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Background: Central nervous system (CNS) tumors are the second most frequent type of neoplasm in childhood and adolescence, after leukemia. Despite the incorporation of molecular classification and improvement of protocols combining chemotherapy, surgery, and radiotherapy, CNS tumors are still the most lethal neoplasm in this age group. Mass spectrometry imaging (MSI) is a powerful tool to map the distribution of molecular species in tissue sections. Among MSI techniques, desorption electrospray ionization (DESI-MSI) has been demonstrated to enable reliable agreement with the pathological evaluation of different adult cancer types, along with an acceptable time scale for intraoperative use. Methods: In the present work, we aimed to investigate the chemical profile obtained by DESI-MSI as an intraoperative surgical management tool by profiling 162 pediatric brain biopsies and reporting the results according to the histopathology and molecular profile of the tumors. Results: The 2D chemical images obtained by DESI-MSI allowed us to distinguish tumor-transformed tissue from non-tumor tissue with an accuracy of 96.8% in the training set and 94.3% in the validation set after statistical modeling of our data using Lasso. In addition, high-grade and low-grade tumors also displayed a distinct chemical profile when analyzed by DESI-MSI. We also provided evidence that the chemical profile of brain tumors obtained by DESI-MSI correlates with methylation-based molecular classes and specific immunophenotypes found in brain biopsies. Conclusions: The results presented herein support the incorporation of DESI-MSI analysis as an intraoperative assistive tool in prospective clinical trials for pediatric brain tumors management in the near future. [ABSTRACT FROM AUTHOR]

Motivation The rank distance model represents genome rearrangements in multi-chromosomal genomes as matrix operations, which allows the reconstruction of parsimonious histories of evolution by rearrangements. We seek to generalize this model by allowing for genomes with different gene content, to accommodate a broader range of biological contexts. We approach this generalization by using a matrix representation of genomes. This leads to simple distance formulas and sorting algorithms for genomes with different gene contents, but without duplications. Results We generalize the rank distance to genomes with different gene content in two different ways. The first approach adds insertions, deletions and the substitution of a single extremity to the basic operations. We show how to efficiently compute this distance. To avoid genomes with incomplete markers, our alternative distance, the rank-indel distance, only uses insertions and deletions of entire chromosomes. We construct phylogenetic trees with our distances and the DCJ-Indel distance for simulated data and real prokaryotic genomes, and compare them against reference trees. For simulated data, our distances outperform the DCJ-Indel distance using the Quartet metric as baseline. This suggests that rank distances are more robust for comparing distantly related species. For real prokaryotic genomes, all rearrangement-based distances yield phylogenetic trees that are topologically distant from the reference (65% similarity with Quartet metric), but are able to cluster related species within their respective clades and distinguish the Shigella strains as the farthest relative of the Escherichia coli strains, a feature not seen in the reference tree. Availability and implementation Code and instructions are available at https://github.com/meidanis-lab/rank-indel. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Keywords: spike-in control; minimal residual disease; acute lymphoblastic leukaemia; next generation sequencing; immunoglobulin heavy-chain (IGH) EN spike-in control minimal residual disease acute lymphoblastic leukaemia next generation sequencing immunoglobulin heavy-chain (IGH) e150 e154 5 05/19/20 20200515 NES 200515 Minimal residual disease (MRD) is the strongest prognostic factor for acute lymphoblastic leukaemia (ALL). Next generation sequencing (NGS) of immunoglobulin/T-cell receptor (Ig/TCR) repertoires is a promising technology for MRD assessment, overcoming many limitations of current quantitative polymerase chain reaction (qPCR) methods. (C and D) Linear correlation between NGS MRD and quantitative polymerase chain reaction (qPCR) MRD results. Paired qPCR and NGS MRD values for 129 leukaemia markers. [Extracted from the article]

Background: Recently, Pereira Zanetti, Biller and Meidanis have proposed a new definition of a rearrangement distance between genomes. In this formulation, each genome is represented as a matrix, and the distance d is the rank distance between these matrices. Although defined in terms of matrices, the rank distance is equal to the minimum total weight of a series of weighted operations that leads from one genome to the other, including inversions, translocations, transpositions, and others. The computational complexity of the median-of-three problem according to this distance is currently unknown. The genome matrices are a special kind of permutation matrices, which we study in this paper. In their paper, the authors provide an O n 3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{3}\right)$\end{document} algorithm for determining three candidate medians, prove the tight approximation ratio 4 3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\frac {4}{3}$\end{document} , and provide a sufficient condition for their candidates to be true medians. They also conduct some experiments that suggest that their method is accurate on simulated and real data. Results: In this paper, we extend their results and provide the following: Three invariants characterizing the problem of finding the median of 3 matrices A sufficient condition for uniqueness of medians that can be checked in O(n) A faster, O n 2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{2}\right)$\end{document} algorithm for determining the median under this condition A new heuristic algorithm for this problem based on compressed sensing A O n 4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{4}\right)$\end{document} algorithm that exactly solves the problem when the inputs are orthogonal matrices, a class that includes both permutations and genomes as special cases. Conclusions: Our work provides the first proof that, with respect to the rank distance, the problem of finding the median of 3 genomes, as well as the median of 3 permutations, is exactly solvable in polynomial time, a result which should be contrasted with its NP-hardness for the DCJ (double cut-and-join) distance and most other families of genome rearrangement operations. This result, backed by our experimental tests, indicates that the rank distance is a viable alternative to the DCJ distance widely used in genome comparisons. [ABSTRACT FROM AUTHOR]

Background: Reorganization of rows and columns of a matrix does not modify data but may ease or impair visual analysis of data similarities in this structure, according to Gestalt spatial proximity laws. However, there are a factorial number of permutations of rows and columns. Matrix reordering algorithms, such as 2D sort and Sugiyama-based reordering, permute matrix rows and columns in order to highlight hidden patterns. Methods: We present PQR sort, a matrix reordering algorithm based on a recent data structure called PQR tree, and compare it with the previous ones in terms of time complexity and quality of reordering, according to predefined evaluation criteria. Results: We found that PQR sort is an interesting method for minimizing minimal span loss functions based on Jaccard or simple matching coefficients, specially for a given pattern called Rectnoise with a noise ratio of 0.01 or 0.02 and a matrix size of 100 × 100 or 1,000 × 1,000. Conclusion: We concluded that "PQR sort" is a valid alternative method for matrix reordering, which may also be extended for other visual structures. [ABSTRACT FROM AUTHOR]

Cattle are divided into 2 groups referred to as taurine and indicine, both of which have been under strong artificial selection due to their importance for human nutrition. A side effect of this domestication includes a loss of genetic diversity within each specialized breed. Recently, the first taurine genome was sequenced and assembled, allowing for a better understanding of this ruminant species. However, genetic information from indicine breeds has been limited. Here, we present the first genome sequence of an indicine breed (Nellore) generated with 52X coverage by SOLiD sequencing platform. As expected, both genomes share high similarity at the nucleotide level for all autosomes and the X chromosome. Regarding the Y chromosome, the homology was considerably lower, most likely due to uncompleted assembly of the taurine Y chromosome. We were also able to cover 97% of the annotated taurine protein-coding genes. [ABSTRACT FROM PUBLISHER]