Development of pH-responsive Eudragit S100-functionalized silk fibroin nanoparticles as a prospective drug delivery system.

Silk fibroin nanoparticles (FNP) have been increasingly investigated in biomedical fields due to their biocompatibility and biodegradability properties. To widen the FNP versatility and applications, and to control the drug release from the FNP, this study developed the Eudragit S100-functionalized FNP (ES100-FNP) as a pH-responsive drug delivery system, by two distinct methods of co-condensation and adsorption, employing the zwitterionic furosemide as a model drug. The particles were characterized by sizes and zeta potentials (DLS method), morphology (electron microscopy), drug entrapment efficiency and release profiles (UV-Vis spectroscopy), and chemical structures (FT-IR, XRD, and DSC). The ES100-FNP possessed nano-sizes of ∼200-350 nm, zeta potentials of ∼ -20 mV, silk-II structures, enhanced thermo-stability, non-cytotoxic to the erythrocytes, and drug entrapment efficiencies of 30%-60%, dependent on the formulation processes. Interestingly, the co-condensation method yielded the smooth spherical particles, whereas the adsorption method resulted in durian-shaped ones due to furosemide re-crystallization. The ES100-FNP adsorbed furosemide via physical adsorption, followed Langmuir model and pseudo-second-order kinetics. In the simulated oral condition, the particles could protect the drug in the stomach (pH 1.2), and gradually released the drug in the intestine (pH 6.8). Remarkably, in different pH conditions of 6.8, 9.5, and 12, the ES100-FNP could control the furosemide release rates depending on the formulation methods. The ES100-FNP made by the co-condensation method was mainly controlled by the swelling and corrosion process of ES100, and followed the Korsmeyer-Peppas non-Fickian transport mechanism. Whereas, the ES100-FNP made by the adsorption method showed constant release rates, followed the zero-order kinetics, due to the gradual furosemide dissolution in the media. Conclusively, the ES100-FNP demonstrated high versatility as a pH-responsive drug delivery system for biomedical applications.

Silk nanoparticles for the protection and delivery of guava leaf (Psidium guajava L.) extract for cosmetic industry, a new approach for an old herb.

Guava (Psidium guajava L.) is a well-known plant containing high levels of natural antioxidants, the phenolic compounds, which have been employed in numerous cosmetic products. However, these molecules are unstable to oxidants, light, temperature, pH, water, and enzymatic activities. Therefore, to enhance their stability and preserve their antioxidant activity, this study investigated the silk fibroin nanoparticles (SFNs) ability to encapsulate, deliver, and heat-protect the phenolic compounds of the guava leaves ethanolic extract. Firstly, the guava ethanolic extract was produced by maceration, which possessed a total phenolic content of 312.6 mg GAE/g DPW and a high antioxidant activity (IC50 = 5.397 ± 0.618 µg/mL). Then, the extract loaded SFNs were manufactured by desolvation method, and the particles demonstrated appropriate sizes of 200-700 nm with narrow size distribution, spherical shape, silk-II crystalline structure, high drug entrapment efficiency of > 70% (dependent on the fibroin content), and a two-phase sustained drug release for at least 210 min. Using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, the antioxidant activity of the guava extract was well-preserved in the extract loaded SFNs. Finally, after being treated with high temperature of 70 °C for 24 h, the guava extract almost loses all of its antioxidant property (5 times decrement), whereas the extract loaded SFNs could retain the extract activity. Conclusively, the SFNs proved much potential to deliver and heat-protect the guava extract phenolic compounds, and preserve their antioxidant activity. Confirmed by this case, SFNs could be further explored in protecting other natural compounds from environmental factors.

Detection of phase shifts in batch fermentation via statistical analysis of the online measurements: a case study with rifamycin B fermentation.

Industrial production of antibiotics, biopharmaceuticals and enzymes is typically carried out via a batch or fed-batch fermentation process. These processes go through various phases based on sequential substrate uptake, growth and product formation, which require monitoring due to the potential batch-to-batch variability. The phase shifts can be identified directly by measuring the concentrations of substrates and products or by morphological examinations under microscope. However, such measurements are cumbersome to obtain. We present a method to identify phase transitions in batch fermentation using readily available online measurements. Our approach is based on Dynamic Principal Component Analysis (DPCA), a multivariate statistical approach that can model the dynamics of non-stationary processes. Phase-transitions in fermentation produce distinct patterns in the DPCA scores, which can be identified as singular points. We illustrate the application of the method to detect transitions such as the onset of exponential growth phase, substrate exhaustion and substrate switching for rifamycin B fermentation batches. Further, we analyze the loading vectors of DPCA model to illustrate the mechanism by which the statistical model accounts for process dynamics. The approach can be readily applied to other industrially important processes and may have implications in online monitoring of fermentation batches in a production facility.