Poly(δ-valerolactone)/Poly(ethylene-co-vinylalcohol)/β-Tricalcium Phosphate Composite as Scaffolds: Preparation, Properties, and In Vitro Amoxicillin Release

Two poly(δ-valerolactone)/poly(ethylene-co-vinylalcohol)/β-tricalcium phosphate (PEVAL/PDVAL/β-TCP) composites containing an equal ratio of polymer and filled with 50 and 70 wt% of β-TCP microparticles were prepared by the solvent casting method. Interconnected pores were realized using the salt leached technique, and the porosity of the resulted composites was evaluated by the scanning electron microscopy (SEM) method. The homogeneity of the hybrid materials was investigated by differential scanning calorimetry (DSC) and X-ray diffraction (XRD) analysis. The prepared materials’ SEM images showed interconnected micropores that respond to the conditions required to allow their uses as scaffolds. The porosity of each scaffold was determined from micro computed tomography (micro-CT) data, and the analysis of the mechanical properties of the prepared materials was studied through the stress-strain compressive test. The proliferation test results used human mesenchymal stem cells (MSCs) to grow and proliferate on the different types of prepared materials, reflecting that the hybrid materials were non-toxic and could be biologically acceptable scaffolds. The antibacterial activity test revealed that incorporation of amoxicillin in the specimens could inhibit the bacterial growth of S. aureus. The in vitro study of the release of amoxicillin from the PEVAL/PDVAL/amoxicillin and PEVAL/PDVAL/β-TCP/amoxicillin drug carrier systems in pH media 7.4, during eight days, gave promising results, and the antibiotic diffusion in these scaffolds obeys the Fickian model

The Efficacy of Recombinant Platelet-Derived Growth Factor on Beta-Tricalcium Phosphate to Regenerate Femoral Critical Sized Segmental Defects: Longitudinal In Vivo Micro-CT Study in a Rat Model

Background and Objectives: Beta-tricalcium phosphate (beta-TCP) has been used for bone regeneration. The objective of this study was to assess longitudinally, the regeneration of critical sized segmental defects (CSSD) in rat femur using beta-TCP with or without recombinant platelet-derived growth factor (PDGF) through in vivo micro-computed tomography (micro-CT). Materials and Methods: Following ethical approval unilateral femoral CSSD measuring 5 mm was surgically created, under general anesthesia, in 30 male Wistar-Albino rats (aged 12–18 months; weighing 450–500 g). CSSD was stabilized using titanium mini-plate (4 holes, 1.0 mm thick with 8 mm bar). Depending upon biomaterial used for regeneration, the animals were randomly divided into: Control group (N = 10): CSSD covered with resorbable collagen membrane (RCM) only; Beta-TCP group (N = 10): CSSD filled with beta-TCP and covered by RCM; Beta-TCP + PDGF group (N = 10): CSSD filled with beta-TCP soaked in recombinant PDGF and covered by RCM. Longitudinal in vivo micro-CT analysis of the CSSD was done postoperatively at baseline, 2nd, 4th, 6th, and 8th weeks to assess volume and mineral density of newly formed bone (NFB) and beta-TCP. Results: Significant increase in NFB volume (NFBV) and mineral density (NFBMD) were observed from baseline to 8-weeks in all groups. Based on longitudinal in vivo micro-CT at 8-weeks, beta-TCP + PDGF group had significantly higher (p < 0.01) NFBV (38.98 ± 7.36 mm3) and NFBMD (3.72 ± 0.32 g/mm3) than the beta-TCP (NFBV—31.15 ± 6.68 mm3; NFBMD—2.28 ± 0.86g/mm3) and control (NFBV: 5.60 ± 1.06 mm3; NFBMD: 0.27 ± 0.02 g/mm3) groups. Significantly, higher reduction in beta-TCP volume (TCPV) and mineral density (TCPMD) were 1 observed in the beta-TCP + PDGF group when compared to the beta-TCP group. Conclusion: Addition of recombinant PDGF to beta-TCP enhanced bone regeneration within rat femoral CSSD and increased resorption rates of beta-TCP particles

Peri-Implant bone response around porous-surface dental implants: A preclinical meta-analysis

Introduction: This meta-analysis of relevant animal studies was conducted to assess whether the use of porous-surface implants improves osseointegration compared to the use of non-porous-surface implants. Material and methods: An electronic search of PubMed (MEDLINE) resulted in the selection of ten animal studies (out of 865 publications) for characterization and quality assessment. Risk of bias assessment indicated poor reporting for the majority of studies. The results for bone-implant contact (BIC%) and peri-implant bone formation (BF%) were extracted from the eligible studies and used for the meta-analysis. Data for porous-surface implants were compared to those for non-porous-surface implants, which were considered as the controls. Results: The random-effects meta-analysis showed that the use of porous-surface implants did not significantly increase overall BIC% (mean difference or MD: 3.63%; 95% confidence interval or 95% CI: −1.66 to 8.91; p = 0.18), whereas it significantly increased overall BF% (MD: 5.43%; CI: 2.20 to 8.67; p = 0.001), as compared to the controls. Conclusion: Porous-surface implants promote osseointegration with increase in BF%. However, their use shows no significant effect on BIC%. Further preclinical and clinical investigations are required to find conclusive evidence on the effect of porous-surface implants

A Multi-Criteria Decision Framework Considering Different Levels of Decision-Maker Involvement to Reconfigure Manufacturing Systems

Reconfigurable Manufacturing Systems (RMSs) rely on a set of technologies to quickly adapt the manufacturing system capacity and/or functionality to meet unexpected disturbances, such as fluctuation/uncertainty of demand and/or unavailability/unreliability of resources. At the operational stage, such disturbances raise new production requirements and risks, which call upon Decision-Makers (DMs) to analyze the opportunity to move from a running configuration to another more competitive one. Such a decision is generally based on an evaluation of a multitude of criteria, and several multi-criteria decision-making (MCDM) approaches have been suggested to help DMs with the reconfiguration process. Most existing MCDM approaches require some assignment of weights to the criteria, which is not a trivial task. Unfortunately, existing studies on MCDM for an RMS have not provided guidelines to weigh the evaluation criteria. This article fills in this gap by offering a framework to set up such weights. We provide a comprehensive set of quantitative indicators to evaluate the reconfiguration decisions during the operation of the RMS. We suggest three weighting methods that are convenient to different levels of DM expertise and desired degree of involvement in the reconfiguration process. These weighting methods are based on (1) intuitive weighting, (2) revised Simos procedural weighting combined with the Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS), and (3) DM independent weighting using ELECTRE IV. The implementation of the suggested framework and a comparison of the suggested methods carried out on an industrial case study are described herein

Analyzing critical failures in a production process: Is industrial IoT the solution?

Machine failures cause adverse impact on operational efficiency of any manufacturing concern. Identification of such critical failures and examining their associations with other process parameters pose a challenge in a traditional manufacturing environment. This research study focuses on the analysis of critical failures and their associated interaction effects which are affecting the production activities. To improve the fault detection process more accurately and efficiently, a conceptual model towards a smart factory data analytics using cyber physical systems (CPS) and Industrial Internet of Things (IIoTs) is proposed. The research methodology is based on a fact-driven statistical approach. Unlike other published work, this study has investigated the statistical relationships among different critical failures (factors) and their associated causes (cause of failures) which occurred due to material deficiency, production organization, and planning. A real business case is presented and the results which cause significant failure are illustrated. In addition, the proposed smart factory model will enable any manufacturing concern to predict critical failures in a production process and provide a real-time process monitoring. The proposed model will enable creating an intelligent predictive failure control system which can be integrated with production devices to create an ambient intelligence environment and thus will provide a solution for a smart manufacturing process of the future