Cytokeratin phenotypes at the dento-gingival junction in relative health and inflammation, in smokers and non-smokers

OBJECTIVES: The cells of the junctional epithelium (JE) provide and maintain the epithelial attachment, and remain morphologically and phenotypically distinct from oral sulcular (OSE) and external oral epithelia (EOE), from which they may be regenerated de novo. Expression of cytokeratins (CK) in human epithelia has been shown to be highly site-specific, implying a functional role. The aims of this study were to differentiate between the cyto-keratin profiles of JE, OSE, EOE and pocket epithelia (PE) in health and disease, in smokers and non-smokers.
MATERIALS AND METHODS: The cytokeratin profiles of 40 samples of healthy and clinically inflamed human gingival tissue taken from 15 smokers and 25 non-smokers were studied by immunocytochemistry. Cryostat sections of fresh frozen gingival tissues were stained with a panel of monoclonal antibodies (mAb) and visualised by a biotin-Streptavidin-peroxidase complex technique.
RESULTS: JE and PE expressed an identical range of cytokeratins irrespective of the inflammatory or smoking status, with the exception of CK4 expression, which tended to be increased in smokers. The OSE and EOE expressed non-cornifying and cornifying differentiation cytokeratins respectively, but in the presence of inflammation, both these epithelia showed increased expression of CK19 at a basal level in association with expression of one or more of the simple cytokeratins. JE/PE expressed CK17 in external layers only, approximating the tooth surface. All epithelia expressed CK6,16 the markers of high cell turnover.
CONCLUSIONS: CK19 was a consistent differentiation marker for JE and PE.Expression of CK8,18 was enhanced by inflammation. CK4 expression increased in association with smoking. Markers of differentiation were not always co-expressed equally within a pair. Pairs were not always completely mutually exclusive with frequent co-localisation.     

Multivariate Analysis of Clinical Factors in Restenosis after Coronary Stenting

Ojbective To find the independent predictors for restenosis after coronary stenting. Methods Quantitative angiography was performed on 60 cases (67 successfully dilated lesions) after angio-plasty over 6-months follow-up, and both univariate and multivariate logistic regression analysis were done to i-dentify the correlations of restenosis with clinical factors. Results The total restenosis rate was 31. 3% (21 of 67 lesions), and according to univariate analysis the patients who underwent coronary stenting≥ 3. 5mm had a lower rate of restenosis ( P < 0. 01). Collateral circulation to the obstruction site, high maximal inflation pressure, smoking and the less minimal lumen diameter after PTCA made the rate of restenosis higherower ( P < 0. 05) . Multivariate logistic regression analysis showed that coronary stenting ≥3. 5mm had a low rate of restenosis, but high maximal inflation pressure and smoking made the restenosis rate higher. Conclusion Coronary stent size, maximal inflation pressure and. smokin     

Patel S,Turner PR,Stubberfield C,Barry E,Rohlff CR,Stamps A,McKenzie E,Young K,Tyson K,Terrett J,Box G,Eccles S,Page MJ. Hyaluronidase gene profiling and role of HYAL‐1 overexpression in an orthotopic model of prostate cancer. International Journal of Cancer 2002;97(4): 416–424.

The original article to which this Erratum refers was published in International Journal of Cancer; 2002; 97(4) 416–422.     

Modulation of gastrointestinal function by MuDelta,a mixed μ opioid receptor agonist/ μ opioid receptor antagonist

BACKGROUND & PURPOSE

Loperamide is a selective µ opioid receptor agonist acting locally in the gastrointestinal (GI) tract as an effective anti-diarrhoeal but can cause constipation. We tested whether modulating µ opioid receptor agonism with δ opioid receptor antagonism, by combining reference compounds or using a novel compound (‘MuDelta’), could normalize GI motility without constipation.

EXPERIMENTAL APPROACH

MuDelta was characterized in vitro as a potent µ opioid receptor agonist and high-affinity δ opioid receptor antagonist. Reference compounds, MuDelta and loperamide were assessed in the following ex vivo and in vivo experiments: guinea pig intestinal smooth muscle contractility, mouse intestinal epithelial ion transport and upper GI tract transit, entire GI transit or faecal output in novel environment stressed mice, or four weeks after intracolonic mustard oil (post-inflammatory). Colonic δ opioid receptor immunoreactivity was quantified.

KEY RESULTS

δ Opioid receptor antagonism opposed µ opioid receptor agonist inhibition of intestinal contractility and motility. MuDelta reduced intestinal contractility and inhibited neurogenically-mediated secretion. Very low plasma levels of MuDelta were detected after oral administration. Stress up-regulated δ opioid receptor expression in colonic epithelial cells. In stressed mice, MuDelta normalized GI transit and faecal output to control levels over a wide dose range, whereas loperamide had a narrow dose range. MuDelta and loperamide reduced upper GI transit in the post-inflammatory model.

CONCLUSIONS AND IMPLICATIONS

MuDelta normalizes, but does not prevent, perturbed GI transit over a wide dose-range in mice. These data support the subsequent assessment of MuDelta in a clinical phase II trial in patients with diarrhoea-predominant irritable bowel syndrome.     

Prediction of response to antiretroviral therapy by human experts and by the EuResist data‐driven expert system (the EVE study)

Objectives

The EuResist expert system is a novel data‐driven online system for computing the probability of 8‐week success for any given pair of HIV‐1 genotype and combination antiretroviral therapy regimen plus optional patient information. The objective of this study was to compare the EuResist system vs. human experts (EVE) for the ability to predict response to treatment.

Methods

The EuResist system was compared with 10 HIV‐1 drug resistance experts for the ability to predict 8‐week response to 25 treatment cases derived from the EuResist database validation data set. All current and past patient data were made available to simulate clinical practice. The experts were asked to provide a qualitative and quantitative estimate of the probability of treatment success.

Results

There were 15 treatment successes and 10 treatment failures. In the classification task, the number of mislabelled cases was six for EuResist and 6–13 for the human experts [mean±standard deviation (SD) 9.1±1.9]. The accuracy of EuResist was higher than the average for the experts (0.76 vs. 0.64, respectively). The quantitative estimates computed by EuResist were significantly correlated (Pearson r=0.695, P<0.0001) with the mean quantitative estimates provided by the experts. However, the agreement among experts was only moderate (for the classification task, inter‐rater κ=0.355; for the quantitative estimation, mean±SD coefficient of variation=55.9±22.4%).

Conclusions

With this limited data set, the EuResist engine performed comparably to or better than human experts. The system warrants further investigation as a treatment‐decision support tool in clinical practice.     

Extensive nodular cutaneous amyloidosis: an unusual presentation

Amyloidosis is characterized by the deposition of a group of unrelated proteins leading to changes in tissue architecture and function. The nodular variant is the rarest form of the cutaneous amyloidoses. We report a patient with localized nodular amyloidosis without systemic amyloid involvement or paraproteinaemia after 6 years of follow-up. The unusual aspects of our case were a plaque presentation rather than nodular, and the disseminated pattern observed.