scholarly journals Silver Nanomaterials as Electron Mediators in a Bio-Electronic Tongue Dedicated to the Analysis of Milks. The Role of the Aspect Ratio of Nanoparticles vs. Nanowires

2021 ◽  
Vol 5 (1) ◽  
pp. 30
Author(s):  
Coral Salvo-Comino ◽  
Clara Perez-Gonzalez ◽  
Fernando Martin-Pedrosa ◽  
Cristina Garcia-Cabezon ◽  
Maria Luz Rodriguez-Mendez
Keyword(s):  
Principal Component Analysis ◽  
Silver Nanowires ◽  
Electronic Tongue ◽  
Principal Component ◽  
Galactose Oxidase ◽  
Electrochemical Biosensors ◽  
Milk Samples ◽  
Silver Nanomaterials ◽  
Electron Mediators

The integration of silver nanomaterials as electron mediators in electrochemical biosensors can be crucial to improve the affinity with biomolecules and the electrochemical response. In this work, two voltammetric bioelectronics tongues (bioET) formed by biosensors based on the combination of enzymes with silver nanoparticles (AgNPs) (bioET-1) or silver nanowires (AgNWs) (bioET-2) have been developed and used to analyze milks. Each array was formed by four biosensors formed by enzymes (glucose oxidase, galactose oxidase, β-galactosidase and a blank), capable to detect compounds usually found in milks. Principal component analysis (PCA) has revealed the ability of both biosensor systems to discriminate between milk samples with different fat contents, but with some differences, attributed to the structure employed in the detection.

scholarly journals Discrimination of Milks with a Multisensor System Based on Layer-by-Layer Films

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2716 ◽  
Author(s):  
Coral Salvo-Comino ◽  
Celia García-Hernández ◽  
Cristina García-Cabezón ◽  
Maria Rodríguez-Méndez
Keyword(s):  
Copper Phthalocyanine ◽  
Electronic Tongue ◽  
Principal Component ◽  
Sensor System ◽  
Galactose Oxidase ◽  
Milk Analysis ◽  
Layer By Layer ◽  
Additional Information ◽  
Milk Samples ◽  
Calibration Models

A nanostructured electrochemical bi-sensor system for the analysis of milks has been developed using the layer-by-layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity, and chitosan (CHI), that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV–vis, and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal component analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using a PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components, such as fats, proteins, and acidity, can also be obtained. The method developed is simple, and the short response time permits its use in assaying milk samples online.

Electronic tongue formed by sensors and biosensors containing phthalocyanines as electron mediators: Application to the analysis of red grapes

2014 ◽  
Vol 18 (01n02) ◽  
pp. 76-86 ◽  
Author(s):  
Cristina Medina-Plaza ◽  
Gema Revilla ◽  
Raquel Muñoz ◽  
José Antonio Fernández-Escudero ◽  
Enrique Barajas ◽  
...  
Keyword(s):  
Glucose Oxidase ◽  
Electronic Tongue ◽  
Principal Component ◽  
Carbon Paste ◽  
Electron Mediator ◽  
Enzyme Substrate ◽  
Voltammetric Sensors ◽  
The Individual ◽  
Electron Mediators

An electronic tongue formed by voltammetric sensors and biosensors containing phthalocyanines has been developed and used to analyze grapes of different varieties. The sensors are prepared using the carbon paste technique and have been chemically modified with different metallophthalocyanines. In turn, biosensors consist of carbon paste electrodes modified with phthalocyanines combined with tyrosinase or glucose oxidase. The response of the individual sensors towards model solutions of glucose and catechol have demonstrated that the voltammetric responses depend on the nature of the phthalocyanine, evidencing the important role of the electron mediator in the performance of the sensors. The capability of the system to discriminate grapes according to their sugar and their polyphenolic content has been evidenced using Principal Component Analysis. It has been demonstrated that the proposed array of sensors combines the advantages of classical phthalocyanine based sensors — that provide global information about the sample —, with the specificity of the enzyme substrate reaction typical of biosensors. For this reason, the selectivity of the multisensor system and its capability of discrimination is clearly improved when biosensors containing glucose oxidase or tyrosinase are included in the array.

scholarly journals Multisensor System Based on Layer by Layer Films. Discrimination of Milks

2018 ◽  
Author(s):  
Coral Salvo-Comino ◽  
Celia Garcia-Hernandez ◽  
Cristina Garcia-Cabezon ◽  
Maria Luz Rodriguez-Mendez
Keyword(s):  
Copper Phthalocyanine ◽  
Electronic Tongue ◽  
Principal Component ◽  
Sensor System ◽  
Galactose Oxidase ◽  
Milk Analysis ◽  
Layer By Layer ◽  
Additional Information ◽  
Milk Samples ◽  
On Line

A nanostructured electrochemical bi-sensor system for analysis of milks has been developed using the Layer by Layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity and chitosan (CHI) that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV-vis and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal Component Analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components such as fats, proteins and acidity can also be obtained. The method developed is simple and the short response time permits its use in assaying milk samples on-line.

scholarly journals The lung microbiota in Korean patients with non-tuberculous mycobacterial pulmonary disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sung-Yoon Kang ◽  
Hyojung Kim ◽  
Sungwon Jung ◽  
Sang Min Lee ◽  
Sang Pyo Lee
Keyword(s):  
Principal Component Analysis ◽  
Respiratory Tract ◽  
Pulmonary Disease ◽  
Beta Diversity ◽  
Lower Respiratory Tract ◽  
Principal Component ◽  
Control Group ◽  
Flexible Bronchoscope ◽  
Bronchial Washing

Abstract Background The microbiota of the lower respiratory tract in patients with non-tuberculous mycobacterial pulmonary disease (NTM-PD) has not been fully evaluated. We explored the role of the lung microbiota in NTM-PD by analyzing protected specimen brushing (PSB) and bronchial washing samples from patients with NTM-PD obtained using a flexible bronchoscope. Results Bronchial washing and PSB samples from the NTM-PD group tended to have fewer OTUs and lower Chao1 richness values compared with those from the control group. In both bronchial washing and PSB samples, beta diversity was significantly lower in the NTM-PD group than in the control group (P = 2.25E-6 and P = 4.13E-4, respectively). Principal component analysis showed that the PSBs and bronchial washings exhibited similar patterns within each group but differed between the two groups. The volcano plots indicated differences in several phyla and genera between the two groups. Conclusions The lower respiratory tract of patients with NTM-PD has a unique microbiota distribution that is low in richness/diversity.

Application of visible and near-infrared spectroscopy for evaluation of ewes milk with different feeds

2019 ◽  
Vol 59 (6) ◽  
pp. 1190 ◽  
Author(s):  
A. Bahri ◽  
S. Nawar ◽  
H. Selmi ◽  
M. Amraoui ◽  
H. Rouissi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Random Forest ◽  
Near Infrared Spectroscopy ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Principal Component ◽  
Least Squares Regression ◽  
Random Forest Regression ◽  
Milk Samples

Rapid measurement optical techniques have the advantage over traditional methods of being faster and non-destructive. In this work visible and near-infrared spectroscopy (vis-NIRS) was used to investigate differences between measured values of key milk properties (e.g. fat, protein and lactose) in 30 samples of ewes milk according to three feed systems; faba beans, field peas and control diet. A mobile fibre-optic vis-NIR spectrophotometer (350–2500 nm) was used to collect reflectance spectra from milk samples. Principal component analysis was used to explore differences between milk samples according to the feed supplied, and a partial least-squares regression and random forest regression were adopted to develop calibration models for the prediction of milk properties. Results of the principal component analysis showed clear separation between the three groups of milk samples according to the diet of the ewes throughout the lactation period. Milk fat, protein and lactose were predicted with good accuracy by means of partial least-squares regression (R2 = 0.70–0.83 and ratio of prediction deviation, which is the ratio of standard deviation to root mean square error of prediction = 1.85–2.44). However, the best prediction results were obtained with random forest regression models (R2 = 0.86–0.90; ratio of prediction deviation = 2.73–3.26). The adoption of the vis-NIRS coupled with multivariate modelling tools can be recommended for exploring to differences between milk samples according to different feed systems, and to predict key milk properties, based particularly on the random forest regression modelling technique.

scholarly journals Identification of Umami Taste in Sous-Vide Beef by Chemical Analyses, Equivalent Umami Concentration, and Electronic Tongue System

Foods ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 251 ◽  
Author(s):  
Young-Hwa Hwang ◽  
Ishamri Ismail ◽  
Seon-Tea Joo
Keyword(s):  
Amino Acids ◽  
Principal Component Analysis ◽  
Food Processing ◽  
Free Amino Acids ◽  
Free Amino ◽  
Electronic Tongue ◽  
Principal Component ◽  
Chemical Analyses ◽  
Umami Taste ◽  
Sous Vide

Behaviour of umami compounds that are associated with non-volatile compounds on slow cooking regimes remains less explored. This study aims to assess the ability of the electronic tongue system on the umami taste from sous-vide beef semitendinosus. The identification was based on the taste-enhancing synergism between umami compounds 5’-nucleotides (IMP, GMP, AMP, inosine, and hypoxanthine) and free amino acids (glutamic and aspartic acid) using the estimation of equivalent umami concentration (EUC) and electronic tongue system. Sous-vide cooked at 60 and 70 °C for 6 and 12 h and cooked using the conventional method at 70 °C for 30 min (as control) were compared. The temperature had a significant effect on 5’-nucleotides, but aspartic and glutamic acid were not influenced by any treatments applied. Sous-vide cooked at 60 °C tended to have higher inosine and hypoxanthine. Meanwhile, desirable 5’-nucleotides IMP, AMP, and GMP were more intensified at the temperature of 70 °C. The principal component analysis predicted a good correlation between EUC and the electronic tongue, with sous-vide at 70 °C for 12 h presenting the most umami. Therefore, the electronic tongue system is a useful tool in food processing, particularly in determining complex sensory properties such as umami, which cannot be evaluated objectively.

scholarly journals A-49 Visual Memory Errors and Intelligence: The Role of Verbal Mediation

2019 ◽  
Vol 34 (6) ◽  
pp. 908-909
Author(s):  
K Hakinson ◽  
J Moses ◽  
J RIvera ◽  
A Guerra ◽  
M Davis ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Perceptual Organization ◽  
Visual Memory ◽  
Principal Component ◽  
Component Analysis ◽  
Spoken Language ◽  
Verbal Mediation ◽  
Memory Errors ◽  
Shared Variance

Abstract Objective Examine the relationship of verbal mediation with visual memory errors and intelligence to understand the role of spoken language on other assessment measures. Method Assessment records were obtained from a Veteran Affairs clinic for veterans (n=100) with diverse neuropsychiatric conditions who completed the Wechsler Adult Intelligence Scale, third edition (WAIS-III), Multilingual Aphasia Examination (MAE), and Benton Visual Retention Test (BVRT). A Principal Component Analysis (PCA) was used to examine the interrelationship among these assessments. The components of spoken language, types of errors on the BVRT, and the four factors of the WAIS-III were factored using the PCA to identify common sources of variance. Results A principal component analysis revealed a six-factor model explaining 68.16% of the shared variance among the WAIS-III factors, MAE components, and BVRT Errors. Omission errors loaded with Processing Speed and Controlled Word Association. Distortions and size errors loaded with Perceptual Organization. Size errors also loaded with Verbal Comprehension and Visual Naming. Misplacements loaded with Working Memory and Sentence Repetition. Misplacements, perseverations, and omissions loaded with the Token Test (a measure associated with auditory comprehension). Rotation errors loaded with Perceptual Organization. Conclusions Results indicated significant shared variance between visual memory errors, spoken language, and intelligence factors. This suggests that spoken language is involved in the process of visual memory, and deficits in spoken language may result in increased errors on visual memory tasks. Therefore, treatment recommendations for visual memory difficulties should take into consideration verbal capabilities and intelligence factors to better individualize treatment.

Evaluation of Sweet Sauce Characteristic Taste Based on Electronic Tongue Technology

2012 ◽  
Vol 554-556 ◽  
pp. 1593-1601
Author(s):  
Ming Quan Huang ◽  
Lu Wang ◽  
Bao Guo Sun ◽  
Hong Yu Tian
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Reducing Sugars ◽  
Electronic Tongue ◽  
Amino Nitrogen ◽  
Physicochemical Characterization ◽  
Principal Component ◽  
On Line

A commercial electronic tongue (ET) with specific sensors was applied on taste distinction and physicochemical characterization of seven kinds of sweet sauces. The response signals of ET sensors were analyzed by Principal Component Analysis (PCA) and Discriminant Factor Analysis (DFA). Meanwhile, these signals were transformed into the four relative taste scores (sourness, saltiness, umami and sweetness) by macro operation, followed by comparing with the corresponding four physiochemical indexes (total acids, sodium chloride, amino nitrogen and reducing sugars) which were determined by the methods in GB/T. The results show that ET can be used to distinguish different kinds of sweet sauces according to overall taste. Moreover, the intensity order of taste scores that obtained from ET is basically matched with the sequence of the corresponding physicochemical indexes, which proves that ET technique can be an effective approach to monitor and guarantee the quality of sweet sauce on line.

scholarly journals The Milk Metabolome of Non-secretor and Lewis Negative Mothers

2021 ◽  
Vol 7 ◽  
Author(s):  
Aidong Wang ◽  
Petya Koleva ◽  
Elloise du Toit ◽  
Donna T. Geddes ◽  
Daniel Munblit ◽  
...  
Keyword(s):  
Human Milk ◽  
Free Amino ◽  
Principal Component ◽  
Blood Type ◽  
Research Report ◽  
Change Analysis ◽  
Milk Samples ◽  
Lactating Mothers ◽  
Fold Change Analysis

Introduction: The functional role of milk for the developing neonate is an area of great interest, and a significant amount of research has been done. However, a lot of work remains to fully understand the complexities of milk, and the variations imposed through genetics. It has previously been shown that both secretor (Se) and Lewis blood type (Le) status impacts the human milk oligosaccharide (HMO) content of human milk. While some studies have compared the non-HMO milk metabolome of Se+ and Se− women, none have reported on the non-HMO milk metabolome of Se− and Le– mothers.Method and Results: To determine the differences in the non-HMO milk metabolome between Se–Le– mothers and other HMO phenotypes (Se+Le+, Se+Le–, and Se–Le+), 10 milk samples from 10 lactating mothers were analyzed using nuclear magnetic resonance (NMR) spectroscopy. Se or Le HMO phenotypes were assigned based on the presence and absence of 6 HMOs generated by the Se and Le genes. After classification, 58 milk metabolites were compared among the HMO phenotypes. Principal component analysis (PCA) identified clear separation between Se–Le– milk and the other milks. Fold change analysis demonstrated that the Se–Le– milk had major differences in free fatty acids, free amino acids, and metabolites related to energy metabolism.Conclusion: The results of this brief research report suggest that the milk metabolome of mothers with the Se–Le– phenotype differs in its non-HMO metabolite composition from mothers with other HMO phenotypes.

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