Preparation of FA-gallic acid/PLGA-PEGylated lipid IO nanoparticles

Gallic acid is dissolved in acetonitrile and added into the PLGA polymeric solution, and the mixture is stirred for 1 h until a clear solution is obtained. The mixture of ferrous chloride tetrahydrate (FeCl24H2O) and ferric chloride hexahydrate (FeCl36H2O) was then sonicated for 1 h separately with 6 ml of ammonium hydroxide. Then, the polymer and drug mixture were added into the above mixture to get the iron oxide core. This core formation was achieved by the interaction of gallic acid with ionic iron at the surface of the nanocore, which increases the reactivity and favours uniform dispersion. The mixture was also stirred for 24 h to produce iron oxide nanoparticles (Xiao Hu et al. 2016). Then, the nanoparticles were dipped in the pre-warmed L-phosphatidylcholine/DSPE-PEG4k-FA mixture and stirred slowly in a shaker for 3–5 h at room temperature. After completion, the solution was centrifuged to remove recalcitrant organic molecules, and the settled nanoparticles were washed and dried. Finally, the surface-modified nanoparticles were collected successfully.

Optimization method (Box–Behnken design)

Experimental design

Our preliminary experimental findings revealed that the design and evaluation of nanoparticles are influenced by three factors, namely the concentration of polymer, lipid, and drug. Response surface methodology using Box–Behnken design (Saba Ibrahim et al. 2021) was chosen because it allows determination of the influence of these factors on the nanoparticle properties with a minimum number of experiments. A Box–Behnken design was used to investigate the effects of three factors (X1; polymer, X2; lipid, and X3; drug) on the response variables Y1 (entrapment efficiency), Y2 (particle size), and Y3 (drug release).

Table 1 lists the independent factors and the dependent variables used in the design. The response surface of the variables inside the experimental domain was analysed using stat Ease design expert software (version no. 10, MacOS) (Ubaidulla 2008). The statistical design provides a polynomial describing the quadratic effect (Deepthi et al. 2017), as well as the interactions of each study factor on the considerable response variable. The general model corresponds to the following equation:

$$begin{aligned} Y_{0} & = b_{0} + b_{1} A + b_{2} B + b_{3} C + b_{12} AB + b_{13} AC + b_{23} BC + b_{23} BC + b_{23} BC , \ & quad +, b_{23} BC + b_{23} BC + b_{11} A_{2} + b_{22} B_{2} + b_{33} C_{2} \ end{aligned}$$

Table 1 The formulation factors and responses of Box–Behnken design for gallic acid nanoparticle

Y is the measured response associated with each factor–level combination; b0 is an intercept; b1b23 are the regression coefficients; and X1, X2, and X3 are the independent variables. The results are shown in Tables 1, 2, and 3 and Fig. 1.

Fig. 1
figure 1

Effect of responses by prepared GANPs

Fig. 2

a FTIR spectrum of Gallic acid (GA), b FTIR spectrum of Polylactic glycolic acid (PLGA), C FTIR spectrum of prepared nanoparticles (GANP)

Fig. 3
figure 3

DSC thermogram of a PLGA, b NPs, c GA

Fig. 4
figure 4

A Gallic acid (GA), B gallic acid nanoparticles (GANP)

Fig. 5
figure 5
Fig. 6
figure 6

Optimized formulation of gallic acid nanocomposite

Fig. 7
figure 7

a SEM, b TEM, c Optical microscopic images of optimized formulation

Fig. 8
figure 8

Magnetic property study of IONPs, FA-GA PEG-LIPID-IONPs

Fig. 9
figure 9

a Zeta potential and b particle size of optimized formulation

Fig. 10
figure 10

a In vitro cell line study (MCF-7) of the pure drug gallic acid (GA), gallic acid iron oxide nanoparticles (GA IONPs), folate-tagged lipid nanoparticles (FA-GA/PLGA PEG-LIONPs). Data shown are means ± SD (n = 3, *P-value < 0.05, ***P-value < 0.001,**P < 0.01 versus concentration. b In vitro cell line study (A54-9) of the pure drug gallic acid (GA), gallic acid iron oxide nanoparticles (GA IONPs), folate-tagged lipid nanoparticles ( FA-GA/PLGA PEG-LIONPs). Data shown are represented as means ± SD (n = 3, *P-value < 0.05, ***P-value < 0.001,**P- < 0.01 versus concentration

Fig. 11
figure 11

Cellular uptake study (confocal microscopic images) of optimized formulation a 5 µg/ml concentration of gallic acid nanoparticles, b 20 µg/ml concentration of gallic acid nanoparticles

Table 2 The design and response of gallic acid-loaded nanoparticles according to the Box–Behnken experimental design
Table 3 ANOVA for the quadratic model developed for the optimization of gallic acid lipid nanoparticles

The characterization of nanoparticles

FTIR study: Fourier-transform infrared spectra of the materials were performed over the range of 400–4000 cm1 with 4 cm1 resolution, using a KBR disc method with approximately 1% of the sample in 200 mg of spectroscopic grade potassium bromide, and the pellets were pressed at 10 tons. The outcomes are shown in Fig. 2.

XRD: The powders of samples were packed strongly in a rectangular aluminium cell, and the samples were exposed to the X-ray beam. The scanning region of the diffraction angle, 2, is 5–80. At room temperature, duplicate measurements were taken. The results are shown in Fig. 4.

Differential scanning calorimetry (DSC): The sample (approx. 2 mg) was sealed in a crimped aluminium cell and heated at a speed of 10 °C/min from 50 to 300 °C in an atmosphere of nitrogen. And finally, the data were recorded. The results are shown in Fig. 3.

Entrapment efficiency: The prepared nanoparticles weighed 20 mg and were completely dissolved in 10 ml of DMSO. Then, the residue was washed and diluted by gently shaking for 24 h at 37 °C. Then, the solution was centrifuged at 16,000 g for 15 min, and the supernatant was collected. An aliquot of 1 ml of supernatant was diluted to 10 ml with DMSO, and adsorbance was measured in UV at 264 nm for gallic acid.

$$% , w/w{text{ drug}};{text{ loading}};{text{ content}} = frac{{{text{weight}};{text{ of}};{text{ drug}};{text{ in}};{text{ nanoparticles}}}}{{{text{The}};{text{ weight}};{text{ of}};{text{ removed}};{text{ nanoparticles}}}}; times ;100$$

$${text{Entrapment efficiency }}left( % right){text{ w/w}} = frac{{text{weight of drug in nanoparticles}}}{{text{The initial weight of the drug fed}}}; times ;100$$

Scanning electron microscopy

The sample was sprinkled on double-sided carbon tape and placed on a brass stub. The surface was coated with a thin layer of palladium (about 30 m) in an auto fine coater. Then, it was placed in the sample chamber of a scanning electron microscope and the morphology of the complex was observed. The results are shown in Fig. 7.

Transmission electron microscopy (TEM)

5 ml of the nanoparticle suspension was placed on a carbon form var-coated grid and left to adsorb for 2 min. After adsorption, the grid was washed with deionized water to remove the excess suspension. The grid was visualized by TEM using a microscope operated at 60 kV.

Surface zeta potential measurements were measured using the laser zeta meter

The nanoparticle samples (2.5 ml) were diluted with double distilled water (50 ml) with NaCl as the suspending electrolyte solution. The pH was adjusted to the required value. The samples were shaken for 30 min. After shaking, the equilibrium pH was recorded and the zeta potential of the particles was measured. The results are revealed in Fig. 9. The analysis was carried out at a scattering angle of 90°A at a temperature of 25 °C using nanoparticles dispersed in deionized distilled water. (2 mg of sample was dissolved in 5 ml of deionized water, and then, sonication was done in a sonicator.)


Thermogravimetry (TGA) and differential thermogravimetry (DTG) were performed in 150 L alumina crucibles using a Mettler-Toledo instrument at a heating rate of 10 degrees per minute in the range of 201000 °C. The results are shown in Fig. 5.

In vitro diffusion study of gallic acid nanoparticles

An in vitro release study of GANPs was conducted in the Franz diffusion cell. The drug release profiles of gallic acid from nanoparticles were carried out at pH 7.4 and 4.8 (Sinha et al. 2018). A 5 mL aqueous dispersion of GA-PLGA-NPs was loaded into the cylinder and coupled to the diffusion cell containing the receptor phase. The dissolution medium was agitated at 25 rpm using a magnetic stirrer. At different time intervals, aliquots of 2 ml were withdrawn and immediately restored with the same volume of buffer solution pH 7.4 and 4.8. The amount of GA released was assessed by a double-beam UV spectrophotometer at 264 nm. The report is represented in Fig. 6.

Kinetic study

Data from in vitro dissolution experiments were analysed using kinetic equations such as zero-order, first-order, Higuchi model, Hixson–Crowell, and Korsmeyer–Peppas. The coefficient of correlation (r2) and constant (k) values were calculated for the linear curves obtained by regression analysis of the plots. The release data obtained via the above procedure were subjected to the R and Peppas model to devise its release mechanism. The percentage of drug release can be determined by the diffusion exponent equation. The equation is:

$$M_{t} /M , = , K_{tn}$$

where Mt is the amount of drug released at time t, M is the nominal total amount of drug released, K is the kinetic constant, and n is the diffusion exponent that is used to characterize the release mechanism. For nanoparticles, a value of n is 0.61, which is an indication of non-fiction release (both diffusion and controlled drug release).

Vibrating sample magnetometry study

10 mg of prepared iron oxide nanoparticles and FA-GA/PLGA-PEGylated-LIONPs were weighed and placed in a separate container, then wrapped with wax to maintain position, and placed in a sample holding rod and kept in between the magnetic field poles. Then, the vibration of the samples was amplified and recorded as a magnetic moment. The result is shown in Fig. 8.

In vitro cytotoxicity test

Gallic acid-loaded iron oxide nanoparticles, gallic acid-loaded iron oxide nanoparticles with PEG/lipid coating, gallic acid-loaded iron oxide with PEG/lipid coating, and FA were prepared and sterilized by membrane filtration before the MTT assay. The assay is used to determine the surviving cell numbers through MTT dye reduction. Here, the dye is reduced by live cells to purple formazan. MCF-7 cell lines were treated with samples, and plates were incubated at 37 °C in a 5% CO2 atmosphere for 24 h. After incubation, the test solutions in the wells were discarded, and 100 l of MTT (5 mg/10 ml of MTT in PBS) was added to each well. The plates were incubated for 4 h at 37 °C in a 5% CO2 atmosphere. The supernatant was removed, 100 l of DMSO was added, and the plate was gently shaken to solubilize the formed formazan. The absorbance was measured using the following formula: The result is shown in Fig. 10.

$${text{Cell viability }}left( % right) = left( {{text{OD Sample }}left( {text{optical density}} right) – {text{OD blank}}} right) , times {1}00$$

Study of cellular internalization

Each confocal dish was seeded with 1 × 105 MCF-7 cells (20 mm in diameter, glass-bottom). For cell adhesion, cells were cultured for an entire night. Following a 4-h incubation with FITC at concentrations of 5 g/mL, 10 g/mL, 20 g/mL, and 40 g/mL, the cells were fixed and permeabilized with 3.8 per cent paraformaldehyde and 0.1 per cent Triton X-100, respectively. With DAPI, the cell nucleus was stained. Cells were examined using DAPI, Rhodamine, and FITC filters under the Olympus FV3000 microscope after being washed with PBS. As a control, cells were treated with FITC of same concentration. The outcome is displayed in Fig. 11.

Fluorescent labelling for research of nuclear morphology

MCF-7 cells were seeded onto a coverslip of a 24-well flat-bottom microplate (1 × 105 cells/well density) and cultured for the night at 37 °C in a CO2 incubator. They were given the IC50 dose of FA-conjugated GA/PLGA-PEGylated LIONPs and then incubated for 48 h at 37 °C. The cells were then fixed with a 4 per cent paraformaldehyde solution for 30 min after being rinsed twice with PBS. After 5 min of dark, room-temperature DAPI incubation on fixed cells, the cells were washed twice with PBS and studied under a fluorescence microscope. In representative fields, the quantity of apoptotic cells was counted, and the percentage of apoptotic cells was calculated. The results are shown in Fig. 12.

Fig. 12
figure 12

Fluorescence microscopic images of GANPs (vs) control cells

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