Analysis of contingency tables based on generalised median polish with power transformations and non-additive models

Contingency tables are a very common basis for the investigation of effects of different treatments or influences on a disease or the health state of patients. Many journals put a strong emphasis on p-values to support the validity of results. Therefore, even small contingency tables are analysed by techniques like t-test or ANOVA. Both these concepts are based on normality assumptions for the underlying data. For larger data sets, this assumption is not so critical, since the underlying statistics are based on sums of (independent) random variables which can be assumed to follow approximately a normal distribution, at least for a larger number of summands. But for smaller data sets, the normality assumption can often not be justified. Robust methods like the Wilcoxon-Mann-Whitney-U test or the Kruskal-Wallis test do not lead to statistically significant p-values for small samples. Median polish is a robust alternative to analyse contingency tables providing much more insight than just a p-value. Median polish is a technique that provides more information than just a p-value. It explains the contingency table in terms of an overall effect, row and columns effects and residuals. The underlying model for median polish is an additive model which is sometimes too restrictive. In this paper, we propose two related approach to generalise median polish. A power transformation can be applied to the values in the table, so that better results for median polish can be achieved. We propose a graphical method how to find a suitable power transformation. If the original data should be preserved, one can apply other transformations – based on so-called additive generators – that have an inverse transformation. In this way, median polish can be applied to the original data, but based on a non-additive model. The non-linearity of such a model can also be visualised to better understand the joint effects of rows and columns in a contingency table

RANKL-induced DC-STAMP is essential for osteoclastogenesis

Osteoclasts are bone-resorbing, multinucleated giant cells that are essential for bone remodeling and are formed through cell fusion of mononuclear precursor cells. Although receptor activator of nuclear factor– B ligand (RANKL) has been demonstrated to be an important osteoclastogenic cytokine, the cell surface molecules involved in osteoclastogenesis are mostly unknown. Here, we report that the seven-transmembrane receptor-like molecule, dendritic cell–specific transmembrane protein (DC-STAMP) is involved in osteoclastogenesis. Expression of DCSTAMP is rapidly induced in osteoclast precursor cells by RANKL and other osteoclastogenic stimulations. Targeted inhibition of DC-STAMP by small interfering RNAs and specific antibody markedly suppressed the formation of multinucleated osteoclast-like cells. Overexpression of DC-STAMP enhanced osteoclastogenesis in the presence of RANKL. Furthermore, DC-STAMP directly induced the expression of the osteoclast marker tartrate-resistant acid phosphatase. These data demonstrate for the first time that DC-STAMP has an essential role in osteoclastogenesis.Toshio Kukita, Naohisa Wada, Akiko Kukita, Takashi Kakimoto, Ferry Sandra, Kazuko Toh, Kengo Nagata, Tadahiko Iijima, Madoka Horiuchi, Hiromi Matsusaki, Kunio Hieshima, Osamu Yoshie and Hisayuki Nomiyam

P2 receptors in macrophage fusion and osteoclast formation

Cells of the mononuclear phagocyte lineage fuse to form multinucleated giant cells and osteoclasts. Several lines of evidence suggest that P2 receptors, in particular P2X7, are involved in this process, although P2X7 is not absolutely required for fusion because P2X7-null mice form multinucleated osteoclasts. Extracellular ATP may be an important regulator of macrophage fusion

Autonomous growth potential of leukemia blast cells is associated with poor prognosis in human acute leukemias

We have described a severe combined immunodeficiency (SCID) mouse model that permits the subcutaneous growth of primary human acute leukemia blast cells into a measurable subcutaneous nodule which may be followed by the development of disseminated disease. Utilizing the SCID mouse model, we examined the growth potential of leukemic blasts from 133 patients with acute leukemia, (67 acute lymphoblastic leukemia (ALL) and 66 acute myeloid leukemia (AML)) in the animals after subcutaneous inoculation without conditioning treatment. The blasts displayed three distinct growth patterns: "aggressive", "indolent", or "no tumor growth". Out of 133 leukemias, 45 (33.8%) displayed an aggressive growth pattern, 14 (10.5%) displayed an indolent growth pattern and 74 (55.6%) did not grow in SCID mice. The growth probability of leukemias from relapsed and/or refractory disease was nearly 3 fold higher than that from patients with newly diagnosed disease. Serial observations found that leukemic blasts from the same individual, which did not initiate tumor growth at initial presentation and/or at early relapse, may engraft and grow in the later stages of disease, suggesting that the ability of leukemia cells for engraftment and proliferation was gradually acquired following the process of leukemia progression. Nine autonomous growing leukemia cell lines were established in vitro. These displayed an aggressive proliferation pattern, suggesting a possible correlation between the capacity of human leukemia cells for autonomous proliferation in vitro and an aggressive growth potential in SCID mice. In addition, we demonstrated that patients whose leukemic blasts displayed an aggressive growth and dissemination pattern in SClD mice had a poor clinical outcome in patients with ALL as well as AML. Patients whose leukemic blasts grew indolently or whose leukemia cells failed to induce growth had a significantly longer DFS and more favorable clinical course

An efficient method for multi-locus molecular haplotyping

Many methods exist for genotyping—revealing which alleles an individual carries at different genetic loci. A harder problem is haplotyping—determining which alleles lie on each of the two homologous chromosomes in a diploid individual. Conventional approaches to haplotyping require the use of several generations to reconstruct haplotypes within a pedigree, or use statistical methods to estimate the prevalence of different haplotypes in a population. Several molecular haplotyping methods have been proposed, but have been limited to small numbers of loci, usually over short distances. Here we demonstrate a method which allows rapid molecular haplotyping of many loci over long distances. The method requires no more genotypings than pedigree methods, but requires no family material. It relies on a procedure to identify and genotype single DNA molecules, and reconstruction of long haplotypes by a ‘tiling’ approach. We demonstrate this by resolving haplotypes in two regions of the human genome, harbouring 20 and 105 single-nucleotide polymorphisms, respectively. The method can be extended to reconstruct haplotypes of arbitrary complexity and length, and can make use of a variety of genotyping platforms. We also argue that this method is applicable in situations which are intractable to conventional approaches

Conversion of a molecular classifier obtained by gene expression profiling into a classifier based on real-time PCR: a prognosis predictor for gliomas

<p>Abstract</p> <p>Background</p> <p>The advent of gene expression profiling was expected to dramatically improve cancer diagnosis. However, despite intensive efforts and several successful examples, the development of profile-based diagnostic systems remains a difficult task. In the present work, we established a method to convert molecular classifiers based on adaptor-tagged competitive PCR (ATAC-PCR) (with a data format that is similar to that of microarrays) into classifiers based on real-time PCR.</p> <p>Methods</p> <p>Previously, we constructed a prognosis predictor for glioma using gene expression data obtained by ATAC-PCR, a high-throughput reverse-transcription PCR technique. The analysis of gene expression data obtained by ATAC-PCR is similar to the analysis of data from two-colour microarrays. The prognosis predictor was a linear classifier based on the first principal component (PC1) score, a weighted summation of the expression values of 58 genes. In the present study, we employed the delta-delta Ct method for measurement by real-time PCR. The predictor was converted to a Ct value-based predictor using linear regression.</p> <p>Results</p> <p>We selected <it>UBL5 </it>as the reference gene from the group of genes with expression patterns that were most similar to the median expression level from the previous profiling study. The number of diagnostic genes was reduced to 27 without affecting the performance of the prognosis predictor. PC1 scores calculated from the data obtained by real-time PCR showed a high linear correlation (r = 0.94) with those obtained by ATAC-PCR. The correlation for individual gene expression patterns (r = 0.43 to 0.91) was smaller than for PC1 scores, suggesting that errors of measurement were likely cancelled out during the weighted summation of the expression values. The classification of a test set (n = 36) by the new predictor was more accurate than histopathological diagnosis (log rank p-values, 0.023 and 0.137, respectively) for predicting prognosis.</p> <p>Conclusion</p> <p>We successfully converted a molecular classifier obtained by ATAC-PCR into a Ct value-based predictor. Our conversion procedure should also be applicable to linear classifiers obtained from microarray data. Because errors in measurement are likely to be cancelled out during the calculation, the conversion of individual gene expression is not an appropriate procedure. The predictor for gliomas is still in the preliminary stages of development and needs analytical clinical validation and clinical utility studies.</p

Light Curves and Colors of the Ejecta from Dimorphos after the DART Impact

On 26 September 2022 the Double Asteroid Redirection Test (DART) spacecraft impacted Dimorphos, a satellite of the asteroid 65803 Didymos. Because it is a binary system, it is possible to determine how much the orbit of the satellite changed, as part of a test of what is necessary to deflect an asteroid that might threaten Earth with an impact. In nominal cases, pre-impact predictions of the orbital period reduction ranged from ~8.8 - 17.2 minutes. Here we report optical observations of Dimorphos before, during and after the impact, from a network of citizen science telescopes across the world. We find a maximum brightening of 2.29 $\pm$ 0.14 mag upon impact. Didymos fades back to its pre-impact brightness over the course of 23.7 $\pm$ 0.7 days. We estimate lower limits on the mass contained in the ejecta, which was 0.3 - 0.5% Dimorphos' mass depending on the dust size. We also observe a reddening of the ejecta upon impact.Comment: Accepted by Natur