Principal component analysis and cluster analysis for the characterization of dental composites

Calcium phosphates as ion-releasing fillers in restorative resin-based materials

Calcium phosphates (CaP) are the main constituents of the mineral phase in bones and teeth and, along with calcium silicates and bioactive glasses, have been extensively investigated in remineralization of enamel and dentin. When used as ion-releasing fillers in resin-based materials, they could contribute to extend the service life of adhesive restorations, remineralize caries-affected dentin or prevent caries lesions under sealants and orthodontic brackets. However, the development of resin-based bioactive materials is not straightforward because of the several compositional variables involved in ion release. Also, CaP particles do not reinforce the material; therefore, if high mechanical properties are required, the ratio between CaP particles and reinforcing fillers must be observed. Several research groups have investigated how CaP phase, particle size and content, as well as resin matrix formulation affect remineralization, ion release kinetics and mechanical properties of these materials. This review presents an overview of the main findings reported in the literature.

Hydroxylapatite nanoparticles: fabrication methods and medical applications

Hydroxylapatite (or hydroxyapatite, HAp) exhibits excellent biocompatibility with various kinds of cells and tissues, making it an ideal candidate for tissue engineering, orthopedic and dental applications. Nanosized materials offer improved performances compared with conventional materials due to their large surface-to-volume ratios. This review summarizes existing knowledge and recent progress in fabrication methods of nanosized (or nanostructured) HAp particles, as well as their recent applications in medical and dental fields. In section 1, we provide a brief overview of HAp and nanoparticles. In section 2, fabrication methods of HAp nanoparticles are described based on the particle formation mechanisms. Recent applications of HAp nanoparticles are summarized in section 3. The future perspectives in this active research area are given in section 4.

Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques

To differentiate heparin samples with varying amounts of dermatan sulfate (DS) impurities and oversulfated chondroitin sulfate (OSCS) contaminants, proton NMR spectral data for heparin sodium active pharmaceutical ingredient samples from different manufacturers were analyzed using multivariate chemometric techniques. A total of 168 samples were divided into three groups: (a) Heparin, [DS] ≤ 1.0% and [OSCS] = 0%; (b) DS, [DS] > 1.0% and [OSCS] = 0%; (c) OSCS, [OSCS] > 0% with any content of DS. The chemometric models were constructed and validated using two well-established methods: soft independent modeling of class analogy (SIMCA) and unequal class modeling (UNEQ). While SIMCA modeling was conducted using the entire set of variables extracted from the NMR spectral data, UNEQ modeling was combined with variable reduction using stepwise linear discriminant analysis to comply with the requirement that the number of samples per class exceed the number of variables in the model by at least 3-fold. Comparison of the results from these two modeling approaches revealed that UNEQ had greater sensitivity (fewer false positives) while SIMCA had greater specificity (fewer false negatives). For Heparin, DS, and OSCS, respectively, the sensitivity was 78% (56/72), 74% (37/50), and 85% (39/46) from SIMCA modeling and 88% (63/72), 90% (45/50), and 91% (42/46) from UNEQ modeling. Importantly, the specificity of both the SIMCA and UNEQ models was 100% (46/46) for Heparin with respect to OSCS; no OSCS-containing sample was misclassified as Heparin. The specificity of the SIMCA model (45/50, or 90%) was superior to that of the UNEQ model (27/50, or 54%) for Heparin with respect to DS samples. However, the overall prediction ability of the UNEQ model (85%) was notably better than that of the SIMCA model (76%) for the Heparin vs DS vs OSCS classes. The models were challenged with blends of heparin spiked with nonsulfated, partially sulfated, or fully oversulfated chondroitin sulfate A, dermatan sulfate, or heparan sulfate at the 1.0, 5.0, and 10.0 wt % levels. The results from the present study indicate that the combination of (1)H NMR spectral data and class modeling techniques (viz., SIMCA and UNEQ) represents a promising strategy for assessing the quality of commercial heparin samples with respect to impurities and contaminants. The methodologies show utility for applications beyond heparin to other complex products.