Multiplex suspension array for human anti-carbohydrate antibody profiling

Glycan-binding antibodies form a significant subpopulation of both natural and acquired antibodies and play an important role in various immune processes. They are for example involved in innate immune responses, cancer, autoimmune diseases, and neurological disorders. In the present study, a microsphere-based flow-cytometric immunoassay (suspension array) was applied for multiplexed detection of glycan-binding antibodies in human serum. Several approaches for immobilization of glycoconjugates onto commercially available fluorescent microspheres were compared, and as the result, the design based on coupling of end-biotinylated glycopolymers has been selected. This method requires only minute amounts of glycans, similar to a printed glycan microarray. The resulting glyco-microspheres were used for detection of IgM and IgG antibodies directed against ABO blood group antigens. The possibility of multiplexing this assay was demonstrated with mixtures of microspheres modified with six different ABO related glycans. Multiplexed detection of anti-glycan IgM and IgG correlated well with singleplex assays (Pearson's correlation coefficient r = 0.95-0.99 for sera of different blood groups). The suspension array in singleplex format for A/B trisaccharide, H(di) and Le(x) microspheres corresponded well to the standard ELISA (r > 0.94). Therefore, the described method is promising for rapid, sensitive, and reproducible detection of anti-glycan antibodies in a multiplexed format.

Thin-Film Sparse Boundary Array Design for Passive Acoustic Mapping During Ultrasound Therapy

A new 2-D hydrophone array for ultrasound therapy monitoring is presented, along with a novel algorithm for passive acoustic mapping using a sparse weighted aperture. The array is constructed using existing polyvinylidene fluoride (PVDF) ultrasound sensor technology, and is utilized for its broadband characteristics and its high receive sensitivity. For most 2-D arrays, high-resolution imagery is desired, which requires a large aperture at the cost of a large number of elements. The proposed array's geometry is sparse, with elements only on the boundary of the rectangular aperture. The missing information from the interior is filled in using linear imaging techniques. After receiving acoustic emissions during ultrasound therapy, this algorithm applies an apodization to the sparse aperture to limit side lobes and then reconstructs acoustic activity with high spatiotemporal resolution. Experiments show verification of the theoretical point spread function, and cavitation maps in agar phantoms correspond closely to predicted areas, showing the validity of the array and methodology.

A 20-channel receive-only mouse array coil for a 3 T clinical MRI system

A 20-channel phased-array coil for MRI of mice has been designed, constructed, and validated with bench measurements and high-resolution accelerated imaging. The technical challenges of designing a small, high density array have been overcome using individual small-diameter coil elements arranged on a cylinder in a hexagonal overlapping design with adjacent low impedance preamplifiers to further decouple the array elements. Signal-to-noise ratio (SNR) and noise amplification in accelerated imaging were simulated and quantitatively evaluated in phantoms and in vivo mouse images. Comparison between the 20-channel mouse array and a length-matched quadrature driven small animal birdcage coil showed an SNR increase at the periphery and in the center of the phantom of 3- and 1.3-fold, respectively. Comparison with a shorter but SNR-optimized birdcage coil (aspect ratio 1:1 and only half mouse coverage) showed an SNR gain of twofold at the edge of the phantom and similar SNR in the center. G-factor measurements indicate that the coil is well suited to acquire highly accelerated images.

MicroRNA Expression Array Identifies Novel Diagnostic Markers for Conventional and Oncocytic Follicular Thyroid Carcinomas

Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

SNP array profiling of childhood adrenocortical tumors reveals distinct pathways of tumorigenesis and highlights candidate driver genes

Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization.

A Faster Circular Binary Segmentation Algorithm for the Analysis of Array CGH Data

Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.

Detection of erythropoietin in exhaled breath condensate of nonhypoxic subjects using a multiplex bead array

As a noninvasive method, exhaled breath condensate (EBC) has gained importance to improve monitoring of lung diseases and to detect biomarkers. The aim of the study was to investigate, whether erythropoietin (EPO) is detectable in EBC. EBC was collected from 22 consecutive patients as well as from healthy individuals. Using a multiplex fluorescent bead immunoassay, we detected EPO in EBC, as well as tumour necrosis factor-alpha (TNF-alpha) in 13 out of 22 patients simultaneously (EPO 0.21 +/- 0.03 in U/mL and TNF-alpha 34.6 +/- 4.2 in pg/mL, mean +/- SEM). No significant differences for EPO levels or correlation between EPO and TNF-alpha were found but TNF-alpha was significantly higher in patients with chronic obstructive pulmonary disease (COPD) than in non-COPD (obstructive sleep apnoea, OSA, and lung healthy patients). This is the first report of detection of EPO in EBC. Due to the small study size more data is needed to clarify the role of EPO in EBC.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.