[«Sulfonamide allergy¼ - which drugs must patients avoid?]. / «Sulfaallergi¼ - hvilke legemidler må pasienten unngå?

Allergic reactions to sulfonamide antibiotics are common. A number of other drugs (for example diuretics, anti-diabetic drugs, cyclooxygenase-2 inhibitors and triptans) are also chemically speaking sulphonamides, and many of these are considered to be contraindicated in patients who have experienced an allergic reaction to sulfonamide antibiotics. What is the risk of allergic cross-reactivity between different sulfonamides and to what extent must this be taken into account in clinical practice?

A gene expression pattern in blood for the early detection of Alzheimer's disease.

A whole genome screen was performed using oligonucleotide microarray analysis on blood from a large clinical cohort of Alzheimer's disease (AD) patients and control subjects as clinical sample. Blood samples for total RNA extraction were collected in PAXgene tubes, and gene expression analysis performed on the AB1700 Whole Genome Survey Microarrays. When comparing the gene expression of 94 AD patients and 94 cognitive healthy controls, a Jackknife gene selection based method and Partial Least Square Regression (PLSR) was used to develop a disease classifier algorithm, which gives a test score indicating the presence (positive) or absence (negative) of AD. This algorithm, based on 1239 probes, was validated in an independent test set of 63 subjects comprising 31 AD patients, 25 age-matched cognitively healthy controls, and 7 young controls. This algorithm correctly predicted the class of 55/63 (accuracy 87%), including 26/31 AD samples (sensitivity 84%) and 29/32 controls (specificity 91%). The positive likelihood ratio was 8.9 and the area under the receiver operating characteristic curve (ROC AUC) was 0.94. Furthermore, the algorithm also discriminated AD from Parkinson's disease in 24/27 patients (accuracy 89%). We have identified and validated a gene expression signature in blood that classifies AD patients and cognitively healthy controls with high accuracy and show that alterations specific for AD can be detected distant from the primary site of the disease.

Gene expression profiling of peripheral blood cells for early detection of breast cancer.

INTRODUCTION: Early detection of breast cancer is key to successful treatment and patient survival. We have previously reported the potential use of gene expression profiling of peripheral blood cells for early detection of breast cancer. The aim of the present study was to refine these findings using a larger sample size and a commercially available microarray platform. METHODS: Blood samples were collected from 121 females referred for diagnostic mammography following an initial suspicious screening mammogram. Diagnostic work-up revealed that 67 of these women had breast cancer while 54 had no malignant disease. Additionally, nine samples from six healthy female controls were included. Gene expression analyses were conducted using high density oligonucleotide microarrays. Partial Least Squares Regression (PLSR) was used for model building while a leave-one-out (LOO) double cross validation approach was used to identify predictors and estimate their prediction efficiency. RESULTS: A set of 738 probes that discriminated breast cancer and non-breast cancer samples was identified. By cross validation we achieved an estimated prediction accuracy of 79.5% with a sensitivity of 80.6% and a specificity of 78.3%. The genes deregulated in blood of breast cancer patients are related to functional processes such as defense response, translation, and various metabolic processes, such as lipid- and steroid metabolism. CONCLUSIONS: We have identified a gene signature in whole blood that classifies breast cancer patients and healthy women with good accuracy supporting our previous findings.

Assessment of transport rates of proteins and peptides across primary human alveolar epithelial cell monolayers.

In this study, we investigated bi-directional fluxes (i.e., in absorptive and secretive directions) of human serum proteins [albumin (HSA), transferrin (TF), and immunoglobulin G (IgG)] and peptides/proteins of potential therapeutic relevance [insulin (INS), glucagon-like peptide-1 (GLP-1), growth hormone (GH), and parathyroid hormone (PTH)] across tight monolayers of human alveolar epithelial cells (hAEpC) in primary culture. Apparent permeability coefficients (P(app); x10(-7)cm/s, mean+/-S.D.) for GLP-1 (6.13+/-0.87 (absorptive) versus 1.91+/-0.51 (secretive)), HSA (2.45+/-1.02 versus 0.21+/-0.31), TF (0.88+/-0.15 versus 0.30+/-0.03), and IgG (0.36+/-0.22 versus 0.15+/-0.16) were all strongly direction-dependent, i.e., net absorptive, while PTH (2.20+/-0.30 versus 1.80+/-0.77), GH (8.33+/-1.24 versus 9.02+/-3.43), and INS (0.77+/-0.15 versus 0.72+/-0.36) showed no directionality. Trichloroacetic acid precipitation analysis of tested molecules collected from donor and receiver fluids exhibited very little degradation. This is the first study on permeability data for a range of peptides and proteins across an in vitro model of the human alveolar epithelial barrier. These data indicate that there is no apparent size-dependent transport conforming to passive restricted diffusion for the tested substances across human alveolar barrier, in part confirming net absorptive transcytosis. The obtained data differ significantly from previously published reports utilising monolayers from different species. It can be concluded that the use of homologous tissue should be preferred to avoid species differences.