Harnessing extracellular vesicles-mediated signaling for enhanced bone regeneration: novel insights into scaffold design.

The increasing prevalence of bone replacements and complications associated with bone replacement procedures underscores the need for innovative tissue restoration approaches. Existing synthetic grafts cannot fully replicate bone vascularization and mechanical characteristics. This study introduces a novel strategy utilizing pectin, chitosan, and polyvinyl alcohol to create interpenetrating polymeric network (IPN) scaffolds incorporated with extracellular vesicles (EVs) isolated from human mesenchymal stem cells (hMSCs). We assess the osteointegration and osteoconduction abilities of these modelsin vitrousing hMSCs and MG-63 osteosarcoma cells. Additionally, we confirm exosome properties through Transmission Electron Microscopy (TEM), immunoblotting, and Dynamic Light Scattering (DLS).In vivo, chick allantoic membrane assay investigates vascularization characteristics. The study did not includein vivoanimal experiments. Our results demonstrate that the IPN scaffold is highly porous and interconnected, potentially suitable for bone implants. EVs, approximately 100 nm in size, enhance cell survival, proliferation, alkaline phosphatase activity, and the expression of osteogenic genes. EVs-mediated IPN scaffolds demonstrate promise as precise drug carriers, enabling customized treatments for bone-related conditions and regeneration efforts. Therefore, the EVs-mediated IPN scaffolds demonstrate promise as precise carriers for the transport of drugs, allowing for customized treatments for conditions connected to bone and efforts in regeneration.

Intelligent salivary biosensors for periodontitis: in vitro simulation of oral oxidative stress conditions.

ASTRACT: One of the most common oral diseases affecting millions of people worldwide is periodontitis. Usually, proteins in body fluids are used as biomarkers of diseases. This study focused on hydrogen peroxide, lipopolysaccharide (LPS), and lactic acid as salivary non-protein biomarkers for oxidative stress conditions of periodontitis. Electrochemical analysis of artificial saliva was done using Gamry with increasing hydrogen peroxide, bLPS, and lactic acid concentrations. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were conducted. From EIS data, change in capacitance and CV plot area were calculated for each test condition. Hydrogen peroxide groups had a decrease in CV area and an increase in percentage change in capacitance, lipopolysaccharide groups had a decrease in CV area and a decrease in percentage change in capacitance, and lactic acid groups had an increase of CV area and an increase in percentage change in capacitance with increasing concentrations. These data showed a unique combination of electrochemical properties for the three biomarkers. Scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) employed to observe the change in the electrode surface and elemental composition data present on the sensor surface also showed a unique trend of elemental weight percentages. Machine learning models using hydrogen peroxide, LPS, and lactic acid electrochemical data were applied for the prediction of risk levels of periodontitis. The detection of hydrogen peroxide, LPS, and lactic acid by electrochemical biosensors indicates the potential to use these molecules as electrochemical biomarkers and use the data for ML-driven prediction tool for the periodontitis risk levels.

The effect of three dental cement types on the corrosion of dental implant surfaces.

Statement of problem: One of the main challenges facing dental implant success is peri-implantitis. Recent evidence indicates that titanium (Ti) corrosion products and undetected-residual cement are potential risk factors for peri-implantitis. The literature on the impact of various types of dental cement on Ti corrosion is very limited. Purpose: This study aimed to determine the influence of dental cement on Ti corrosion as a function of cement amount and type. Materials and methods: Thirty commercially pure Ti grade 4 discs (19 × 7mm) were polished to mirror-shine (Ra ≈ 40 nm). Samples were divided into 10 groups (n = 3) as a cement type and amount function. The groups were no-cement as control, TempBond NE (TB3mm, TB5mm, and TB8mm), FujiCEM-II (FC3mm, FC5mm, and FC8mm), and Panavia-F-2.0 (PC3mm, PC5mm, and PC8mm). Tafel's method estimated corrosion rate (icorr) and corresponding potential (Ecorr) from potentiodynamic curves. Electrochemical Impedance Spectroscopy (EIS) data was utilized to obtain Nyquist and Bode plots. An equivalent electrical circuit estimated polarization resistance (Rp) and double-layer capacitance (Cdl). Inductively coupled plasma mass spectrometry (ICP-MS) analysis was conducted to analyze the electrolyte solution after corrosion. pH measurements of the electrolyte were recorded before and after corrosion tests. Finally, the corroded surface was characterized by a 3D white-light microscope and scanning electron microscope. Statistical analysis was conducted using either one-way ANOVA followed by Tukey's Post Hoc test or Kruskal-Wallis followed by Dunn's test based on data distribution. Results: Based on cement amount, FC and PC significantly increased icorr in higher amounts (FC8mm-icorr = 8.22 × 10-8A/cm2, PC8mm-icorr = 5.61 × 10-8A/cm2) compared to control (3.35 × 10-8A/cm2). In contrast, TB3mm decreased icorr significantly compared to the control. As a function of cement type, FC increased icorr the most. EIS data agrees with these observations. Finally, corroded surfaces had higher surface roughness (Ra) compared to non-corroded surfaces. Conclusion: The study indicated that cement types FC and PC led to increased Ti-corrosion as a function of a higher amount. Hence, the implant stability could be impacted by the selection, excessive cement, and a potentially increased risk of peri-implantitis.

Machine learning enabled multiplex detection of periodontal pathogens by surface-enhanced Raman spectroscopy.

Periodontitis is a chronic inflammation of the periodontium caused by a persistent bacterial infection, resulting in destruction of the supporting structures of teeth. Analysis of microbial composition in saliva can inform periodontal status. Actinobacillus actinomycetemcomitans (Aa), Porphyromonas gingivalis (Pg), and Streptococcus mutans (Sm) are among reported periodontal pathogens, and were used as model systems in this study. Our atomic force microscopic (AFM) study revealed that these pathogens are biological nanorods with dimensions of 0.6-1.1 µm in length and 500-700 nm in width. Current bacterial detection methods often involve complex preparation steps and require labeled reporting motifs. Employing surface-enhanced Raman spectroscopy (SERS), we revealed cell-type specific Raman signatures of these pathogens for label-free detection. It overcame the complexity associated with spectral overlaps among different bacterial species, relying on high signal-to-noise ratio (SNR) spectra carefully collected from pure species samples. To enable simple, rapid, and multiplexed detection, we harnessed advanced machine learning techniques to establish predictive models based on a large set of raw spectra of each bacterial species and their mixtures. Using these models, given a raw spectrum collected from a bacterial suspension, simultaneous identification of all three species in the test sample was achieved at 95.6 % accuracy. This sensing modality can be applied to multiplex detection of a broader range and a larger set of periodontal pathogens, paving the way for hassle-free detection of oral bacteria in saliva with little to no sample preparation.

The Progress in Tribocorrosion Research (2010-21): Focused on the Orthopedics and Dental Implants.

Tribocorrosion is an integration of two areas-tribology and corrosion. It can be defined as the material degradation caused by the combined effect of corrosion and tribological process at the material interfaces. Significant development has occurred in the field of tribocorrosion over the past years. This development is due to its applications in various fields, such as aerospace, marine, biomedical, and space. Focusing on biomedical applications, tribocorrosion finds its applications in the implants used in cardiovascular, spine, orthopedics, trauma, and dental areas. It was reported that around 7.2 million Americans are living with joint implants. Implant surgery is a traumatic and expensive procedure. Tribocorrosion can affect the lifespan of the implants, thus leading to implant failure and a potential cause of revision surgery. Hence, it is essential to understand how tribocorrosion works, its interaction with the implants, and what procedures can be implemented to protect materials from tribocorrosion. This paper discusses how tribocorrosion research has evolved over the past 11 years (2010-2021). This is a comprehensive overview of tribocorrosion research in biomedical applications.