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.

Investigation of cell-accelerated corrosion (CAC) on the CoCrMo alloy with segregation banding: Hip implant applications.

Metal alloy microstructure plays a crucial role in corrosion associated with total hip replacement (THR). THR is a prominent strategy that uses metal implants such as cobalt-chromium-molybdenum (CoCrMo) alloys due to their advantageous biological and mechanical properties. Despite all benefits, these implants undergo corrosion and wear processes in-vivo in a synergistic manner called tribocorrosion. Also, the implant retrieval findings reported that fretting corrosion occurred in-vivo, evidenced by the damage patterns that appeared on the THR junction interfaces. There is no scientific data on the studies reporting the fretting corrosion patterns of CoCrMo microstructures in the presence of specific biological treatments to date. In the current study, Flat-on-flat fretting corrosion set-up was customized and used to study the tribocorrosion patterns of fretting corrosion to understand the role of alloy microstructure. Alloy microstructural differences were created with the implant stock metal's longitudinal and transverse cutting orientations. As a result, the transverse created the non-banded, homogenous microstructure, whereas the longitudinal cut resulted in the banded, non-homogenous microstructure on the surface of the alloy (in this manuscript, the terms homogenous and banded were used). The induced currents were monitored using a three-electrode system. Three different types of electrolytes were utilized to study the fretting corrosion patterns with both homogeneous and banded microstructures: 1. Control media 2. Spent media (the macrophage cell cultured media) 3. Challenged media (media collected after the macrophage was treated with CoCrMo particles). From the electrochemical results, in the potentiostat conditions, the banded group exhibited a higher induced current in both challenged and spent electrolyte environments than in control due to the synergistic activity of CoCrMo particles and macrophage demonstrating more corrosion loss. Additionally, both Bode and Nyquist plots reported a clear difference between the banded and homogeneous microstructure, especially with challenged electrolytes becoming more corrosion-resistant post-fretting than pre-fretting results. The banded microstructure showed a unique shape of the fretting loop, which may be due to tribochemical reactions. Therefore, from the electrochemical, mechanical, and surface analysis data results, the transverse/homogenous/non-banded alloy microstructure groups show a higher resistance to fretting-corrosion damage.

Early Detection of Fretting Corrosion in Hip Replacement by Acoustic Emission Non-Invasive Technique.

The present study aimed to investigate the feasibility of using acoustic emission (AE) as a detection method for identifying failure mechanisms at the modular junction interface in total hip replacements (THRs) subjected to fretting corrosion. The experimental setup involved simulating fretting corrosion using a Ti6Al4V disc representing the femoral neck and a ZrO2 pin representing the femoral head. Mechanical testing provided insights into the wear and frictional behavior occurring at the modular junction interface. The results revealed that for all three potential conditions, a fretting condition of partial slip was observed. These findings highlight the importance of understanding the mechanical interactions and their influence on the overall performance and longevity of THRs. Electrochemical analysis shed light on the corrosion behavior under different potentiostatic conditions. High potentials in the anodic condition led to increased corrosion and ion transfer due to the breakdown of the passive oxide layer. Conversely, the cathodic potential condition exhibited a regrowth of the passive oxide layer, protecting the Ti6Al4V surface from further corrosion. The mid-range corrosion potential condition showed a dynamic equilibrium between corrosion and passivation processes. These electrochemical insights enhance our understanding of the mechanisms involved in fretting corrosion. The AE data proved to be promising in detecting and monitoring the onset and progression of failure mechanisms. The AE signals exhibited distinctive patterns that correlated with the severity of fretting corrosion. Notably, the hit driven data results, derived from AE signals, demonstrated the ability to differentiate between different levels of fretting conditions. This suggests that AE can serve as a valuable diagnostic tool for early detection and continuous monitoring of implant failure in THRs.

Development of End-to-End Artificial Intelligence Models for Surgical Planning in Transforaminal Lumbar Interbody Fusion.

Transforaminal lumbar interbody fusion (TLIF) is a commonly used technique for treating lumbar degenerative diseases. In this study, we developed a fully computer-supported pipeline to predict both the cage height and the degree of lumbar lordosis subtraction from the pelvic incidence (PI-LL) after TLIF surgery, utilizing preoperative X-ray images. The automated pipeline comprised two primary stages. First, the pretrained BiLuNet deep learning model was employed to extract essential features from X-ray images. Subsequently, five machine learning algorithms were trained using a five-fold cross-validation technique on a dataset of 311 patients to identify the optimal models to predict interbody cage height and postoperative PI-LL. LASSO regression and support vector regression demonstrated superior performance in predicting interbody cage height and postoperative PI-LL, respectively. For cage height prediction, the root mean square error (RMSE) was calculated as 1.01, and the model achieved the highest accuracy at a height of 12 mm, with exact prediction achieved in 54.43% (43/79) of cases. In most of the remaining cases, the prediction error of the model was within 1 mm. Additionally, the model demonstrated satisfactory performance in predicting PI-LL, with an RMSE of 5.19 and an accuracy of 0.81 for PI-LL stratification. In conclusion, our results indicate that machine learning models can reliably predict interbody cage height and postoperative PI-LL.

A Case of Life-Threatening Abdominal Wall Hematoma Formation in a Patient on Warfarin Therapy with Concurrent Influenza Infection.

Warfarin therapy provides extensive antithrombotic benefits and, thus, is widely used in the general population. However, as with most medications, there are also risks associated with warfarin use. Specifically, because of the narrow therapeutic window of this drug, patients taking it are at a much higher risk of accidental bleeding. Additionally, patients may also present with bleeding complications when infected with illnesses with coughing as a symptom, such as influenza or COVID-19. These patients have the potential to suffer hemorrhagic morbidities related to the increased intra-abdominal and intra-thoracic pressures that are generated from coughing. Moreover, a synergistic effect is seen when patients find themselves in a situation where they are taking anticoagulation therapy and become infected with illnesses such as influenza or COVID-19. We present a case in which an individual on warfarin therapy was infected with Influenza A. This combination of factors eventually led to massive hemorrhage and large abdominal wall hematoma formation. This case brings to light the importance of having a low threshold for considering the prospect of massive hemorrhage in any patient who is anticoagulated and develops a condition that is associated with increased abdominal pressure. Because these bleeding events can have devastating effects, raising awareness of this risk is increasingly important. Early detection of massive hemorrhage will lead to better outcomes and can ultimately be life-saving for these patients.

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.

Prevalence of the metabolic syndrome by household food insecurity status in the United States adolescent population, 2001-2020: a cross-sectional study.

BACKGROUND: Household food insecurity (FI) is a modifiable social determinant of health linked to chronic health outcomes. Little is known, however, about the prevalence of metabolic syndrome (MetS) in pediatric population-based studies by household FI status. OBJECTIVES: The objective of the study was to estimate the prevalence of the MetS by household FI status over the past 2 decades. METHODS: This cross-sectional study used data from the 2001-2020 National Health and Nutrition Examination Survey (NHANES). Participants were nonpregnant adolescents ages 12- 18 y in United States. The prevalence of MetS [elevated waist circumference and >2 of the following risk factors: elevated blood pressure, and fasting glucose, triglyceride, and/or low high-density lipoprotein (HDL) cholesterol concentrations] by FI status was evaluated using chi-square and logistic regression analyses. RESULTS: The estimated prevalence of MetS was 2.66% [95% confidence interval (CI): 2.28%, 3.09%] in the final analytical sample (unweighted N = 12,932). A total of 3.39% (95% CI: 2.53%, 4.53%) of adolescents from FI households had MetS compared to 2.48% (95% CI: 2.11%, 2.9%) among adolescents with no household FI. Hispanic adolescents had the highest prevalence of MetS (3.73%, 95% CI: 3.05, 4.56) compared with adolescents who identified as non-Hispanic White (2.78%, 95% CI: 2.25, 3.43), non-Hispanic Black (1.58%, 95% CI: 1.19, 2.10). Adolescents with household FI (23.20%) were more likely to have MetS [odds ratio (OR): 1.38; 95% CI: 1.02, 1.88; I=0.039) compared with adolescents with no household FI, but in fully adjusted models this was not significant (OR: 1.13; 95% CI: 0.75, 1.72). CONCLUSIONS: Using the most current NHANES data, the estimated prevalence of MetS in adolescents in United States was slightly higher among those from FI households. However, after adjusting for potential confounders, the relationship between household FI and MetS was nonsignificant, highlighting the complexity of factors contributing to MetS in this population. Hispanic adolescents share a disproportionate burden of MetS compared with their non-Hispanic counterparts.

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.

In Vitro Tribocorrosion Evaluation of Carbide-derived Carbon (CDC) for Hip Implants.

Carbide-derived carbon (CDC) was previously proposed as a surface modification method for hip implant applications since it showed excellent tribocorrosion performance under open-circuit potential (OCP) conditions. Nonetheless, a systematic evaluation of CDC's tribocorrosion properties was still missing. Therefore, our objective is to test CDC's tribocorrosion performance under various electrochemical conditions and to identify the synergism between wear and corrosion. Based on the findings, the variations in OCP for CDC (0.626 mV) is smaller than Ti6Al4V (1.91 mV), and CDC showed lower induced current than T6Al4V for all potentials, suggesting CDC is more stable than Ti6Al4V under tribocorrosive conditions. Eventually, the weight loss of Ti6Al4V (50.662±5.19 µg) was found to be significantly higher than that of CDC (4.965±5.19 µg), which agrees with the electrochemical results. In summary, CDC showed better tribocorrosion performance than Ti6Al4V and was determined as an Antagonism regime.

Fretting-corrosion Apparatus with Low Magnitude Micro-motion (≤5 µm): Development and Preliminary Outcome.

Fretting-corrosion is one of the failure processes in many applications, including biomedical implants. For example, the modern design of hip implants with multiple components offers better flexibility and inventory storage. However, it will trigger the fretting at the implant interfaces with a small displacement amplitude (< 5 µm) and usually in a partial slip region. Although many studies have been reported on the fretting, they have high displacement amplitude and are in the gross slip region. It is imperative to have an apparatus to overcome such limitations, specifically for hip implant applications. Therefore, this study describes the development of a fretting-corrosion apparatus with low micro-motion (≤ 5 µm) that can simultaneously monitor the corrosion process. Initial experiments with Ti6Al4V-Ti6Al4V in 0.9% saline, Ti6Al4V-Ti6Al4V in bovine calf serum (BCS), and ZrO2-Ti6Al4V in BCS were conducted to validate the system. As a result, the fretting regime of all groups remained partially slip region throughout the 3600 cycles, and the possible failure mechanisms are proposed in this manuscript.

Proteomic-based electrochemical non-invasive biosensor for early breast cancer diagnosis.

Breast cancer is the second highest cause of cancer-related mortality in women worldwide and in the United States, accounting for around 571,000 deaths per year. Early detection of breast cancer increases treatment results and the possibility of a cure. While existing diagnostic modalities such as mammography, ultrasound, and biopsy exist, some are prohibitively expensive, uncomfortable, time-consuming, and have limited sensitivity, necessitating the development of a cost-effective, rapid, and highly sensitive approach such as an electrochemical biosensor. Our research focuses on detecting breast cancer patients using the ECM1 biomarker, which has higher expression in synthetic urine. Our study has two primary objectives: (i) Diverse ECM1 protein concentrations are measured using electrochemical impedance spectroscopy and ELISA. Establishing a standard curve for the electrochemical biosensor by calibrating ECM-1 protein levels using electrochemical impedance spectroscopy. (ii) Validation of the effectiveness of the electrochemical biosensor. This aim entails testing the unknown concentration of ECM1 in the synthetic urine to ensure the efficiency of the biosensor to detect the biomarker in the early stages. The results show that the synthetic urine solution's ECM-1 detection range ranges from 1 pg/ml to 500 ng/ml. This shows that by detecting changes in ECM-1 protein levels in patient urine, the electrochemical biosensor can consistently diagnose breast cancer in its early stages or during increasing recurrence. Our findings highlight the electrochemical biosensor's efficacy in detecting early-stage breast cancer biomarkers (ECM-1) in patient urine. Further studies will be conducted with patient samples and develop handheld hardware for patient usage.

Early Predicting Tribocorrosion Rate of Dental Implant Titanium Materials Using Random Forest Machine Learning Models.

Early detection and prediction of bio-tribocorrosion can avert unexpected damage that may lead to secondary revision surgery and associated risks of implantable devices. Therefore, this study sought to develop a state-of-the-art prediction technique leveraging machine learning(ML) models to classify and predict the possibility of mechanical degradation in dental implant materials. Key features considered in the study involving pure titanium and titanium-zirconium (zirconium = 5, 10, and 15 in wt%) alloys include corrosion potential, acoustic emission(AE) absolute energy, hardness, and weight-loss estimates. ML prototype models deployed confirms its suitability in tribocorrosion prediction with an accuracy above 90%. Proposed system can evolve as a continuous structural-health monitoring as well as a reliable predictive modeling technique for dental implant monitoring.

Survivability of Titanium Implant Materials: In Vitro Simulated Inflammatory and Infectious Environment.

Titanium-based implants utilized in total joint arthroplasties could restore primary musculoskeletal function to patients suffering from osteoarthritis and other conditions. Implants are susceptible to failure stemming from aseptic loosening and infection at the joint site, eventually requiring revision surgery. We hypothesized that there might be a feedback loop by which metal degradation particles and ions released from the implant decrease cell viability and increase immune response, thereby creating biochemical conditions that increase the corrosion rate and release more metal ions. This study focused on the synergistic process through cell viability assays and electrochemical tests. From the results, inflammatory conditions from ion release resulting in cell death would further increase the corrosion rate at the metal implant site. The synergistic interaction in the implant surroundings in which infectious conditions produce Ti ions that contribute to more infection, creating a potential cycle of accelerating corrosion.

Severe outcomes following pediatric cannabis intoxication: a prospective cohort study of an international toxicology surveillance registry.

INTRODUCTION: An increasing number of jurisdictions have legalized recreational cannabis for adult use. The subsequent availability and marketing of recreational cannabis has led to a parallel increase in rates and severity of pediatric cannabis intoxications. We explored predictors of severe outcomes in pediatric patients who presented to the emergency department with cannabis intoxication. METHODS: In this prospective cohort study, we collected data on all pediatric patients (<18 years) who presented with cannabis intoxication from August 2017 through June 2020 to participating sites in the Toxicology Investigators Consortium. In cases that involved polysubstance exposure, patients were included if cannabis was a significant contributing agent. The primary outcome was a composite severe outcome endpoint, defined as an intensive care unit admission or in-hospital death. Covariates included relevant sociodemographic and exposure characteristics. RESULTS: One hundred and thirty-eight pediatric patients (54% males, median age 14.0 years, interquartile range 3.7-16.0) presented to a participating emergency department with cannabis intoxication. Fifty-two patients (38%) were admitted to an intensive care unit, including one patient who died. In the multivariable logistic regression analysis, polysubstance ingestion (adjusted odds ratio = 16.3; 95% confidence interval: 4.6-58.3; P < 0.001)) and cannabis edibles ingestion (adjusted odds ratio = 5.5; 95% confidence interval: 1.9-15.9; P = 0.001) were strong independent predictors of severe outcome. In an age-stratified regression analysis, in children older than >10 years, only polysubstance abuse remained an independent predictor for the severe outcome (adjusted odds ratio 37.1; 95% confidence interval: 6.2-221.2; P < 0.001). As all children 10 years and younger ingested edibles, a dedicated multivariable analysis could not be performed (unadjusted odds ratio 3.3; 95% confidence interval: 1.6-6.7). CONCLUSIONS: Severe outcomes occurred for different reasons and were largely associated with the patient's age. Young children, all of whom were exposed to edibles, were at higher risk of severe outcomes. Teenagers with severe outcomes were frequently involved in polysubstance exposure, while psychosocial factors may have played a role.

Unpredictable Electrochemical Processes in Ti Dental Implants: The Role of Ti Ions and Inflammatory Products.

Peri-implantitis is a substantially prevailing condition. A potential risk factor for peri-implantitis is Ti implant corrosion. During inflammation, substantial quantities of reactive oxygen species (ROS) secretion and local acidification occur. Little is known about the interaction between the inflammatory and corrosion products on Ti surface corrosion. Therefore, the objective of the current study was to evaluate the synergistic effect of hydrogen peroxide (H2O2), lactic acid, and Ti ions on Ti corrosion. Twenty-seven commercially pure Ti samples were polished (Ra ≈ 45 nm) and divided into 9 groups as a function of electrolyte: (1) artificial saliva (AS) as control (C), (2) AS + Ti ions 20 ppm (Ti), (3) AS + lactic acid (pH = 5.5) (L), (4) AS + lactic acid + Ti ions 20 ppm (TiL), (5) AS + H2O2 0.5 mM (HP0.5), (6) AS + H2O2 1.0 mM (HP1.0), (7) AS + H2O2 0.5 mM + Ti ions 20 ppm (HP0.5Ti), (8) AS + H2O2 0.5 mM + lactic acid (HP0.5L), and (9) AS + H2O2 0.5 mM + Ti ions 20 ppm + lactic acid (HP0.5TiL). Electrochemical tests were performed following ASMT guidelines. Based on Tafel's method, current density (icorr) and corresponding potential (Ecorr) were acquired from potentiodynamic curves. Using electrochemical intensity spectroscopy (EIS), Nyquist and Bode plots were derived. Using a modified Randles circuit, charge transfer resistance (Rct) and capacitance (Cdl) were estimated. Based on open-circuit potential data, groups C and Ti had the lowest potentials (around -0.3 and -0.4 V vs SCE, respectively), indicating a lower passivation tendency compared to the other groups. From potentiodynamic curves, groups HP0.5 and HP1.0 increased icorr the most. From EIS data, groups HP0.5 and HP1.0 demonstrated the lowest impedance and phase angle on the Bode plot, indicating the highest corrosion kinetics. Based on EIS modeling, the combination of Ti ions, lactic acid, and H2O2 (group HP0.5TiL) significantly decreased Rct (p < 0.05). In conclusion, the concurrent presence of Ti ions, lactic acid, and H2O2 in the vicinity of the Ti surface increased the corrosion kinetics. High corrosion may produce more Ti products in the peri-implant tissues, which may increase the potential risk of peri-implantitis.

A Review on Saliva-Based Health Diagnostics: Biomarker Selection and Future Directions.

The human body has a unique way of saying when something is wrong with it. The molecules in the body fluids can be helpful in the early detection of diseases by enabling health and preventing disease progression. These biomarkers enabling better healthcare are becoming an extensive area of research interest. Biosensors that detect these biomarkers are becoming the future, especially Point Of Care (POC) biosensors that remove the need to be physically present in the hospital. Detection of complex and systemic diseases using biosensors has a long way to go. Saliva-based biosensors are gaining attention among body fluids due to their non-invasive collection and ability to detect periodontal disease and identify systemic diseases. The possibility of saliva-based diagnostic biosensors has gained much publicity, with companies sending home kits for ancestry prediction. Saliva-based testing for covid 19 has revealed effective clinical use and relevance of the economic collection. Based on universal biomarkers, the detection of systemic diseases is a booming research arena. Lots of research on saliva-based biosensors is available, but it still poses challenges and limitations as POC devices. This review paper talks about the relevance of saliva and its usefulness as a biosensor. Also, it has recommendations that need to be considered to enable it as a possible diagnostic tool.

Recent advances of polypyrrole conducting polymer film for biomedical application: Toward a viable platform for cell-microbial interactions.

Polypyrrole (PPy) is one of the most studied conductive polymers due to its electrical conductivity and biological properties, which drive the possibility of numerous applications in the biomedical area. The physical-chemical features of PPy allow the manufacture of biocompatible devices, enhancing cell adhesion and proliferation. Furthermore, owing to the electrostatic interactions between the negatively charged bacterial cell wall and the positive charges in the polymer structure, PPy films can perform an effective antimicrobial activity. PPy is also frequently associated with biocompatible agents and antimicrobial compounds to improve the biological response. Thus, this comprehensive review appraised the available evidence regarding the PPy-based films deposited on metallic implanted devices for biomedical applications. We focus on understanding key concepts that could influence PPy attributes regarding antimicrobial effect and cell behavior under in vitro and in vivo settings. Furthermore, we unravel the several agents incorporated into the PPy film and strategies to improve its functionality. Our findings suggest that incorporating other elements into the PPy films, such as antimicrobial agents, biomolecules, and other biocompatible polymers, may improve the biological responses. Overall, the basic properties of PPy, when combined with other composites, electrostimulation techniques, or surface treatment methods, offer great potential in biocompatibility and/or antimicrobial activities. However, challenges in synthesis standardization and potential limitations such as low adhesion and mechanical strength of the film must be overcome to improve and broaden the application of PPy film in biomedical devices.

Current advancements in bio-ink technology for cartilage and bone tissue engineering.

In tissue engineering, the fate of a particular organ/tissue regeneration and repair mainly depends on three pillars - 3D architecture, cells used, and stimulus provided. 3D cell supportive structure development is one of the crucial pillars necessary for defining organ/tissue geometry and shape. In recent years, the advancements in 3D bio-printing (additive manufacturing) made it possible to develop very precise 3D architectures with the help of industrial software like Computer-Aided Design (CAD). The main requirement for the 3D printing process is the bio-ink, which can act as a source for cell support, proliferation, drug (growth factors, stimulators) delivery, and organ/tissue shape. The selection of the bio-ink depends upon the type of 3D tissue of interest. Printing tissues like bone and cartilage is always challenging because it is difficult to find printable biomaterial that can act as bio-ink and mimic the strength of the natural bone and cartilage tissues. This review describes different biomaterials used to develop bio-inks with different processing variables and cell-seeding densities for bone and cartilage 3D printing applications. The review also discusses the advantages, limitations, and cell bio-ink compatibility in each biomaterial section. The emphasis is given to bio-inks reported for 3D printing cartilage and bone and their applications in orthopedics and orthodontists. The critical/important performance and the architectural morphology requirements of desired bone and cartilage bio-inks were compiled in summary.