Time-resolved lanthanide luminescence for lab-on-a-chip detection of biomarkers on cancerous tissues.

PDMS-based microfluidic devices combined with lanthanide-based immunocomplexes have been successfully tested for the multiplex detection of biomarkers on cancerous tissues, revealing an enhanced sensitivity compared to classical organic dyes.

Circulating microRNAs as biomarkers for detection of autologous blood transfusion.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate various biological processes. Cell-free miRNAs measured in blood plasma have emerged as specific and sensitive markers of physiological processes and disease. In this study, we investigated whether circulating miRNAs can serve as biomarkers for the detection of autologous blood transfusion, a major doping technique that is still undetectable. Plasma miRNA levels were analyzed using high-throughput quantitative real-time PCR. Plasma samples were obtained before and at several time points after autologous blood transfusion (blood bag storage time 42 days) in 10 healthy subjects and 10 controls without transfusion. Other serum markers of erythropoiesis were determined in the same samples. Our results revealed a distinct change in the pattern of circulating miRNAs. Ten miRNAs were upregulated in transfusion samples compared with control samples. Among these, miR-30b, miR-30c, and miR-26b increased significantly and showed a 3.9-, 4.0-, and 3.0-fold change, respectively. The origin of these miRNAs was related to pulmonary and liver tissues. Erythropoietin (EPO) concentration decreased after blood reinfusion. A combination of miRNAs and EPO measurement in a mathematical model enhanced the efficiency of autologous transfusion detection through miRNA analysis. Therefore, our results lay the foundation for the development of miRNAs as novel blood-based biomarkers to detect autologous transfusion.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Early detection of idiopathic Parkinson's disease based on magnetic resonance imaging

The diagnosis of idiopathic Parkinson's disease (IPD) is entirely clinical. The fact that neuronal damage begins 5-10 years before occurrence of sub-clinical signs, underlines the importance of preclinical diagnosis. A new approach for in-vivo pathophysiological assessment of IPD-related neurodegeneration was implemented based on recently developed neuroimaging methods. It is based on non- invasive magnetic resonance data sensitive to brain tissue property changes that precede macroscopic atrophy in the early stages of IPD. This research aims to determine the brain tissue property changes induced by neurodegeneration that can be linked to clinical phenotypes which will allow us to create a predictive model for early diagnosis in IPD. We hypothesized that the degree of disease progression in IPD patients will have a differential and specific impact on brain tissue properties used to create a predictive model of motor and non-motor impairment in IPD. We studied the potential of in-vivo quantitative imaging sensitive to neurodegeneration- related brain tissue characteristics to detect changes in patients with IPD. We carried out methodological work within the well established SPM8 framework to estimate the sensitivity of tissue probability maps for automated tissue classification for detection of early IPD. We performed whole-brain multi parameter mapping at high resolution followed by voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) comparing healthy subjects to IPD patients. We found a trend demonstrating non-significant tissue property changes in the olfactory bulb area using the MT and R1 parameter with p<0.001. Comparing to the IPD patients, the healthy group presented a bilateral higher MT and R1 intensity in this specific functional region. These results did not correlate with age, severity or duration of disease. We failed to demonstrate any changes with the R2* parameter. We interpreted our findings as demyelination of the olfactory tract, which is clinically represented as anosmia. However, the lack of correlation with duration or severity complicates its implications in the creation of a predictive model of impairment in IPD.

Treatment and detection of ALK-rearranged NSCLC.

The recent approval of crizotinib for the treatment of anaplastic lymphoma kinase (ALK)-rearranged advanced non-small cell lung cancer (NSCLC) in the US and other countries has provoked intense interest in ALK rearrangements as oncogenic drivers, and promises to revolutionise the way in which NSCLC is diagnosed and treated. Here, we review clinical data to date for the use of crizotinib to treat patients with advanced, ALK-positive NSCLC and consider issues surrounding the detection of ALK-positivity including the use of fluorescence in situ hybridisation and the other potential techniques available, and their suitability for ALK screening. We also discuss the emergence of resistance to crizotinib therapy and the range of other ALK inhibitors currently in development.

Enhanced sensitivity detection of protein immobilization by fluorescent interference on oxidized silicon.

We present a silicon chip-based approach for the enhanced sensitivity detection of surface-immobilized fluorescent molecules. Green fluorescent protein (GFP) is bound to the silicon substrate by a disuccinimidyl terephtalate-aminosilane immobilization procedure. The immobilized organic layers are characterized by surface analysis techniques, like ellipsometry, atomic force microscopy (AFM) and X-ray induced photoelectron spectroscopy. We obtain a 20-fold enhancement of the fluorescent signal, using constructive interference effects in a fused silica dielectric layer, deposited before immobilization onto the silicon. Our method opens perspectives to increase by an order of magnitude the fluorescent response of surface immobilized DNA- or protein-based layers for a variety of biosensor applications.

Simple method for detection of MYH11 DNA rearrangements in patients with inv(16)(p13q22) and acute myeloid leukemia.

The pericentric inversion on chromosome 16 [inv(16)(p13q22)] and related t(16;16)(p13;q22) are recurrent aberrations associated with acute myeloid leukemia (AML) M4 Eo. Both abberations result in a fusion of the core binding factor beta (CBFB) and smooth muscle myosin heavy chain gene (MYH11). A selected genomic 6.9-kb BamHl probe detects MYH11 DNA rearrangements in 18 of 19 inv(16)/t(16;16) patients tested using HindIII digested DNA. The rearranged fragments were not detectable after remission in two cases tested, while they were present after relapse in one of these two cases tested.

The application of NMR and MS methods for detection of adulteration of wine, fruit juices, and olive oil. A review

This review covers two important techniques, high resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), used to characterize food products and detect possible adulteration of wine, fruit juices, and olive oil, all important products of the Mediterranean Basin. Emphasis is placed on the complementary use of SNIF-NMR (site-specific natural isotopic fractionation nuclear magnetic resonance) and IRMS (isotope-ratio mass spectrometry) in association with chemometric methods for detecting the adulteration.

Characterization and detection of naturally occurring antibodies against IL-1 alpha and IL-1 beta in normal human plasma.

During the development and testing of a radioreceptor assay (RRA) for human IL-1, we have detected and identified the presence of auto-antibodies to IL-1 in normal human plasma (NHP). The RRA is based on the competition between human 125I-labeled rIL-1 alpha and standard or unknown quantities of IL-1 alpha or IL-1 beta for binding to a limited amounts of IL-1 receptor (IL-1R) isolated from the EL4 mouse thymoma cell line. NHP from 20 out of 100 unselected blood donors were found to completely inhibit the binding of 125I-labeled IL-1 alpha to its receptor, suggesting the presence in these NHP samples of either abnormal amounts of IL-1 or of a factor binding to the 125I-labeled IL-1 alpha. Special care was taken to ascertain that the inhibitory factors were antibodies and not soluble IL-1 receptor antagonist. When plasma samples with inhibiting activity were incubated with labeled IL-1 alpha and chromatographed on a Sephadex G200 column, they were found to contain 125I-labeled complexes with an apparent molecular weight of 150-200kD. The IL-1 binding factor could be eliminated from plasma by incubation with protein A-Sepharose, suggesting that it consisted in IgG antibodies directed against IL-1. Furthermore, the antibody nature of the inhibiting factor was confirmed by its binding to purified rIL-1 coupled to Sepharose. Screening of 200 NHP samples by incubation with 100 pg of 125I-labeled IL-1 followed by precipitation with 12% of polyethylene glycol (PEG) confirmed that about 25% of NHP contain detectable IgG antibodies to IL-1 alpha, while only 2% of NHP contain antibodies to IL-1 beta. No correlation between the presence of these anti-IL-1 antibodies and any particular major histocompatibility complex or any pathological conditions was detected. We suggest that all serum samples assayed for IL-1 alpha or IL-1 beta content should be pretested with the PEG precipitation assay described here.

Contribution of ultrasonographic examination to the prenatal detection of chromosomal abnormalities in 19 centres across Europe.

The objective of this study was to evaluate the prenatal detection of chromosomal abnormalities by fetal ultrasonographic examination in a large database provided by 19 Registries of Congenital Anomalies from 11 European countries. This study included 1738 cases of chromosomal abnormalities, liveborn, stillborn or termination of pregnancy regardless of maternal age from a population of 664,340 births during the period 1996 - 1998. The most frequent chromosomal anomalies were Down syndrome (n=1050), trisomy 18 (n=191), Turner syndrome (n=125), trisomy 13 (n=86), and triploidy (n=56). Fetal ultrasonographic examination resulted in the prenatal detection of 37.7% of the chromosomal abnormalities, thereby resulting in a reduction of 28.6% in their prevalence at birth due to terminations of pregnancy. The detection rate by ultrasound examination varied according to local policies of prenatal diagnosis : it was lower in countries where routine scan were not performed and higher in countries in which at least one routine anomaly scan during the second trimester of pregnancy was performed. The ultrasound detection varied according to the specific chromosomal anomaly and was lowest for Klinefelter syndrome (5.7%) and highest for triploidy (78.6%). For Down syndrome it was 26.4%. Termination of pregnancy was performed in 75.9% of the cases. Among the 655 cases detected by ultrasound, the most frequent ultrasound signs by category of chromosomal abnormalities were analysed. This study shows that ultrasound screening is an important tool in the prenatal detection of chromosomal abnormalities in Europe, leading to a significant reduction in the prevalence of livebirth children with chromosomal anomalies.

Reference Cluster Normalization Improves Detection of Frontotemporal Lobar Degeneration by Means of FDG-PET.

Positron emission tomography with [18F] fluorodeoxyglucose (FDG-PET) plays a well-established role in assisting early detection of frontotemporal lobar degeneration (FTLD). Here, we examined the impact of intensity normalization to different reference areas on accuracy of FDG-PET to discriminate between patients with mild FTLD and healthy elderly subjects. FDG-PET was conducted at two centers using different acquisition protocols: 41 FTLD patients and 42 controls were studied at center 1, 11 FTLD patients and 13 controls were studied at center 2. All PET images were intensity normalized to the cerebellum, primary sensorimotor cortex (SMC), cerebral global mean (CGM), and a reference cluster with most preserved FDG uptake in the aforementioned patients group of center 1. Metabolic deficits in the patient group at center 1 appeared 1.5, 3.6, and 4.6 times greater in spatial extent, when tracer uptake was normalized to the reference cluster rather than to the cerebellum, SMC, and CGM, respectively. Logistic regression analyses based on normalized values from FTLD-typical regions showed that at center 1, cerebellar, SMC, CGM, and cluster normalizations differentiated patients from controls with accuracies of 86%, 76%, 75% and 90%, respectively. A similar order of effects was found at center 2. Cluster normalization leads to a significant increase of statistical power in detecting early FTLD-associated metabolic deficits. The established FTLD-specific cluster can be used to improve detection of FTLD on a single case basis at independent centers - a decisive step towards early diagnosis and prediction of FTLD syndromes enabling specific therapies in the future.