Close Encounter of Three Black Holes Revisited

We study the evolution of close triple black hole system with full numerical relativity techniques. We consider an equal mass non spinning hierarchical system with an inner binary ten orbits away from merger and study the effects of the third outer black hole on the binary's merger time and its eccentricity evolution. We find a generic time delay and an increase in the number of orbits to merger of the binary, that can be modeled versus the distance $D$ to the third black hole as $\sim1/D^{2.5}$. On the other hand, we find that the orientation of the third black hole orbit has little effect on the binary's merger time when considering a fiducial initial distance of $D=30M$ to the binary (with initial orbital separation $d=8M$). In those scenarios the evolution of the inner binary eccentricity presents a steady decay, roughly as expected, but in addition shows a modulation with the time scale of the outer third black hole orbital semiperiod around the binary, resembling a beating frequency.Comment: 13 pages, 12 figures, 6 table

The time course of recombinant production in Streptomyces coelicolor.

SUMMARYThe process leading to gene recombination can be interrupted in the filamentous bacteriaStreptomyces coelicolorby growing mixed cultures on cellophane disks lying on complete medium. The mycelium is harvested, broken, diluted and the broken hyphae plated at different time intervals. By this means some markers can be excluded from heteroclones or from recombinant progeny in early samples. The recombinant pattern clearly changes with time, with an increase of markers contributed to the recombinant progeny. In crosses between male (NF) and female (UF) strains, the maleness is the first donor trait to appear in the cells of the recipient parent. The fertility factor does not produce a transfer origin on the donor chromosomes; the donor contribution may extend on either side or on both sides of the factor which appears to be compulsory for zygote formation. The longer the time of contact between parental cells, the longer the segment of the donor chromosome contributing to the recombinant progeny. When spores are formed they contain almost exclusively recombinant nuclei derived from segregation processes

Metaplastic carcinoma with extensive dendritic cell differentiation: a previously unrecognised type of triple-negative breast cancer

The case of a metaplastic carcinoma of the breast exhibiting dendritic cell differentiation is described. The clinico-pathologic and immunohistochemical features are reported, together with the differential diagnosis

Automated DNA Fragments Recognition and Sizing through AFM Image Processing

This paper presents an automated algorithm to determine DNA fragment size from atomic force microscope images and to extract the molecular profiles. The sizing of DNA fragments is a widely used procedure for investigating the physical properties of individual or protein-bound DNA molecules. Several atomic force microscope (AFM) real and computer-generated images were tested for different pixel and fragment sizes and for different background noises. The automated approach minimizes processing time with respect to manual and semi-automated DNA sizing. Moreover, the DNA molecule profile recognition can be used to perform further structural analysis. For computer-generated images, the root mean square error incurred by the automated algorithm in the length estimation is 0.6% for a 7.8 nm image pixel size and 0.34% for a 3.9 nm image pixel size. For AFM real images we obtain a distribution of lengths with a standard deviation of 2.3% of mean and a measured average length very close to the real one, with an error around 0.33%

B3 0003+387: AGN Marked Large-Scale Structure at z=1.47?

We present evidence for a significant overdensity of red galaxies, as much as a factor of 14 over comparable field samples, in the field of the z=1.47 radio galaxy B3 0003+387. The colors and luminosities of the brightest red galaxies are consistent with their being at z>0.8. The radio galaxy and one of the red galaxies are separated by 5" and show some evidence of a possible interaction. However, the red galaxies do not show any strong clustering around the radio galaxy nor around any of the brighter red galaxies. The data suggest that we are looking at a wall or sheet of galaxies, possibly associated with the radio galaxy at z=1.47. Spectroscopic redshifts of these red galaxies will be necessary to confirm this large-scale structure.Comment: 19 pages, 7 figures, LaTeX2e/AASTeX v5.0.2. The full photometric catalog is included as a separate deluxetable file. To appear in the Astronomical Journal (~Nov 00

A survey on data integration for multi-omics sample clustering

Due to the current high availability of omics, data-driven biology has greatly expanded, and several papers have reviewed state-of-the-art technologies. Nowadays, two main types of investigation are available for a multi-omics dataset: extraction of relevant features for a meaningful biological interpretation and clustering of the samples. In the latter case, a few reviews refer to some outdated or no longer available methods, whereas others lack the description of relevant clustering metrics to compare the main approaches. This work provides a general overview of the major techniques in this area, divided into four groups: graph, dimensionality reduction, statistical and neural-based. Besides, eight tools have been tested both on a synthetic and a real biological dataset. An extensive performance comparison has been provided using four clustering evaluation scores: Peak Signal-to-Noise Ratio (PSNR), Davies-Bouldin(DB) index, Silhouette value and the harmonic mean of cluster purity and efficiency. The best results were obtained by using the dimensionality reduction, either explicitly or implicitly, as in the neural architecture

ClusterFix: A Cluster-Based Debiasing Approach without Protected-Group Supervision

The failures of Deep Networks can sometimes be ascribed to biases in the data or algorithmic choices. Existing debiasing approaches exploit prior knowledge to avoid unintended solutions; we acknowledge that, in real-world settings, it could be unfeasible to gather enough prior information to characterize the bias, or it could even raise ethical considerations. We hence propose a novel debiasing approach, termed ClusterFix, which does not require any external hint about the nature of biases. Such an approach alters the standard empirical risk minimization and introduces a per-example weight, encoding how critical and far from the majority an example is. Notably, the weights consider how difficult it is for the model to infer the correct pseudo-label, which is obtained in a self-supervised manner by dividing examples into multiple clusters. Extensive experiments show that the misclassification error incurred in identifying the correct cluster allows for identifying examples prone to bias-related issues. As a result, our approach outperforms existing methods on standard benchmarks for bias removal and fairness

PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity

Background: Tumors are composed by a number of cancer cell subpopulations (subclones), characterized by a distinguishable set of mutations. This phenomenon, known as intra-tumor heterogeneity (ITH), may be studied using Copy Number Aberrations (CNAs). Nowadays ITH can be assessed at the highest possible resolution using single-cell DNA (scDNA) sequencing technology. Additionally, single-cell CNA (scCNA) profiles from multiple samples of the same tumor can in principle be exploited to study the spatial distribution of subclones within a tumor mass. However, since the technology required to generate large scDNA sequencing datasets is relatively recent, dedicated analytical approaches are still lacking. Results: We present PhyliCS, the first tool which exploits scCNA data from multiple samples from the same tumor to estimate whether the different clones of a tumor are well mixed or spatially separated. Starting from the CNA data produced with third party instruments, it computes a score, the Spatial Heterogeneity score, aimed at distinguishing spatially intermixed cell populations from spatially segregated ones. Additionally, it provides functionalities to facilitate scDNA analysis, such as feature selection and dimensionality reduction methods, visualization tools and a flexible clustering module. Conclusions: PhyliCS represents a valuable instrument to explore the extent of spatial heterogeneity in multi-regional tumour sampling, exploiting the potential of scCNA data