Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma.

PURPOSE: To develop an image analysis technique that distinguishes pseudoprogression from true progression by analyzing tumour heterogeneity in T2-weighted images using topological descriptors of image heterogeneity called Minkowski functionals (MFs). METHODS: Using a retrospective patient cohort (n = 50), and blinded to treatment response outcome, unsupervised feature estimation was performed to investigate MFs for the presence of outliers, potential confounders, and sensitivity to treatment response. The progression and pseudoprogression groups were then unblinded and supervised feature selection was performed using MFs, size and signal intensity features. A support vector machine model was obtained and evaluated using a prospective test cohort. RESULTS: The model gave a classification accuracy, using a combination of MFs and size features, of more than 85% in both retrospective and prospective datasets. A different feature selection method (Random Forest) and classifier (Lasso) gave the same results. Although not apparent to the reporting radiologist, the T2-weighted hyperintensity phenotype of those patients with progression was heterogeneous, large and frond-like when compared to those with pseudoprogression. CONCLUSION: Analysis of heterogeneity, in T2-weighted MR images, which are acquired routinely in the clinic, has the potential to detect an earlier treatment response allowing an early change in treatment strategy. Prospective validation of this technique in larger datasets is required.

Investigation of transcriptional responses of juvenile mouse bone marrow to power frequency magnetic fields.

To seek alterations in gene transcription in bone marrow cells following in vivo exposure of juvenile mice to power frequency magnetic fields, young (21-24-day old) C57BL/6 mice were exposed to a 100µT 50Hz magnetic field for 2h. Transcription was analysed by three methods, High Coverage Expression Profiling (HiCEP), Illumina microarrays and quantitative real-time polymerase chain reaction (QRT-PCR). A pilot HiCEP experiment with 6 exposed (E) and 6 non-exposed (NE) mice identified four candidate responsive transcripts (two unknown transcripts (AK152075 and F10-NED), phosphatidylinositol binding clathrin assembly protein (Picalm) and exportin 7 (Xpo7)). A larger experiment compared 19 E and 15 NE mice using two independent QRT-PCR assays and repeated microarray assays. No significant field-dependent changes were seen, although Picalm showed a trend to significance in one QRT-PCR assay (E/NE=0.91; P=0.06). However, the study was underpowered to detect an effect of this magnitude (52% power at P=0.05). These data indicate the current experimental constraints in detecting small changes in transcription that may occur in response to magnetic fields. These constraints result from technical limitations in the accuracy of assays and biological variation, which together were sufficient to account statistically for the number of differentially expressed transcripts identified in the pilot experiment.

Gene expression profiles in white blood cells of volunteers exposed to a 50 Hz electromagnetic field.

Consistent and independently replicated laboratory evidence to support a causative relationship between environmental exposure to extremely low-frequency electromagnetic fields (EMFs) at power line frequencies and the associated increase in risk of childhood leukemia has not been obtained. In particular, although gene expression responses have been reported in a wide variety of cells, none has emerged as robust, widely replicated effects. DNA microarrays facilitate comprehensive searches for changes in gene expression without a requirement to select candidate responsive genes. To determine if gene expression changes occur in white blood cells of volunteers exposed to an ELF-EMF, each of 17 pairs of male volunteers age 20-30 was subjected either to a 50 Hz EMF exposure of 62.0 ± 7.1 µT for 2 h or to a sham exposure (0.21 ± 0.05 µT) at the same time (11:00 a.m. to 13:00 p.m.). The alternative regime for each volunteer was repeated on the following day and the two-day sequence was repeated 6 days later, with the exception that a null exposure (0.085 ± 0.01 µT) replaced the sham exposure. Five blood samples (10 ml) were collected at 2 h intervals from 9:00 to 17:00 with five additional samples during the exposure and sham or null exposure periods on each study day. RNA samples were pooled for the same time on each study day for the group of 17 volunteers that were subjected to the ELF-EMF exposure/sham or null exposure sequence and were analyzed on Illumina microarrays. Time courses for 16 mammalian genes previously reported to be responsive to ELF-EMF exposure, including immediate early genes, stress response, cell proliferation and apoptotic genes were examined in detail. No genes or gene sets showed consistent response profiles to repeated ELF-EMF exposures. A stress response was detected as a transient increase in plasma cortisol at the onset of either exposure or sham exposure on the first study day. The cortisol response diminished progressively on subsequent exposures or sham exposures, and was attributable to mild stress associated with the experimental protocol.

Proton NMR analysis of plasma is a weak predictor of coronary artery disease.

Multivariate analysis of 1H-NMR spectra of blood sera was reported previously to predict angiographically defined advanced coronary artery disease (CAD) with >90% accuracy and specificity. The analysis depended mainly on the major lipid regions of the spectra, but many variables, including gender and drug treatment, affect lipid composition and are potential confounders. We have determined the predictive power of the same methodology for angiographically defined CAD using plasma samples from groups of male patients, classified by statin treatment, who had normal coronary arteries (NCAs) or CAD. Predictions for NCA and CAD groups were only 80.3% correct for patients not treated with statins and 61.3% for treated patients, compared with random correct predictions of 50%. A confidence limit of >99% was achieved for 36.2% of predictions for untreated groups and 6.2% for treated groups. Detection of CAD by 1H-NMR with >99% confidence was therefore very weak compared with angiography.

Transforming growth factor-beta1 inhibits thrombin activation of endothelial cells.

Transforming growth factor-beta1 (TGF-beta1) is reported to exert both pro- and anti-inflammatory effects on the chronic activation of endothelial cells (ECs) in vitro by cytokines such as tumour necrosis factor-alpha (TNF-alpha). However, the effects of TGF-beta1 on acute inflammatory responses of ECs in vitro (e.g. to thrombin) have not been characterised. Pretreatment with TGF-beta1 (10 ng/mL) effectively inhibited all the thrombin-stimulated responses in rat aortic endothelial cells (RAECs) examined: adhesion and migration of polymorphonuclear leukocytes, adhesion of platelets and lymphocytes. Substantial inhibition of thrombin stimulation occurred after 30 min of pretreatment with TGF-beta1 and maximal inhibition was obtained after 1-20 h of pretreatment. Inhibition by TGF-beta1 pretreatment for 30 min was not affected by cycloheximide and was therefore independent of protein synthesis. Treatment with TGF-beta1 for 20 h did not affect the total levels of P-selectin and von Willebrand factor (vWF) in RAECs, but reduced thrombin-stimulated recruitment of P-selectin and vWF to the cell surface. The data demonstrate that TGF-beta1 exerts a potent anti-thrombin effect on ECs, effective after long and short pretreatment times.