ArticlePDF Available

Understanding the significance variables for fabrication of fish gelatin nanoparticles by Plackett-Burman design

Abstract and Figures

The aim of this experiment is to screen and to understand the process variables on the fabrication of fish gelatin nanoparticles by using quality-design approach. The most influencing process variables were screened by using Plackett-Burman design. Mean particles size, size distribution, and zeta potential were found in the range 240±9.76 nm, 0.3, and −9 mV, respectively. Statistical results explained that concentration of acetone, pH of solution during precipitation step and volume of cross linker had a most significant effect on particles size of fish gelatin nanoparticles. It was found that, time and chemical consuming is lower than previous research. This study revealed the potential of quality-by design in understanding the effects of process variables on the fish gelatin nanoparticles production.
Content may be subject to copyright.
IOP Conference Series: Materials Science and Engineering
PAPER • OPEN ACCESS
Understanding the significance variables for fabrication of fish gelatin
nanoparticles by Plackett-Burman design
To cite this article: Deni Subara et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 290 012006
View the article online for updates and enhancements.
This content was downloaded from IP address 185.143.230.174 on 30/01/2018 at 00:34
1
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution
of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Published under licence by IOP Publishing Ltd
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
Understanding the significance variables for fabrication of
fish gelatin nanoparticles by Plackett-Burman design
Deni Subara1, Irwandi Jaswir1,2, Maan Fahmi Rashid Alkhatib1 and Ibrahim Ali
Noorbatcha1
1Department of Biotechnology Engineering, Faculty of Engineering, International
Islamic University Malaysia 53100 Kuala Lumpur, Malaysia
2International Institute for Halal Research and Training (INHART), International
Islamic University Malaysia Gombak, Kuala Lumpur, Malaysia
Email: deni.subara@yahoo.com
Abstract. The aim of this experiment is to screen and to understand the process variables on
the fabrication of fish gelatin nanoparticles by using quality-design approach. The most
influencing process variables were screened by using Plackett-Burman design. Mean particles
size, size distribution, and zeta potential were found in the range 240±9.76 nm, 0.3, and 9
mV, respectively. Statistical results explained that concentration of acetone, pH of solution
during precipitation step and volume of cross linker had a most significant effect on particles
size of fish gelatin nanoparticles. It was found that, time and chemical consuming is lower than
previous research. This study revealed the potential of quality-by design in understanding the
effects of process variables on the fish gelatin nanoparticles production.
1. Introduction
Gelatin is an excellent materials for production nanoparticles that have been described well in the
literature [1], [2]. Gelatin is obtained from hydrolysis of collagen. Furthermore gelatin considered as
GRAS or generally regarded as safe by FDA (food drug administration) [3]. Gelatin is also the cheap
materials because it’s abundant, readily available, high nutrition value, biocompatible, and
biodegradable [3]. Due to the characteristic of gelatin, it has been successful encapsulated different
type of drug, such as antibiotics [4], bioactive extract [5], and anti-cancer [6]. The origin gelatin in the
market was from porcine skin and bovine bone. Because of that, almost gelatin nanoparticles have
been produced from mammalian gelatin. However, the application of mammalian gelatin was not
suitable for some group, such as Jews prefer Kosher and Muslim prefer Halal [7]. Alternative source
such as fish gelatin nanoparticles would be fulfill the requirement of some groups.
Mainly, mammalian gelatin nanoparticles was produced by several method, such as emulsion [8],
coarcevation [9], self-assembly [10], and two-desolvation method [11]. In this experiment, two-step
desolvation method was applied because this method could produce small size nanoparticles with
narrow size distribution [3]. However, due to lower gelling point, lower gel strength, and lower
melting point of fish gelatin [12], the preparation of fish gelatin nanoparticles will be different
compare to mammalian gelatin nanoparticles. In order to fabricate the fish gelatin nanoparticles with
small size, the fabrication variables need to be screen and optimize.
In two-step desolvation method, many formulation parameters affect the quality of gelatin
nanoparticles. Less chemical consuming and short production time in the process production were
2
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
became the main purpose, and as well as the ability of the process production brings the product to
commercialization. Because of that, quality by design (QbD) was initiated by FDA [13]. QbD requires
better understanding on phenomenon in each process production in order to improve their
performance. One of the common methods is design of experiment. Design of experiment was the
precise technique to know the most significant variables in the pharmaceutical development. Jones et
al., [14] explains that the design of experiment have been used to define the objective of investigation,
decide the nature of variable and response, and had a minimum number of experimental run. Usually
experimental design divides to two step, the first step to screen the significant factors (Plackett-
Burman design or Factorial design), the second step to optimized the significant factors (usually by
Central composite design or Box-Behnken) [15].
This research focused on the potential of fish gelatin in producing gelatin nanoparticles by two-
desolvation method. Plackett-Burman design was applied to screen the effect of various process
variables. The selected process variables were pH of solution, concentration of acetone, volume of
glutaraldehyde, stirring speed, and stirring time. The effects of the variables on particles size were
analyzed. The particles size distribution and shape of fish gelatin nanoparticles was also studied using
Zeta sizer and FESEM.
2. Experimental procedures
2.1. Materials
Fish gelatins were fabricated by our research group using suggested method by Jamilah [12]. The fish
gelatins were stored in the 4 °C fridge before further use. Others chemicals were purchased from
Sigma Aldrich such as Acetone and glutaraldehyde grade 1 (25% vol% aqueous solution). Deionized
waters (18.2 mΩ cm) were used trough experiment.
2.2. Preparation of fish gelatin nanoparticles
Fish gelatin nanoparticles were prepared by using two-step desolvation method that introduced by
Coester [16]. This method divided on two steps; the first step is fractionation and the second step is
precipitation step. Precipitation step was the main focus in this current experiment.
About 0.9 g fish gelatin was dissolved in 10 ml deionized water with constant stirring (600 rpm)
and constant heating (45 °C) until clear solutions were received. Fish gelatin solutions then were
transferred to falcon tube and were added with 10 ml acetone. The mixed solutions were centrifuged
for 5 min in constant speed (12000 g). The supernatants were immediately discarded and the
precipitated were re-dissolved in 10 ml deionized water. The pH of precipitate solution was adjusted
using 0.1 M HCl until reach certain number of suggested design. The solutions then were added with
acetone and were cross-linked using glutaraldehyde solution. The solutions were stirred with specified
hour. The fish nanoparticles colloids were centrifuged for 30 min at 14000 rpm. The precipitates were
stored at fridge until further use.
2.3. Design of experiment
These experiments were focused on the screening of the significant variables that involve in
precipitation step or in second step from two-step desolvation method. In this experiment experimental
design (DOE) using Plackett-Burman design was applied. Plackett-Burman (PB) design was applied
because less time consuming and less chemical consuming. Plackett-Burman design involved
relatively less runs experiment (12 runs) to screen huge number of variables resulting critical and good
degree of accuracy compared to factorial design [17]. PB matrix was generated by using Minitab® 16.
The expression of linear equation was developed and shown in equation 1 below.
         (1.0)
Where Y is the dependent variable or response, b0 is the constant and b1, b2... bn are the coefficient of
the variables X1, X2, X3, X4, X5.... Xn (representing the effect of each factor ordered within 1, +1).
3
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
In this PB matrix were involved twelve experimental runs including five independent variables, one
dummy variable and one dependent variable. Each experimental run was carried triplicate. Table 1
shows the list of the independent variables and table 2 describes experimental run matric. Before
experimental design, the chosen variables (five variables) and levels have been made base on previous
researcher and preliminary research [18][25]. The selected independent variables were pH of the fish
gelatin solution (X1), acetone concentration (X2), volume of glutaraldehyde (X3), stirring speed (X4),
and stirring time (X5). One dependent variable was fish gelatin nanoparticles size. The results were
evaluated by statistical analysis using Analysis of variance (ANOVA). Means variable plot were also
establish to analyzed the most significant variables.
2.4. Particles size measurement and FESEM measurement
The fish gelatin nanoparticles size was measured by dynamic light scattering (DLS) at 90° in 10 mm
diameter cells with a Malvern (Zen3600, UK). About 300 µl nanoparticle colloid was mixed to 30 ml
of deionized water. The mixtures were sonicated at 60 Amp for 20 min. The size and particles
distribution were analyzed. The polydistersity index (PdI) is ranging from 0.0 to 1.0. The surface
charge of nanoparticle was measured using Zeta potential Malvern.
Shape, size, and surface morphology of fish gelatin nanoparticles were visualize using Field
Emission Scanning Electron Microscope (FESEM) (JEOL, JSM 6700F Model) at an accelerating
voltage of 10 kV. Prior to visualization, fish gelatin nanoparticles were mounted on small adapter and
was sputter with a thin layer of gold. The adapter was then placed in the chamber.
3. Results and Discussion
3.1. Impact of fabrication parameters on fish gelatin nanoparticles size
Table 2 depicts the experimental results of twelve run from five independent variables. The statistical
analysis were applied to this results in order to quantify the most influence significant variables on the
fabrication fish gelatin nanoparticles by using Minitab® 16 software. The behavior of the individual
variables to particles size were also analyzed by alternatively treated at the highest and lowest level.
While others variables were kept constant at center levels.
Figure 1 shows the plot of main effect of each variable on the particles size. This figure not only
depicts the effect of respective processing variables, but also shows the positive or negative trend of
each variable in studied range. It can be seen that pH of solution and percentage of acetone had
significant positive effects, while volume of glutaraldehyde had a significant negative effect on the
particles size. This statement describes that small size fish nanoparticles could be produced at low pH
solution, low percentage of acetone and huge volume of glutaraldehyde. This result agrees with
previous works [19][21], that small size gelatin nanoparticles were produced bellow isoelectric point,
low concentration of acetone and high volume of glutaraldehyde. It is because isoelectric point of fish
gelatin had same range of with mammalian gelatins that have been used at previous work. The
isoelectric point of fish gelatin is around pH 6-9 [12], [26].
Table 1. Experimental variables and level of Plackett-Burman design.
Variables
Units
Experimental value
Low (1)
High (+1)
pH
1.5
5.5
Percentage of Acetone
%(v/v)
15
65
Volume of Glutaraldehyde
µl
100
600
Stirring Speed
rpm
300
900
Stirring Time
hour
3
21
4
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
Furthermore, we found fish gelatin nanoparticles could be produced below pH 3.5 while optimum
pH to produce mammalian gelatin was at pH 3.5. Producing fish gelatin nanoparticles within
isoelectric point would produce large-scale of gelatin nanoparticles, due to the electrostatic attraction
[21]. Decreasing the pH solution leads to protonate the side chain amino acid and create the stable
suspension [21]. High concentration of acetone creates large aggregate [19]. Moreover, high
concentration of glutaraldehyde forced the particles become harder [27]. In other hand, short or long
time stirring of gelatin solution had insignificant effect for production small nanoparticles.
Table 2. Plackett-Burman design matrix.
Run
pH
(X1)
Concentration
of Acetone
(%, vol v/v)
(X2)
Volume of
Glutaraldeyde
l) (X3)
Stirring
Speed
(rpm)
(X4)
Stirring
Time
(hours)
(X5)
Observed
Particles
size (nm)
Predicted
Particles
size
1
5.5
15
600
300
3
275.72±0.07
274.54
2
5.5
65
100
900
3
850.45±6.57
722.38
3
1.5
65
600
300
21
244.49±2.05
264.16
4
5.5
15
600
900
3
245.88±4.09
280.12
5
5.5
65
100
900
21
882.13±3.85
708.95
6
5.5
65
600
300
21
518.19±6.46
364.52
7
1.5
65
600
900
3
227.85±1.07
283.18
8
1.5
15
600
900
21
205.25±5.60
166.34
9
1.5
15
100
900
21
191.84±3.16
182.09
10
5.5
15
100
300
21
233.04±2.10
276.86
11
1.5
65
100
300
3
267.34±2.76
293.35
12
1.5
15
100
300
3
204.71±0.72
189.93
5,53,51,5
450
400
350
300
250
654015 600350100
900600300
450
400
350
300
250
21123
pH
Paarticles size (nm)
% Acetone (v/v) Glutaraldeyde (µl)
Stirring Speed (rpm) Stirring Time (h)
Variables Plot for Particles size
Data Means
Figure 1. Main effect of variables in Plackett-Burman design of experiment on particles size.
5
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
3.2. Statistical analysis of Plackett-Burman design
In this experiment, we performed analysis of variance (ANOVA). The statistical analysis with
ANOVA would produce the significance of models and regression coefficient in Plackett-Burman
design. This experiment carried out by using 95% of confidence level. Means, the significance
variables will be calculated based on p value at 0.05. The variable would be considered as insignificant
variables when p value are higher than 0.05. The ANOVA results agree that pH of the solution,
concentration of acetone, and volume of glutaraldehyde are the effective variable on producing small
size nanoparticles, because they have lower p value than 0.05. The p value of model was obtained to
be low value, this result representing that the regression model was also significant with a 95%
confidence level. The R square of the results was at 0.86, means good correlation between observed
particles size and predicted particles size. This R square also depicts that this model could explain
almost 86% of the response variation. However, the p value of curvature was found to be higher than
0.05. That means, the levels of variables is in slope area and need to be changed in order to choose the
correct level before optimization.
The polynomial equation between particles size and independent variables was given below.
        (3.0)
3.3. Characterization of prepared fish gelatin nanoparticles
The fish gelatin nanoparticle was fabricated using suggested variables such as pH at 1.5, percentage of
acetone at 15%, and volume of glutaraldehyde at 600 µl, briefly, while other insignificant variables
were treated in the center point. Figure 2 shows the particles size distribution from zeta-sizer analysis.
It can be seen that, the average particles size of fish gelatin nanoparticles was about 240±9.76 nm, and
the polydispersity index was at 0.3. This fish gelatin nanoparticle had slightly difference in particles
size compared with mammalian gelatin nanoparticles was produced by Kumari around 110-257 nm
[1]. The morphology of fish gelatin nanoparticles was quantified using FESEM (Figure 2b). FESEM
result shows fish gelatin nanoparticles had a round shape. However, some variation in size distribution
was depicted in the FESEM images. This phenomenon due to the uncontrolled effect of neutralization
the molecule charge during specific pH [19], [28].
4. Conclusion
Fish gelatin nanoparticle was successfully developed using two-step desolvation method.
Plackett-Burman quality by design approach was used to screen the independent variables and to
understand the effect of most significant factors for production of fish gelatin nanoparticles. From the
a)
b)
Figure 2. Particles size distribution of fish gelatin nanoparticles (a) and FESEM images of
fish gelatin nanoparticles (b).
0
5
10
15
00 200 400 600 800
Internsity (percent)
Particles Diameter (nm)
6
1234567890
ICAMME 2017 IOP Publishing
IOP Conf. Series: Materials Science and Engineering 290 (2017) 012006 doi:10.1088/1757-899X/290/1/012006
Plackett-Burman results, three variables such as pH solution, percentage of acetone, and volume
glutaraldehyde were found to have significant effects. While other variables like stirring time and
stirring speed were insignificant on response. This results means by this method, we can reduce time
and energy consuming in producing fish gelatin nanoparticles. To be concluded Plackett-Burman
design is an efficient method for screening the most significant factors with minimum experimental
run. Additionally, studies will continue to further optimization on production of fish gelatin
nanoparticles.
Acknowledgement
This work was financially supported by Postgraduate Research Grant Scheme (PRGS) (Grant
no. 13-087-0328) from Malaysian Ministry of Education.
References
[1] Kumari S K A Yadav and Yadav S C 2010 Colloids Surf. B: Biointerfaces 75 118
[2] Farokhzad O C and Langer R 2009 ACS. Nano. 3 1620
[3] Elzoghby A O 2013 J. Control. Release 172 10751091
[4] Mahor A, Prajapati S K, Verma A, Gupta R, Iyer A K and Kesharwani P 2010 J. Colloid
Interface Science 483 132138
[5] Hani N, Azarian M H, Torkamani A E, and Kamil Mahmood W A 2016 Int. J. Food Sci
Technol. 51 23272337
[6] Han S, Li M, Liu X, Gao H, and Wu Y 2013 Colloids Surf. B:Biointerfaces 102 833841
[7] Karim A A and Bhat R 2008 Trends Food Sci. Technol. 19 644656
[8] Bajpai A K and Choubey J 2006 J. App. Polym. Sci. 101 23202332
[9] Kasankala L, Xue Y, Yao W, Hong S, and He Q 2007 Bioresour. Technol. 98 333843
[10] Li Z and Gu L 2011 J. Agric. Food Chem. 59 42254231
[11] Dixit N, Vaibhav K, Pandey R S, Jain U K, Katare O P, Katyal A, and Madan J 2015 Biomed.
Pharmacother. 69 110
[12] Jamilah B and Harvinder K 2002 Food Chem. 77 814
[13] Rahman Z, Zidan A S, Habib M J, and Khan M A Int. J. Pharm. 389 186194
[14] Jones R Pharm. Eng. product quality 29 110
[15] Gupta B, Poudel B K, Pathak S, Tak J W, Lee H H, Jeong J, Choi H G, Yong C S and Kim J O
2015 AAPS PharmSciTech 15 111
[16] Coester C, Langer K, Von Briesen H and Kreuter 2000 J. Microencapsul. 17 187193
[17] Plackett R L and Burman J P 1946 Biometrika33 305325
[18] Ofokansi K, Winter G, Fricker G, Coester C, Winte R G, Fricker G and Coester C 2010 Eur. J.
Pharma. Biopharm. 76 19
[19] Azarmia S, Huang Y, Chend H, Steve M, Abramse D, Road W, Löbenberga R, Azarmi S,
Huang Y and Chen H 2006 J. Pharm. Sci. 9 124132
[20] Langer K, Balthasar S, Vogel V, Dinauer N, Von Briesen H and Schubert D 2003 Int. J. Pharm.
257 169180
[21] Saxena A, Sachin K, Bohidar H B B and Verma A K 2005 Colloids Surf. B: Biointerfaces 45
4248
[22] Taheri E S, Jahanshahi M and Mosavian M T H 2012 Part. Part. Syst. Charact. 29 211222
[23] Von Storp B, Engel A, Boeker A, Ploeger M and Langer K 2012 J. Microencapsul. 29 13846
[24] Baharifar H and Amani A 2017 J. Pharm. Sci. 106 411417
[25] Balavandy S K, Shameli K, Biak D R B A and Abidin Z Z 2014 Chem. Cent. J. 8 1114
[26] Gudmundsson M 2002 J Food Sci. 6 21722176
[27] Nahar M, Mishara D, Dubey V and Jain N K 2008 Nanomedicine 4 252261
[28] Mazerski J, Grzybowska J and Borowski E 1990 Eur. Biophys. J 18 15964
Article
Insofar the cost of repairing concrete structures reaches the trillions of dollars, new technologies, such as concrete self‐healing, are investigated continuously. Consequently, the main objective of this work is on the production of a cheap and easy‐to‐make material, which can be used in large‐scale applications, besides presenting similar results as other ones more complex systems. In brief, a core‐shell system is produced and investigated as a self‐healing agent. Aiming this, a mix of gelatin and sodium silicate (Na2SiO3) is used as the core, while poly(vinyl alcohol) (PVA) is the glutaraldehyde crosslinked shell. The obtained materials are characterized using several techniques, such as Fourier transform infrared spectroscopy (FTIR), as well as, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). FTIR proves the obtaining of the proposed system. In turn, TGA and DSC showed that the material could endure real‐life applications. Also, granulometry tests show that the obtained materials are mostly in the micrometric scale. The Na2SiO3 release is especially tested in aqueous media, proving the core‐shell system swells, releasing its active agent. Thereby, the obtained results allow concluding that the presented core‐shell material is useful to the self‐healing applications.
Article
In this study, bagasse was pretreated with ionic liquid (IL) 1-butyl-3-methylimidazolium chloride ([Bmim]Cl) and 1% NaOH solution for initial activation of bagasse. A mixed fermentation of treated bagasse by Aspergillus niger and Candida shehatae showed the optimal conditions with the addition of C. shehatae 12 h later at a 1:1 proportion to A. niger. To further improve the ethanol production and obtain optimal fermentation conditions, a Plackett–Burman design was applied to screen the significant formulation and process variables. The optimal ethanol fermentation conditions with IL pretreated bagasse were determined using response surface methodology by Box–Behnken design. Three variables “initial pH, (NH4)2SO4, fermentation time” were regarded as significant factors in the optimization study. The resulting optimum fermentation conditions for bioethanol was identified as: initial pH of 5.89, (NH4)2SO4 concentration of 0.40 g/50 mL, and fermentation time of 3.60 days. The verification experimental ethanol concentration was 8.14 g/L, which agreed with the predicted value. An enhancement of approximately 153.58% compared with initial fermentation conditions in ethanol production was found using optimized conditions. It demonstrated that optimization methodology had a positive effect on the improvement of ethanol production. Under the optimal fermentation medium and conditions, the ethanol production with IL-pretreated bagasse and untreated bagasse was 8.14 g/L and 5.03 g/L, respectively, which exhibited 62% increase, compared to initial conditions with production of 3.21 g/L and 2.67 g/L, respectively, which displayed 20% increase. Both under optimal and original fermentation conditions, compared to the fermentation medium with untreated bagasse, all the results indicated that IL-pretreated bagasse resulted in higher ethanol production than untreated bagasse, demonstrating that IL-pretreated bagasse successfully increased the ethanol production in the mixed fermentation by A. niger and C. shehatae.
Article
Full-text available
When designing nanoparticles for drug delivery, many variables such as size, loading efficiency, and cytotoxicity should be considered. Usually, smaller particles are preferred in drug delivery because of longer blood circulation time and their ability to escape from immune system, whereas smaller nanoparticles often show increased toxicity. Determination of parameters which affect size of particles and factors such as loading efficiency and cytotoxicity could be very helpful in designing drug delivery systems. In this work, albumin (as a protein drug model)-loaded chitosan nanoparticles were prepared by polyelectrolyte complexation method. Simultaneously, effects of 4 independent variables including chitosan and albumin concentrations, pH, and reaction time were determined on 3 dependent variables (i.e., size, loading efficiency, and cytotoxicity) by artificial neural networks. Results showed that concentrations of initial materials are the most important factors which may affect the dependent variables. A drop in the concentrations decreases the size directly, but they simultaneously decrease loading efficiency and increase cytotoxicity. Therefore, an optimization of the independent variables is required to obtain the most useful preparation.
Article
Full-text available
This study aims to investigate the influence of different stirring time for synthesis of silver nanoparticles in glutathione (GSH) aqueous solution. The silver nanoparticles (Ag-NPs) were prepared by green synthesis method using GSH as reducing agent and stabilizer, under moderate temperature at different stirring times. Silver nitrate (AgNO3) was taken as the metal precursor while Ag-NPs were prepared in the over reaction time. Formation of Ag-NPs was determined by UV-vis spectroscopy where surface plasmon absorption maxima can be observed at 344-354 nm from the UV-vis spectrum. The synthesized nanoparticles were also characterized by X-ray diffraction (XRD). The peaks in the XRD pattern confirmed that the Ag-NPs possessed a face-centered cubic and peaks of contaminated crystalline phases were unable to be located. Transmission electron microscopy (TEM) revealed that Ag-NPs synthesized were in spherical shape. Zeta potential results indicate that the stability of the Ag-NPs is increases at the 72 h stirring time of reaction comparison to GSH. The Fourier transform infrared (FT-IR) spectrum suggested the complexation present between GSH and Ag-NPs. The use of green chemistry reagents, such as peptide, provides green and economic features to this work. Ag-NPs were successfully synthesized in GSH aqueous solution under moderate temperature at different stirring times. The study clearly showed that the Ag-NPs synthesized in the long times of stirring, thus, the kinetic of GSH reaction is very slow. TEM results shows that with the increase of stirring times the mean particle size of Ag-NPs become increases. The FT-IR spectrum suggested the complexation present between GSH and Ag-NPs. These suggest that Ag-NPs can be employed as an effective bacteria inhibitor and can be applied in medical field.
Article
The current research focuses on developing positively charged gelatin nanoparticles loaded with moxifloxacin for its effective ocular delivery and controlled release in corneal eye layer. We selected type A gelatin because of its biodegradable and non-toxic nature as the polymer of choice for fabricating the nanoparticles by a modified two step desolvation technique. The produced nanoparticles were positively charged (+24±0.12 mV) with a narrow particle size of 175±1.11 nm as measure by dynamic light scattering (DLS). The in-vitro drug release from the nanoformulations exhibited a burst effect in the first hour followed by a controlled release of the drug for the subsequent 12 hours. The Korsmeyer-Peppas model showed better linearity and the formulations displayed non-Fickian drug release pattern. The optimized formulation was assessed for its utility as an anti-bacterial agent and its effectiveness was tested on the corneal eye surface of rabbits. The in-vivo tolerance tests revealed that the drug loaded nano-formulations was non-irritant to the ocular tissues indicating its safety. The in-vivo anti-bacterial activity of the nanosuspension was more effective against S. aureus than the commercially market product, MoxiGram®. Microbiological efficacy assessed against B. subtilus using cup-plate method suggested that our fabricated nanosuspension possess better anti-microbial activity as compared to the commercial agent, MoxiGram® revealing promising potentials for the currently developed gelatin based nanoformualtions.
Article
This study describes the preparation and characterisation of nanoparticles with gelatin as the wall matrix to encapsulate Moringa oleifera (MO) extract using an electrospraying technique. The electrospraying conditions for voltage, flow rate and emitter/collector distance were 20 kV, 0.5 mL h À1 and 10 cm, respectively. Nanoparticles with encapsulated MO extract (1–5%, w/w) were successfully produced and characterised in relation to spectroscopic, morphological and thermal properties. Increasing amounts of MO extract resulted in a significant decrease in the nanocapsule size (ranging from 140 and 179 nm) produced. Spectroscopic analysis indicated no chemical interactions between core and wall materials. The encapsulation efficiency (EE) of MO extract-loaded nanocapsules obtained was 83.0 AE 4.0%. Surface analysis showed that roughness decreased from 91 nm (empty beads) to 57.5 nm with addition of 3% MO extract. The thermal stability of encapsulated nanoparticles slightly increased and the glass transition temperature (T g) disappeared due to increase in crystallinity.
Article
Protein nanoparticles have been recognized as carriers to deliver low molecular-weight drugs, anticancer drug, DNA, vaccines, oligonucleotides, peptides and etc. The purpose of this research was preparation of Egg Albumin (EA) nanoparticle with suitable size/size distribution and good surface properties for drug delivery application based on simple coacervation method along with optimization of the nanoparticles by employing Taguchi method. Several synthesis parameters were examined to characterize their impacts on nanoparticle size and topography. These variables were including temperature, EA concentration, desolvating agent volume, pH value and agitation speed. In addition, size and morphology of prepared nanoparticles were analyzed by photon correlation spectroscopy (PCS) as well as atomic force microscopy (AFM). As result of Taguchi analysis in this research, desolvating agent volume and pH were most influencing factors on particle size. The minimum size of nanoparticles (∼51 nm) were obtained at Temperature 55 °C, 30 mg/ml EA concentration, desolvating agent volume 50 ml, agitation speed of 500 rpm and pH 4. The mechanistic of optimum conditions for preparing protein nanoparticles from Egg Albumin for the first time and their characterization as delivering nano system are discussed.
Article
Gelatin is one of the most versatile natural biopolymers widely used in pharmaceutical industries due to its biocompatibility, biodegradability, low cost and numerous available active groups for attaching targeting molecules. These advantages led to its application in the synthesis of nanoparticles for drug and gene delivery during the last thirty years. The current article entails a general review of the different preparation techniques of gelatin nanoparticles (GNPs): desolvation, coacervation-phase separation, emulsification-solvent evaporation, reverse phase microemulsion, nanoprecipitation, self-assembly and layer-by-layer coating, from the point of view of the methodological and mechanistic aspects involved. Various crosslinkers used to improve the physicochemical properties of GNPs including aldehydes, genipin, carbodiimide/N-hydroxysuccinimide, and transglutaminase are reported. An analysis is given of the physicochemical behavior of GNPs including drug loading, release, particle size, zeta-potential, cytotoxicity, cellular uptake and stability. This review also attempts to provide an overview of the major applications of GNPs in drug delivery and gene therapy and their in vivo pharmacological performances, as well as site-specific drug targeting using various ligands modifying the surface of GNPs. Finally, nanocomplexes of gelatin with polymers, lipids or inorganic materials are also discussed.
Article
Novel biodegradable amphiphilic copolymer nanoparticles based on gelatin, poly(lactide) and 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE) (gelatin-co-PLA-DPPE) have been successfully fabricated. In order to estimate the feasibility as drug carriers, an anti-tumor model drug doxorubicin hydrochloride salt (DOX) was incorporated into polymeric nanoparticles by double emulsion or nanoprecipitation method. The nanoparticle size, size distribution and encapsulation efficiency (EE) were influenced by the feed weight ratio of the copolymer to DOX and different fabrication methods of nanoparticles. In addition, in vitro release experiments exhibited the release behavior was affected by pH of release media. The DOX-loaded nanoparticles showed that faster release at pH 5.0 than their release at pH 7.4 buffer. The DOX-loaded copolymer nanoparticles showed comparable anticancer efficacy with the free drug in vitro and in vivo. These results demonstrate a feasible application of the gelatin derivative as a promising nanocarrier for delivery of anti-tumor drugs.
Article
Gelatin (Type A) nanoparticles were prepared by a single W/O emulsion technique and characterized by infrared (IR) spectra, scanning electron microscopy (SEM), and particle size analysis. The IR spectra clearly confirmed the presence of gelatin and cytarabine in the loaded nanoparticles while the scanning electron micrograph (SEM) image depicts smooth surface, spherical shape and uneven size of nanoparticles (100–300 nm). The prepared nanoparticles were loaded with cytarabine, a well-known anticancer drug, and the release dynamics of entrapped drug was investigated as a function of various experimental factors, such as percent loading of the drug, chemical architecture of the nanocarriers, and pH, temperature, ionic strength, and nature of the release medium. The nanoparticles were also studied for their water sorption capacity by optical microscopic method taking advantage of the aggregation of nanoparticles. The drug release process was analyzed kinetically using Ficks power law, and a correlation was established between the quantity of released drug and swelling of the nanoparticles. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2320–2332, 2006