Biological impact of adding albumin and silver nanoparticles to concentrated growth factors

TL;DR

Adding albumin and silver nanoparticles to concentrated growth factors improves their stability and antimicrobial properties, making them more effective for long-term medical applications.

Contribution

The study introduces albumin and silver nanoparticle modifications to CGF, demonstrating enhanced sustained release and antibacterial activity.

Findings

ALB-CGF-SNP showed the highest growth factor concentrations at Day 30 and the best bacterial inhibition.

ALB-CGF prolonged growth factor release and resisted degradation better than standard CGF.

SEM analysis revealed structural differences, with ALB-CGF-SNP having an irregular network and denatured protein distribution.

Abstract

Concentrated Growth Factor (CGF) is widely used in regenerative medicine and dentistry, but its rapid degradation limits long-term applications. Albumin-modified CGF (ALB-CGF) and silver nanoparticles (ALB-CGF-SNP) enhance stability and antimicrobial properties. This study evaluates growth factor release, degradation resistance, structural morphology and antibacterial efficacy of CGF, ALB-CGF and ALB-CGF-SNP.

Blood samples from 15 healthy volunteers were processed to obtain CGF, ALB-CGF and ALB-CGF-SNP. Growth factor release, including Platelet-Derived Growth Factor-AB (PDGF-AB), Vascular Endothelial Growth Factor (VEGF), Transforming Growth Factor Beta-1 (TGF-β1) and Epidermal Growth Factor (EGF), was quantified using Enzyme-Linked Immunosorbent Assay (ELISA) at 1, 7, 14, 30 and 60 days of samples incubation at 37 °C. Degradation was assessed via a Bicinchoninic Acid (BCA) assay. Structural morphology was analyzed using Scanning Electron Microscopy (SEM). Antibacterial efficacy against Staphylococcus aureus was evaluated using CFU counts. Statistical tests, including one-way ANOVA or Welch ANOVA with Tukey’s HSD or Dunnett T3 post hoc comparisons, were performed using GraphPad Prism version 10 (P < 0.05).

CGF exhibited a rapid release of growth factors within 7 days, peaking on Day 1 (TGF-β1: 15,398 pg/mL). By Day 14, ALB-CGF had significantly higher VEGF (448.4 vs. 296.4 pg/mL, P = 0.004) and TGF-β1 (5800 vs. 3519 pg/mL, P = 0.004) than CGF, while EGF (P = 0.397) and PDGF-AB (P = 0.368) showed no significant differences. ALB-CGF-SNP had the lowest initial release but maintained the highest concentrations at Day 30 (P < 0.001 for VEGF and EGF, P < 0.0001 for TGF-β1, not significant for PDGF-AB). Degradation analysis showed that CGF degraded rapidly, whereas ALB-CGF and ALB-CGF-SNP retained proteins beyond 60 days (P < 0.001). SEM revealed CGF’s dense fibrin matrix, ALB-CGF’s porous structure and ALB-CGF-SNP’s irregular network with denatured protein distribution. ALB-CGF-SNP showed the highest bacterial inhibition at 24 h (P < 0.0001), though CGF-based group differences were not statistically significant.

ALB-CGF-SNP exhibited sustained growth factor release, extended degradation resistance and enhanced antibacterial activity. While CGF provides immediate effects, ALB-CGF prolongs release and ALB-CGF-SNP supports long-term bioactivity, making the latter a promising option for scaffold stability and infection control.

The online version contains supplementary material available at 10.1186/s12903-025-07440-x.

Figures

Quantification of four growth factors released from CGF, ALB-CGF and ALB-CGF-SNP over 1–60 days, measured using ELISA assays with statistical significance as follows: ns (not significant, *P* > 0.05), * (*P* < 0.05), (*P* < 0.01), * (*P* < 0.001) and (*P* < 0.0001)

Degradation analysis of CGF, ALB-CGF and ALB-CGF-SNP over 1–60 days, assessed through protein quantification using the BCA protein assay kit

Scanning Electron Microscopy (SEM) images illustrating the surface and cross-sectional structure of CGF, ALB-CGF and ALB-CGF-SNP samples, captured at magnifications of 100 ×, 800 ×, 3 k ×, 6 k ×, 12 k × and 24 k ×, corresponding to images A, B, C, D, E and F, respectively

Mean growth of Staphylococcus aureus in the presence of CGF, ALB-CGF and ALB-CGF-SNP over 0–24 h, with Staphylococcus aureus as the negative control and methicillin as the positive control with statistical significance as the follows: ns (not significant, *P* > 0.05), * (*P* < 0.05), (*P* < 0.01), * (*P* < 0.001) and (*P* < 0.0001).

Full text

Introduction

The primary objective of contemporary surgery is to enhance clinical recovery while minimizing patient discomfort and procedural morbidity. Regenerative surgery has emerged as an essential approach in this regard [1]. Tissue regeneration involves restoring hard and soft tissues to their native structural and functional states. The success and predictability of regenerative procedures necessitate orchestrating intricate biological processes, including cellular migration, adhesion, proliferation and differentiation [2].

Platelets play a fundamental role in hemostasis and wound healing, thereby contributing to potential strategies for effective tissue regeneration. This is attributable to a rich reservoir of bioactive materials, among which are growth factors acting as key regulators in the sequential phases of tissue repair, cellular recruitment, proliferation and angiogenesis [3]. Given that plasma and platelets serve as the principal sources of these growth factors, platelet-derived biomaterials have been extensively incorporated into medical and dental regenerative applications to accelerate tissue healing and repair [4].

Platelet-rich plasma (PRP), the first generation of platelet concentrates, was developed to promote tissue repair but required anticoagulants and additives. Some studies reported contradictory effects on regeneration [5]. To address these drawbacks, platelet-rich fibrin (PRF) was introduced by [6], as a second-generation concentrate prepared without additives, providing a denser fibrin matrix and a more sustained release of platelets, leukocytes and growth factors [7, 8].

Concentrated growth factor (CGF), which is one of the PRF generations introduced by Sacco in 2006, is generated using a specialized centrifugation protocol (Medifuge, Silfradent srl, Italy), yielding a denser fibrin network with an increased concentration of growth factors [9]. While PRF has demonstrated clinical efficacy across multiple regenerative applications [5, 10], CGF offers enhanced regenerative potential, particularly in maxillofacial and periodontal reconstructive procedures, such as sinus augmentation and alveolar ridge preservation and different applications in regenerative dentistry [11, 12].

Despite its regenerative potential, PRF in the form of a membrane, made by compressing the PRF clot using a metal lid or two layers of gauze to remove excess exudate while preserving the fibrin matrix and bioactive components, exhibits a limited functional capacity given an in vivo resorption period of approximately 10–14 days. A further modification of PRF involving heat compression, as described by *Kawase *et al., extends stability and application in guided tissue regeneration (GTR). Heat-compressed PRF has been reported to persist for at least three weeks post-implantation, whereas non-modified PRF undergoes complete degradation within two weeks [13].

In facial aesthetics and reconstructive surgery, plasma-based biomaterials have been extensively refined to address the rapid degradation of plasma-derived matrices. In this approach, platelet-poor plasma (PPP), predominantly composed of albumin (~ 60%), is subjected to controlled thermal denaturation at 75 °C for 10 min, resulting in a reorganized protein structure with enhanced stability and prolonged resorption over 4–6 months [14–16]. However, a significant limitation of heat-treated PRF/PPP lies in its reduced regenerative capacity due to the irreversible denaturation of cellular components and growth factors. To overcome this limitation, a modified approach, termed albumin platelet-rich fibrin (ALB-PRF), has been proposed, whereby the platelet-rich layer from the buffy coat is re-integrated into the heated PPP following cooling [14].

A significant challenge in regenerative procedures is the potential exposure of barrier membranes to oral microbiota, which can lead to bacterial colonization and compromise treatment outcomes [17]. Such contamination increases the rate of degradation in saliva, maximizes the risk of infection and impedes osseous regeneration, even in medically healthy individuals. Given the growing concerns over antimicrobial resistance (AMR) and hypersensitivity to conventional antibiotics, there is an increasing demand for alternative antimicrobial strategies in regenerative medicine [18]. As a result, the incorporation of inorganic antimicrobial agents into biomaterials has emerged as a promising approach to enhance their antibacterial properties and improve clinical outcomes. Among these, silver nanoparticles (SNP) have been extensively explored due to their biocompatibility, broad-spectrum antimicrobial activity and physicochemical stability [19]. Numerous studies have demonstrated their efficacy against a wide range of bacterial species, including Gram-negative and Gram-positive pathogens and multidrug-resistant strains. Additionally, SNPs have shown antifungal and antiviral properties, further broadening their clinical utility [20].

Various investigations have examined the composition, mechanical integrity and degradation kinetics of platelet-derived biomaterials, such as PRP, plasma rich in growth factors PRGF, advanced platelet-rich fibrin A-PRF and CGF [21]. Efforts to enhance their longevity have included the integration of albumin and the incorporation of SNPs into PRF matrices [22, 23]. However, no experimental studies have systematically evaluated the combination of silver nanoparticles with albumin-CGF to optimize its specific properties. A significant knowledge gap remains, therefore, regarding the histological and biological characteristics of albumin-CGF and its silver nanoparticle-enriched counterpart. This study seeks to provide novel insights into these biomaterials, elucidating their degradation profiles, histological characteristics, antimicrobial efficacy and growth factor release kinetics.

Study hypothesis

This study proposes that incorporating ALB and SNPs into CGF synergistically improves its longevity, sustains growth-factor release and enhances its antibacterial efficacy and histological characteristics compared with unmodified CGF. The research evaluates these parameters to determine whether such modifications provide a synergistic improvement in biological performance and degradation resistance. The null hypothesis states that no significant differences exist between CGF, ALB-CGF and ALB-CGF-SNP or that the inclusion of ALB and SNPs may not improve or even reduce these properties.

Methodology

Participant recruitment and eligibility

Sample size was determined using GPower software, with statistical parameters set at a power of 0.95, a significance level (α) of 0.05 and an effect size of 0.75, derived from initial experimental observations. Based on these calculations, fifteen participants were enrolled. Each participant completed a detailed medical history questionnaire structured using a standardized template. Ethical protocols were strictly followed to ensure voluntary participation and all individuals were screened based on predefined inclusion and exclusion criteria outlined in Appendix Table 1.Table 1. Average subtractive concentrations of four growth factors released from CGF, ALB-CGF and ALB-CGF-SNP over 1–60 days, all growth factors were analyzed using the Welch ANOVA followed by the Dunnett T3 post hoc test for both days 1 and 60, except for PDGF-AB, the same statistical analysis was applied for the time intervals of days 1, 7, and 14. The remaining time intervals for each growth factor, where the assumption of homogeneity of variance was met, were analyzed using one-way ANOVA followed by Tukey’s HSD post hoc testGroupGroup \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}$$\end{document} (CGF) N = 12Group \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}\mathbf{\rm I}$$\end{document} (Alb-CGF) N = 12Group \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} 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Participant consent

This study followed the ethical principles outlined in the Declaration of Helsinki (2013). Before blood collection, informed consent was obtained from all participants to ensure they had a clear understanding of the study’s objectives, significance and potential risks. Participants were provided with detailed information sheets and consent forms explaining all study aspects, including their right to withdraw at any stage without consequence. Blood donation records were reviewed to ensure compliance with established safety guidelines. Confidentiality was strictly maintained, with all data securely stored and scheduled for destruction upon study completion. Ethical approval was granted by Ulster University’s Research Ethics Committee (REC/23/0072) and the College of Medicine and Dentistry.

Preparation of CGF, ALB-CGF and ALB-CGF-SNP samples

Blood samples were collected at the Blood Laboratory within the Center for Molecular Biosciences, Human Intervention Studies Unit (HISU) at Ulster University. The study involved 15 healthy volunteers, each providing nine 9 mL tubes for subsequent processing. For CGF preparation, three 9 mL VACUETTE® Serum Clot Activator plastic tubes with red caps (Greiner Bio-One, Austria) were used. Additionally, six 9 mL VACUETTE® additive-free Serum plastic tubes with white caps (Greiner Bio-One, Austria) were allocated to prepare ALB-CGF and ALB-CGF-SNP. The methodology described here is consistent with that reported in the first publication of this research [24].

Centrifugation process and CGF preparation

The separation process involved two centrifugation cycles to ensure adequate sample processing. Initially, the three red-capped tubes and an additional tube filled with normal saline for balance were centrifuged, followed by the six white-capped tubes from each participant. Centrifugation (Medifuge MF200, Silfradent, Srl, Forli, Italy) was programmed for all samples as follows:

• Acceleration: 30 s
• 2 min at 2,700 rpm (500 g)
• 4 min at 2,400 rpm (400 g)
• 4 min at 2,700 rpm (500 g)
• 3 min at 3,000 rpm (600 g)
• Deceleration: 36 s

The total centrifugation duration was about 14 min, separating the blood into three distinct layers. These were: platelet-poor plasma (PPP) in the upper layer, concentrated growth factors (CGF) in the middle layer and red blood cells (RBCs) at the bottom [24, 25]. The CGF clot was carefully extracted from the RBC layer using sterile forceps and scissors, ensuring the buffy coat was retained to maximize the yield of white blood cells (WBCs) and platelets. The extracted CGF material was transferred to a sterile environment for further processing.

Preparation of ALB-CGF

Three white-capped tubes were processed for ALB-CGF preparation. Following centrifugation, 2.5 mL of PPP was withdrawn using a syringe fitted +- an 18G needle. The extracted plasma was then subjected to thermal denaturation at 75 °C for 10 min (APAG® system, Silfradent, Italy). The samples were stabilized by cooling in a water bath at 2–4 °C for 10 min. The buffy coat layer was combined with the denatured plasma, facilitating fibrin polymerization within 5 min and forming the ALB-CGF clot [14].

Preparation of ALB-CGF-SNP

Silver nanoparticles (SNPs) are commonly utilized in medical applications within a typical concentration range of 0.001% to 0.1% (w/w) and are approved by the United States Food and Drug Administration (FDA) for therapeutic applications [26]. For the ALB-CGF-SNP preparation, 1 mL of a SNPs suspension (0.2 mg/mL), prepared using silver nitrite, sodium borohydride and 1% polyvinyl alcohol) (PVA), was added to each tube before centrifugation. To ensure homogeneous distribution, the tubes were inverted up to 10 times and placed on a rotator for 1 min to facilitate thorough mixing. Following centrifugation, 2.5 mL of PPP was denatured following the same protocol as ALB-CGF. The buffy coat fraction was then collected using a syringe and mixed with the denatured PPP, enabling fibrin polymerization within 5 min and forming the ALB-CGF-SNP clot [23, 24].

To evaluate the biological and antibacterial efficacy of SNPs against Staphylococcus aureus ATCC 6538, a working dose of 0.02 mg/mL was prepared by diluting 1 mL of a 0.2 mg/mL suspension in 9 mL of whole blood. The findings of [27], who reported an MIC of 0.025 mg/mL and a zone of inhibition of 10.1 mm, are in line with this study and its methodology. The synthesized SNPs demonstrated a Z-average size of 32.12 nm, with a PDI of 0.115, indicating a uniform and monodisperse distribution, and a zeta potential of approximately −27 mV, confirming their electrostatic stability and low tendency for agglomeration. The choice of silver nanoparticles in this study is supported by their well-established biocompatibility and antimicrobial potential, comparable to other metallic nanoparticles widely utilized in biomedical and dental fields. Similar to the findings of [28], who justified the biomedical use of titanium nanoparticles for their non-cytotoxicity and surface stability, and [29], who highlighted the safe functionalization and biological performance of gold nanoparticles, the use of silver nanoparticles here is likewise rationalized by their stability, nanoscale uniformity, and suitability for incorporation within fibrin-based scaffolds for regenerative and antimicrobial applications. Similarly, [30] confirmed the efficacy, safety and biocompatibility of SNPs against RBCs and peripheral blood mononuclear cells (PBMCs), showing low cytotoxicity and strong compatibility with blood components. These combined results support the reliability of the selected dose and highlight the potential of SNPs as safe and versatile candidates for antibacterial biomaterials, including scaffolds, wound dressings and implant coatings.

Sample standardization and storage

To ensure consistency across all samples, weight standardization was conducted using a digital balance in a laminar flow cabinet, with each sample adjusted to 2.00 g using a sterile kit. The prepared samples were stored at −80 °C until further analysis. All procedures were conducted under sterile conditions, strictly adhering to manufacturer protocols to preserve sample integrity.

Growth factors quantification

Thirty-six samples across all groups (n = 12 per group: CGF, ALB-CGF and ALB-CGF-SNP) were analyzed for growth factors. Sample preparation was conducted in a laminar flow cabinet, after thawing and then incubated in 10 mL of Dulbecco’s Modified Eagle Medium DMEM (1X) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) without antibiotics or glucose to ensure a controlled environment for degradation assessment. The incubation was carried out under physiological conditions (37 °C, humidified atmosphere containing 5% CO₂).

The conditioned culture media were collected at 1, 7, 14, 30 and 60 days and stored at −80 °C for subsequent analysis. From each sample, 4 mL was aliquoted into four different 1.8 mL cryovials, with 1 mL in each, ensuring separate storage for each growth factor. Upon initiating the ELISA assay, the initial dilution assessment confirmed that no additional dilution was required, as the samples fell within the standard curve concentration.

Growth factors were quantified using uncoated ELISA kits (Elabscience Biotechnology Inc., Wuhan, China), including Human PDGF-AB, VEGF, TGF-β1 and EGF ELISA Kits. The assays were performed following the manufacturer’s instructions across four independent experiments. According to the protocol, the final optical density (OD) was measured at 450 nm (SpectraMax ABS Plus microplate reader, Molecular Devices, San Jose, CA, USA).

Degradation study and protein kit assay

Thirty-six samples from all CGF generations (n = 12 per group) were included in the degradation analysis. Thawed samples were weighed (2.00 g). The analysis was carried out in synchrony with the growth factor release experiment using the Bicinchoninic Acid (BCA) assay kit (KTD3001, Abbkine, Wuhan, China) with 10 mL of DMEM medium per sample. Samples were incubated at 37 °C in a humidified atmosphere containing 5% CO₂. At each interval (1, 7, 14, 30 and 60 days), the complete 10 mL of DMEM was removed and replaced with fresh medium. At each time interval, the protein measured reflected only what had been released during that specific period, as the entire medium was replaced and any previously released proteins were removed. This method provided a direct and time-specific indication of degradation activity, known as the subtractive technique. In contrast, an accumulative technique involves taking only a small portion of the medium (for example, 50–100 µL) at each interval and replenishing it with an equal volume of fresh medium. This allows proteins to gradually build up in the remaining medium, representing the total accumulated release over time rather than distinct stages of degradation. From each tube, 4 mL was allocated for growth factor analysis and 1 mL for BCA assessment. Aliquots were stored at −80 °C, thawed before analysis, centrifuged at 1000 RCF for 15 min at 2–8 °C to remove debris and diluted 15-fold for consistency with the standard curve. Protein degradation was then quantified by subtractive protein concentration at each time interval.

Scanning electron microscopy

CGF samples were fixed overnight at 4 °C in 2.5% glutaraldehyde solution (Sigma-Aldrich, St. Louis, MO, USA). Following fixation, each sample was cut carefully into sections for cross-sectional and surface imaging. The prepared sections were rinsed three times with phosphate-buffered saline (PBS) pH 7.4 (Oxoid Ltd., Basingstoke, Hampshire, UK), lasting 20 min. Samples then underwent a graded ethanol dehydration process using ethanol concentrations of 30%, 50%, 70%, 90%, 100% and 100% (Honeywell, Riedel-de Haën, Seelze, Germany), with 15-min incubation at each concentration. For further dehydration, hexamethyldisilazane (HMDS) (Sigma-Aldrich, St. Louis, MO, USA) was applied in a stepwise process, using the following ratios with ethanol: 50:50 (HMDS:ethanol) for 10 min, 10:90 (HMDS:ethanol) for 10 min, 100% HMDS for 10 min (twice). After complete dehydration, the samples were subjected to gold sputter coating before imaging.

SEM imaging was conducted using an Environmental Scanning Electron Microscope (ESEM), FEI Quanta™ 200 (FEI Company, Eindhoven, The Netherlands) under an accelerating voltage of 30 kV. Images were captured at magnifications of 100 ×, 800 ×, 3000 ×, 6000 ×, 12,000 × and 24,000 × for each sample, focusing on both surface and cross-sectional morphology to describe the key differences in fibrillar organization, porosity and cellular integration.

Antibacterial experiment

Staphylococcus aureus ATCC 6538 was used in this study and confirmed by 16S rRNA sequencing (GenBank accession numbers: DQ212950.1) and Gram stain. The strain was propagated in Tryptone Soya Broth (TSB) and Tryptone Soya Agar (TSA) (Oxoid Ltd., UK) and incubated overnight at 37 °C. Following incubation, 20 µL of the overnight culture was transferred into 20 mL of fresh TSB and incubated at 37 °C for 3 h. The optical density (OD) at 600 nm (Novaspec II Spectrophotometer, Pharmacia Biotech, Uppsala, Sweden) was measured and diluted to 0.1 OD, followed by a 100-fold dilution according to EUCAST guidelines.

Thirty-six samples from all groups (n = 12 per group) were standardized to 2.00 g. Plasma was separated and transferred to a sterile tube, while the remaining clot was minced using sterilized scissors. The plasma was then reintroduced into the clot, vortexed and 100 µL of each sample was mixed with 100 µL of the final diluted bacterial suspension. This preparation method was chosen to achieve a uniform distribution of cells, cytokines, chemokines, and growth factors, ensuring consistent exposure of bacterial cultures to the bioactive components of the CGF derivatives. Such homogenization allows a more accurate assessment of the intrinsic antibacterial potential, independent of surface variability. The experimental setup consisted of five groups: CGF, ALB-CGF and ALB-CGF-SNP, a negative control (S. aureus only) and a positive control (Methicillin at 2.5 µg/mL). Each condition was tested in triplicate with 12 replicates per sample type and sterility controls containing only TSB were included.

Samples were incubated and aliquots were taken at 0, 1, 4 and 24 h; serial dilutions were performed up to 10⁻⁸ after which 10 µL of each sample was spotted onto TSA plates for CFU/mL determination and bacterial counts were calculated using Eq. 1:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text{CFU per mL}=\frac{\text{number of colonies x dilution factor}}{\text{volume plated (mL)}}$$\end{document}

Bacterial growth was assessed across the experimental and control groups to determine the antibacterial efficacy of the tested samples.

S.aureus was selected for its clinical and experimental relevance. It adheres to titanium, is frequently isolated from peri-implant lesions and has been linked to implant failure and peri-implant infections [31–33] It is also implicated in oral biofilms, dentoalveolar and wound infections [34, 35] and cross-infections [36], while offering practical advantages in laboratory testing due to rapid propagation and reproducible CFU counts.

Statistical analysis

Data analysis was performed with GraphPad Prism 10 (Inc., La Jolla, CA, USA), using one-way ANOVA and Welch ANOVA to assess group differences (mean ± SD, P < 0.05). For large samples (> 30), parametric tests are suitable even with normality assumption violations according to the central limit theorem [37]. Kolmogorov–Smirnov confirmed normality in most data, while Bartlett’s test showed mixed homogeneity results. Both Welch ANOVA and one-way ANOVA were applied according to the outcome of Bartlett’s test for homogeneity of variance. When homogeneity was present, one-way ANOVA was conducted, followed by Tukey’s Honestly Significant Difference (HSD) test for post hoc comparisons. Where heterogeneity of variance was detected, Welch ANOVA was applied, with Dunnett’s T3 test used for multiple comparisons.

Results

Growth factor concentration

After testing the homogeneity of variances using Bartlett’s test, all growth factors were analyzed using the Welch ANOVA followed by the Dunnett T3 post hoc test for both days 1 and 60, except for PDGF-AB, the same statistical analysis was applied for the time intervals of days 1, 7, and 14. The remaining time intervals for each growth factor, where the assumption of homogeneity of variance was met, were analyzed using one-way ANOVA followed by Tukey’s HSD post hoc test. Growth factor release profiles showed distinct patterns, with CGF displaying a rapid burst release and the modified groups demonstrating a more gradual and sustained release. The release profile of PDGF-AB, VEGF, TGF-β1 and EGF demonstrated distinct yet interrelated trends across the different formulations. CGF exhibited the highest initial burst release of all growth factors on Day 1, with TGF-β1 peaking at 15,398 pg/mL, followed by PDGF-AB (4308 pg/mL), EGF (1972 pg/mL) and VEGF (896.5 pg/mL). In all cases, CGF significantly exceeded both ALB-CGF and ALB-CGF-SNP (P < 0.05 for VEGF and TGF-β1, P = 0.0001 for PDGF-AB and P < 0.01 for EGF), reinforcing its role in immediate growth factor availability. By Day 7, CGF remained the dominant formulation for PDGF-AB, whereas TGF-β1, VEGF and EGF levels exhibited no statistically significant differences among the groups (P > 0.05). This convergence suggests that TGF-β1, VEGF and EGF reach an earlier stabilization phase, whereas PDGF-AB continues to decline over a more extended period. By Day 14, a notable shift occurred, wherein ALB-CGF surpassed CGF in the release of VEGF (448.4 vs. 296.4 pg/mL, P = 0.004) and TGF-β1 (5800 vs. 3519 pg/mL, P = 0.004). However, EGF levels remained comparable between groups (P = 0.397), while PDGF-AB showed no significant difference (1180 vs. 947.6 pg/mL, P = 0.368). Throughout this period, ALB-CGF-SNP exhibited consistently lower release levels across all markers. By Day 30, ALB-CGF-SNP demonstrated the highest growth factor concentrations compared to ALB-CGF, with statistically significant differences (P < 0.001 for VEGF and EGF, P < 0.00001 for TGF-β1), whereas PDGF-AB levels remained statistically unchanged (P > 0.05). By Day 60, all growth factors had stabilized, with ALB-CGF-SNP exhibiting the highest residual concentrations, Albeit without significant differences among the formulations, as elucidated in Table 1 and Fig. 1.Fig. 1. Quantification of four growth factors released from CGF, ALB-CGF and ALB-CGF-SNP over 1–60 days, measured using ELISA assays with statistical significance as follows: ns (not significant, P > 0.05), * (P < 0.05), ** (P < 0.01), *** (P < 0.001) and **** (P < 0.0001)

Degradation of CGF generations

Following the evaluation of homogeneity of variance using Bartlett’s test the protein concentrations were analyzed using Welch ANOVA followed by the Dunnett T3 post hoc test at days 14, 30 and 60, while the remaining intervals where variance homogeneity was confirmed were analyzed using one-way ANOVA followed by Tukey’s HSD test. The protein degradation profile, as determined by BCA assay, demonstrated a clear inverse relationship between initial protein concentration and stability. Formulations with the highest initial protein levels underwent the most rapid degradation, reflecting their reduced structural integrity over time. CGF, which exhibited the highest initial protein content, had the steepest decline, whereas ALB-CGF and ALB-CGF-SNP displayed a more controlled degradation profile, retaining proteins for a longer duration.

At Day 1, degradation across the three groups was statistically significant (P < 0.001), with CGF exhibiting the highest degradation (18,941 µg/mL). However, there was no significant difference between ALB-CGF and ALB-CGF-SNP (P = 0.86), indicating that both modified formulations followed a similar degradation pattern at this early stage. By Day 7, the degradation process had become more pronounced across all groups (P < 0.001), with CGF experiencing the most substantial decline compared to its initial value. The statistical analysis revealed a significant difference between CGF and ALB-CGF-SNP (P < 0.001), whereas CGF and ALB-CGF (P = 0.06) and ALB-CGF and ALB-CGF-SNP (P = 0.45) did not exhibit statistically significant differences. This suggests that while all groups continued to degrade, ALB-CGF-SNP displayed the lowest initial degradation rate, possibly due to structural modifications enhancing protein retention. By Day 14, the degradation process appeared to stabilize across all groups (P = 0.10), with protein levels higher than those recorded on Day 7. This trend can be attributed to the subtractive nature of the assay, where degradation is measured based on clot breakdown rather than accumulation in the surrounding medium. The similarity in protein retention at this stage suggests that degradation rates were converging, reducing the disparities observed at earlier time points. The initial readings at Day 1 primarily represented the soluble plasma proteins already present within the scaffold. By Day 7, the measured proteins reflected those released through early degradation of the CGF fibrin matrix, while by Day 14, the higher values corresponded to the major degradation phase of the matrix, as supported by previous reports indicating that most CGF fibrin-based scaffold degradation and protein release occur after the second week of incubation.

As the degradation process continued, results on Day 30 revealed a widening disparity between the groups (P < 0.001). ALB-CGF retained the highest protein concentration (1,779 µg/mL), while ALB-CGF-SNP exhibited the lowest degradation rate, showing no significant difference from CGF (P = 0.94), which was nearly degraded by this stage. The sustained protein presence in ALB-CGF suggests a structural resistance to enzymatic breakdown, while ALB-CGF-SNP followed a similar but slightly accelerated degradation pattern compared to ALB-CGF. By Day 60, significant differences between the groups were observed (P < 0.001). CGF had undergone complete degradation, confirming its instability over time, whereas ALB-CGF (2,257 µg/mL, P < 0.001) and ALB-CGF-SNP (1,252 µg/mL, P < 0.001) continued to retain substantial protein levels. Although ALB-CGF-SNP exhibited the lowest degradation rate at this stage, its difference from ALB-CGF was not statistically significant (P = 0.11), as detailed in Table 2 and Fig. 2.Table 2. Mean values of subtractive protein concentration measured by the BCA assay during CGF, ALB-CGF and ALB-CGF-SNP degradation over 1–60 days were statistically analyzed using Welch ANOVA followed by the Dunnett T3 post hoc test at days 14, 30, and 60, while the remaining intervals were analyzed using one-way ANOVA followed by Tukey’s HSD testGroupGroup \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}$$\end{document} (CGF)N = 12Group \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}\mathbf{\rm I}$$\end{document} (ALB-CGF) N = 12Group \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} 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\usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}-\mathbf{\rm I}\mathbf{\rm I}$$\end{document} )P( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}-\mathbf{\rm I}\mathbf{\rm I}\mathbf{\rm I}$$\end{document} )P( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbf{\rm I}\mathbf{\rm I}-\mathbf{\rm I}\mathbf{\rm I}\mathbf{\rm I}$$\end{document} )Day 1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1894\pm 2183$$\end{document} [17554–20327] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10077\pm 1722$$\end{document} [8983–11171] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$9700\pm 1440$$\end{document} [8785–10614]10.04000.00000.00000.00000.8600Day 7 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4440\pm 1346$$\end{document} 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\usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7061\pm 733.5$$\end{document} [6595–7527] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$6711\pm 301.3$$\end{document} [6520–6903]3.39000.10000.11000.49000.3600Day 30 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$710.4\pm 597$$\end{document} [331.1–1090] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1779\pm 555$$\end{document} [1426–2131] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$802.\pm 231.8$$\end{document} [655.4–950]17.56000.00000.00000.94000.0000Day 60 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.00\pm 343.7$$\end{document} [−218.4–218.4] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2257\pm 1182$$\end{document} [1506–3009] \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1252\pm 1093$$\end{document} [557.2–1947]16.98000.00000.00000.00000.1100Fig. 2Degradation analysis of CGF, ALB-CGF and ALB-CGF-SNP over 1–60 days, assessed through protein quantification using the BCA protein assay kit

Structural assessment of CGF samples by SEM

Utilizing SEM, a morphological analysis was conducted on the surface and cross-sectional architectures of CGF, ALB-CGF and ALB-CGF-SNP formulations at incremental magnifications (100 ×, 800 ×, 3000 ×, 6000 ×, 12,000 × and 24,000 ×). This detailed visual exploration showed critical distinctions in the fibrillar arrangement, porosity and cellular incorporation (Fig. 3), highlighting profound implications on fibrin network integrity and its functional capacities for regenerative medicine.Fig. 3. Scanning Electron Microscopy (SEM) images illustrating the surface and cross-sectional structure of CGF, ALB-CGF and ALB-CGF-SNP samples, captured at magnifications of 100 ×, 800 ×, 3 k ×, 6 k ×, 12 k × and 24 k ×, corresponding to images A, B, C, D, E and F, respectively

CGF surface morphology exhibited a dense fibrin network, resembling a highly interconnected fiber mesh. These fibers were tightly arranged, manifesting as a continuous and robust scaffold indicative of superior structural integrity. The minimal porosity, illustrated by sparse micro-voids of enhanced mechanical resilience. Significantly, the CGF scaffold was characterized by substantial cellular integration, embedding an abundance of platelets, RBCs and WBCs, underscoring its biological robustness and potential for potent regenerative applications (Fig. 3).

In the cross-sectional view, CGF maintained a highly structured, dense arrangement with stratified fibrin layers reinforcing its mechanical stability. Cellular entrapment was prolific, notably abundant in platelets and RBCs, which suggests an optimized biological environment conducive to tissue healing and regeneration. In contrast, the ALB-CGF formulation, enriched with albumin, presented noticeable variations in fibrin architecture. SEM images revealed thinner fibrin strands, with an apparent reduction in packing density and enhanced porosity. This increase in structural openness, characterized by larger voids, ostensibly improved nutrient transport and facilitated cellular migration within the matrix. Platelet presence remained consistent, although RBC and WBC incorporation decreased significantly, suggesting an albumin-mediated modulation of the fibrin environment to curtail inflammation and potentially enhance regenerative properties. Cross-sectional analysis of ALB-CGF further reinforced these observations, revealing a heterogeneous fibrillar organization with enhanced permeability due to increased internal porosity (Fig. 3). This architecture likely fostered superior biological exchange and cellular infiltration, underscoring a functional improvement over traditional CGF in specific regenerative contexts.

The ALB-CGF-SNP samples exhibited a porous and irregular fibrin network with loosely arranged, thinner fibers interspersed among denatured albumin fragments. Numerous silver nanoparticles were visible along the fibrin strands, imparting a fine granular texture and influencing the overall conformation of the matrix. SEM revealed embedded cellular components, including RBC, WBC and platelets, mainly located near nanoparticle-coated areas, suggesting maintained biocompatibility at the lower FDA-recommended concentration. Cross-sectional views confirmed a porous internal architecture with fragmented fibrin-albumin layers and sparse but evident cellular remnants. These observations indicate that SNPs incorporation modified the ultrastructure towards enhanced permeability and antimicrobial potential while preserving acceptable biocompatibility. These SEM insights distinctly elucidate the functional and structural versatility across CGF, ALB-CGF and ALB-CGF-SNP formulations, underpinning their respective regenerative capabilities and clinical applicability in advanced tissue engineering strategies.

Mean bacterial growth over time

Following the assessment of variance homogeneity using Bartlett’s test, the data met the assumption of equal variances; therefore, statistical analysis was performed using one-way ANOVA followed by Tukey’s HSD post hoc test. The antibacterial activity of CGF, ALB-CGF and ALB-CGF-SNP was assessed over four time intervals (0, 1, 4 and 24 h) to evaluate effectiveness against S. aureus ATCC 6538. The results were statistically analyzed against the negative control (S. aureus group) and methicillin as a positive control to determine their inhibitory potential, as elaborated in Table 3 and Fig. 4. At 0 h, there were no statistically significant differences among the groups (P = 0.819), confirming a uniform bacterial load across all conditions, ensuring comparability in subsequent analyses. By 1 h, methicillin exhibited a significant bacterial reduction (3.52 × 10^5^ CFU/mL, P < 0.0001 vs. negative control), confirming its early bactericidal effect. Among the CGF-based formulations, no statistically significant difference was observed when comparing ALB-CGF and ALB-CGF-SNP (P > 0.05). However, when compared with CGF, a statistically significant difference was noted (P = 0.020). While CGF, ALB-CGF and ALB-CGF-SNP demonstrated substantial reductions compared to the negative control (P < 0.05 for all CGF groups), no significant difference was observed among the CGF-based formulations themselves (P > 0.05). At 4 h, bacterial suppression became more pronounced, with the negative control group exhibiting a significantly higher bacterial count (1.17 × 10⁹ CFU/mL) compared to all treated groups (P < 0.0001). However, no statistically significant difference was observed among CGF-based formulations (P > 0.05 for all comparisons), indicating similar inhibitory effects across these groups. Among them, ALB-CGF-SNP exhibited the highest bacterial inhibition (3.96 × 10⁷ CFU/mL, P = 0.0001 vs. negative control). Methicillin maintained near-complete bacterial suppression (3.97 × 10^3^ CFU/mL, P < 0.0001 vs. negative control group), while no significant difference was found between methicillin and the CGF-based groups (P > 0.05). By 24 h, the negative control group displayed extensive bacterial proliferation (1.91 × 10^1^⁰ CFU/mL), significantly higher than all treated groups (P < 0.0001). Among the CGF-based formulations, ALB-CGF-SNP exhibited the most pronounced bacterial suppression (3.33 × 10⁹ CFU/mL), followed by CGF (5.38 × 10⁹ CFU/mL) and ALB-CGF (7.35 × 10⁹ CFU/mL). However, no significant differences were observed among the CGF-based groups (P > 0.05). Methicillin achieved complete bacterial clearance (P < 0.0001 vs. negative control group), while no difference was detected when compared to CGF and ALB-CGF-SNP (P > 0.05). The only statistically significant difference observed was between methicillin and ALB-CGF (P = 0.029).Table 3Staphylococcus aureus average propagation and Post-hoc comparison over 0–24 h in the presence of CGF, ALB-CGF and ALB-CGF-SNP, with Staphylococcus aureus as the negative control and methicillin as the Positive control. Data were analyzed using one-way ANOVA followed by Tukey’s HSD post hoc test for all time intervalsGroupGroup I S.A + CGF N = 12Group II S.A + ALB-CGF N = 12Group III S.A + ALB-CGF-SNP N = 12Group IV S.AUREUS N = 12Group V Methicillin N = 12Parameter \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\boldsymbol{m}}{\boldsymbol{e}}{\boldsymbol{a}}{\boldsymbol{n}}\pm {\boldsymbol{S}}{\boldsymbol{D}}$$\end{document} (CFU/mL)95%CI \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\boldsymbol{m}}{\boldsymbol{e}}{\boldsymbol{a}}{\boldsymbol{n}}\pm {\boldsymbol{S}}{\boldsymbol{D}}$$\end{document} (CFU/mL)95%CI \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\boldsymbol{m}}{\boldsymbol{e}}{\boldsymbol{a}}{\boldsymbol{n}}\pm \boldsymbol{ }\boldsymbol{ }\boldsymbol{ }\boldsymbol{ }\boldsymbol{ }\boldsymbol{ }\boldsymbol{ }{\boldsymbol{S}}{\boldsymbol{D}}$$\end{document} (CFU/mL)95%CI \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\boldsymbol{m}}{\boldsymbol{e}}{\boldsymbol{a}}{\boldsymbol{n}}\pm {\boldsymbol{S}}{\boldsymbol{D}}$$\end{document} (CFU/mL)95%CI \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\boldsymbol{m}}{\boldsymbol{e}}{\boldsymbol{a}}{\boldsymbol{n}}\pm {\boldsymbol{S}}{\boldsymbol{D}}$$\end{document} (CFU/mL)95%CI0 h480275±137491[392918–567633]459720± 131498[376170543270]449443± 117153[375007–5523878]514997± 184250[397930–632064]463052± 140419[373834–552270]1 h859441±363282[628622–1090259]791108± 349481[569059–1013158]656664±175176[545362–767965]1320552±437302[1042704–1598401]351944± 541696[7767–696121]4 h62861050±66743489[20454260–105267840]77333200±62753693[37461405–117204995]39638700±41636927[13183859–66093541]1177220333±1176576751[429659131–1924781536]3972± 3122[1989–5956]24 h5380822167±6306577834[1373813780–9387830553]7352758333±664149179[3132955768–11572560898]3339429000±4307376398[6026526056076205395]19141635833±8605036968[1367425618524609015481]0.00TimeFP- ANOVAMultiple comparisons testP (I-II)P (I-III)P (I-IV)P (I-V)P (II-III)P (II-IV)P (II-V)P (III-IV)P (III-V)P (IV-V)0 h0.38100.81900.99700.98500.97600.99801.00000.88000.99900.79800.99900.90201 h9.66500.00010.99300.71300.04300.02000.91700.01400.06100.00100.32800.00004 h11.07000.00010.99900.99900.00010.99800.99900.00010.99600.00010.99900.000124 h18.07000.00010.92600.91600.00010.18800.47000.00010.02900.00010.64500.0001Fig. 4Mean growth of Staphylococcus aureus in the presence of CGF, ALB-CGF and ALB-CGF-SNP over 0–24 h, with Staphylococcus aureus as the negative control and methicillin as the positive control with statistical significance as the follows: ns (not significant, P > 0.05), * (P < 0.05), ** (P < 0.01), *** (P < 0.001) and **** (P < 0.0001).

Discussion

CGF is widely used in regenerative medicine and dentistry, but its rapid degradation limits longevity. Albumin modification (ALB-CGF) enhances stability, while inclusion of silver nanoparticles (ALB-CGF-SNP) improves antimicrobial properties. This study examined the release profiles of key regenerative growth factors PDGF-AB, VEGF, TGF-β1 and EGF from three types of CGF. The observed release kinetics correspond with the inherent biochemical properties of these growth factors and their interactions with biomaterial matrices. A notable initial burst release was identified in unmodified CGF within the first week. In contrast, ALB-CGF exhibited a peak in growth factor release at two weeks, although at a lower magnitude than CGF. The most sustained release was observed in ALB-CGF-SNP, where growth factor levels remained elevated for up to one month. This prolonged release suggests enhanced structural stability, enabling a gradual and extended release of growth factors, which is particularly advantageous for regenerative applications requiring long-term bioactivity.

Research on growth factors and their applications in regenerative medicine and dentistry has explored platelet concentrates and their therapeutic potential. A study by *Calabriso *et al., focused on the angiogenic properties of CGF-derived soluble factors, including VEGF, TGF-β1, MMP-9 and MMP-2. The findings demonstrated the ability of CGF to stimulate endothelial cell migration, tubule formation and angiogenic mediator expression. Furthermore, CGF-derived cells exhibited characteristics similar to endothelial progenitor cells, underscoring their potential role in vasculogenesis and tissue regeneration [38]. However, this study did not investigate the effects of additive materials such as albumin or nanoparticles, focusing exclusively on CGF in its native form.

A related study by *Fujioka-Kobayashi *et al., examined ALB-PRF, a composite of autologous albumin gel and liquid platelet-rich fibrin, demonstrating a gradual release of seven growth factors over ten days, with a particular emphasis on TGF-β1 and PDGF-AA/AB. The study reported enhanced cell compatibility within 24 h and increased fibroblast proliferation at five days compared to a control. Additionally, a significant increase in TGF-β and collagen I mRNA expression was observed at three and seven days, indicating a potential role in tissue regeneration [39]. These findings suggest that the slow degradation of albumin gel prolongs growth factor release, highlighting its clinical potential and the need for further in vivo studies on degradation properties.

The integration of albumin into CGF (ALB-CGF) substantially altered the release dynamics, extending the bioavailability of growth factors, particularly evident on Day 14. This sustained release is likely attributed to albumin’s controlled thermal denaturation, which generates a structured fibrillar network, modulating the release kinetics. These findings align with those reported by *Gheno *et al., who demonstrated similar sustained release patterns in albumin-enriched PRF formulations [40]. Additionally, *Mourão *et al., described ALB-CGF membranes as structurally stable, moldable and capable of sustaining growth factor release over seven days, supporting their applicability in guided tissue regeneration [14].

Incorporating silver nanoparticles into ALB-CGF-SNP modified the release profile, delaying peak concentrations and extending growth factor availability for up to 30 days. This modulation is due to physicochemical interactions between nanoparticles and the fibrin network, a mechanism that has been extensively documented in nanoparticle-based drug delivery systems. These findings are consistent with recent research by *de Lima Barbosa *et al., who investigated nanostructured carbonated hydroxyapatite combined with denatured albumin and PRF. Their results indicated that the addition of nanocarboapatite microspheres reduced the initial biological activity of ALB-PRF, resulting in a delayed growth factor release and altered osteoblast behavior, findings comparable to those in the present study beyond two weeks [41]. However, unlike the current investigation, their study did not involve silver nanoparticles, nor did it extend the observation period beyond 21 days.

*Salih *et al., evaluated the role of platelet-rich fibrin matrix (PRFM) combined with SNPs in enhancing bone healing in a rabbit fracture model. The results showed that the group treated with both PRFM and SNPs demonstrated faster bridging of the bone gap and more mature histological bone formation compared to groups receiving either treatment alone [42]. These findings support the additive or potentially synergistic effect of combining platelet-based biomaterials with silver nanoparticles.

Although the incorporation of SNPs and albumin resulted in a lower immune cell population compared with the traditional CGF membrane, the modified ALB-CGF-SNP still provides superior biological potential relative to non-autologous collagen membranes. The study by *Kumar *et al., compared PRF membranes with collagen in guided tissue regeneration and demonstrated that PRF offered markedly superior biological performance, releasing higher levels of TGF-β1, PDGF-BB, and VEGF over 14 days, and promoting significantly greater fibroblast migration. While collagen membranes ensured structural stability, they lacked the bioactive and immunomodulatory components intrinsic to autologous platelet concentrates [43]. In contrast, the present study explored a modified CGF matrix enriched with albumin and SNPs, aiming not only to sustain growth factor release but also to enhance scaffold durability and antimicrobial performance. Despite the modest reduction in leukocyte content, the ALB-CGF-SNP membrane preserved key regenerative mediators and demonstrated extended degradation resistance, suggesting improved longevity and handling compared with earlier generations. Moreover, its antibacterial efficacy, together with the biocompatibility profile reported in *Kazi *et al., for biosynthesized calcium oxide nanoparticles [44], supports the clinical potential of ALB-CGF-SNP as a safe, autologous, and multifunctional biomaterial for tissue regeneration as confirmed by [30] regarding the safety and biocompatibility of SNPs with blood cells.

The degradation characteristics of current biomaterials offer valuable insights into their stability and clinical applicability. CGF demonstrated a high initial protein concentration, as determined by the BCA assay, indicating a rapid degradation phase within the first two weeks. This aligns with previous findings by Isobe et al., who reported similar degradation rates in CGF and A-PRF, with no significant delay observed [45]. However, their study did not explore the impact of SNPs incorporation on degradation resistance. *Zheng *et al., investigated heat-treated PRF gels' mechanical and degradation properties and observed that thermal treatment effectively prolonged degradation without compromising cellular viability [46]. Although the rapid degradation of CGF may limit its effectiveness as a long-term barrier membrane, it remains suitable for applications requiring short-term regenerative effects. In contrast, ALB-CGF and ALB-CGF-SNP exhibited extended structural integrity during 60 days, underscoring their potential for long-term tissue regeneration. *Khorshidi *et al., demonstrated that L-PRF membranes modified with SNPs exhibited superior tensile strength and antibacterial properties, highlighting SNP’s potential to enhance both structural and functional characteristics of platelet-rich fibrin membranes [23]. While incorporating SNPs in the present study did not significantly enhance the tensile strength of CGF due to the concurrent presence of albumin, it effectively delayed degradation. This finding aligns with observations on the stabilizing role of SNP. Conventional PRF resorbs within two to three weeks, which limits its ability to act as a reliable barrier during the critical phases of healing. By contrast, ALB-PRF demonstrates an extended resorption profile, lasting 4–6 months and thereby ensuring longer protection and stability. *Fujioka-Kobayashi *et al., highlighted that titanium mesh exposure occurs in almost 50% of augmentation cases and represents a major complication. Such exposure leads to wound breakdown, direct communication with the oral cavity, bacterial contamination, and ultimately compromised regenerative outcomes. They recommended the use of ALB-PRF to cover titanium mesh in order to reduce these risks, since its prolonged stability can help to prevent exposure and contamination. The prolonged degradation profile of ALB-CGF and ALB-CGF-SNP suggests its suitability for applications requiring sustained scaffold presence [39]. Furthermore, for ethical and religious considerations, the use of autologous membranes is preferred over xenogenic collagen membranes derived from bovine or porcine sources, thereby avoiding materials of animal origin while maintaining full biocompatibility and regenerative efficacy. Similarly, *Gheno *et al., reported increased degradation resistance in albumin-modified PRF membranes, emphasizing the protective function of albumin in reducing enzymatic breakdown [40].

Regarding the potential impact on tissue phenotype compared to connective tissue grafts (CTG), *Houshmand *et al., demonstrated that activated plasma albumin gel undergoes substantial biodegradation within 21 days, as evidenced by SEM imaging and weight loss analysis. The observed reduction in structural integrity suggests a relatively high degradation rate. Consequently, the study recommends the use of thicker membranes than conventional CTG thickness to compensate for biodegradation and ensure long-term stability in soft tissue regeneration [47]. Additionally, *Wu *et al., examined the effects of thermal manipulation on H-PRF membranes and found that increasing the temperature above 90 °C enhanced mechanical strength and degradation resistance. However, excessive heating at 105 °C significantly reduced cell viability and impaired osteoblast proliferation. These findings indicate that while thermal modification can improve membrane stability, precise temperature control is essential to maintain biological functionality [48]. Comparing these findings with the present study underscores the importance of achieving a balance between structural reinforcement and bioactivity in regenerative applications. However, existing literature does not explicitly address the effects of albumin incorporation and potential denaturation under thermal conditions. Recent research by *Alshirah *et al., demonstrated that the combination of albumin and silver nanoparticles in CGF membranes further enhanced degradation resistance, as measured through weight loss calculations over time, reinforcing these observations [24].

The apparent detection of residual growth factors at Day 60 can be attributed to the difference in assay sensitivity, measurement units, and decimal precision between the two analytical techniques. The BCA assay quantified total protein concentration in micrograms (µg/mL), where mean values were recorded to two decimal places, reflecting the overall protein mass that approached zero after complete CGF degradation. In contrast, the ELISA assay measured specific growth factors in picograms (pg/mL), with values recorded to three digits, indicating far greater analytical sensitivity and precision. Therefore, the minimal residual readings observed at Day 60 represent trace amounts of soluble growth factors detectable only due to ELISA’s higher resolution and extended decimal registration, rather than any continued protein presence or active release from the degraded scaffold.

Structural analysis using SEM provided critical evidence supporting the observed degradation and biological characteristics. CGF exhibited a dense fibrillar network, indicating its mechanical resilience and regenerative potential. This structural organization aligns with its function in the initial phases of wound healing, where rapid clot stabilization and cellular adhesion play a crucial role. In contrast, ALB-CGF displayed a more porous fibrin architecture, facilitating enhanced cellular infiltration and nutrient diffusion, key factors for sustained tissue regeneration. Notably, ALB-CGF-SNP demonstrated a distinctive shift in fibrin morphology, characterized by irregular fibrillar arrangements and increased porosity. These structural modifications may enhance the diffusion of bioactive molecules and contribute to antimicrobial activity, potentially reducing bacterial colonization and improving wound healing outcomes. *Stanca *et al., described a dense fibrin network externally, with few corpuscular elements, while the inner surface contained activated platelets and a high cellular presence. The findings from SEM analysis corroborate these observations, particularly in highlighting platelet distribution and fibrin organization, reinforcing CGF’s role in growth factor release and its regenerative applications [49].

Barbosa et a,l examined the structural integrity of ALB-PRF membranes incorporating nano-carbonated hydroxyapatite (ncHA) microspheres. Their study demonstrated that these membranes maintain a dense fibrin network with structural stability over 21 days. In the present study involving CGF, albumin and silver nanoparticles, structural robustness was also evident [41]. However, unlike *Barbosa *et al., who utilized ncHA particles, this study focused on silver nanoparticles, which may have distinct effects on fibrin porosity and bioactivity. This comparison highlights the significance of particle composition in determining the structural and functional properties of biomaterials.

*Simões-Pedro *et al., utilized SEM analysis to compare the fibrin architecture of L-PRF, A-PRF and A-PRF +, identifying key differences in fiber orientation, porosity and cellular distribution. A highly compact matrix characterized L-PRF, whereas A-PRF and A-PRF + exhibited elongated fibers and increased porosity, which facilitated platelet adhesion and vascularization [50]. In contrast, the present study specifically investigated adding silver nanoparticles to CGF, an approach for which direct SEM comparisons are lacking in existing literature. This underscores the novelty of this investigation, particularly in evaluating how nanoparticle interactions influence fibrin architecture and bioactivity.

The SEM analysis indicated a reduction in the cellular content of ALB-CGF-SNP, including platelets, red blood cells (RBCs) and white blood cells (WBCs). This observation is consistent with our earlier findings reported by [24], where the cellular composition of different CGF generations was quantitatively assessed using a hematology analyser (Sysmex machine). That study demonstrated a lower leukocyte concentration compared with whole blood, while platelet levels remained comparable, highlighting that CGF membranes retain a minimum but functionally relevant cellular profile. Although the overall cellular content is reduced, the fibrin matrix preserves its ability to entrap and gradually release bioactive molecules. In the present work, the release kinetics revealed an extended peak of growth factor activity, 30 days for ALB-CGF-SNP and 14 days for ALB-CGF, contrasting with only the first 7 days for CGF, thereby confirming prolonged biological efficacy. This sustained release aligns with the PASS principle: Primary closure, Angiogenesis, Stability of the clot and Space maintenance [51]. with angiogenesis recognized as a central driver of bone regeneration. Moreover, even in the absence of enriched leukocyte content, gradual release of VEGF, PDGF and TGF-β is sufficient to support vascular ingrowth and healing [52]. Taken together, these findings suggest that the combination of structural stability, antibacterial potential and extended growth factor release makes ALB-CGF-SNP an attractive candidate for use as a barrier membrane in guided bone regeneration (GBR) and guided tissue regeneration (GTR).

The antibacterial properties of these biomaterial formulations are of considerable clinical relevance. Among them, ALB-CGF-SNP exhibited the most potent antibacterial activity against S. aureus, further substantiating the well-established antimicrobial potential of silver nanoparticles. *Alauddin *et al., conducted an in vitro investigation to assess the antibacterial efficacy of Concentrated Growth Factor (CGF) against S. aureus and Streptococcus mutans. Using blood samples obtained from a healthy donor, the study employed a specialized centrifugation protocol to prepare CGF, followed by antibacterial evaluation through multiple assays, including the agar diffusion method for inhibition zones, broth microdilution to determine the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) and crystal violet assays for biofilm quantification. Chlorhexidine (0.12%) was used as a positive control [53].

While all CGF-based formulations exhibited inherent antibacterial properties, likely attributable to platelet-derived antimicrobial peptides, presence of leukocytes, cytokines and chemokines, the sustained bacterial inhibition observed in ALB-CGF-SNP suggests an additional benefit in mitigating postoperative infection risks. Although ALB-CGF-SNP demonstrated a clear numerical trend toward greater antibacterial inhibition, no statistically significant difference was observed among the CGF-based generations after 24 h. This indicates that the antibacterial efficacy of all CGF-derived membranes was comparable, suggesting that the inherent antibacterial activity of CGF and ALB-CGF, primarily attributed to leukocytes, cytokines, and chemokines, remains substantial. The inclusion of SNPs provided a measurable but not statistically separable enhancement under the applied experimental conditions. *Mariani *et al., explored the potential mechanisms underlying this antibacterial activity by examining the presence of microbicidal proteins released from platelet concentrates. Cytokines and chemokines such as Macrophage Inflammatory Protein-1 alpha (MIP-1α), Regulated upon Activation, Normal T-cell Expressed and Secreted (RANTES), Growth-Regulated Alpha Protein (GRO-α), Interleukin-8 (IL-8), Neutrophil-Activating Peptide 2 (NAP-2), Stromal Cell-Derived Factor 1 alpha (SDF-1α), and Interleukin-6 (IL-6) were identified as potential contributors to the observed bacterial inhibition. These mediators play key roles in modulating immune cell recruitment and inflammatory response, suggesting that the antimicrobial efficacy of platelet-rich preparations may result from the synergistic action of cytokines, chemokines, and leukocytes, rather than being solely dependent on cellular concentration or preservation state [54].

*Feng *et al., compared the antibacterial efficacy of platelet-rich fibrin (PRF) prepared via horizontal centrifugation (H-PRF) and leukocyte- and platelet-rich fibrin (L-PRF) against S. aureus and Escherichia coli by in vitro conditions. Blood samples from eight donors were utilized for PRF preparation and the study aimed to correlate antibacterial effects with immune cell concentrations. H-PRF, which contained a higher leukocyte count, demonstrated superior antibacterial activity compared to L-PRF. Antimicrobial effects were assessed through inhibition zone measurements and plate-counting techniques, with findings indicating that wet PRF exhibited greater antibacterial activity than its solid counterpart. The study underscored the role of immune cell content in modulating the antimicrobial properties of PRF [55].

*Jasmine *et al., further proposed that injectable PRF (i-PRF) exhibits potential antimicrobial activity against biofilm-producing Staphylococcus species associated with oral infections [56]. However, limitations related to sample size and exclusion criteria were noted and the study recommended further investigations with larger cohorts to ensure comprehensive evaluation.

*Haddadi *et al., compared the anti-biofilm efficacy of conventional L-PRF and silver nanoparticle-modified L-PRF (AgNP-L-PRF) against Candida and Streptococcus species. Using blood samples from 18 healthy volunteers, L-PRF and AgNP-L-PRF membranes were prepared via centrifugation and biofilm formation was assessed using an ELISA reader. Both membranes inhibited Candida Albicans and C. parapsilosis biofilms, though effects against C. glabrata and Streptococcus mitis were less pronounced. Higher silver nanoparticle concentrations (10–20 mg/mL) enhanced biofilm suppression [57].

Previous studies have demonstrated that SNPs exhibit enhanced antibacterial efficacy primarily through multiple synergistic mechanisms. These include the release of silver ions, which disrupt bacterial cell membranes, interfere with DNA replication and induce oxidative stress leading to bacterial apoptosis. Furthermore, SNPs contribute to physical disruption by inhibiting bacterial adhesion and biofilm formation on fibrin matrices, thereby preventing microbial colonization and proliferation [58, 59]. These combined antibacterial mechanisms likely explain the observed enhanced antimicrobial properties of ALB-CGF-SNP membranes.

The sustained antibacterial efficacy observed in ALB-CGF-SNP suggests its potential as a viable alternative to conventional antibiotic-dependent infection control strategies, particularly in implantology and periodontal therapy, where infection management is crucial. The findings of this study hold significant clinical implications. While unmodified CGF remains a suitable option for applications requiring immediate regenerative effects, such as post-extraction healing and early implant integration, the enhanced release profile and structural resilience of ALB-CGF make it more appropriate for medium-term regenerative applications, including soft tissue augmentation and guided bone regeneration. The extended stability and antibacterial properties of ALB-CGF-SNP further suggest its applicability in high-risk cases requiring prolonged regenerative support and infection control, such as peri-implant defect management and sinus augmentation procedures. These findings align with the increasing focus on biomaterial modifications to optimize regenerative capacity and antimicrobial defense.

The broader clinical landscape and research agenda are well synthesized by *Miron *et al. Their review charts three decades of APCs optimization, from anticoagulant-free tubes and refined centrifugation (including horizontal paradigms and C-PRF) to the pivotal “Bio-Heat” protocol that denatures albumin to create an extended PRF (e-PRF) with resorption prolonged from 2–3 weeks to 4–6 months. Crucially, the authors assemble evidence for applications not only within dentistry, recession coverage, extraction-site management, lateral-window closure in sinus grafting and soft-tissue healing around implants, but also across medicine: chronic wounds (including diabetic ulcers), joint pain and cartilage degeneration in sports medicine and aesthetic medicine for skin rejuvenation, scar management and hair restoration. They also identify clear gaps: standardizing heating parameters; delivering well-designed, adequately powered RCTs with long follow-up; benchmarking against xenogeneic membranes; and exploiting APCs as carriers for exosomes, antibiotics and other small biomolecules. ALB-CGF and ALB-CGF-SNP sit naturally in that trajectory: they retain the albumin-driven extension of scaffold life while adding targeted antimicrobial function and, potentially, favorable immunomodulation. The evidence to date supports these materials as credible next-generation, autologous options for guided bone regeneration (including mesh-exposure-prone cases), periodontal plastic surgery (as connective-tissue-graft substitutes), sinus augmentation, facial aesthetics and dermatology (including UV-related photoaging and hair applications), sports and skeletal medicine and chronic wound care in diabetic contexts. The next step is disciplined translation: protocol optimizations (heating time, temperature, albumin ratio, nanoparticle loading and provenance), rigorous in-vivo validation across oral and extra-oral indications, and comparative trials against incumbent standards to confirm durability, safety and superior patient-centered outcomes [60].

Beyond the oral surgery applications, clinical arenas show immediate translational promise. Aesthetics and dermatology: *Zhang *et al., demonstrated that CGF counters ultraviolet (UVA)-induced photoaging in human dermal fibroblasts (HDFs) by modulating the mitogen-activated protein kinase (MAPK)/activator protein-1 pathway, providing mechanistic grounds for anti-ageing effects [61]. Clinically, *Tang *et al., combined CGF with autologous fat to treat alopecia after hyaluronic-acid filler complications and observed improved follicular regeneration [62]. Taken together, these data warrant development of ALB-CGF and ALB-CGF-SNP as autologous injectable fillers that marry volumetric correction with biological rejuvenation, with the extended resorption profile expected to curb the rapid volume loss that limits conventional liquid PRF applications.

Future research should focus on validating these findings through in vitro studies to investigate further cellular viability, growth factor release and cytokine expression. Additionally, broader bacterial strain testing, including Gram-negative and anaerobic bacteria, would provide a more comprehensive understanding of the antimicrobial spectrum. Long-term in vivo studies evaluating the clinical efficacy of ALB-CGF and ALB-CGF-SNP in various regenerative applications would be instrumental in determining their real-world performance. Further investigations into the concentration-dependent effects of silver nanoparticles cytotoxicity and biocompatibility on cellular responses and immune modulation are warranted to optimize their integration into clinical practice. Moreover, exploring biofilm resistance mechanisms across a broader range of bacterial species would contribute to a more thorough understanding of the full antimicrobial potential of these biomaterials.

Conclusion

This study highlights the distinct regenerative potential of ALB-CGF-SNP, which exhibits a controlled and prolonged release of growth factors, extended degradation resistance and strong antibacterial properties, making it fundamentally different from CGF. Unlike CGF, which degrades rapidly and releases growth factors in an initial burst, ALB-CGF-SNP maintains prolonged bioactivity, supporting long-term tissue regeneration. ALB-CGF, on the other hand, demonstrates enhanced structural stability due to albumin’s role in modulating fibrin architecture and growth factor retention, offering benefits for medium-term applications. SEM analysis confirmed these structural adaptations, reinforcing the impact of albumin and silver nanoparticles in regulating degradation and antibacterial effects. Although ALB-CGF-SNP demonstrated a clear numerical trend toward higher antibacterial inhibition, no significant difference was observed among the CGF-based groups after 24 h. This indicates that the antibacterial efficacy of all CGF-derived membranes was comparable, with the inherent antibacterial properties of CGF and ALB-CGF primarily attributed to the presence of leukocytes, cytokines and chemokines. The inclusion of SNPs contributed to a measurable yet not statistically separable enhancement under the current experimental conditions. While CGF remains suitable for immediate healing, ALB-CGF and ALB-CGF-SNP provide sustained regenerative benefits, particularly in complex cases requiring scaffold longevity and infection control. Future in vivo studies should further evaluate their clinical efficacy, optimizing nanoparticle integration and exploring broader antimicrobial applications. In addition, future research should include systematic evaluation of cytotoxicity, assessment of alternative concentrations of silver nanoparticles and incorporation of biologically derived or green-synthesised nanoparticles. Complementary studies should also focus on cell viability assays, extended in vitro and in vivo experimentation, as well as preclinical and clinical investigations to fully establish the translational potential of these biomaterials.

Supplementary Information

Supplementary Material 1.