Effects of antidiabetic drugs on dipeptidyl peptidase IV activity: Nateglinide is an inhibitor of DPP IV and augments the antidiabetic activity of glucagon-like peptide-1

Dipeptidyl peptidase IV (DPP IV) is the primary inactivator of glucoregulatory incretin hormones. This has lead to development of DPP IV inhibitors as a new class of agents for the treatment of type 2 diabetes. Recent reports indicate that other antidiabetic drugs, such as metformin, may also have inhibitory effects on DPP IV activity. In this investigation we show that high concentrations of several antidiabetic drug classes, namely thiazolidinediones, sulphonylureas, meglitinides and morphilinoguanides can inhibit DPP IV The strongest inhibitor nateglinide, the insulin-releasing meglitinide was effective at low therapeutically relevant concentrations as low as 25 mu mol/l. Nateglinide also prevented the degradation of glucagon-like peptide-1 (GLP-1) by DPP IV in a time and concentration-dependent manner. In vitro nateglinide and GLP-1 effects on insulin release were additive. In vivo nateglinide improved the glucose-lowering and insulin-releasing activity of GLP-1 in obese-diabetic ob/ob mice. This was accompanied by significantly enhanced circulating concentrations of active GLP-1(7-36)amide and lower levels of DPP IV activity. Nateglinide similarly benefited the glucose and insulin responses to feeding in ob/ob mice and such actions were abolished by coadministration of exendin(9-39) and (Pro(3))GIP to block incretin hormone action. These data indicate that the use of nateglinide as a prandial insulin-releasing agent may partly rely on inhibition of GLP-1 degradation as well as beta-cell K-ATP channel inhibition. (C) 2007 Elsevier B.V. All rights reserved.

British drugs policy: Problematizing the distinction between legal and illegal drugs and the definition of the ‘drugs problem’.

This article draws upon an extensive literature review of the social and medical sciences, official documents and various websites to critically re-evaluate the basis of British drugs policy. The article problematizes the rationale for criminalizing certain substances and questions the distinctions created between legal and illegal drugs; in so doing, the article argues that the definition of the `drugs problem' is the real problem. It shows that the debate on illegal drugs is filled less with factual truths and more with misinformation which creates public fear and provides a questionable basis for public policy. The article questions current thinking regarding the drugs/crime relationship and concludes by exploring some implications for policy and practice.

sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.

Results
This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies.

Conclusion
The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Background

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006), Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures.

Results

Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively). Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method.

Conclusion

The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.

The Effects of Anti-Hypertensive Drugs Evaluated Using Markov Modelling for Northern Ireland Chronic Kidney Disease Patients

The aim of this paper is to use Markov modelling to
investigate survival for particular types of kidney patients
in relation to their exposure to anti-hypertensive treatment
drugs. In order to monitor kidney function an intuitive three
point assessment is proposed through the collection of blood
samples in relation to Chronic Kidney Disease for Northern
Ireland patients. A five state Markov Model was devised
using specific transition probabilities for males and
females over all age groups. These transition probabilities
were then adjusted appropriately using relative risk scores
for the event death for different subgroups of patients. The
model was built using TreeAge software package in order to
explore the effects of anti-hypertensive drugs on patients.