Ultra-fast sustainable synthesis, optimization and characterization of guava phenolic extract functionalized nanosilver with enhanced biomimetic attributes

2.1 Preparation of phenolic-rich guava extract (GVE)

Guava leaves was obtained locally in Songkhla province, Thailand. The identity of the plant sample was authenticated by matching with a reference sample (voucher specimen number: SKP 123 160701) domiciled at the Herbarium of the Faculty of Pharmaceutical Sciences, Prince of Songkla University, Thailand. The powder (60 g) was extracted with 1600 mL of 70% ethanol (v/v) using an overhead electric stirrer at 300 rpm for 2 h. The extract was filtered, and the filtrate was re-extracted using 1600 mL of fresh solvent. Both filtrate were combined, and ethanol was evaporated under reduced pressure. The aqueous extract was freeze-dried to give a light brown phenolic-rich powder (GVE).

2.2 Determination of total phenolic content

The amount of phenolic constituents in the extract was assessed using Folin-Ciocalteu assay as previously described (Eze et al., 2019). The standard curve was prepared using gallic acid and the total phenolic content was expressed in mg gallic acid equivalent per gram of GVE in dry weight (mg GAE/g GVE dw).

2.3 Synthesis of biogenic silver nanoparticles

Biogenic silver nanoparticles was synthesized as previously described (Jayeoye et al., 2021). Briefly, into 95 mL of aqueous silver nitrate (0.5–2 mM) being stirred on magnetic stirrer was added 5 mL of guava extract (5 mg/mL) solution. Prior to addition, the pH of the extract was adjusted to 9.0. The reaction mixture was monitored visually and through UV–visible spectroscopy for 2 h.

2.4 Characterization of GVE-SNP

UV–vis analysis was performed as previously described (Eze et al., 2019). The UV–vis spectrum of the extract and the as-synthesized GVE-SNP was monitored at room temperature using UV–visible spectrophotometer (Agilent Technologies, Cary 60, USA). The unique surface plasmon resonance band characteristic of oscillating silver nanoparticles was also noted. The shape and distribution of the as-prepared silver nanoparticles was evaluated using transmission electron microscopy. The as-prepared nanoparticles was diluted with ultrapure water (1:150 v/v). A drop of the diluted nanoparticles was carefully placed on the TEM grid and air-dried at room temperature. The nanoparticles was observed using electron microscope, JEM-2010 (JEOL ltd., Tokyo, Japan) operating at 160 kV. The surface morphology of the nanoparticles was examined using field emission scanning electron microscopy (FESEM), Apreo, FEI (Czech Republic). FTIR analysis of the obtained nanoparticles was performed on Perkin Elmer (USA) Spectrum FTIR spectrometer and 32 scans were obtained per sample at a resolution of 4 cm⁻¹. The RAMAN spectra of the nanoparticles was obtained using Raman Microscope Spectrometer, RAMANforce, Nanophoton, Japan at an excitation wavelength of 532.06 nm, power of 0.10 mW, power density of 2.72 × 10³, and wavelength range of 0–4000 cm⁻¹. X-ray diffraction spectra of the samples were obtained using X-ray diffractometer, Empyrean, PANalytical (Netherlands) operating at 40 kV and 30 mA, with Cu Kɑ radiation at a wavelength of 0.154 nm over a scan range (2θ) of 5 to 90° at s at a speed of 70.2 s. Additionally, the hydrodynamic diameter and zeta potential of the nanoparticles were recorded using Zetasizer Nano ZS (Malvern Instruments, Worcestershire, UK). The resistance of the nanoparticle to thermal degradation was evaluated using thermogravimetric (TGA) analysis. TGA analysis of the sample was performed on Thermogravimetric Analyzer, TGA8000 (Perkin Elmer, USA) with a scanning program consisting of heating from 25 °C to 800 °C at 5 °C/min under an atmosphere of nitrogen.

2.5 Antioxidant properties

2.6 Tyrosinase inhibitory activity

Tyrosinase inhibitory activity of the samples was determined as described previously (Jiménez et al., 2018). Phosphate buffer solution (120 µL, 20 mM, pH 6.8) was added into 96-well plate. L-DOPA solution (5.07 mM, 20 µL) was added into the plate followed by 20 µL of GVE (90 µg/mL), GVE-SNP (90 µg/mL) or Kojic acid (45 µg/mL). The solutions were incubated in the dark for 5 min. Subsequently, 20 µL of tyrosinase (500 units/mL) was added to the mixtures and incubated for 20 min. The absorbance of the mixtures was read at 475 nm. The tyrosinase inhibitory activity was expressed as percentage inhibition.

2.7 Antimicrobial activity

The antimicrobial properties of GVE-SNP against selected gram positive bacterial isolates was evaluated using agar well diffusion assay as previously described (Eze et al., 2019). GVE and media solution served as controls, while vancomycin was used as the positive control.

2.8 Determination of cell viability by MTT assay

The cytotoxic effect of the nanoparticles was assessed on mouse L929 fibroblast using MTT assay as previously described (Eze et al., 2021). Briefly, cultured cells in 96-well plates (1.5 × 10⁴/well) were challenged with various concentrations of GVE-SNP in culture media. Cells treated with only culture media served as control. The plate was subsequently incubated for 24 h. Thereafter, the viability of the cells were determined using MTT assay.

3.1 Preparation of phenolic-rich guava extract

It is well-known that the efficacy of phyto-mediated biogenic synthesis of metal nanoparticles is a function of the type and content of phytoconstituents acting as reductants and/or stabilizers (Bhutto et al., 2018). Plant phenolic-rich extracts had previously been demonstrated as efficacious reducers/stabilizers of gold and silver nanoparticles (Nath et al., 2020). In this work, phenolic-rich extract from guava leaf was prepared in a facile and eco-friendly approach that did not require any toxic organic reagent. The approach gave a high yield of 18% (w/w) phenolic-rich guava extract as a light brown hydrophilic powder. The total phenolic content was 96.85 ± 1.76 mg GAE/g GVE dw. Several authors had previously noted the high content of phenolics in guava leaf (Rahman et al., 2018). Besides, the current approach had been demonstrated to recover high yields of phenolics (Eze et al., 2019). In light of the above, the obtained extract is expected to be rich in phenolic constituents present in guava leaf, such as quercetin, gallic acid, guaijavarin, catechin, epicatechin, rutin, gallic acid, kaempferol and glycosides (Lorena et al., 2022; vBarbalho et al., 2012; Rahman et al., 2018). It is germane to underscore that the approach used to prepare GVE is very simple, but more importantly, no toxic organic solvent or residue was needed or created. This was clearly different from previous works where conventional noxious organic solvents such hexane or dichloromethane were used for removing chlorophyll and other lipophilic pigments from the extract. The high total phenolic compounds of GVE was a good indicator of its potential for efficacious synthesis of biogenic silver nanoparticles.

3.2 Preparation and characterization of biogenic silver nanoparticles (GVE-SNP)

Successful synthesis of biogenic silver nanoparticles based on GVE monitored visually and using UV–vis spectroscopy (Fig. 1). Upon addition of GVE solution to silver nitrate solution, the clear colorless Ag solution instantly became sparkling yellow suggesting the formation of silver nanoparticles. Notably, there was a concentration dependent increase in the color intensity of the solutions in relation to the concentration of silver nitrate (Fig. 1A). Concurrently, the UV–visible spectra of the nanoparticle solutions were obtained from 280 to 700 nm (Fig. 1B). The ostensible presence of an absorption maximum around 425 nm was because of the surface plasmon resonance (SPR) band of oscillating nanoparticles due to the incident light, and a strong indication of the presence of silver nanoparticles in the solution. The nanoparticle solutions featured prominent SPR peaks at 418, 425, 431, 430/31 nm for 0.5, 1, 2, and 4 mM of AgNO₃ solutions. It is generally accepted that there is a direct relationship between the λ^max and the size of the obtained nanoparticles (Navarro and Werts, 2012; Paramelle et al., 2014). As such, the solution prepared with 0.5 mM AgNO₃ will feature nanoparticles with the smallest size. On the other hand, the SNP solution from 4 mM AgNO₃ did not only present a lower λ^max intensity, but also seem to aggregate. Also, judging from the intensities of the UV–vis spectra, the highest intensity was recorded for the solution with 1 mM AgNO₃. Thus, based on the λ^max and intensity, 1 mM AgNO₃ was used as the optimal metal salt concentration. Similar to metal salt concentration, the synthesis was optimized for time by monitoring the λ^max at 425 nm from 0 to 60 min (Fig. 1C). Indeed, it appeared that there was no major change in both the intensity and peak position of the reaction solution from 0.5 to 60 min, underscoring the instant reduction of the precursor into nanosilver. The relationship between the synthesis and time was further depicted in a curve to understand the kinetics (Fig. 1D). During this timeframe, the highest absorbance was recorded between 7.5 and 10 min. Beyond 10 min, the absorbance seemed to decline slightly (Fig. 1D). The impact of pH on the synthesis effectiveness was equally assessed. The pH of GVE solution was quickly adjusted before adding to the solution of AgNO₃. The UV–visible spectra and corresponding image of the as prepared GVE-SNP various pH conditions is presented in Supplementary Fig. S1. In general, a pH-dependent increase in the intensity of the UV–vis spectra of GVE-SNP solutions can be seen. At slightly acidic pH 5.5, no clear SPR band was seen. However, as the pH increased, i.e., 6.5 – 8.6, not only did a prominent SPR band appeared around 425 nm, with sharp and symmetrical peaks, but the peak intensities also increased correspondingly. Similar, the intensity of the characteristic yellow color of the nanoparticle solution deepened. Polyphenolic compounds such as guaijavarin and quercetin which populate GVE are more soluble and tend to autoxidize at alkaline pH (Jurasekova et al., 2014). Under this condition hydrogen atoms are made available for the bioreduction of silver ions (Ag⁺) into nanosilver (Ag⁰). This perhaps explains the rapid and efficacious synthesis at pH 8.6. It is also worth mentioning that phenolic compounds tend to easily degrade at very high pH, reducing their capacity not only as reductants but also as stabilizing agents of the as-formed nanoparticles (Jurasekova et al., 2014). Very high pH ≥ 10 was excluded in this work since this has been shown to undermine nanoparticle stability and instead favor aggregation (Brasiunas et al., 2021). Therefore, for reproducible guava phenolic extract mediated synthesis of biogenic SNP, the optimized condition consisted of final concentration of extract and silver precursor of 0.25 mg/mL and 0.169 mg/mL, respectively, at room temperature and pH 8.6 for 10 min.

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Fig. 1

(a) Photographic representation of GVE-SNP solution synthesized with increasing concentrations of AgNO_3. (b) Corresponding UV–visible spectra of the as-synthesized GVE-SNP. (c) Effect of time on GVE-SNP synthesis. (d). Plot of absorbance at 425 nm against time for the synthesis of GVE-SNP using 1 mM AgNO₃ solution at room temperature.

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The phyto-fabrication of silver nanoparticles can be broadly elucidated in three stages: reduction, growth and stabilization (Jayeoye et al., 2021). During the reduction and nucleation phase, silver ions (Ag⁺) in the silver nitrate solution are autocatalytically reduced by polyphenols and powerful flavonoids in GVE, such as quercetin and guaijavarin into small sized silver nanoparticles (Ag⁰). During the growth phase, excess Ag⁺ ions in the solution react with bioactives on the surface of the formed small-sized silver nanoparticles, become reduced, leading to the formation of large-sized silver nanoparticles (Thanh et al., 2014). In the stabilization phase, the mature silver nanoparticles are stabilized in solution by polyphenols and other compounds including sugars, so as to ensure that the particles are well-dispersed and free from aggregation or precipitation. For instance, the carboxylic groups of gallic acid present in GVE are capable of covering the surface of the as-formed SNP by electrostatic attraction (Lorena et al., 2022; Yoosaf et al., 2007). Given that the surface of every SNP in the solution is now covered by these relatively large compounds, they tend to be more stable (Iravani et al., 2014). Moreover, since the surrounding groups on the surface of the individual SNP have the same kind of charges, they tend to repel each other, thereby ensuring that the nanoparticles stay freely dispersed in the solution. Schematic depiction of the putative synthesis mechanism of GVE-SNP is presented in Fig. 2.

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Fig. 2

Schematic representation of putative mechanism of synthesis for GVE-SNP from guava phenolic extract as the reductant/stabilizer and silver nitrate solution as the precursor.

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Given that the biological and physico-chemical properties of metal nanoparticles are often dependent on their size and shape, the morphology of GVE-SNP was evaluated using TEM. The electron micrograph revealed that the as-synthesized GVE-SNP were round and well-dispersed (Fig. 3A). The high resolution TEM image (Supplementary Fig. S2) and concentric rings revealed in the selected area electron diffraction (SAED) pattern (Fig. 3D) indicated that the nanoparticles are of pure crystalline nature. The observed bright white rings apparently emerged from reflections of the Bragg’s planes of fcc silver. The particle size analysis of the nanoparticles based on the TEM micrograph using ImageJ software revealed that GVE-SNP had a mean particle diameter of about 5.88 nm. The nanoparticles presented a relatively narrow distribution with over 70% of the sample having a diameter in the range 4.4 to 7.5 nm (Fig. 3C). Furthermore, the size of the nanosilver in aqueous solution was also determined by DLS. The DLS technique in principle measures the random motion of the particles due to bombardment by surrounding fluid (Brownian motion) and relates this to particles size. It is important to mention that the velocity of the Brownian motion is defined by an entity known as the translational diffusion coefficient and the size of the particles is calculated from this property using the Stokes-Einstein equation. Given that the diameter that is obtained via DLS is a value that indicates how a particle diffuses within a fluid, this diameter is referred to as the hydrodynamic diameter. This diameter is that of a sphere of equivalent translational diffusion coefficient. The translational diffusion coefficient is dependent on the particle ‘core’, any surface structure, as well as the type and concentration of ions in the fluid. Consequently, the DLS is capable of providing complementary information with regards to the interaction behavior of the nanoparticles with the surrounding milieu (Ruseva et al., 2018). Herein, the colloidal nanosilver had an average hydrodynamic size of 17.2 nm (Fig. 3D), which was larger than the TEM data. This apparent increase in the DLS size data over that of TEM stems could be due to the fact that TEM measures the size of the dry particles on the grid whereas the DLS value is a reflection of the hydrodynamic size of the nanoparticles, which is inclusive of the hydration shells around them (Gubitosa et al., 2020; Thomä et al., 2019). The phytochemicals on the surface of the nanoparticles also contributed to the hydrodynamic size. The poly dispersity index (PDI) of the colloidal nanoparticles obtained by DLS was 0.279. The PDI is a measure of the width of particle size distribution. The PDI value could vary from 0.0 (for a sample with perfect size uniformity) to 1.0 (highly polydisperse sample). Previously, Costa asserted that PDI values of 0.08–0.7 are typical for a system with average polydispersity (Costa, 2012) while Cervantes et al noted that particles with PDI values around 0.3 are adequate for cellular uptake (Cervantes et al., 2019). Based on the PDI value obtained for colloidal GVE-SNP solution, the sample of nanoparticles had acceptable size uniformity. Zeta potential measurement of the particles revealed a value of −24.69 mV, suggesting that the colloids were reasonably well-dispersed and stable in aqueous solution. The FESEM image portrayed small white specks against a dark background (Fig. 4A). The shiny white speckles represent the round shaped tiny silver nanostructures, which were found to be lower than 10 nm. EDX analysis revealed a substantial proportion of the nanomaterial was derived from silver (Fig. 4B). The presence of silver was revealed in the EDX spectrum between 2.5 and 3.5 keV consistent with previous reports (Raghunandan et al., 2011). Other elements, notably, C, O, and Cl were also present, presumably from the bioactive compounds in GVE, which served as capping agents on the nanomaterial surface. The unassigned peak that emerged around 0.9 keV is likely from the brass stub where the GVE-SNP sample was mounted during the analysis. The elemental map of GVE-SNP indicated a uniform distribution of the silver in the nanostructure (Fig. 4C).

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Fig. 3

(a) TEM micrograph of GVE-SNP obtained at 250,000 x. (b) Selected area electron diffraction (SAED) pattern (c) Particle size distribution of GVE-SNP captured by TEM and prepared with ImageJ software and (d) Hydrodynamic particle size distribution obtained by DLS.

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Fig. 4

(a) FESEM images GVE-SNP revealing the small nanoparticles as shiny white speckles (b) EDX spectra of GVE-SNP depicting strong peaks of silver between 2.5 and 3.5 keV and (c) Elemental maps of the different elements present in GVE-SNP revealing the uniform showing the uniform distribution of silver.

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FTIR analysis was used to elucidate the functional group interactions that participated in the production of the nanoparticle. The infra-red spectrum of GVE revealed prominent absorption bands at 3369 cm⁻¹ and 2928 cm⁻¹ corresponding to the —O—H and C—H or N—H stretching vibrations, respectively (Fig. 5A). Other notable peaks were also observed at 1692 cm⁻¹ (C⚌O stretching) and 1609 cm⁻¹ (C⚌C stretching) and 1044 cm⁻¹ (—C—O—C- stretching) (Qiao et al., 2014). The FTIR pattern of the nanoparticles was quite similar to that of the extract, suggestive of the presence of GVE metabolites on the surface of the nanostructure. Nonetheless, when both spectra were compared, some changes were observed in terms of the major peak positions. In particular, minor shifts were observed in most of the major peak positions appearing in GVE-SNP. For instance, the peaks at 1692, 1609, 1447 and 1210 cm⁻¹ in GVE shifted to lower positions at 1691, 1603, 1442 and 1205 cm⁻¹, respectively in GVE-SNP, while the one at 1518 cm⁻¹ moved to a higher wavenumber, 1523 cm⁻¹. What these peak transitions demonstrate are molecular interactions between the components of GVE and the surface of the nanomaterial (Zhao et al., 2010), putatively contributing to its stability post-synthesis. The functional moieties deposited on the silver nanoparticles were further investigated using RAMAN spectrometry with the RAMAN spectra of the extract and nanoparticles presented in Fig. 5B. The extract exhibited weak RAMAN signals at 122, 1045, 1374 and 1531 cm⁻¹. The silver nanoparticles produced enhanced signals around the same locations at 117, 1063, 1352.6, and 1547 cm⁻¹, which were consistent with RAMAN shifts of polyphenolic compounds such as quercetin and ellagic acid derivatives (R. Pompeu et al., 2018). These compound had been noted as some of the major bioactives known to constitute guava extract (Díaz-de-Cerio et al., 2016). The sharp RAMAN peak at 236 cm⁻¹ is indicative of the lattice vibration of Ag nanoparticles. Similar signal was previously observed at 233 cm⁻¹ in the RAMAN spectrum of biogenic Ag nanoparticles from Neem extract (Ulaeto et al., 2020). The slight shift in peak positions of GVE-SNP relative to GVE can be attributed to intermolecular interactions between the bioactives and metal surface. The RAMAN profile of GVE-SNP confirmed that the surface of the metal nanoparticles was covered by bioactives from GVE. These findings are well corroborated by previous reports (Padilla-Cruz et al., 2021).

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Fig. 5

(a) FTIR and (b) RAMAN spectra of GVE-SNP with peaks representative of major functional groups present in the nanomaterial. (c) XRD profile of GVE-SNP showing major diffraction peaks. (d) TGA/DTG thermograms of GVE-SNP.

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The crystalline attributes of the as-prepared GVE-SNP was characterized by X-ray diffraction analysis. Peaks of the diffractogram were observed at 2θ position 27–85° (Fig. 5C). Although the presence of some crystalline matter can be observed from the XRD profile of GVE, the plant extract was largely amorphous. Conversely, the XRD pattern of the nanostructure presented several clearly defined peaks. Of prominence were the peaks identified at 2θ (°) position around 38, 44, 64, 77 and 81, which corresponded to Bragg reflection of the (1 1 1), (2 0 0), (2 2 0), (3 1 1), and (2 2 2) crystallographic plane lattice. These can be attributed to the face centered cubic (fcc) crystal nature of the silver (ICDD No. 01-071-4613). Meanwhile, some minor peaks were also apparent in the XRD profile of GVE-SNP, such as those featuring at 2θ position 27.83° (a), 32.24° (b), 54.85° (c) and 57.48° (d). These peaks could be ascribed to the (1 1 1), (2 0 0), (3 1 1), (2 2 2) reflections of fcc of silver chloride crystallites (ICDD No. 00-031-1238) (Supplementary Fig. S3). The crystallite particle size of GVE-SNP was determined based on Scherrer’s equation with peak position (2θ) at 38.26° given that it featured the maximum intensity. On the basis of its XRD data, GVE-SNP was found to have an average crystallite size of 4.56 nm. The d-spacing and hkl values were 2.3521 Å and (1 1 1), respectively. Upon computation, lattice parameter (a) of 4.0739 Å was obtained, which is consistent with the standard lattice parameter of silver, 4.0729 Å (Vinayagam et al., 2018).

The thermal stability of GVE-SNP was interrogated via thermogravimetric analysis. The TGA and DTG profiles of the nanoparticle is presented in Fig. 5D. The weight loss response of GVE-SNP as a function of increasing temperature can be characterized in three phases (Supplementary Table S1). The first phase spanning about 24–172 °C with an onset degradation temperature of 31.75 °C mainly reflects the loss of bound water from the nanomaterial. The second phase found within the range of 172–518 °C represents the loss of volatile constituents, degradation and pyrolysis of organic components encapsulating the nanoparticle. Following the third stage of thermal degradation, the nanomaterial lost about 34% of its mass. Of particular significance was the considerable amount of residual ash at the end of the thermal procedure. This is noteworthy because the residual ash content can be taken as an approximation of the resistance of a material to thermal degradation. Compared to prior reports, the ash content of 65.94% is quite high and thus a strong indication of the superior thermal stability of GVE-SNP. This high thermal stability could be attributed to the strong binding of the capping agents over the surface of the nanoparticles. Encouraged by impressive physico-chemical attributes in terms of size, uniform morphology and distribution, as well as stability, we were prompted to evaluate the biological properties of GVE-SNP.

3.3 Biological characterization of GVE-SNP

3.3.1

3.3.1 Antioxidant activities of GVE-SNP

Nanomaterials have been shown to have antioxidant properties leading to the term ‘Nanoantioxidants’ (Sandhir et al., 2015). Interestingly, some of these nanomaterials even exhibited better antioxidant properties than their respective synthesis components (Rehana et al., 2017). In an attempt to know whether GVE-SNP possess any antioxidant property, ABTS and DPPH assays were performed. Generally, all the samples (GVE, GVE-SNP and Vit. C) demonstrated anti-radical activities on ABTS^•+ and DPPH^• (Fig. 6). GVE-SNP exhibited potent anti-radical effect against ABTS^•+ in a concentration dependent manner. Expectedly, vit. C, the standard, had the best antiradical activity of all the samples. What was even more notable was that GVE-SNP displayed better radical scavenging effect than GVE. It has been reported that AgNO₃ solution has no antioxidant activity. On the other hand, GVE is reputed for its strong antioxidant effect. The superior antiradical activity of GVE-SNP could thus be an attribute of its features as a nanomaterial as well as the synergistic effect of the SNP and the GVE that covers its surface. Similar increase in the antioxidant property of plant mediated silver nanoparticles over the reducing/stabilizing plant extract had previously been reported for Cassia fistula extract (Eze et al., 2021).

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Fig. 6

Anti-radical activity of GVE-SNP against (a) ABTS^•+ and (b) DPPH^•.

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3.3.2

3.3.2 Tyrosinase inhibitory activity of GVE-SNP

The synthesis and distribution of melanin, melanogenesis, takes place in specialized pigment producing cells (melanocytes) located amongst the basal layer epidermal cells and dermal macrophages of the skin. Melanin is the pigment responsible for skin complexion and, plays a vital role in protection of the skin against deleterious solar radiation which could lead to cancers and other diseases. However, excessive production of melanin could give rise to hyperpigmentation and skin discoloration. Melanin is synthesized in a cascade known as melanogenesis. Melanogenesis is largely a non-enzymatic oxidative process. The only enzyme involved in the production of melanin is tyrosine (Sugumaran and Barek, 2016). Thus, the inhibition of tyrosinase has been proposed as an effective approach for modulating the synthesis of melanin.

In this work, the tyrosinase inhibitory property of GVE-SNP was determined using the dopachrome assay. In the presence of the inhibitor, the enzymatic oxidation of L-DOPA into a brown solution is prevented. GVE, GVE-SNP and the standard kojic acid (KA) all inhibited tyrosinase (Fig. 7) and thus prevented the enzymatic oxidation of L-DOPA to dopaquinone. The suppression of tyrosinase activity by GVE-SNP was significant (p < 0.001) and occurred in a dose-dependent manner. Compared to both GVE and KA, the tyrosinase inhibitory effect of GVE-SNP was lower. It has been previously reported that guava leaf extract is a potent inhibitor of tyrosinase (You et al., 2011). Thus, it is possible that the tyrosinase inhibitory effect of GVE-SNP is a product of the anti-tyrosinase property of the extract components that encapsulate the nanoparticles. This findings indicated that besides the remarkable antioxidant properties of GVE-SNP, the nanoparticles could also protect against melanin-induced hyperpigmentation and skin discoloration.

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Fig. 7

Tyrosinase inhibitory activity of GVE-SNP.

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3.3.3

3.3.3 Cytotoxicity of GVE-SNP

The potential of GVE-SNP to impact normal cells was assessed using L929 fibroblasts derived from mouse connective tissue. L929 cells were selected considering their high sensitivity and wide used in in vitro toxicity testing. Untreated cells containing only the media was used as controls. The viability of L929 cells upon exposure of various concentrations of GVE-SNP is presented in Fig. 8A. The cells showed a high level of viability above 80% following 24 h incubation with GVE-SNP up to a concentration of 25 µg/mL. At GVE-SNP concentrations greater than 25 µg/mL, the cell viability reduced substantially to below 50%. These results indicated that the maximum non-cytotoxic concentration of GVE-SNP in L929 fibroblasts is 25 µg/mL. This concentration was taken into consideration in subsequent biological investigations.

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Fig. 8

(a) Cell viability of mouse L929 cells after 24 h treatment with various concentrations of GVE-SNP. The effect of GVE-SNG on the growth of (b) S. aureus and (c) S. epidermidis illustrated by the presence or absence of clear inhibition zones.

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