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Nanocarriers for Controlled Release and Target Delivery of Bioactive Compounds
| Nanocarriers for Controlled Release and Target Delivery of Bioactive Compounds |
| Autore | Noore Shaba |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (91 pages) |
| Altri autori (Persone) |
PathaniaShivani
FuciñosPablo O'DonnellColm P TiwariBrijesh K |
| Collana | SpringerBriefs in Food, Health, and Nutrition Series |
| ISBN | 3-031-57488-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Chapter 1: Introduction -- 1.1 Nanocarriers -- Chapter 2: Lipid-Based Nanocarriers -- 2.1 Nanoemulsions -- 2.2 Nanoliposomes -- 2.3 Cubosomes and Hexosomes -- 2.4 Tocosome -- 2.5 Solid Lipid Nanoparticles -- 2.6 Nanostructured Lipid Carriers -- 2.7 Smart Lipid Nanocarriers -- Chapter 3: Protein-Based Nanocarriers -- 3.1 Nanoparticles -- 3.2 Hollow Nanoparticles -- 3.3 Nanohydrogels -- 3.4 Nanofibrils -- 3.5 Electrospun Nanofibers -- 3.6 Nanotubes -- 3.7 Natural Nanocarriers -- 3.8 Cage-Like Proteins Nanoencapsulation -- 3.9 Ferritin Nanocages -- 3.10 Dps Nanocage -- 3.11 Heat Shock Protein -- 3.12 Encapsulation Protein -- 3.13 Pyruvate Dehydrogenase -- Chapter 4: Carbohydrate Based Nanocarriers -- 4.1 Polymeric Nanoparticles -- 4.2 Polymeric Micelles -- 4.3 Polymeric Nanogels -- 4.4 Dendrimers -- Chapter 5: Synthetic Polymeric Nanocarriers -- 5.1 Echogenic Immunoliposomes -- 5.2 Nanobots -- 5.3 Hybrid Nanocarriers -- 5.4 Decorating Nanocarriers -- 5.4.1 Quantum Dots -- 5.4.2 Silver Nanoparticles -- 5.4.3 Gold Nanoparticle -- 5.4.4 Graphene Oxide -- 5.4.5 Zinc Oxide -- Chapter 6: Quality Parameters of Nanoencapsulation -- 6.1 Particle Size Measurement -- 6.2 Zeta Potential -- 6.3 Morphology -- 6.4 Entrapment Efficiency -- 6.5 Crystallinity and Polymorphism -- 6.6 Magnetic Resonance Investigation -- 6.7 Raman and Fourier Transform Infrared Spectroscopy -- Chapter 7: Nanoencapsulation of Bioactive Compounds -- 7.1 Bioactive Peptides/Proteins -- 7.2 Lipids -- 7.3 Minerals -- 7.4 Vitamin E -- 7.5 Vitamin C -- 7.6 Plant Extracts and Essential Oils -- 7.7 Natural Pigments -- 7.7.1 Curcumin -- 7.7.2 Anthocyanins -- 7.7.3 Carotenoids -- 7.8 Flavours and Aroma -- 7.9 Non-anthocyanin Phenolic Compounds -- 7.10 Bacteriophages -- 7.11 Other Small Molecules.
Chapter 8: Controlled Release and Target Delivery of Nanoencapsulated Compounds -- 8.1 Commercial Products -- Chapter 9: Future Challenges and Conclusions -- Acknowledgement -- References -- Index. |
| Record Nr. | UNINA-9910855389403321 |
Noore Shaba
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Process Analytical Technology for the Food Industry / / edited by Colm P. O'Donnell, Colette Fagan, P.J. Cullen
| Process Analytical Technology for the Food Industry / / edited by Colm P. O'Donnell, Colette Fagan, P.J. Cullen |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (301 p.) |
| Disciplina |
54
543.2-543.8 641.3 664 |
| Collana | Food Engineering Series |
| Soggetto topico |
Food science
Spectrum analysis Food Science Spectroscopy |
| ISBN | 1-4939-0311-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Contributors; Chapter 1; Benefits and Challenges of Adopting PAT for the Food Industry ; 1.1 Introduction; 1.1.1 Evolution of PAT; 1.1.2 Learning From Other Process Industries; 1.1.3 PAT Drivers in the Food Industry; 1.1.4 Technology Advances; 1.1.5 Challenges; References; Chapter 2; Multivariate Data Analysis (Chemometrics); 2.1 Introduction; 2.1.1 Definition of Chemometrics; 2.1.2 PAT and Chemometrics; 2.2 Design of Experiments; 2.2.1 Problem Formulation; 2.2.2 Screening Designs; 2.2.2.1 Full Factorial Designs (2k); 2.2.2.2 Fractional Factorial Designs (2k−p)
2.2.2.3 Other Screening Designs2.2.3 Optimisation Designs: Response Surface Methodology; 2.2.3.1 Central Composite Designs; 2.2.3.2 Other Optimisation Designs; 2.2.3.3 Mixture Designs; 2.3 Exploratory Analysis; 2.3.1 Data Preprocessing; 2.3.1.1 Classical Preprocessing Methods; 2.3.1.2 Signal Correction Methods; 2.3.1.3 Dimensionality Reduction Methods; 2.3.2 Principal Component Analysis; 2.3.2.1 Introduction-Objective of PCA; 2.3.2.2 Geometrical Interpretation; 2.3.2.3 Mathematical Computation; 2.3.2.4 Interpretation of PCA; 2.3.3 Outlier Detection and Handling 2.3.3.1 Outlier Detection in Exploratory Analysis2.3.3.2 Outlier Detection in Predictive Analysis; 2.3.3.3 Robust Statistics; 2.4 Quantitative Predictive Modelling; 2.4.1 Introduction; 2.4.2 Linear Modelling; 2.4.2.1 Linear Regression Principle; 2.4.2.2 Multiple Linear Regression (MLR); 2.4.2.3 Principal Component Regression (PCR); 2.4.2.4 PLS Regression; 2.4.2.5 Model Optimisation and Validation; 2.4.2.6 Science-Based Calibration; 2.4.3 Non-Linear Modelling; 2.4.3.1 Non-Linear PLS; 2.4.3.2 Local Modelling; 2.4.3.3 Least-Squares Support Vector Machines; 2.4.3.4 Artificial Neural Networks 2.4.4 Robustness Issue and Calibration Transfer2.4.4.1 Models Using a Standardisation Set; 2.4.4.2 Models Using a Small Experimental Design; 2.4.4.3 Models When Only a Few Reference Control Points are Available; 2.5 Classification; 2.5.1 Clustering Techniques; 2.5.1.1 Introduction; 2.5.1.2 Hierarchical Clustering Analysis; 2.5.1.3 Non-hierarchical Clustering Methods; 2.5.2 Supervised Discrimination; 2.5.2.1 Introduction; 2.5.2.2 Linear Supervised Discrimination; 2.5.2.3 Non-linear Supervised Discrimination; 2.5.2.4 A Particular Case: k-Nearest Neighbours (k-NN) 2.6 Multivariate Process Monitoring2.6.1 Multivariate Statistical Process Control; 2.6.1.1 Introduction; 2.6.1.2 Process Analysis; 2.6.1.3 Process Monitoring and Fault Diagnosis; 2.6.1.4 Process Control; 2.6.2 Multivariate Curve Resolution; 2.7 Multi-block and Multi-way Analyses; 2.7.1 Multi-block Analysis; 2.7.1.1 Definition of Multi-block Data Sets; 2.7.1.2 Exploratory Multi-block Analyses; 2.7.1.3 Predictive Multi-block Analyses; 2.7.2 Multi-way Analysis; 2.7.2.1 Definition of Trilinear Data Sets; 2.7.2.2 Exploratory Multi-way Analyses; 2.7.2.3 Predictive Multi-way Analyses; 2.8 Conclusion Annex: Figures of Merit |
| Record Nr. | UNINA-9910298652003321 |
| New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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