Neuropeptide YY1 receptor in human dental pulp cells of noncarious and carious teeth

Aim To determine the distribution of the NPY Y1 receptor in carious and noncarious human dental pulp tissue using immunohistochemistry. A subsidiary aim was to confirm the presence of the NPY Y1 protein product in membrane fractions of dental pulp tissue from carious and noncarious teeth using western blotting. Methodology Twenty two dental pulp samples were collected from carious and noncarious extracted teeth. Ten samples were processed for immunohistochemistry using a specific antibody to the NPY Y1 receptor. Twelve samples were used to obtain membrane extracts which were electrophoresed, blotted onto nitrocellulose and probed with NPY Y1 receptor antibody. Kruskal-Wallis one-way analysis of variance was employed to test for overall statistical differences between NPY Y1 levels in noncarious, moderately carious and grossly carious teeth. Results Neuropeptide Y Y1 receptor immunoreactivity was detected on the walls of blood vessels in pulp tissue from noncarious teeth. In carious teeth NPY Y1 immunoreactvity was observed on nerve fibres, blood vessels and inflammatory cells. Western blotting indicated the presence and confirmed the variability of NPY Y1 receptor protein expression in solubilised membrane preparations of human dental pulp tissue from carious and noncarious teeth. Conclusions Neuropeptide Y Y1 is expressed in human dental pulp tissue with evidence of increased expression in carious compared with noncarious teeth, suggesting a role for NPY Y1 in modulation of caries induced pulpal inflammation. © 2008 International Endodontic Journal.

Neuropeptides Regulate Expression of Angiogenic Growth Factors in Human Dental Pulp Fibroblasts

Abstract
INTRODUCTION:
Neuropeptides play an important role in inflammation and repair and have been implicated in mediating angiogenesis. Pulp fibroblasts express neuropeptide receptors, and the aim of this research was to investigate whether neuropeptides could regulate angiogenic growth factor expression in vitro
METHODS:
An angiogenic array was used to determine the levels of 10 angiogenic growth factors expressed by human pulp fibroblasts.
RESULTS:
Pulp fibroblasts were shown to express angiogenin, angiopoietin-2, epidermal growth factor, basic fibroblast growth factor, heparin-binding epidermal growth factor, hepatocyte growth factor, leptin, platelet-derived growth factor, placental growth factor, and vascular endothelial growth factor. Furthermore, the neuropeptides substance P, calcitonin gene-related peptide, vasoactive intestinal polypeptide, and neuropeptide Y altered angiogenic growth factor expression in vitro.
CONCLUSIONS:
The regulation of angiogenic growth factor expression by neuropeptides suggests a novel role for neuropeptides in pulpal inflammation and repair.

Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals

A fundamental aspect of health care management is the effective allocation of resources. This is of particular importance in geriatric hospitals where elderly patients tend to have more complex needs. Hospital managers would benefit immensely if they had advance knowledge of patient duration of stay in hospital. Managers could assess the costs of patient care and make allowances for these in their budget. In this paper, we tackle this important problem via a model which predicts the duration of stay distribution of patients in hospital. The approach uses phase-type distributions conditioned on a Bayesian belief network.

Using Coxian Phase-Type Distributions to Identify Patient Characteristics for Duration of Stay in Hospital

Coxian phase-type distributions are a special type of Markov model that describes duration until an event occurs in terms of a process consisting of a sequence of latent phases. This paper considers the use of Coxian phase-type distributions for modelling patient duration of stay for the elderly in hospital and investigates the potential for using the resulting distribution as a classifying variable to identify common characteristics between different groups of patients according to their (anticipated) length of stay in hospital. The identification of common characteristics for patient length of stay groups would offer hospital managers and clinicians possible insights into the overall management and bed allocation of the hospital wards.