Fish evaluation of additional cytogenetic aberrations and hyperdiploidy in childhood Burkitt lymphoma.

Beyond MYC rearrangement, Burkitt lymphoma (BL) often presents with additional aberrations. Biopsy touch imprints from 72 children with BL were tested with interphase fluorescence in-situ hybridization (i-FISH) for MYC, BCL2, BCL6, IGH, IGK and IGL rearrangements and copy-number aberrations involving 1q21/1p32, 7cen/7q31, 9cen/9p21, 13q14/13q34 and 17cen/17p13. Diploid status deviations were investigated with chromosome enumeration probes. MYC rearrangement was demonstrated in all cases. Additional aberrations included +1q (21/72:29.2%), +7q (14/72:19.4%), 13q- (14/72:19.4%), 9p-(6/72:8.3%) and hyperdiploidy (6/72:8.3%). Advanced clinical stage IV, +7q and 9p- were associated with shorter overall survival, with stage IV and +7q retaining prognostic significance on multivariate analysis. No relapse or death was reported among the hyperdiploid cases. This i-FISH investigation provides information on the genetic profile of BL and may prove valuable for patients with no karyotype analysis. Demonstration of hyperdiploidy could evolve research on clonal evolution pathways and probably identify a subgroup of children with favorable prognosis.

Contribution of immunophenotype to the investigation and differential diagnosis of Burkitt lymphoma, double-hit high-grade B-cell lymphoma, and single-hit MYC-rearranged diffuse large B-cell lymphoma.

BACKGROUND: There are no immunophenotypic guidelines for the investigation of MYC-rearranged lymphomas. We aimed to identify simple immunophenotypic features that would help to differentiate between MYC-rearranged lymphomas and guide cytogenetic analysis. METHODS: We reviewed diagnostic samples from patients diagnosed with Burkitt lymphoma (BL), double-hit lymphoma (DHL), MYC-rearranged diffuse large B-cell lymphoma (MYC-DLBCL), and standard (non-MYC-rearranged) DLBCL over the last decade in our Institution. Using flow cytometry (with antibodies CD20, CD10, CD38, bcl-2, Ki-67, FMC-7, CD43, CD27, CD79b, CD23, and CD22) we determined antigen% expression and median-fluorescence intensity ratios (MFIR). The forward scatter (FS) and side scatter (SS) characteristics of tumor B-cells were compared with normal T-cells (B/T ratios) for patients with MYC-rearranged lymphomas. RESULTS: We identified 51 patients of whom 14 had BL, 10 had DHL (6 MYC+/BCL2+; 4 MYC+/BCL6+), 8 MYC-DLBCL, and 19 standard DLBCL. The significant differences (p <.05) were: higher CD38% in BL than standard DLBCL; higher CD10% in BL and DHL versus MYC-DLBCL and standard DLBCL; higher CD10MFIR in BL than MYC-DLBCL and standard DLBCL; higher Ki-67% in BL than DHL and MYC-DLBCL; higher bcl-2% in DHL than BL; higher FMC-7% in BL than MYC-DLBCL and standard DLBCL; and lower SS (B/T) ratio in DHL than MYC-DLBCL. CONCLUSIONS: The combination of CD38% > 90, CD10% > 80, CD10MFIR > 10, bcl-2% < 30, and Ki-67% > 70 was characteristic of BL. "Deviation" from these cut-offs should raise suspicion for DHL and, therefore, BCL2 and/or BCL6 FISH is required. We also found that a diagnosis of DHL rather than of MYC-DLBCL was significantly associated with CD10% > 60, Ki-67% > 50, and SS (B/T) <1.5.

Flow cytometric predictive scoring systems for common fusions ETV6/RUNX1, BCR/ABL1, TCF3/PBX1 and rearrangements of the KMT2A gene, proposed for the initial cytogenetic approach in cases of B-acute lymphoblastic leukemia.

INTRODUCTION: In B-acute lymphoblastic leukemia (B-ALL), the identification of cytogenetic prognostic factors is important for stratifying patients into risk groups and tailoring treatment accordingly. The purpose of this study was to propose flow cytometric (FCM) scoring systems (SSs) for predicting t(12;21)(p13;q22), t(9;22)(q34;q11), t(11q23), and t(1;19)(q23;p13.3) translocations. METHODS: We analyzed retrospectively the FCM immunophenotype of 377 patients with B-ALL with regard to the major cytogenetic findings revealed by interphase fluorescence in situ hybridization (i-FISH). Comparing descriptive data on the expression of each antigen and performing receiver operating characteristic (ROC) analysis, we identified the most reliable predictive markers for each translocation and sought to establish a specific SS for each translocation, based on specific antibody panels. RESULTS: CD27, CD9, CD66c, CD10, CD25, and CD34 were employed for the prediction of t(12;21), CD25, CD38, CD34, and CD66c for t(9;22), NG2, CD10, CD15, CD34, and CD20 for t(11q23), and CD34, cµ, CD123, and CD66c for t(1;19). The sensitivity and specificity, respectively, of each predictive score were 89.29% and 96.15% for t(12;21), 75.00% and 88.19% for t(9;22), 84.21% and 99.04% for t(11q23), and 85.71% and 92.71% for t(1;19). CONCLUSION: Four highly specific and significantly sensitive FCM-obtained SSs are proposed for the prediction of the four major translocations observed in patients with B-ALL. Prospective evaluation of the proposed SSs could lead to a better targeted cytogenetic investigation and therefore to more cost-effective laboratory practice.

An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com.

Exploiting multispectral imaging for non-invasive contamination assessment and mapping of meat samples.

Recently, imaging and machine vision are gaining attention to food stakeholders since these are considered to be the emerging tools for food safety and quality assessment throughout the whole food chain. Herein, multispectral imaging, a surface chemistry sensor type, has been evaluated in terms of monitoring aerobically packaged beef filet spoilage at different storage temperatures (2, 8, and 15°C) and storage time. Spectral data acquired from the surface of meat samples (with/without background flora; +BF/-BF respectively) along with microbiological analysis. Qualitative analysis was employed for the discrimination of meat samples in two microbiological quality classes based on the values of total viable counts (TVC<2log10CFU/g and TVC>2log10CFU/g). Furthermore, a Support Vector Regression model was developed to provide quantitative estimations of microbial counts during storage. Results exhibit good performance with overall correct classification rate for the two quality classes ranging from 89.2% to 80.8% for model validation. The calculated regression results to an R-square of 0.98.

High Throughput Multispectral Image Processing with Applications in Food Science.

Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

An extended fluorescence in situ hybridization approach for the cytogenetic study of cholangiocarcinoma on endoscopic retrograde cholangiopancreatography brushing cytology preparations.

The cytological diagnosis of cholangiocarcinoma has been significantly aided by applying a 4-probe fluorescence in situ hybridization system on endoscopic retrograde cholangiopancreatography brushing smears, aiming mainly at the detection of hyperdiploidy. However, this approach adds little to our understanding of the genetic background of the disease. With the prospect of obtaining additional data on chromosomal aberrations, we have extended the fluorescence in situ hybridization study, with the application of 4 independent 2-probe systems in 35 patients with documented cholangiocarcinoma. Fluorescence in situ hybridization assays were performed on endoscopic retrograde cholangiopancreatography brushing smears, with probes for the 7q31, 11q13 (CCND1), 17p53 (TP53), and 9p21 (INK4 locus) bands, together with the respective centromeric probe. Hyperdiploidy, involving at least 2 of the 4 chromosomes targeted, was found in 31 patients. 17p13 deletion was detected in 3, and 9p21 deletion, in 5 of the hyperdiploid cases, with the 2 aberrations concurrent in 1. CCND1 amplification was found in 1 case as the sole abnormality and in another together with hyperdiploidy, but in apparently unrelated clones. This work indicates that interphase fluorescence in situ hybridization is a practical and useful tool for the cytogenetic study of cholangiocarcinoma on endoscopic retrograde cholangiopancreatography brushing smears, which is often the only available tissue specimen of the tumor. Apart from hyperdiploidy, it provides additional data on the genetic profile of cholangiocarcinoma, especially regarding structural chromosomal aberrations and clonal diversity. This line of investigation may prove useful in the delineation of oncogenesis and the interpretation of the diverse clinical features of the disease.

Gallium-nitride-based plasmonic multilayer operating at 1.55 µm.

In this Letter, we have designed and fabricated a III-V semiconductor multilayer based on surface plasmon resonance (SPR) operating at the telecom wavelength. Optimization of the optogeometrical parameters and the metal/semiconductor layers required for this novel structure was conducted accurately by theoretical tools using the Maxwell equations. Technological fabrication of the device and its experimental characterizations using an evanescent coupling configuration was performed: the results have confirmed the existence of SPR associated to a sharp width response. This study could be a first step in the design of new plasmonic-semiconductor-based optical devices such as modulators and switches.

A self-supporting monolith of highly aligned carbon nanotubes as device structure for sensor applications.

A novel approach towards fabricating free-standing and self-supporting highly aligned CNT arrays with integrated top and bottom contacts for the design and implementation of future CNT-based sensor devices is reported.