Fluctuation analysis with cell deaths

The classical Luria-Delbr\"uck model for fluctuation analysis is extended to the case where cells can either divide or die at the end of their generation time. This leads to a family of probability distributions generalizing the Luria-Delbr\"uck family, and depending on three parameters: the expected number of mutations, the relative fitness of normal cells compared to mutants, and the death probability of mutants. The probabilistic treatment is similar to that of the classical case; simulation and computing algorithms are provided. The estimation problem is discussed: if the death probability is known, the two other parameters can be reliably estimated. If the death probability is unknown, the model can be identified only for large samples

Bifurcation analysis in a frustrated nematic cell

Using Landau-de Gennes theory to describe nematic order, we study a frustrated cell consisting of nematic liquid crystal confined between two parallel plates. We prove the uniqueness of equilibrium states for a small cell width. Letting the cell width grow, we study the behaviour of this unique solution. Restricting ourselves to a certain interval of temperature, we prove that this solution becomes unstable at a critical value of the cell width. Moreover, we show that this loss of stability comes with the appearance of two new solutions: there is a symmetric pitchfork bifurcation. This picture agrees with numerical simulations performed by P. Palffy-Muhorray, E.C. Gartland and J.R. Kelly. Some of the methods that we use in the present paper apply to other situations, and we present the proofs in a general setting. More precisely, the paper contains the proof of a general uniqueness result for a class of perturbed quasilinear elliptic systems, and general considerations about symmetric solutions and their stability, in the spirit of Palais' Principle of Symmetric Criticality

Quantitative imaging of the collective cell movements shaping an embryo

The recent development of imaging and image processing techniques, such as 4D microscopy and 3D cell tracking, enables analysis through quantification of the movement of large cell populations in vivo. These imaging approaches provide an opportunity to study embryonic morphogenesis during development from the level of cellular processes to the scale of entire organism. Image analysis reveals cell collective behaviors that shape an embryo and offers some surprising insights into the cell-cell interactions involved in concerted movements. We illustrate the power of this approach by studying the early development of Drosophila embryos

Single cell transcriptome analysis using next generation sequencing.

The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

Full-Duplex MIMO Small-Cell Networks: Performance Analysis

Full-duplex small-cell relays with multiple antennas constitute a core element of the envisioned 5G network architecture. In this paper, we use stochastic geometry to analyze the performance of wireless networks with full-duplex multiple-antenna small cells, with particular emphasis on the probability of successful transmission. To achieve this goal, we additionally characterize the distribution of the self-interference power of the full-duplex nodes. The proposed framework reveals useful insights on the benefits of full-duplex with respect to half-duplex in terms of network throughput

Cell degradation detection based on an inter-cell approach

Fault management is a crucial part of cellular network management systems. The status of the base stations is usually monitored by well-defined key performance indicators (KPIs). The approaches for cell degradation detection are based on either intra-cell or inter-cell analysis of the KPIs. In intra-cell analysis, KPI profiles are built based on their local history data whereas in inter-cell analysis, KPIs of one cell are compared with the corresponding KPIs of the other cells. In this work, we argue in favor of the inter-cell approach and apply a degradation detection method that is able to detect a sleeping cell that could be difficult to observe using traditional intra-cell methods. We demonstrate its use for detecting emulated degradations among performance data recorded from a live LTE network. The method can be integrated in current systems because it can operate using existing KPIs without any major modification to the network infrastructure