a significant influence on the volatile composition of bread extracts.     

Genetic analysis of an artificial insemination progeny test program

The success of the progeny test (PT) program from one Spanish artificial insemination (AI) organization was evaluated. The annual genetic trend for the organization was compared with PT programs from other countries. The relationships among parents' estimated breeding values (EBV) and PT results for sons were also studied. Estimated breeding values for type and production traits were obtained from international genetic evaluations from February 2004. The annual genetic gain of the Spanish PT program was similar to that of other international programs. The Spanish AI organization graduated 13% of its sampled bulls, and 52% of primiparous cows were daughters of Spanish bulls (32% from proven bulls and 20% from sampling bulls).Correlations between EBV for PT bulls and their pedigree indices (0.52 to 0.70) were slightly lower than correlations between EBV for PT bulls and their parent averages (0.63 to 0.73). Both young and mature cows contributed to genetic progress. Success of PT bulls (defined by number of second-crop daughters) depended mainly on their EBV for final score, protein yield, and the type-production index. Significant correlations of sire EBV were found for final score and type-production index with the number of second-crop daughters (0.22 and 0.17). Likewise, significant correlations of dam EBV for final score and type-production index with the number of second crop daughters were found (0.25 and 0.18). Final score and protein yield were the main factors in success of a PT bull. The type-production index for PT bulls was not important for success unless it was 2.5 standard deviations above average. The PT bulls with low EBV for type-production index were used as proven bulls when they had higher EBV either for protein or final score.     

基于因子分析及BP神经网络的鱼糜挤压膨化产品工艺

文中对11个鱼糜挤压膨化产品属性指标进行了因子分析。结果表明:前5个公共因子可以解释产品属性的89.732%,各因子贡献率分别为47.220%,16.823%,13.346%,6.775%,5.568%。在此基础上,采用BP人工神经网络模拟操作工艺参数对各因子值的影响,并进行了优化,经优化后的工艺参数为挤压机Ⅲ区加热温度172.0℃、螺杆转速219 r/min、喂料速率8.2 r/min。     

Superhydrophobic nanofibre membranes: effects of particulate coating on hydrophobicity and surface properties

Superhydrophobic electrospun polyacrylonitrile nanofibre membranes have been prepared by surface coating of silica nanoparticles and fluorinated alkyl silane. The coated membranes were characterised by scanning electron microscopy, water contact angle, thermogravimetry analysis, Brunauer–Emmett–Teller, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and atomic force microscopy. It was shown that the loading of nanoparticle on the nanofibre membrane was controlled by the particle concentration in the coating solution, which played a critical role in the formation of superhydrophobic surface. Increased particle loading led to higher surface roughness and WCA. The nanoparticle coating had little influence on the porosity of the nanofibre membranes. However, overloading of the particles would affect the specific surface area of the nanofibre membrane.     

Evaluation of an artificial olfactory system for grain quality discrimination

A commercially available Cyranose-320™ conducting polymer-based electronic nose system was used to analyze the headspace from stored barley samples. Three types of barley samples were analyzed, namely, clean barley, naturally Fusarium infected barley and Fusarium inoculated clean barley. The barley samples were stored at moisture contents of 13, 18, 20 and 25 g of water/100 g sample. The raw signals obtained from the electronic nose system were pre-processed by various signal-processing techniques to extract area-based features. Principal component analysis was subsequently performed on the processed signals to further reduce the dimensionalities. Classification models using linear (LDA) and quadratic discriminant analyses (QDA) were developed using the extracted features. The performance of the developed models was validated using leave-1-out cross validation and bootstrapping method. The models classified the barley samples stored into two groups based on the ergosterol content, i.e., “acceptable” (ergosterol content <3.0 μg/g) and “unacceptable” (ergosterol content ?3.0 μg/g). Overall, the total maximum classification accuracy obtained was 86.8% by both LDA and QDA when leave-1-out cross-validation was used. By bootstrapping validation the maximum total classification accuracy obtained was 86.4% and 86.1% respectively, by QDA and LDA. The study proves that there is potential in using an electronic nose system for indicating mold spoilage in stored grains, and necessitates future studies in this direction.     

The methodological problems of an experimental study of artificial feeding

General requirements have been presented for the organization and performing of experiments on artificial feeding in small laboratory animals. Some operation methods and devices applicable in the investigation of the body functions under conditions of parenteral and tube feeding have been described. The possibility of using this experimental biological model in the study of artificial feeding has been evidenced by the results of the test on 15-day tube feeding of rats.     

Characteristics of protein digestion in artificial feeding in an experiment

It has been established that during artificial feeding with milk substitute containing different protein components (casecite, bovine serum albumin, fibrinogen), the proximal-distal gradient of cavitary digestion of proteins is observed, with this gradient being more demonstrable as compared with natural feeding of postnatal animals. It has been shown that during experimental natural feeding, the proximal-distant gradient is observed in the distribution of acid proteinases in the small bowel, whereas during artificial feeding one can see a uniform distribution of acid proteinases in the proximal and distal parts of the small bowel. The activity of acid proteinases in the gastric mucosa of 18-day-old animals kept on natural feeding does not differ from the activity of these proteinases under artificial feeding with a substitute containing casecite as protein component. Artificial feeding with a substitute containing bovine serum albumin and fibrinogen as protein component entails a decrease in the activity of acid proteinases in the gastric mucosa.     

Monitoring the authenticity of low-fat yogurts by an artificial neural network

The growing consumption of low- and reduced-fat dairy products demands routine control of their authenticity by health agencies. The usual analyses of fat in dairy products are very simple laboratory methods; however, they require manipulation and use of reagents of a corrosive nature, such as sulfuric acid, to break the chemical bounds between fat and proteins. Additionally, they generate chemical residues that require an appropriate destination. In this work, the use of an artificial neural network based on simple instrumental analyses, such as pH, color, and hardness (inputs) is proposed for the classification of commercial yogurts in the low- and reduced-fat categories (outputs). A total of 108 strawberry-flavored yogurts (48 probiotic low-fat, 36 low-fat, and 24 full-fat yogurts) belonging to several commercial brands and from different batches were used in this research. The statistical analysis showed different features for each yogurt category; thus, a database was built and a neural model was trained with the Levenberg-Marquardt algorithm by using the neural network toolbox of the software MATLAB 7.0.1. Validation with unseen data pairs showed that the proposed model was 100% efficient. Because the instrumental analyses do not require any sample preparation and do not produce any chemical residues, the proposed procedure is a fast and interesting approach to monitoring the authenticity of these products.     

Electricity generation from artificial wastewater using an upflow microbial fuel cell

The upflow microbial fuel cell (UMFC) was developed to generate electricity while simultaneously treating wastewater. During a five-month period of feeding a sucrose solution as the electron donor, the UMFC continuously generated electricity with a maximum power density of 170 mW/m2. To achieve this power density, the artificial electron-mediator hexacyanoferrate was required in the cathode chamber. The power density increased with increasing chemical oxygen demand (COD) loading rates up to 2.0 g COD/ L/day after which no further increases in power density were observed, indicating the presence of limiting factors. The overarching limiting factor for the UMFC in this study was the internal resistance, which was estimated as 84 omega at the maximum power density, and restricted the power output by causing a significant decrease in operating potential. Low Coulombic efficiencies varying from 0.7 to 8.1% implied that the electron-transfer bacteria were incapable of converting all of the available organics into electricity, so the excessive substrate created niches for the growth of methanogens. We found that the soluble COD (SCOD) removal efficiencies remained over 90% throughout the operational period, mainly because of methanogenic activity, which accounted for 35 to 58% of the SCOD removed at a loading rate of 1.0 g COD/L/ day. Additionally, transport limitation due to insufficient substrate diffusion was shown by cyclic voltammetry (CV).     

Initial stages of protein assimilation in artificial feeding in an experiment

The content of pepsinogen in the gastric mucosa and acid phosphatase activity in the gastric chyme are adaptively altered in animals with change from natural to artificial feeding. This change is attended by redistribution of gly-gly-dipeptidase activity along the small intestine. It has been established that fibrinogen and casein are characterized by similar values of the compensation coefficient.