Reduction in gingival overgrowth associated with conversion from cyclosporin A to tacrolimus

Background: Unsightly gingival overgrowth affects many individuals immunosuppressed with cyclosporin A (CsA), Current management involves repeated periodontal surgery and intensive hygienist support. Tacrolimus is an effective alternative immunosuppressive agent for renal transplantation which does not appear to produce gingival enlargement.

The calcium channel blocker used with cyclosporin has an effect on gingival overgrowth

Background/aims, To investigate whether the choice of calcium channel blocker, used in conjunction with cyclosporin A, affected the prevalence of gingival overgrowth.

Changes in substance P and neurokinin A in gingival crevicular fluid in response to periodontal treatment

Background: The study of periodontitis provides a unique model for assessing the involvement of neuropeptides in inflammatory disease.

Carboxypeptidase-mediated metabolism of calcitonin gene-related peptide in human gingival crevicular fluid - a role in periodontal inflammation?

Background: Metabolism by peptidases plays an important role in modulating the levels of biologically-active neuropeptides. The metabolism of the anti-inflammatory neuropeptide calcitonin gene-related peptide (GCRP), but not the pro-inflammatory neuropeptides substance P (SP) and neurokinin A (NKA) by components of the gingival crevicular fluid (GCF), could potentiate the inflammatory process in periodontitis.

Quantitative analysis of MRP-8 in gingival crevicular fluid in periodontal health and disease using microbore HPLC.

BACKGROUND:

The protein components of GCF can be separated by reverse-phase microbore HPLC on a C18 column with detection on the basis of 214 nm absorbance. A single major symmetrical protein peak eluting with a retention time of 26 min (50% acetonitrile) was evident in gingival crevicular fluid (GCF) from periodontitis patients but not in healthy GCF. This protein was identified as human MRP-8 by N-terminal amino acid sequencing and liquid chromatography quadropole mass spectrometry.

AIMS:

To quantify the amount of MRP-8 detectable in GCF from individual healthy, gingivitis and periodontitis affected sites and to study the relationship, if any, between the levels of this responsive protein and periodontal health and disease.

METHODS:

GCF was sampled (30 s) from healthy, gingivitis, and periodontitis sites in peridontitis subjects (n=15) and from controls (n=5) with clinically healthy gingiva and no periodontitis. Purified MRP-8 was sequenced by Edmann degradation and the phenylthiohydantoin (PTH) amino acid yield determined (by comparison of peak area with external PTH amino acid standards). This value was subsequently used to calculate the relative amount of protein in the peak eluting with a retention time of 26.0 min (MRP-8) in individual GCF chromatograms.

RESULTS:

Higher levels of MRP-8 were detected in inflammatory sites: periodontitis 457.0 (281.0) ng; gingivitis 413.5 (394.5) ng compared with periodontally healthy sites in diseased subjects 14.6 (14.3) ng and in controls 18.6 (18.5) ng, p=0.003. There was at least 20-fold more MRP-8 in the inflammatory compared with the healthy sites studied.

CONCLUSIONS:

The preliminary data indicate that MRP-8 is present in GCF, with significantly greater amounts present at diseased than healthy sites. A systematic study of the relationship of this protein to periodontal disease could prove useful in further clarifying whether MRP-8 could be a reliable GCF biomarker of gingivitis and periodontitis.

Computer simulating a trial of a load-bearing implant: example of an intramedullary prosthesis

Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted for an idealised or ‘average’ patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population—effectively simulating a clinical trial. Specifically we hypothesise that an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or ‘average’ patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young’s modulus implant (View the MathML source) to one with a higher Young’s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis for an idealised of ‘average’ patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance–simulating a clinical trial–present a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.